TW201606084A - Method of predicting or determining plant phenotypes - Google Patents
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Abstract
Description
本發明大體而言與分子生物學領域有關。特別是關於用於偵測及利用單核苷酸多型性以篩選油棕櫚的作物基因。The invention is generally related to the field of molecular biology. In particular, it relates to crop genes for detecting and utilizing single nucleotide polymorphism to screen oil palm.
馬來西亞及印尼的油棕櫚(Elaeis guineensis )產業最初是使用Deli duras 作為商業化植栽作物而建立。Deli duras 是由1848年種植於Bogor Botanic Garden中四棵油棕櫚所繁育。一開始作為林蔭大道觀賞用棕櫚樹種植的油棕櫚,隨著1917年於雪蘭峨(Selangor)的Tennamaran Estate第一個油棕櫚園之設立,遂成為商業作物。馬來西亞的油棕櫚產業在過去50年來快速地發展,油棕櫚的栽種面積也從1960年的5萬4千公頃成長至2010年的5百萬公頃。The oil palm ( Elaeis guineensis ) industry in Malaysia and Indonesia was originally established using Deli duras as a commercial planting crop. Deli duras was bred by four oil palms planted in Bogor Botanic Garden in 1848. At first, as a boulevard, the oil palm planted with palm trees was established as a commercial crop in 1917 at the Tennamaran Estate's first oil palm garden in Selangor. Malaysia's oil palm industry has developed rapidly over the past 50 years, and the oil palm planting area has grown from 54,000 hectares in 1960 to 5 million hectares in 2010.
自1941年公開殼厚之遺傳特性後(Beirnaert and Vanderweyen, Congo Belge, Ser. Sci, 27:1-101, 1941),商業油棕櫚植栽作物逐漸由duras 轉移至dura xpisifera (或DxP 雜交)或teneras 。相較起dura ,DxP具有較高的中果皮對果實的比例(60%至超過80%)的,使得油產量增加約30%。Since the hereditary properties of shell thickness were revealed in 1941 (Beirnaert and Vanderweyen, Congo Belge, Ser. Sci, 27:1-101, 1941), commercial oil palm planting crops were gradually transferred from duras to dura x pisifera (or DxP hybrid). Or teneras . Compared to dura , DxP has a higher ratio of mesocarp to fruit (60% to over 80%), resulting in an increase in oil production of about 30%.
為了產生高產量的DxP植栽作物,油棕櫚的培育者分別改良dura 與pisifera ,並挑選菁英的dura 及pisifera 棕櫚以產生種子。舉例而言,在dura 的例子中,選出具有合意性狀的dur 被並用以產生dura xdura (或DxD)雜交。將產生的種子在苗圃培育一年,接著移至田間種植。視種植的地點,這些棕櫚會在2年半至3年間結果。接著記錄這些棕櫚的產量5年以判定其產量潛力以用於另一輪挑選及改良。In order to produce high-yield DxP plants, the oil palm breeders modified dura and pisifera , respectively, and selected dura and pisifera palms to produce seeds. For example, in the example of dura , a dur with a desirable trait is selected and used to generate a dura x dura (or DxD) hybrid. The resulting seeds are incubated in the nursery for one year and then moved to the field for planting. Depending on the location of the plant, these palms will result in two and a half to three years. These palms were then recorded for 5 years to determine their yield potential for another round of selection and improvement.
在pisifera 的改良計畫中,將選出的pisifera 與選出的tenera 雜交產生tenera xpisifera (或TxP)雜交。或選出的tenera 可用於在tenera xtenera (或TxT)雜交中產生pisifera 。如同dura 般將種子在苗圃培育,接著移至田間種植,唯一的不同在於pisifera 為雌性不孕或發育不全的,因此無法進行產量記錄。產量紀錄僅能於dura 或tenera 同胞中進行。In pisifera improvement plan, the selected pisifera with tenera hybrid selected to produce tenera x pisifera (or TxP) hybridization. Or the selected tenera can be used to produce pisifera in the tenera x tenera (or TxT) cross. Seeds were bred in nurseries like dura and then moved to the field. The only difference is that pisifera is female infertility or underdeveloped, so production records cannot be made. Production records can only be made in dura or tenera compatriots.
經過多年油棕櫚培育已改良油棕櫚植栽作物的產量潛力。舉例而言,李姓學者等人( Lee et al., Proc. Workshop ‘Progress of oil palm breeding populations’ (1990) p.p 81-89.)發現經過4代選種的dura
族群比起未經選種的dura
棕櫚在油產量上有顯著的增加(5.0噸油/公頃/年 VS 3.1噸油/公頃/年,其表示增加61.3%的產量)。同樣地, DxP植栽作物的油棕櫚產量經過多年已顯著地改良,如下表所示: 表1:馬來西亞的植栽作物產量表現
據報迄今達成的最高商業產量為32.15公頃之田具有47.65噸FFB/公頃/年的新鮮果串(fresh fruit bunch, FFB)產量(Pang Oil Palm: Sabah’s Future, Paper Presented in PIPOC (2005))。從這些植栽作物之商業田地收穫的果串之實驗室分析據報為30%油/果串以上,雖然油廠最高萃取量為25.01%。The highest commercial yield reported to date is 32.15 hectares with 47.65 tons of FFB/ha/year fresh fruit bunch (FFB) production (Pang Oil Palm: Sabah’s Future, Paper Presented in PIPOC (2005)). Laboratory analysis of fruit bunches harvested from commercial fields of these planted crops was reported to be above 30% oil/fruit bunch, although the highest extraction volume of the oil plant was 25.01%.
儘管自第一座油棕櫚園建立以來於油棕櫚之產量上有所改良,但其持續之努力仍然面臨許多挑戰。Although the production of oil palm has improved since the first oil palm plant was established, its ongoing efforts still face many challenges.
在馬來西亞大多數油棕櫚的培育係以藉由紀錄田地中之表現型,並依據顯現之性狀、表現及組合力選擇出最好的油棕櫚用以培育之傳統選種方法為基礎。此方法具有幾個限制:(a)無法避免由於合意基因與不合意表現型之結合之連鎖負累(linkage drag);(b)改良油棕櫚所需時間非常長,以傳統培育而言通常從挑選和雜交到最後的產量紀錄至少需要12年;(c)在複雜性狀,例如選擇產量的情況下,當產量的不同構成要素之間可能存在交互作用時,要精準地估算選擇的淨效應是非常困難的,舉例而言,一個構成要素的增加可能對另一個有負面作用。The cultivation of most oil palms in Malaysia is based on the selection of the phenotypes in the field and the selection of the best oil palm for breeding based on the traits, performance and combination of appearance. This method has several limitations: (a) linkage drag due to the combination of desirable genes and undesired phenotypes; (b) the time required to improve oil palms is very long, usually in terms of traditional cultivation. It takes at least 12 years to select and hybridize to the final production record; (c) in the case of complex traits, such as the choice of production, when there may be interactions between different components of production, the net effect of the selection is accurately estimated. Very difficult, for example, an increase in one component may have a negative effect on the other.
此外,用以生產DxP植栽作物之母系的異型接合度會導致個別棕櫚產量的變化。可預期來自優良油棕櫚株的約15%或以上的改良產量。In addition, the heterozygous degree of maternal lineage used to produce DxP planting crops can result in changes in individual palm yields. Improved yields of about 15% or more from elite oil palm strains are expected.
在嘗試解決傳統培育及選種方法所遭遇的問題,並進一步地改良優棕櫚的產量上,已使用以分子為基礎的方法以加速優秀油棕櫚植栽作物之發展。舉例而言,已使用利用基因資料(以可得自特定子代表現之田野資料為基礎)鑑別與特定特徵(例如高FFB產量)持續相關聯之特定基因序列之分子標記輔助選種。這些基因序列接下來可作為分子標記,用於例如,甚至於苗圃階段選種高FFB產量,藉此將培育過程的週期從12年減為6年。In an attempt to address the problems encountered in traditional cultivation and selection methods, and to further improve the yield of superior palm, molecular-based methods have been used to accelerate the development of excellent oil palm planting crops. For example, molecular marker-assisted selection of specific gene sequences that are consistently associated with a particular feature (eg, high FFB production) has been identified using genetic material (based on field data available from a particular progeny). These gene sequences can then be used as molecular markers for, for example, selecting high FFB production even at the nursery stage, thereby reducing the cycle of the incubation process from 12 years to 6 years.
因此,存在基於與合意表現型相關的基因標記之間的基因分析對照結果,利用其預測作物表現型和可加快作物子代選種程序的基因標記的需求,從而以時間及花費上較有效率的方式促進作物培育過程。Therefore, there is a genetic analysis based on genetic markers associated with desirable phenotypes, using it to predict crop phenotypes and the need for genetic markers that speed up crop progeny selection procedures, resulting in greater time and expense. The way to promote the crop cultivation process.
在第一方面,本發明涉及一種預測或判定感興趣的作物表現型之方法,其中方法包括偵測選自於由SEQ ID NO: 1 至 SEQ ID NO: 115組合而成之群組中之一個或多個多型性基因標記的存在與否。In a first aspect, the invention relates to a method of predicting or determining a phenotype of a crop of interest, wherein the method comprises detecting one selected from the group consisting of SEQ ID NO: 1 to SEQ ID NO: 115 Or the presence or absence of multiple polymorphic gene markers.
在第二方面,本發明涉及根據任一前述主張之一個或多個多型性基因標記,作為作物選種之準則之用途,其中選種係以一個或多個多型性基因標記存在的與否為基礎。In a second aspect, the invention relates to the use of one or more polymorphic gene markers according to any of the foregoing claims as a criterion for crop selection, wherein the selection is carried out by one or more polymorphic gene markers No basis.
定義definition
用於本文的下述字詞及術語具有指定的意思:The following words and terms used herein have the meanings specified:
用於本文之術語「多型性」意指一物種中的某些成員中產生之基因區域之序列的變異或不同。不同的序列可藉由參考該物種任意或非任意的標準序列而定義。因此多型性被稱為是「對偶的(allelic)」,意即為,由於多型性的存在,一物種的某些成員可具有「標準」序列(也就是標準「對偶基因」),而另一些成員可具有「變異」序列(也就是變異「對偶基因」)。因此,如用於本文中,對偶基因為基因可供選擇之兩個或多個版本中的一個,或為在染色體上之特定位置的其他基因區域。在最簡單的狀況中,可僅存在一個變異序列,而其多型性因此被稱為雙對偶。在其他的狀況中,物種族群可包含多個對偶基因,則其多型性被稱為三對偶…等等。The term "polymorphism" as used herein refers to a variation or difference in the sequence of a gene region produced in certain members of a species. Different sequences can be defined by reference to an arbitrary or non-arbitrary standard sequence of the species. Therefore, polymorphism is called "allelic", which means that certain members of a species may have a "standard" sequence (that is, a standard "dual gene") due to the existence of polymorphism. Other members may have a "mutation" sequence (that is, a variant "dual gene"). Thus, as used herein, a dual gene is one of two or more versions of a gene to choose from, or other genetic regions at a particular location on a chromosome. In the simplest case, there can be only one variant sequence, and its polymorphism is therefore called double pair. In other cases, the ethnic group can contain multiple dual genes, and its polymorphism is called three pairs... and so on.
基因或基因區域可具有多個不同的、不相關的多型性。舉例而言,其可能在一個位置具有一個雙對偶多型性,在另一個位置具有另一個雙對偶多型性,且在又另一位置具有一個多對偶多型性。當在作物中的染色體基因座之對偶基因群組序列全部相同時,此對偶基因被稱為「同型接合」在基因座。當在作物中特定基因座之任一對偶基因序列不同時,該對偶基因群被稱為「異型接合」在基因座。A gene or gene region can have multiple, unrelated polymorphisms. For example, it may have one double dual polymorphism at one location, another dual dual polymorphism at another location, and one polydox polymorphism at yet another location. When the sequence of the dual gene group in the chromosomal locus in the crop is all the same, the dual gene is referred to as "homotype" at the locus. When any of the dual gene sequences in a particular locus in a crop is different, the dual gene group is referred to as a "heterotypic junction" at the locus.
表現型性狀可因環境及/或遺傳因子而變化。舉例而言,在特定染色體基因座上的多型性可以影響與該基因座相關的表現型性狀。Phenotypic traits may vary depending on environmental and/or genetic factors. For example, polymorphism at a particular chromosomal locus can affect phenotypic traits associated with that locus.
用於本文之術語「表現型性狀(phenotypic trait)」係關於由作物顯現的能夠被繼承的任一特徵或性狀,不論是自然發生或用其他方式。此外,舉例而言,感興趣的性狀可為短暫的、永久的或僅於作物或其部分受到環境刺激或挑戰時呈現。感興趣的表現型性狀可為合意或正面的性狀。在別的狀況中,感興趣的表現型性狀可為不合意或負面的性狀。The term "phenotypic trait" as used herein relates to any feature or trait that can be inherited by a crop, whether naturally occurring or otherwise. Further, for example, the trait of interest may be transient, permanent, or only present when the crop or portion thereof is subjected to environmental stimuli or challenges. The phenotypic trait of interest can be a desirable or positive trait. In other situations, the phenotypic trait of interest may be an undesirable or negative trait.
農藝及園藝感興趣的許多性狀可由單一基因控制,屬於少數相異表現型類別。這些表現型類別稱為不連續性狀,且可以用來預測個體的基因型。Many traits of interest in agronomy and horticulture can be controlled by a single gene and belong to a few distinct phenotypes. These phenotypic categories are called discontinuous traits and can be used to predict an individual's genotype.
其他性狀不屬於分離類型。確切來說,當分離族群以這些性狀來分析時,會發現一連續分布。舉例而言,如果一個性狀不屬於小分布,而是顯現常態分布的鐘形曲線,這種性狀類型被稱為連續性狀,且不能以與不連續性狀相同的方式分析。因為連續性狀通常被給定一個數量值,其通常被稱為數量性的性狀。此外,控制這些性狀的基因座被稱為數量性狀基因座或QTL。Other traits are not of the separation type. Specifically, when the isolated population is analyzed by these traits, a continuous distribution is found. For example, if a trait does not belong to a small distribution, but rather a bell-shaped curve that exhibits a normal distribution, this trait type is called a continuous trait and cannot be analyzed in the same manner as the discontinuous trait. Because continuous traits are usually given a numerical value, they are often referred to as quantitative traits. In addition, loci controlling these traits are referred to as quantitative trait loci or QTLs.
此外,表現型性狀並不侷限於可見的性狀。雖然表現型性狀可以是任一性狀,感興趣的較佳性狀為具有農學重要性的。農學性狀的例子包括提供疾病或化學抗性的效應產量的要素以及影響例如花粉或胚珠等等發育性狀,以及影響作物或作物部分,包括種子、蛋白質或油、澱粉或糖的成分、營養組成及相似之物的成分。在更進一步的例子中,性狀包括,但不侷限於影響例如FFB產量之產量、串之數目、樹幹尺寸或其組合的要素之性狀。在另一例中,產量的構成要素包括,但不侷限於新鮮果串重、串之尺寸、果實尺寸、油之萃取比例、串之數目或其組合。Furthermore, phenotypic traits are not limited to visible traits. Although the phenotypic trait can be any trait, the preferred trait of interest is of agronomic importance. Examples of agronomic traits include elements that provide effect yields of disease or chemoresistance, as well as developmental traits such as pollen or ovules, as well as components or crop components that affect crops or crops, including seeds, proteins or oils, starch or sugar, and nutrient composition. The composition of similar things. In still further examples, traits include, but are not limited to, traits that affect factors such as yield of FFB production, number of strands, trunk size, or combinations thereof. In another example, the constituent elements of the yield include, but are not limited to, the weight of the fresh fruit bunch, the size of the string, the size of the fruit, the extraction ratio of the oil, the number of strings, or a combination thereof.
在預測或判定感興趣作物基因型之方法的例子,包括但不侷限於下列步驟:起初取得待分析之作物、種子或幼樹的樣本。作物基因分析會顯示出於何處存在何種單核苷酸多型性(single nucleotide polymorphisms, SNPs)。接下來,將此樣本的這種類型的基因分析或基因定位之結果與已知的SNPs清單比較,其中該已知SNPs清單已經以該作物一個或多個之特徵聯結,例如作物高度、果實產量等等。因此樣本的基因分析與SNPs清單比較,能推論受試作物到時表現出合意特徵的統計機率。為了使此方法可行,在樣本中須存在至少一個SNP。Examples of methods for predicting or determining a genotype of a crop of interest include, but are not limited to, the steps of initially obtaining a sample of a crop, seed or sapling to be analyzed. Crop genetic analysis will show where there are single nucleotide polymorphisms (SNPs). Next, the results of this type of genetic analysis or gene mapping of this sample are compared to a list of known SNPs, which have been linked by one or more characteristics of the crop, such as crop height, fruit yield and many more. Therefore, the genetic analysis of the sample compared with the SNPs list can infer the statistical probability that the tested crops will exhibit desirable characteristics. In order for this method to be feasible, at least one SNP must be present in the sample.
如同上面所解釋的,許多表現型性狀是由多個基因或遺傳因子所導致的結果,舉例而言,由數量性狀對偶基因導致的表現型性狀。數量性狀基因座的對偶基因可包括多個基因或其他甚至於連續基因區域或連鎖群中的遺傳因子。As explained above, many phenotypic traits are the result of multiple genes or genetic factors, for example, phenotypic traits caused by quantitative traits of the dual gene. A dual gene of a quantitative trait locus can include multiple genes or other genetic factors even in a continuous gene region or linkage group.
「基因座(Locus)」意指在物種基因體上可以找到特定基因的特定染色體位置。用於本文之「數量性狀基因座(quantitative trait loci, QTL)」係指包含構成數量性狀的基因或連結構成數量性狀的基因的DNA區域。定位包含涉及特定數量性狀的基因之基因體的區域係使用分子標籤例如AFLP或較常見的SNPs進行。此為對構成性狀變化的真實基因識別及排序的初期步驟。數量性狀意指程度上的變化及可歸因於多基因效應,例如兩個或以上基因的產物及其環境,的表現型(特徵)。因而其可被定義為于連續地變動性狀中影響基因變化的表現型。"Locus" means the specific chromosomal location of a particular gene that can be found on the genome of a species. As used herein, "quantitative trait loci (QTL)" refers to a DNA region comprising a gene that constitutes a quantitative trait or a gene that binds to a quantitative trait. Localization of a region comprising a gene involved in a gene of a particular quantitative trait is performed using molecular tags such as AFLP or more common SNPs. This is an initial step in the identification and sequencing of true genes that constitute trait changes. A quantitative trait means a change in the degree and a phenotype (characteristic) attributable to a multi-gene effect, such as the product of two or more genes and their environment. Thus it can be defined as a phenotype that affects gene changes in continuously varying traits.
用於本文之「數量性狀基因座分析(QTL analysis)」為連結表現型資料(性狀測量)和基因型資料(通常分子標記)兩種資訊類型的統計方法,以意圖闡明複雜性狀中變異的遺傳基礎。因此QTL分析使某些複雜的表現型連結至染色體的特定區域。此程序的目標是識別這些區域的行為、交互作用、數目及精確的位置。As used herein, "QTL analysis" is a statistical method that links two types of information, phenotypic data (trait measurement) and genotype data (usually molecular markers), with the intent to clarify the inheritance of mutations in complex traits. basis. Therefore, QTL analysis links certain complex phenotypes to specific regions of the chromosome. The goal of this program is to identify the behavior, interactions, numbers, and precise locations of these areas.
用於本文之「數量性狀基因座的對偶基因(allele of a quantitative trait locus)」包含多於一種的基因或遺傳因子,每個單獨的基因或遺傳成分皆能顯現對偶變化,且每個基因或遺傳因子皆對於所討論的數量性狀具有表現型作用。As used herein, "allele of a quantitative trait locus" encompasses more than one gene or genetic factor, each individual gene or genetic component exhibits a dual change, and each gene or Genetic factors have a phenotypic effect on the quantitative traits in question.
術語「染色體斷片(chromosome segment)」係指定為於單一染色體上存在於作物中之基因體DNA相鄰的線形範圍。位於單一染色體斷片上的基因元件或基因為物理性地連結。在本發明的上下文中,位於染色體斷片之中基因元件也基因性地連結,通常在小於或等於10分摩基因重組的距離。換句話說,減數分裂時,單一染色體斷片中的兩個基因元件彼此以小於或等於大約10%的頻率經歷重組。The term "chromosome segment" is defined as the linear range adjacent to the genomic DNA present in a crop on a single chromosome. A genetic element or gene located on a single chromosome fragment is physically linked. In the context of the present invention, genetic elements located within a chromosomal fragment are also genetically linked, typically at a distance of less than or equal to 10 points of gene recombination. In other words, at meiosis, two genetic elements in a single chromosome fragment undergo recombination with each other at a frequency of less than or equal to about 10%.
用於本文之「標記(marker)」係為至少一種多型性的存在指標。標記優選為核酸分子。理解的是標記可為,舉例而言,寡核酸探針或引子。分子標記以基因分型為首選,因為這些標記不太會影響感興趣的性狀。在某些例子中,標記包含但不侷限於SNPs、簡單序列重複(simple sequence repeats, SSRs或微衛星)、AFLPs、隨機擴增多型性DNA(random amplification of polymorphic DNAs, RAPDs) 限制片段長度多型性(restriction fragment length polymorphisms, RFLPs)、轉位元位置及其組合。A "marker" as used herein is an indicator of the presence of at least one polymorphism. The label is preferably a nucleic acid molecule. It is understood that the label can be, for example, an oligonucleic acid probe or primer. Molecular markers are preferred for genotyping because they do not affect the trait of interest. In some instances, markers include, but are not limited to, SNPs, simple sequence repeats (SSRs or microsatellites), AFLPs, and random amplification of polymorphic DNAs (RAPDs). Restriction fragment length polymorphisms (RFLPs), index bit positions, and combinations thereof.
用於本文之術語「單核苷酸多型性(SNPs)」被定義為DNA序列的變異,其發生於生物物種成員之間或人類成對染色體之間的基因組序列中單核苷酸(A、T、C及G)改變或不同之時。因此,用於本文之SNPs係為任一多型性,其多型性以至少一個對偶基因的特定物理位置中有不同的單核苷酸為特徵。被給定的族群中每個個體具有共同造就個體獨一無二的DNA組態的許多SNPs。用於本文之「簡單序列重複(SSRs)」,也可稱為微衛星(microsatellites)或短縱列重複序列(short tandem repeats, STRs),為2至6個DNA的鹼基對之重複序列。其為變異性重複序列(variable number tandem repeat, VNTR)的一種類型。SSRs通常為共顯性的。The term "single nucleotide polymorphisms (SNPs)" as used herein is defined as a variation of a DNA sequence that occurs in a genomic sequence between members of a biological species or between human pairs of chromosomes (A) , T, C, and G) change or be different. Thus, the SNPs used herein are of any polymorphism whose polymorphism is characterized by a different single nucleotide in a particular physical location of at least one of the dual genes. Each individual in a given group has many SNPs that together create an individual's unique DNA configuration. As used herein, "simple sequence repeats (SSRs)", also referred to as microsatellites or short tandem repeats (STRs), are repeats of base pairs of 2 to 6 DNAs. It is a type of variable number tandem repeat (VNTR). SSRs are usually codominant.
用於本文之術語「增幅片段長度多型性(AFLPs)」係有關於創造或取消了限制性核酸內切酶的辨識位置之SNPs或INDELs所引起的限制片段長度不同。AFPL技術是基於來自基因體DNA的完全消化之限制片段的選擇聚合酶連鎖反應(polymerase chain reaction, PCR)增幅。As used herein, the term "amplified fragment length polymorphisms (AFLPs)" differs in the length of restriction fragments caused by SNPs or INDELs that create or eliminate the recognition site for restriction endonucleases. The AFPL technique is based on the selection of polymerase chain reaction (PCR) amplification based on restriction fragments of complete digestion of genomic DNA.
用於本文之術語「隨機擴增多型性DNA(RAPD)」係為來自以任意核苷酸序列的單一引子基因體DNA之隨機斷片之PCR增幅的DNA片段。不像傳統的PCR分析,RAPD不需要目標有機體DNA序列的任何特定知識:相同的10單位引子將會或不會增幅DNA斷片,其取決於引子序列的互補位置。舉例而言,如果引子黏著的太開或引子的3'末端沒有面對彼此,那麼就不會生成片段。因此,如果模板DNA之前與引子互補的某一點發生突變,PCR產品便不會產生,導致膠體上增幅DNA斷片的不同組態。RAPD在不容許區分異型接合和同型接合狀態的RAPD帶存在上具優勢。The term "random amplified polymorphic DNA (RAPD)" as used herein is a DNA fragment amplified from a PCR fragment of a random fragment of a single primer gene DNA of any nucleotide sequence. Unlike traditional PCR analysis, RAPD does not require any specific knowledge of the target organism's DNA sequence: the same 10 unit primer will or will not augment the DNA fragment, depending on the complementary position of the primer sequence. For example, if the primers are too open or the 3' ends of the primers do not face each other, no fragments will be generated. Therefore, if the template DNA is mutated at a point complementary to the primer, the PCR product will not be produced, resulting in a different configuration of the amplified DNA fragment on the colloid. RAPD is advantageous in the presence of RAPD bands that do not allow for the differentiation of heterotypic and isomeric states.
用於本文之術語「限制片段長度多型性(RFLP)」係有關於創造或取消了限制性核酸內切酶的辨識位置之SNPs或INDELs所引起的限制片段長度不同。RFLP分析法係藉由使化學標籤的DNA探針與由限制性核酸內切酶消化DNA的南方墨點法雜交而執行。The term "restriction fragment length polymorphism (RFLP)" as used herein relates to a restriction fragment length caused by SNPs or INDELs that create or eliminate the recognition position of a restriction endonuclease. RFLP analysis is performed by hybridizing a chemically tagged DNA probe to a Southern blot method for digesting DNA by restriction endonucleases.
用於本文之術語「核酸標記(nucleic acid marker)」意指能夠成為偵測多型性標記的核酸分子。The term "nucleic acid marker" as used herein means a nucleic acid molecule capable of detecting a polymorphic marker.
用於本文之術語「與…相關(associated with)」或「相關(associated)」在本發明上下文中用於核酸(例如基因標記)和表現型性狀時,意指處於連鎖相失衡之核酸和表現型性狀。術語「連鎖相失衡(linkage phase disequilibrium)」或「連鎖失衡(linkage disequilibrium)」意指遺傳基因座的非隨機分離。其意味著沿著染色體段的這些基因座為充分物理性的接近,使其趨於以大於隨機的頻率一起分離。As used herein, the terms "associated with" or "associated" when used in the context of the present invention for nucleic acids (eg, genetic markers) and phenotypic traits, mean nucleic acids and expressions that are in linkage phase imbalance. Type traits. The term "linkage phase disequilibrium" or "linkage disequilibrium" means a non-random separation of genetic loci. It means that these loci along the chromosome segment are sufficiently physically close that they tend to separate together at a frequency greater than random.
用於本文之術語「基因性地連結(genetically linked)」意指在相同染色體上彼此物理性上足夠接近的遺傳基因座(包括基因標記基因座),使其具有小於0.5重組頻率。當其意指兩個基因元件之間的關係時,例如影響產量的基因元件與近側的標記,「耦合(coupling)」相連鎖表示位於產量基因座的「有利(favourable)」對偶基因被物理性地聯結於相同染色體股上,作為各自連結標記基因座的「有利」對偶基因的狀態。As used herein, the term "genetically linked" means a genetic locus (including a gene marker locus) that is physically close enough to each other on the same chromosome to have a recombination frequency of less than 0.5. When it refers to the relationship between two genetic elements, such as genetic elements affecting yield and proximal markers, "coupling" is linked to indicate that the "favourable" dual gene at the production locus is physically Sexually linked to the same chromosomal strand as the state of the "favorable" dual gene of each of the linked marker loci.
在耦合相中,兩個有利對偶基因皆由繼承了染色體股的子代一起繼承。在「相斥(repulsion)」相連鎖中,位於產量基因座的「有利」對偶基因與位於近側標記基因座的「不利(unfavourable)」對偶基因物理性地連結,且兩個「有利」對偶基因不會一起被繼承(換句話說,此兩個基因座彼此為「異相(out of phase)」)。In the coupled phase, both favorable dual genes are inherited by the progeny that inherit the chromosomal strands. In the "repulsion" phase linkage, the "favorable" dual gene at the production locus is physically linked to the "unfavourable" dual gene at the proximal marker locus, and the two "favorable" dualities Genes are not inherited together (in other words, the two loci are "out of phase" with each other).
用於本文之術語「物理性地連結(physically linked)」用以表示兩個遺傳基因座(例如兩個標記基因座,一個標記基因座及一個影響表現型變異的基因座)實際上存在於相同染色體上。這兩個基因座位置通常緊密地接近,因此同源染色體對之間的重組不會以高頻率發生於這兩個基因座之間。也就是發生在兩個物理性地連結基因座之間的重組頻率大約低於10%,合適的頻率小於5%,更合適的頻率為2%或更少,或1%或更少。因此,位於相同染色體的兩個基因座,且其間發生重組的頻率低於10%的距離,稱之為彼此近側(proximal)。As used herein, the term "physically linked" is used to mean that two genetic loci (eg, two marker loci, one marker locus, and one locus that affects phenotypic variation) actually exist in the same On the chromosome. The positions of these two loci are usually close together, so recombination between pairs of homologous chromosomes does not occur at high frequency between the two loci. That is, the frequency of recombination occurring between two physically linked loci is less than about 10%, a suitable frequency is less than 5%, and a more suitable frequency is 2% or less, or 1% or less. Thus, two loci located on the same chromosome with a frequency of recombination less than 10% are referred to as proximal to each other.
用於本文之術語「基因圖譜(genetic map)」係描述給定物種中在一或多個染色體(或連鎖群)上基因座之間的基因連鎖關係,通常以圖表或表格的形式描述。「基因定位(mapping)」係透過使用基因標記、標記的族群分離及重組頻率的標準遺傳法則來定義基因座連鎖關係的程序。「圖譜位置(map location)」係為於給定物種中可找到特定標記之對應連結基因標記之處之基因圖譜上的指定位置。The term "genetic map" as used herein describes the genetic linkage between loci on one or more chromosomes (or linkage groups) in a given species, usually in the form of a graph or table. "Mapping" is the process of defining locus linkages through the use of genetic markers, marker population segregation, and standard genetic rules for recombination frequencies. A "map location" is a specified position on a genetic map of a given marker in a given species where a corresponding linked gene marker can be found.
用於本文之術語「基因型(genotype)」係為於一個或多個遺傳基因座上的個體(或個體之群)之基因組成。基因型係由已自其親代繼承而來的個體之一個或多個已知基因座的對偶基因定義。「單倍型(haplotype)」係為於複數個遺傳基因座上之個體的基因型。通常描述為單倍型的基因座為物理性且基因性地連結,換句話說,在相同的染色體斷片上。The term "genotype" as used herein is a genetic component of an individual (or group of individuals) at one or more genetic loci. A genotype is defined by a dual gene of one or more known loci of an individual that has been inherited from its parent. "Haplotype" is the genotype of an individual at a plurality of genetic loci. The loci, which are generally described as haplotypes, are physically and genetically linked, in other words, on the same chromosomal fragment.
若在給定的基因座上僅具有一種類型的對偶基因,此個體為「同型接合(homozygous)」(例如在基因座上帶有相同對偶基因的兩分拷貝之雙倍體個體)。若在給定的基因座上存在不只一種的對偶基因類型,此個體為「異型接合(heterozygous)」(例如雙倍體個體帶有兩個不同的對偶基因各一份拷貝)。術語「同質性(homogeneity)」表示在一個或多個的特定基因座中具有相同的基因型之族群成員。術語「異質性(heterogeneity)」表示在一個或多個的特定基因座的相異基因型族群之個體。If there is only one type of dual gene at a given locus, the individual is a "homozygous" (eg, a diploid individual with a two-copy copy of the same dual gene at the locus). If there is more than one type of dual gene at a given locus, the individual is "heterozygous" (eg, a diploid individual with one copy of each of the two different dual genes). The term "homogeneity" refers to a member of a group having the same genotype in one or more particular loci. The term "heterogeneity" refers to an individual of a distinct genotype group at one or more specific loci.
「系(line)」或「品系(strain)」係為有相同家系的個體之群組,其通常有某種程度上的近親交配且於大多數的基因座上為同型接合及同質的。A "line" or "strain" is a group of individuals with the same family, which usually have some degree of inbreeding and are homozygous and homogenous at most loci.
「菁英系(elite line)」或「菁英品系(elite strain)」係為經過對於優秀農藝表現進行許多培育及選種的週期所產生的基因優秀系。大豆培育所屬技術領域中具有通常知識者已知且可利用許多菁英系。「菁英族群(elite population)」係為菁英系的分類,用以代表給定作物物種(例如油棕櫚)的農藝優秀基因型方面之技術領域的狀態。"Elite line" or "elite strain" is an excellent gene system produced by a cycle of many cultivation and selection of excellent agronomic performance. Soybean cultivation is known to those of ordinary skill in the art and many elite systems are available. The "elite population" is a classification of elite elites that represents the state of the art in the agronomically superior genotype of a given crop species (eg, oil palm).
用於本文之術語「寡核苷酸(oligonucleotide)」意指用於例如雜交探針之短核酸分子、核苷酸排列元件或增幅引子。寡核苷酸係由兩個或多個核苷酸,也就是去氧核糖核苷酸或核糖核苷酸所組成,最好多於5個且至30個或更多。其實際大小取決於許多因素,依次取決於最終功能或寡核苷酸的用途。寡核苷酸可包括成綑的天然核酸分子或合成核酸分子且包括10到150個核苷酸或12到100個核苷酸之間,其具有可以與多型性DNA之股雜交的核苷酸序列,例如以容許多型性的偵測。The term "oligonucleotide" as used herein means a short nucleic acid molecule, a nucleotide alignment element or an amplification primer for use in, for example, a hybridization probe. Oligonucleotides are composed of two or more nucleotides, namely deoxyribonucleotides or ribonucleotides, preferably more than 5 and up to 30 or more. The actual size depends on a number of factors, which in turn depend on the end function or the use of the oligonucleotide. An oligonucleotide may comprise a bundle of natural nucleic acid molecules or synthetic nucleic acid molecules and comprises between 10 and 150 nucleotides or between 12 and 100 nucleotides having a nucleoside that can hybridize to a strand of polymorphic DNA. The acid sequence, for example, allows for the detection of many types.
此寡核苷酸可為用在固體陣列(solid arrays)上的核酸元件(例如合成或做記號)。在本發明優選態樣,此寡核苷酸包括少至12個的雜交核苷酸,例如其中寡核苷酸亦包括可偵測標籤的陣列。在本發明另一優選態樣,寡核苷酸包括少至約15個的雜交核苷酸,例如用以單鹼基延伸排列。Such oligonucleotides can be nucleic acid elements (e.g., synthesized or labeled) for use on solid arrays. In a preferred aspect of the invention, the oligonucleotide comprises as few as 12 hybrid nucleotides, such as an array in which the oligonucleotide also includes a detectable tag. In another preferred aspect of the invention, the oligonucleotide comprises as few as about 15 hybrid nucleotides, for example, arranged in a single base extension.
此種寡核苷酸在聚合酶連鎖反應(PCR)或其他反應中也可當成引子使用。用於本文之術語「引子(primer)」意指核酸分子,尤其是寡核苷酸,特別是從自然存在的分子衍生,像是從限制消化分離出來者,或是合成產生者,當其在能誘發與核酸股互補之引子衍生生成物的合成條件下,換句話說,在存在核苷酸及聚合作用因子例如DNA聚合酶及合適的溫度與pH下,可以作為合成的起始點。為最大化增幅的效率,引子優選為單股的,但可替代性地為雙股。如果為雙股,那麼在用以製備衍生生成物之前要先將其雙股分離處理。引子優選地為寡去氧核糖核苷酸。引子必須要足夠長以能於聚合作用因子存在之下啟動衍生生成物的合成。引子的實際長度取決於許多因素,包括溫度及引子的來源。舉例而言,取決於目標序列的複雜度,寡核苷酸引子通常包含至少15個,優選地為18個核苷酸,其與模板相同或互補;以及選擇性地具有不需要與模板匹配之可變長度的尾部。尾部的長度不應長至妨礙模板的辨識。短的引子分子通常需要較低的溫度以與模板形成足夠穩定的雜交複合體。Such oligonucleotides can also be used as primers in polymerase chain reaction (PCR) or other reactions. As used herein, the term "primer" means a nucleic acid molecule, especially an oligonucleotide, particularly derived from a naturally occurring molecule, such as from a restricted digestion, or a synthetic producer, when Under the synthetic conditions that induce the primer-derived product complementary to the nucleic acid strand, in other words, in the presence of nucleotides and polymerization factors such as DNA polymerase and suitable temperature and pH, it can be used as a starting point for synthesis. To maximize the efficiency of the amplification, the primers are preferably single stranded, but may alternatively be double stranded. In the case of double strands, the double strands are separated prior to being used to prepare the derivative. The primer is preferably an oligodeoxyribonucleotide. The primer must be long enough to initiate synthesis of the derivative product in the presence of a polymerization factor. The actual length of the primer depends on many factors, including the temperature and the source of the primer. For example, depending on the complexity of the sequence of interest, the oligonucleotide primer typically comprises at least 15, preferably 18 nucleotides, which are identical or complementary to the template; and optionally have no need to match the template. Variable length tail. The length of the tail should not be long enough to prevent the identification of the template. Short primer molecules typically require lower temperatures to form a sufficiently stable hybrid complex with the template.
此處所選的引子與每一個待增幅之特定序列的不同股「實質上(substantially)」互補。此意即為引子必須要實質上互補以與它們的各別股雜交。因此引子序列不需要反映模板的具體序列。舉例而言,非互補的核苷酸片段可貼附於引子的5′端,引子序列的剩餘部分與股互補。或者是非互補鹼基或較長的序列可散置於引子中,使引子序列與待增幅之股的序列具有足夠的互補性,以與其雜交,並因此形成用於其他引子衍生生成物的合成之模板。電腦利用程式像是Primer3(www-genome.wi.mit.edu/cgi-bin/primer/primer3.cgi)、STSPipeline(www-genome.wi.mit.edu/cgi-bin/www-STS_Pipeline)或GeneUp產生檢索,舉例而言,可以用以識別潛在的PCR引子。例示性引子包括18至50個鹼基長的引子,其至少有18至25個鹼基與模板序列之斷片的至少18至25個鹼基相同或互補。The primers selected herein are "substantially" complementary to the different strands of each particular sequence to be amplified. This means that the primers must be substantially complementary to hybridize to their respective strands. Therefore, the primer sequence does not need to reflect the specific sequence of the template. For example, a non-complementary nucleotide fragment can be affixed to the 5' end of the primer and the remainder of the primer sequence is complementary to the strand. Alternatively, a non-complementary base or a longer sequence may be interspersed in the primer such that the primer sequence is sufficiently complementary to the sequence of the strand to be amplified to hybridize therewith and thus form a synthesis for other primer-derived products. template. Computer applications like Primer3 (www-genome.wi.mit.edu/cgi-bin/primer/primer3.cgi), STSPipeline (www-genome.wi.mit.edu/cgi-bin/www-STS_Pipeline) or GeneUp A search is generated, for example, to identify potential PCR primers. Exemplary primers include primers of 18 to 50 bases in length that are at least 18 to 25 bases identical or complementary to at least 18 to 25 bases of the fragment of the template sequence.
為了偵測多型性,本發明亦設想並提供用於核酸分子的增幅之引子對。用於本文的「引子對(primer pair)」意指以目標核酸序列的兩個分離序列斷片為基礎之兩個一組的寡核苷酸引子。引子對的其中之一為「順向引子(forward primer)」或「5′引子」,其具有與多於分離序列斷片(+股) 的5′端相同的序列。引子對的另一個為「反向引子(reverse primer)」或「3′引子」,其具有與多餘分離序列斷片(+股)的3′端反向互補的序列。引子對能使分離序列斷片之間的核酸序列增幅及其包括的核酸序列增幅。選擇性的,每個引子對可包括於每個引子5′端的額外序列(例如一般的引子序列或限制性核酸內切酶位), 例如以促進克隆、DNA序列或目標核酸序列的再增幅。To detect polymorphism, the present invention also contemplates and provides primer pairs for amplification of nucleic acid molecules. As used herein, "primer pair" means a set of two oligonucleotide primers based on two separate sequence fragments of a target nucleic acid sequence. One of the pair of primers is a "forward primer" or a "5' primer" having the same sequence as the 5' end of the fragment of the isolated sequence (+ strand). The other pair of primer pairs is a "reverse primer" or a "3' primer" having a sequence complementary to the 3' end of the excess isolated sequence fragment (+ strand). The primer pair is capable of amplifying the nucleic acid sequence between the fragments of the isolated sequence and the nucleic acid sequence thereof. Alternatively, each primer pair can include additional sequences at the 5' end of each primer (eg, a general primer sequence or a restriction endonuclease site), for example, to facilitate cloning, DNA sequence or re-amplification of the target nucleic acid sequence.
用於油棕櫚的上下文之術語「克隆(cloning)」意指選種後棕櫚(原株)的相同拷貝之程序,其拷貝係由帶有合意特徵之tenera 油棕櫚的葉片組織之生長幼苗複製而來。The term "cloning" in the context of oil palm refers to the procedure for the selection of the same copy of the palm (original strain), the copy of which is replicated by the growing seedlings of the leaf tissue of the tenera oil palm with the desired characteristics. Come.
用於本文之「定位族群(mapping population)」係指能夠以標記使用以定位性狀基因位置的作物集合體。As used herein, "mapping population" refers to a collection of crops that can be used with markers to locate the location of a trait gene.
用於本文之「多型性標記(polymorphic marker)」係指能夠偵測一個或多個多型性的標記。As used herein, "polymorphic marker" refers to a marker that is capable of detecting one or more polymorphisms.
本發明提供為標記的核酸分子,也就是能夠偵測散佈於整個定位族群基因組的多型性。The invention provides nucleic acid molecules that are labeled, that is, capable of detecting polymorphisms that are interspersed throughout the entire population of the targeted population.
用於本文之「定性多型性(characterized polymorphism)」係指在基因組上已知其實際位置的多型性。在一個例子中,在分離的核酸分子(像是包括油棕櫚基因體DNA的細菌人工染色體)上的定性多型性之實際位置已知。因此本發明也提供能夠偵測整個基因組中定性多型性的核酸分子。As used herein, "characterized polymorphism" refers to polymorphism in which the actual location of a genome is known. In one example, the actual location of the qualitative polymorphism on an isolated nucleic acid molecule, such as a bacterial artificial chromosome comprising oil palm genomic DNA, is known. The invention therefore also provides nucleic acid molecules capable of detecting qualitative polymorphisms throughout the genome.
在一個例子中,定性多型性為存在於油棕櫚定位族群中的最少兩個多型性之核酸序列為已知(定序定性多型性)之任意多型性。In one example, the qualitative polymorphism is that any of the two polymorphic nucleic acid sequences present in the oil palm locating population is any polymorphism of known (sequencing qualitative polymorphism).
能夠被本發明的核酸分子偵測的多型性以使與表現型性狀相關之基因區域在某種程度上的有效率識別之方式散佈於定位族群的整個基因組。在一個例子中,多型性以每100kb有高於一個的多型性、更好為每50kb有高於一個的多型性、甚至每25kb、10kb、7kb、5kb或3kb有高於一個的多型性的密度,散佈於整個基因組,其基因組的60%、更好為70%、更加好為80%、甚至90、95或100%具有定性多型性。在另一例中,多型性以每3.5cM有高於一個的多型性、更好為每3.25cM有高於一個的多型性、甚至每3cM、2.75cM、2.5cM、2.0cM、1.5cM、1.0cM或0.5cM有高於一個的多型性的密度,散佈於整個基因組,其基因組的60%、更好為70%、更加好為80%、甚至90、95或100%具有定性多型性。The polymorphisms that can be detected by the nucleic acid molecules of the present invention are such that the regions of the genes associated with the phenotypic traits are dispersed to the entire genome of the localized population in a manner that is efficiently recognized to some extent. In one example, polymorphism has more than one polymorphism per 100 kb, more preferably more than one polymorphism per 50 kb, even more than one per 25 kb, 10 kb, 7 kb, 5 kb or 3 kb. The density of polymorphism is spread throughout the genome, with 60%, more preferably 70%, even better 80%, or even 90, 95 or 100% of the genome having qualitative polymorphism. In another case, polymorphism has more than one polymorphism per 3.5 cM, more preferably more than one polymorphism per 3.25 cM, even every 3 cM, 2.75 cM, 2.5 cM, 2.0 cM, 1.5 cM, 1.0 cM or 0.5 cM has a density of more than one polymorphism, spread over the entire genome, with 60%, more preferably 70%, even better 80%, or even 90, 95 or 100% of the genome. Polymorphic.
在一個例子中,揭露與表現型性狀(例如QTL或單一基因)相關之基因區域的有效率識別,其中基因區域自定性多型性小於100kb,更好為小於50kb,甚至小於25kb、10kb、7kb、5kb或3kb。在另一例中,與表現型性狀相關之基因區域的有效率識別,基中因區域自定性多型性小於3.5cM、更好為小於3.25cM、甚至小於3cM、2.75cM、2.5cM、2.0cM、1.5cM、1.0cM或0.5cM。In one example, efficient identification of gene regions associated with phenotypic traits (eg, QTLs or single genes) is disclosed, wherein the gene region has a self-determining polymorphism of less than 100 kb, more preferably less than 50 kb, or even less than 25 kb, 10 kb, 7 kb, 5 kb or 3 kb. In another case, the efficient identification of the gene region associated with the phenotypic trait, the regional self-determination polymorphism is less than 3.5 cM, more preferably less than 3.25 cM, or even less than 3 cM, 2.75 cM, 2.5 cM, 2.0. cM, 1.5 cM, 1.0 cM or 0.5 cM.
要理解的是,多型性的分佈在基因組中須為不平均的,某些區域會顯現較高平均密度的多型性(例如非中節區域),而某些區域會顯現較低平均密度的多型性(例如中節區域)。It is to be understood that the distribution of polymorphisms must be uneven in the genome, some regions will exhibit higher average density polymorphism (eg, non-middle region regions), and some regions will exhibit lower average density. Polymorphism (eg mid-section area).
在一個例子中,與感興趣的表現型性狀相關之基因區域的有效率識別係由同時篩查25個或以上、更好為50個或以上、甚至75個或以上、100個或以上、150個或以上、200個或以上、250個或以上、300個或以上、400個或以上、500個或以上、1,000個或以上、2,000個或以上、3,000個或以上或4,000個或以上多型性之存在來獲得。當利用高處理量的檢測(例如以微陣列)時,其可處理篩查5000個或以上(例如最少10,000或甚至15,000個多型性)多型性之存在的篩查。在另一例中,與感興趣的表現型性狀相關之基因區域的有效率識別將由同時篩查25個或以上、更好為50個或以上、甚至(恰當的)100個或以上或250個或以上等多型性之存在來獲得。In one example, the efficient identification of a gene region associated with a phenotypic trait of interest is simultaneously screened by 25 or more, more preferably 50 or more, or even 75 or more, 100 or more, 150 One or more, 200 or more, 250 or more, 300 or more, 400 or more, 500 or more, 1,000 or more, 2,000 or more, 3,000 or more, or 4,000 or more polytypes The existence of sex comes to be obtained. When utilizing high throughput assays (e.g., in a microarray), it can process screening for the presence of 5,000 or more (e.g., at least 10,000 or even 15,000 polymorphism) polymorphisms. In another example, the efficient identification of the region of the gene associated with the phenotypic trait of interest will be simultaneously screened for 25 or more, more preferably 50 or more, or even (appropriate) 100 or more or 250 or The above polymorphism exists to obtain.
「分子標記輔助選種(Marker Assisted Selection, MAS)」意指利用基因標記在培育族群中選擇合意表現型的進行。"Marker Assisted Selection (MAS)" means the use of genetic markers to select desirable phenotypes in an cultivating population.
「雜交作物(hybrid plants)」意指由基因相異的個體之間雜交出來的作物。"Hybrid plants" means crops that are crossed by individuals with different genes.
用於本文之術語「雜交(crossed or cross)」意指配子的結合,例如藉由授粉作用產生子代(也就是細胞、種子或作物)。此術語包含有性雜交(一作物藉由另一作物的授粉作用)及自花授粉(自我授粉,也就是當花粉及胚珠皆來自同一作物時)。As used herein, the term "crossed or cross" means the binding of a gamete, for example by pollination to produce progeny (i.e., cells, seeds or crops). This term encompasses sexual crosses (a pollination of one crop by another) and self-pollination (self-pollination, ie when both pollen and ovules are from the same crop).
在另一例中,與感興趣的表現型性狀相關之基因區域的有效率識別將於單一檢測期間篩查25個或以上,更好為50個或以上,甚至75個或以上、100個或以上、150個或以上、200個或以上、250個或以上、300個或以上、400個或以上、500個或以上、1,000個或以上、2,000個或以上、3,000個或以上或4,000個或以上多型性之存在來獲得。在又另一例中,與感興趣的表現型性狀相關之基因區域的有效率識別係由經過單一檢測期間篩查25個或以上,更好為50個或以上,甚至(恰當的)100個或以上或250個或以上等等的多型性之存在來獲得。單一檢測包括許多步驟,一個或多個此些步驟可依序發生。In another example, efficient identification of gene regions associated with phenotypic traits of interest will be screened for 25 or more, preferably 50 or more, or even 75 or more, 100 or more, during a single assay. , 150 or more, 200 or more, 250 or more, 300 or more, 400 or more, 500 or more, 1,000 or more, 2,000 or more, 3,000 or more, or 4,000 or more The existence of polymorphism is obtained. In yet another example, the efficient identification of the gene region associated with the phenotypic trait of interest is screened by 25 or more, preferably 50 or more, or even (appropriate) 100 or The above or the presence of 250 or more polymorphisms is obtained. A single test involves many steps, and one or more of these steps can occur sequentially.
在某些例子中,此檢測可利用高處理量系統來執行。高處理量系統可涉及固相陣列,在一個例子中,此固相陣列可包括微陣列。In some examples, this detection can be performed using a high throughput system. High throughput systems can involve a solid phase array, which in one example can include a microarray.
在下述的檢測中,多型性標記的集合體包括少量至數百萬不同的核酸分子。舉例而言,利用簡單的點墨雜交法便可產生帶有許多核酸分子的薄膜以用於篩查。描述於以下且為該領域所知悉的固相技術可用作為多型性的高處理量監測。在這些方法中,不同的固定化核酸分子探針以每平方英吋高達數百萬核酸分子的密度設置於微陣列的固態載體上。同樣地靠著一個或多個的探針,相當大量的核酸分子組可被固定以同時篩查。In the assays described below, the collection of polytype markers includes small to millions of different nucleic acid molecules. For example, a thin film with a plurality of nucleic acid molecules can be produced for screening using a simple dot-and-ink hybridization method. Solid phase techniques, described below and known in the art, can be used as high throughput monitoring for polymorphism. In these methods, different immobilized nucleic acid molecule probes are placed on the solid support of the microarray at a density of up to several million nucleic acid molecules per square inch. Also with one or more probes, a relatively large number of sets of nucleic acid molecules can be immobilized for simultaneous screening.
用於本文之術語「增加(increase)」及「減少(decrease)」意指在族群子集合中選定特徵比起存在於整體族群之同一特徵的相對改變。因此增加表示規模的正向變化,而減少表示規模的負向變化。用於本文之術語「變化(change)」也意指獨立族群子集合的選定特徵比起整體族群之同一特徵的差異。然而此術語不用於計算其差異。As used herein, the terms "increase" and "decrease" mean the relative change in a selected feature in a subset of a population compared to the same feature present in the overall population. Therefore, the positive change in scale is increased, and the negative change in scale is reduced. The term "change" as used herein also means that the selected features of the independent ethnic sub-set differ from the same features of the overall ethnic group. However, this term is not used to calculate the difference.
「實質上(substantially)」並不排除「完全地(completely)」,例如某合成物「實質上不含」Y有可能為完全不含Y。必要時,「實質上」可從本發明的定義中省略。"Substantially" does not exclude "completely". For example, a composition "substantially free" Y may be completely free of Y. "Substantially" may be omitted from the definition of the present invention as necessary.
除非特別說明,否則術語「包括(comprising/comprise)」及其文法的變體皆意圖表示「開放」或「包含」的語法,使其不只包含所述的元件,也允許包含額外、未被提及的元件。Unless specifically stated otherwise, the terms "comprising/comprise" and variations of the grammar are intended to mean "open" or "contained" grammar so that they contain not only the elements but also additional, unmentioned And components.
本文之術語「大約(about)」用於配方成分之濃度的上下文時,通常意指為所述數據的+/- 5%、更常見的是+/- 4%、更常見的是+/- 3%、更常見的是+/- 2%、更常見的甚至是+/- 1%及更常見的甚至是+/- 0.5%。As used herein, the term "about", when used in the context of the concentration of a formulation ingredient, generally means +/- 5% of the data, more commonly +/- 4%, more commonly +/- 3%, more commonly +/- 2%, more common even +/- 1% and more commonly even +/- 0.5%.
於整篇本揭露中,某些實施方式可以範圍的格式揭露。要理解的是範圍格式的敘述僅是為了方便及簡潔,不應當作為對揭露範圍之不可改變的限制。因此範圍中的敘述應被認為是具有明確揭露的全部可能次範圍以及其範圍中的單體數值。舉例而言,像是1至6的敘述應被認為是具有明確揭露的次範圍像是1至3、1至4、1至5、2至4、2至6、3至6等等以及其範圍的單獨數值,例如1、2、3、4、5及6。不論其範圍多廣皆可適用。Throughout this disclosure, certain embodiments may be disclosed in a range format. It is to be understood that the description of the range format is for convenience and conciseness and should not be construed as an unrestricted limitation of the scope of the disclosure. The recitations in the range are therefore to be considered as all the sub-ranges that are explicitly disclosed and the singular values in the range. For example, statements such as 1 through 6 should be considered to have a clearly disclosed sub-range such as 1 to 3, 1 to 4, 1 to 5, 2 to 4, 2 to 6, 3 to 6, etc. and Individual values for ranges, such as 1, 2, 3, 4, 5, and 6. It can be applied regardless of its scope.
某些實施方式也可廣泛且概括地敘述於本文中。落入一般揭露的縮限的物種及次屬之群的每一個亦形成該揭露組成的一部分。這包括那些具有從種類移除任何物件之但書或負面限制的一般揭露,不論其除去的物質在本文中是否有被明確地提及。Certain embodiments are also broadly and broadly described herein. Each of the species and sub-groups that fall within the general disclosure limits form part of the disclosure. This includes general disclosures of books or negative limitations that remove any item from the species, whether or not the substance removed therefrom is specifically mentioned herein.
本發明的詳細敘述Detailed description of the invention
分子類方法為關聯性定位,其不需要利用子代即可偵測連接標記的性狀。相較於僅考慮在親代傳遞給子代時發生之減數分裂的連鎖定位,關聯性定位更優秀的顧及了在遙遠過去便已建立的關聯,其包括數個世代的減數分裂。此讓關聯性定位提供了更高的分辨度或偵測能力以識別標記與表現型之間的連結。Molecular methods are associative positioning, which does not require the use of progeny to detect the properties of the connected markers. Compared to considering only the linkage of meiosis that occurs when the parent is passed on to the offspring, the relevance of the association is better considering the associations that have been established in the distant past, including meiosis of several generations. This allows associative positioning to provide higher resolution or detection capabilities to identify links between markers and phenotypes.
關聯性定位已被用於尋找與人類疾病相關的標記以及一些作物像是玉蜀黍(Zea mays ,L .)、大豆(Glycine max (L.) Merr. )、大麥(Hordeum vulgare L. )、小麥(Triticum aestivum L. )、番茄(Lycopersicon esculentum Mill. )、高粱(Sorghum bicolor (L.) Moench )及馬鈴薯(Solanum tuberosum L. ),還有一些樹種像是白楊類(Populus tremula L. )及火炬松(Pinus taeda L. )中。Relevance positioning mark and have been used to find a number of human diseases associated with crops such as maize (Zea mays, L.), Soybean (Glycine max (L.) Merr. ), Barley (Hordeum vulgare L.), wheat ( Triticum aestivum L. ), tomato ( Lycopersicon esculentum Mill. ), sorghum bicolor (L.) Moench and potato ( Solanum tuberosum L. ), and some species like Populus tremula L. and Pinus taeda ( Pinus taeda L. ).
在此揭露中,油棕櫚的族群可包括具有不同遺傳背景的油棕櫚族群。舉例而言,油棕櫚族群可包括但不侷限於,限制起源的培育族群(breeding populations of restricted origins, BPRO),像是東蘇門答臘橡膠園主聯合總會(Algemene Vereniging van Rubberplanters ter Oostkust van Sumatra, AVROS)、德里(Deli)、揚甘比(Yangambi)、喀麥隆(Cameroon)、埃科納(Ekona)、卡拉巴爾(Calabar)及其組合。此族群可根據其結構,因為地理因素、天擇或人擇而被挑選。對關聯性定位而言,給定的樣本可落入由族群結構定義出的五個種類之一,族群結構與區域性適應、多樣性天擇和來自最接近共同祖先之家族關聯性有關。理想上,帶有最小族群結構或家族關聯性的樣本產生最大的統計能力,提供散佈良好的感興趣性狀。In this disclosure, the population of oil palms can include oil palm populations with different genetic backgrounds. For example, oil palm populations may include, but are not limited to, breeding populations of restricted origins (BPRO), such as the Algemene Vereniging van Rubberplanters ter Oostkust van Sumatra, AVROS ), Delhi (Deli), Yangambi, Cameroon, Ekona, Calabar, and combinations thereof. This group can be selected based on its structure, because of geographic factors, natural choices, or choices. For associative positioning, a given sample can fall into one of the five categories defined by the ethnic structure, which is related to regional adaptation, diversity of natural selection, and family relevance from the closest common ancestor. Ideally, samples with minimal ethnic structure or family association produce the greatest statistical power and provide well-distributed traits of interest.
提供表現型資料收集的期間作為下述的例子,且可以想見收集資料的其它時間段被用於此程序。舉例而言,表現型資料的收集期間可能為三個月或以上、更好為六個月或以上、甚至九個月或以上、十二個月或以上、十八個月或以上、二十四個月或以上、三十六個月或以上、四十五個月或以上、六十個月或以上以測量、收集和分析表現型資料。在某些例子中,表現型資料收集為四十五個月。在更進一步的例子中,表現型資料收集為五十四個月。The period during which phenotypic data collection is provided is exemplified below, and other time periods in which data are collected may be used for this procedure. For example, the collection period of phenotypic data may be three months or more, more preferably six months or more, or even nine months or more, twelve months or more, eighteen months or more, twenty The phenotypic data were measured, collected and analyzed for four months or more, thirty-six months or more, forty-five months or more, sixty months or more. In some cases, phenotypic data was collected for forty-five months. In a further example, phenotypic data was collected for fifty-four months.
在某些例子中,表現型用於分析並連結作物中(像是油棕櫚)之一個或多個多型性基因標記,可包括但不侷限於新鮮果串產量、串之數目、樹幹高度、疾病抗性、種子樹木、高度增量、油之成分、油之含量、胡蘿蔔素含量、維生素E/參雙鍵生殖酚、作物的量測及類似。任何可量測之數量的或品質的性狀皆可作為表現型資料。In some instances, the phenotype is used to analyze and link one or more polymorphic genetic markers in a crop (such as oil palm), which may include, but are not limited to, fresh fruit bunch yield, number of strands, trunk height, Disease resistance, seed trees, height increments, oil components, oil content, carotene content, vitamin E/double bond retort, crop measurements and the like. Any measurable quantity or quality trait can be used as phenotypic data.
在某些例子中,描述如本文所述之方法,其中該方法進一步地包括對於感興趣的表現型及表現型資料已記錄之作物的遺傳物質的基因型,從至少一作物物種之作物群紀錄表現型資料的步驟。In certain instances, a method as described herein is described, wherein the method further comprises a genotype of genetic material of the crop that has been recorded for the phenotypic and phenotypic data of interest, from a crop group record of at least one crop species Steps for phenotypic data.
對於數量性狀而言,數量傳遞不平衡檢測(Quantitative Transmission Disequilibrium Test, QTDT)用於關聯性定位係為所屬技術領域中具有通常知識者所熟悉。物種中增大且對偶多樣性更廣的樣本通常含有族群結構或帶有建構族群的家族關係。For quantitative traits, the Quantitative Transmission Disequlibrium Test (QTDT) is used in association locating systems to be familiar to those of ordinary skill in the art. Samples that are larger in species and more diverse in their duality usually contain a population structure or a family relationship with a constructed population.
此方法可適用於任何可觀察或測量到的表現型類型。在需要減少感興趣的性狀而非增加的情況中,用以預測效應的標記將以負數來取代。This method can be applied to any phenotype that can be observed or measured. In cases where it is desirable to reduce the trait of interest rather than increase, the marker used to predict the effect will be replaced by a negative number.
本發明進一步地描述了可以個別地或合併地用以預測或判定作物(像是應用於油棕櫚)的表現型性狀之基因標記組的發展。這種對於尚不明顯之表現型的早期預測或判定的執行是為了幫助已判定為有益之表現型種類作物的選種,從而使減少培育所需時間且減少培育過程花費成為可能。The present invention further describes the development of a panel of genetic markers that can be used individually or in combination to predict or determine phenotypic traits of a crop, such as that applied to oil palm. This early prediction or determination of phenotypes that are not yet apparent is to aid in the selection of phenotypic crops that have been determined to be beneficial, thereby making it possible to reduce the time required for cultivation and reduce the cost of the cultivation process.
在某些例子中,於敘述的方法中,其中用以識別多型性標記的作物材料係由至少兩個、至少三個或至少四個或以上具有不同遺傳背景之相同物種的不同作物族群獲得。有利的是,本發明發現利用包含不同遺傳背景,能提升其分辨標記連結至性狀的能力。In some examples, in the method recited, wherein the crop material used to identify the polymorphic marker is obtained from at least two, at least three, or at least four or more different crop populations of the same species having different genetic backgrounds. . Advantageously, the present invention finds the ability to enhance the ability of its distinguishing markers to be linked to a trait by utilizing a different genetic background.
在一個例子中,描述了與感興趣的表現型連結作物物種的多型性基因標記的識別方法,其中該方法包括由關聯性定位識別就作物及感興趣表現型而言已識別的多型性標記之間統計上顯著的連結;選出在以下發現之標記 a)被連結至感興趣的表現型,其對感興趣的表現型,不論是負向或正向具有最顯著的效應,其係藉由判定每一個以識別之標記的效果大小下, a)並選出對感興趣表現型具有最正向或最負向效應。In one example, a method of identifying a polymorphic genetic marker for a phenotype-linked crop species of interest is described, wherein the method includes identifying the polymorphism identified for the crop and the phenotype of interest by relevance mapping. A statistically significant link between the markers; the marker found in the following is selected a) to be linked to the phenotype of interest, which has the most significant effect on the phenotype of interest, whether negative or positive, By determining the effect size of each of the identified markers, a) and selecting the most positive or negative effect on the phenotype of interest.
在另一例中,揭露了用以預測或判定感興趣之作物表現型的方法,其方法包括偵測一個或多個的多型性基因標記存在與否,其基因標記包括但不侷限於SEQ ID NOs. 1至115。在另一例中,此方法包括偵測兩個或多個、三個或多個、四個或多個、五個或多個、六個或多個、七個或多個、八個或多個、九個或多個、十一個或多個或全部的多型性基因標記存在與否,基因標記包括但不侷限於SEQ ID NOs. 1至115。在另一例中,基因標記包括但不侷限於標記號1 (SEQ ID NO. 10)、2(SEQ ID NO. 20)、3(SEQ ID NO. 13)、4(SEQ ID NO. 8)、5(SEQ ID NO. 19)、6(SEQ ID NO. 34)、7(SEQ ID NO. 90)、8(SEQ ID NO. 105)、9(SEQ ID NO. 106)、10(SEQ ID NO. 99)及11(SEQ ID NO. 80)。In another example, a method for predicting or determining a phenotype of a plant of interest is disclosed, the method comprising detecting the presence or absence of one or more polymorphic gene markers, including but not limited to SEQ ID NOs. 1 to 115. In another example, the method includes detecting two or more, three or more, four or more, five or more, six or more, seven or more, eight or more The presence or absence of one, nine or more, eleven or more or all of the polytype gene markers including, but not limited to, SEQ ID NOs. 1 to 115. In another example, the gene signature includes, but is not limited to, marker number 1 (SEQ ID NO. 10), 2 (SEQ ID NO. 20), 3 (SEQ ID NO. 13), 4 (SEQ ID NO. 8), 5 (SEQ ID NO. 19), 6 (SEQ ID NO. 34), 7 (SEQ ID NO. 90), 8 (SEQ ID NO. 105), 9 (SEQ ID NO. 106), 10 (SEQ ID NO 99) and 11 (SEQ ID NO. 80).
用於本文之術語「預測(predicting)」或「預測(prediction)」定義為預先陳述或使某事物被預先知悉,特別是使用推論或專門知識。在此意指聚有此知識讓所屬技術領域中具有通常知識者在關於特定作物之多型性基因標記之位置與數量上能夠預測此特定作物成熟時是否能夠表現出推導的表現型。The term "predicting" or "prediction" as used herein is defined to pre-state or make something known in advance, particularly using inferences or expertise. It is hereby meant that this knowledge is gathered to enable a person of ordinary skill in the art to be able to predict whether a particular crop can exhibit a deduced phenotype when the location and number of polymorphic gene markers for a particular crop are predicted.
用於本文之術語「判定(determining)」或「判定(determination)」定義為藉由研究或計算準確地查明或證實某事物。在此情況中,感興趣的作物表現型之判定係為作物樣本之基因分析的直接結果。The term "determining" or "determination" as used herein is defined as the precise identification or verification of something by research or calculation. In this case, the determination of the crop phenotype of interest is a direct result of the genetic analysis of the crop sample.
在進一步的例子中,揭露了如同前述的方法,其作物為油棕櫚。此外在另一例中,如同前面所揭露的,油棕櫚為Elaeis 屬。在另一例中,如同前面所揭露的屬係由dura 及tenera 組成。在另一例中,如同前面所揭露的屬係由變異pisifera 組成。用於本文之生物術語「類型(form)」定義為第二分類等級,第二分類等級在品種之下,而品種之順位在物種之下。當用於該技術領域時,類型通常用來標示出帶有顯而易見卻較不重要之歧異的群體。舉例而言,通常具有彩色花朵之物種中的白花類型可被命名為「f. alba」。用於本文之生物術語「品種(variety)」定義為在物種之下的分類等級,但在類型之上。品種與其他品種呈現差異,但是當被帶往與其他品種接觸時,可不受限制地雜交且產生後代。一般而言,物種彼此為地理上地分離。In a further example, a method as described above is disclosed, the crop of which is oil palm. Further in another example, as previously disclosed, the oil palm is of the genus Elaeis . In another example, the genus as disclosed above consists of dura and tenera . In another example, the genus as disclosed above consists of a variant pisifera . The biological term "form" as used herein is defined as the second classification level, the second classification level is below the variety, and the breed order is below the species. When used in this field of technology, types are often used to identify groups with obvious but less important differences. For example, a white flower type in a species that usually has colored flowers can be named "f. alba." The biological term "variety" as used herein is defined as the classification level below the species, but above the type. Varieties differ from other varieties, but when brought into contact with other species, they can cross without restriction and produce offspring. In general, species are geographically separated from one another.
任何培育計畫的終極目標皆為盡可能多地結合有利對偶基因使其進入相較於其祖先基因上較優秀(就一個或多個的農藝性狀而言)的種源菁英品種。本文描述的標記識別染色體斷片,也就是基因區域及對偶基因(對偶形式)其經過長期選種有利於產量。因此,這些標記可用於帶有優秀農藝成果之油棕櫚作物的分子標記輔助選種。舉例而言,在目標基因座上互補有利對偶基因的親代之間的雜交,可選出比親代包含更多有利對偶基因的子代。我們預測這些子代表現型地優於親代。舉例而言,實際上,培育之後,本文揭露的方法可用於藉由從所述作物取樣、分析多型性基因標記存在與否及根據此些標記與之前已識別的標記和它們已知的表現型做的比較,來測試它們是否顯現出選擇的表現型,並且預測這些特定的作物在成長期間或成熟時是否會顯現合意的表現型。The ultimate goal of any breeding program is to combine as much of the beneficial dual genes as possible into a species of elite elite that is superior to its ancestral genes (in terms of one or more agronomic traits). The markers described herein identify chromosome fragments, that is, gene regions and dual genes (dual forms) that are favored for yield through long-term selection. Therefore, these markers can be used for molecular marker-assisted selection of oil palm crops with excellent agronomic achievements. For example, hybridization between parental counterparts of a favorable dual gene at a locus of interest may select progeny that contain more favorable dual genes than the parent. We predict that these offspring are phenotypically superior to the parent. For example, in practice, after incubation, the methods disclosed herein can be used to sample or analyze the presence or absence of a polymorphic genetic marker from the crop and based on such markers and previously identified markers and their known expressions. Types are compared to test whether they exhibit a selected phenotype and predict whether these particular crops will exhibit a desirable phenotype during growth or maturity.
對於受限的子代棕櫚而言,偵測與性狀連結的標記的分辨度減少且以分摩(centimorgans, cM)為單位表示的標記距離變大,從而使標記的預測能力減弱。包含更多的標記會增加標記落於分辨度限制之內的機率但不會減少其分辨能力。這是由於連鎖定位方法本身的限制,其透過減數分裂現象及對其於子代與親代棕櫚之間進行比較,來偵測基因交換。For restricted progeny palms, the resolution of the markers linked to the traits is reduced and the marker distance expressed in units of centimorgans (cM) is increased, thereby reducing the predictive power of the markers. Including more markers increases the chance that the marker falls within the resolution limit without reducing its resolution. This is due to the limitations of the linkage localization method, which detects gene exchange through meiosis and comparison between progeny and parental palm.
為了克服這個問題,將高代互交系(advanced intercross lines),像是第六或更高的世代雜交,應用於其他作物的作物改良計畫。然而這些作物改良計畫並不適用於油棕櫚,因為這會花上數百年去產生這些雜合作用線。To overcome this problem, advanced intercross lines, such as the sixth or higher generation, are crossed to apply to crop improvement programs for other crops. However, these crop improvement programs are not applicable to oil palm, as it will take hundreds of years to produce these hybrid lines.
在油棕櫚中使用連鎖定位導致了基因標記的發展及識別,基因標記與感興趣的性狀統計性地連結且用於篩查。此方法藉由能夠進行早期階段的篩查來促進培育並增加預測性狀的準確度,從而縮短了培育過程的週期時間以及減少其花費。The use of linkage targeting in oil palm results in the development and identification of gene markers that are statistically linked to the trait of interest and used for screening. This method facilitates nurturing and increases the accuracy of predictive traits by enabling early stage screening, thereby reducing the cycle time of the incubation process and reducing its cost.
使用本發明的標記的分子標記輔助選種(MAS)及其識別的染色體斷片,在例如油棕櫚培育計畫的情境中有助於增加產量改良效率。用於大量樣本之感興趣之性狀,像是產量的表現型,篩查可昂貴且耗時。此外,由於上位作用和對表現型的非基因(例如環境)作用效應,單單採用表現型篩查通常是不可靠的。MAS提供了在田野評估方面的優點,其可不考慮生長季或發育階段地在年間的任何時間執行。此外,MAS有助於在分離區域或不同條件下的生物成長評估。The use of the labeled molecular marker-assisted selection (MAS) of the present invention and its identified chromosomal fragments, in the context of, for example, an oil palm cultivating program, contributes to increased yield improvement efficiency. For traits of interest for large numbers of samples, such as phenotypes of yield, screening can be expensive and time consuming. In addition, phenotypic screening alone is often unreliable due to epistatic effects and non-genetic (eg, environmental) effects on phenotypes. MAS provides advantages in field assessment that can be performed at any time of the year regardless of the growing season or developmental stage. In addition, MAS contributes to the assessment of biological growth in isolated areas or under different conditions.
想要培育具有增加產量之油棕櫚的具有通常知識的培育者,可採用本文敘述的MAS方法,使用例如本文敘述的例示性標記或定位於藉由以下表1及表2所列的標記所識別的染色體斷片的連結標記,以衍生出帶有較優秀農藝表現的油棕櫚品系。Breeders with the usual knowledge of cultivating oil palms with increased yield can be identified using the MAS methods described herein, using, for example, the exemplary markers described herein or positioned by the markers listed in Tables 1 and 2 below. The chromosomal fragment is linked to the oil palm line with superior agronomic performance.
基因標記對偶基因、連結標記、QTL、包含對產量很重要的遺傳元件的識別染色體斷片被用以識別作物,其在一個或多個的基因座包含合意基因型,並被預期傳遞此合意基因型,隨著合意表現型一同傳遞至其子代。標記對偶基因(或QTL對偶基因)可用以識別作物,其在一個基因座或在數個之未連結或已連接的基因座(例如單倍型)上包含合意基因型,並被預期傳遞此合意基因型,伴隨著合意表現型一同傳遞至其子代。同樣地,藉由識別缺少了合意對偶基因的作物,可識別出帶有非合意的表現型(例如低產量的作物)的作物,並例如,將其從後續的雜交移除。需要意識到的是,對於MAS的用途來說,術語「標記(marker)」同時包含了標記及QTL基因座,當其皆可用以識別帶有合意性狀的作物時。Gene-tagged dual genes, linked markers, QTLs, recognition chromosomal fragments containing genetic elements important for yield are used to identify crops that contain a desired genotype at one or more loci and are expected to deliver this desired genotype , along with the desired phenotype, passed to its offspring. A marker dual gene (or QTL dual gene) can be used to identify a crop that contains a desired genotype at a locus or at several unlinked or linked loci (eg, haplotypes) and is expected to deliver this consensus. The genotype is passed along with the desired phenotype to its offspring. Likewise, by identifying a crop lacking a desirable dual gene, crops with undesired phenotypes (e.g., low yield crops) can be identified and removed, for example, from subsequent hybridization. It will be appreciated that for the use of MAS, the term "marker" encompasses both the marker and the QTL locus, all of which can be used to identify crops with desirable traits.
在合意表現型及多型性染色體基因座(例如標記基因座或QTL)被判定為一起分離(也就是判定為連鎖相失衡)之後,便可選出對應於合意表現型的對偶基因。簡單地說,與標記核酸對應的核酸在被挑選的作物之生物樣本上被偵測。此偵測行為可採取探針核酸對標記的雜交形式,例如使用對偶基因特定雜交(allele-specific hybridization)、南方墨點法(Southern analysis)、北方墨點法(Northern analysis)、原位雜交法(in situ hybridization)、引子雜交後由包含標記產物的PCR增幅或類似。生物樣本中特定標記的存在與否確認之後,便可挑選作物並選擇性地雜交以產生子代作物。After the desired phenotype and polymorphic chromosomal loci (eg, marker loci or QTL) are determined to be isolated together (ie, determined to be a linkage phase imbalance), a dual gene corresponding to the desired phenotype can be selected. Briefly, the nucleic acid corresponding to the labeled nucleic acid is detected on the biological sample of the selected crop. This detection behavior may take the form of hybridization of the probe nucleic acid to the label, for example, using allele-specific hybridization, Southern analysis, Northern analysis, in situ hybridization. ( in situ hybridization), amplification of the primers by PCR containing the labeled product or similar. After confirmation of the presence or absence of a particular marker in a biological sample, the crop can be selected and selectively hybridized to produce a progeny crop.
當族群因為影響一個或多個性狀之多個基因座分離時(例如與單一疾病抗性有關之多個基因座或與不同的疾病抗性有關之各多個基因座),MAS的效率相較起表現型篩查來得更加優秀,因為從單一DNA樣本而來的全部基因座可以在實驗室中一起處理。因此於培育過程中的每一個性狀的標記訊息是便利的。When a population is separated by multiple loci that affect one or more traits (eg, multiple loci associated with a single disease resistance or multiple loci associated with different disease resistance), the efficiency of MAS is comparable Phenotypic screening is even better because all loci from a single DNA sample can be processed together in the lab. Therefore, the marking information of each personality in the cultivation process is convenient.
要意識到的是作物(對本發明的標記為正向)可以根據與特定培育計畫相關的任何培育協定來選種及雜交。因此子代可由選定的作物產生,其藉由將選定的作物與根據相同或不同標記選定的一個或多個額外的作物雜交而來,例如與優秀農藝表現相關的不同標記或不同的感興趣之表現型(例如對於特定疾病的抗性)。或者是選定的作物可以回頭去與一個或兩個親代雜交。It will be appreciated that crops (marked positive for the present invention) can be selected and hybridized according to any incubation protocol associated with a particular breeding program. Thus progeny can be produced from selected crops by crossing selected crops with one or more additional crops selected according to the same or different markers, such as different markers associated with superior agronomic performance or different interests of interest. Phenotype (eg resistance to a particular disease). Or the selected crop can go back to hybridize with one or two parents.
逆代雜交(Backcrossing)通常是為了將來自供體親代的一或多個基因座基因滲入來自輪迴親代(通常為菁英)之其他的合意遺傳背景 。執行越多次的逆代雜交週期,輪迴親代對所得品種的遺傳效應就越大。被選定的作物也可與例如不存在於其系譜的作物或品系異交。這樣的作物可從受到前一輪分析的族群中選出,或重新導入培育計畫之中。合意標記為正向的作物也可自交(selfed)產生出帶有相同基因型的標準培育品系。Backcrossing is typically used to infiltrate one or more locus genes from the donor parent into other desirable genetic backgrounds from the recurrent parent (usually elite). The more repeated the reverse hybridization cycle, the greater the genetic effect of the recurrent parent on the resulting variety. The selected crop can also be outcrossed with, for example, crops or lines that are not present in its pedigree. Such crops can be selected from the population that was analyzed in the previous round or reintroduced into the breeding program. Crops that are desirably labeled as positive can also self-produce a standard breeding line with the same genotype.
在某些例子中,如同本文所述之方法,其中多型性標記為來自油棕櫚來的多型性標記。本發明所用的標記為單核苷酸多型性(SNP)標記,不過此方法可應用於所屬技術領域中具有通常知識者所熟知之任何基因標記。In certain instances, such as the methods described herein, wherein the polytype marker is a polymorphic marker from oil palm. The markers used in the present invention are single nucleotide polymorphism (SNP) markers, although this method can be applied to any gene marker well known to those of ordinary skill in the art.
本文描述了基因標記的一些例子。在某些例子中,存在如同本文所述之方法,其中多型性基因標記為SNPs(單核苷酸多型性)、SSRs(簡單序列重複)、AFLPs(增幅片段長度多型性)、RAPDs(隨機擴增多型性DNA)及其組合。This article describes some examples of gene markers. In some instances, there are methods as described herein in which polymorphic genes are labeled as SNPs (single nucleotide polytype), SSRs (simple sequence repeats), AFLPs (amplified fragment length polymorphism), RAPDs (random amplified polymorphic DNA) and combinations thereof.
在一個例子中,存在如同本文所述之方法,其多型性基因標記為SNPs(單核苷酸多型性)。In one example, there is a method as described herein in which the polymorphic gene is labeled as SNPs (single nucleotide polytype).
在一個例子中,一個或多個多型性基因標記存在與否係於包含遺傳物質的作物樣本中判定,其中樣本材料係選自於由葉、嫩莖葉、莖、幼樹、根、芽、花、種子及果實組成之群組。In one example, the presence or absence of one or more polymorphic gene markers is determined in a crop sample comprising genetic material selected from the group consisting of leaves, tender stems, stems, saplings, roots, shoots a group of flowers, seeds, and fruits.
替代的方法,也可執行像是利用與合適的分析步驟配合之不同的標記以識別顯示出可以用以進一步的分析的叢集型樣之標記。這些例子為SSR標記、AFLP標記、RAPD標記及其他已知的基因標記。Alternative methods may also perform the use of different markers in conjunction with appropriate analysis steps to identify markers that display cluster patterns that can be used for further analysis. These examples are SSR markers, AFLP markers, RAPD markers, and other known gene markers.
一但族群及標記被選定,描述執行QTL分析的方法。在某些例子中,可雜交母株,產生異型接合(F1 )的個體,且這些個體接著如前述一樣地雜交。最後將衍生 (F2 )族群之表現型及基因型評分。與影響感興趣之性狀的QTL基因性連結的標記將會與性狀值更頻繁地分離,然而未連結的標記將不會顯示與表現型明顯的關聯。Once the ethnic group and the marker are selected, describe the method of performing the QTL analysis. In certain instances, hybridization mother plant can produce individual shaped joining (F 1), and these individuals then hybridized in the same manner as described above. Finally, the phenotype and genotype of the derived (F 2 ) population are scored. Markers that are genetically linked to QTLs that affect the trait of interest will be more frequently separated from trait values, whereas unligated markers will not show a significant association with phenotype.
對於由數十或數百個基因控制的性狀來說,母系不需要真的與討論中的表現型不同,反而它們僅必須簡單地包含不同的對偶基因,其接著憑藉著於衍生族群中重組以產生表現型數值的範圍。舉例而言,設想由四個基因所控制的性狀,其中大寫的對偶基因會增加性狀數值,小寫的對偶基因會減少性狀數值。於此,如果四個基因的對偶基因影響力類似,帶有AABBccdd 和aabbCCDD 基因型的個體應具有大致相同的表現型。F1 世代(AaBbCcDd )的成員為無變化的且具有中間表現型。然而F2 世代,或來自F1 個體與其親代中之任一逆代雜交的子代,將會產生變化。F2 後代於任一處將會具有零至八個大寫對偶基因,逆代雜交後代於任一處將會具有四至八個大寫對偶基因。For traits controlled by tens or hundreds of genes, the maternal lines do not need to be really different from the phenotypes in question, but instead they must simply contain different dual genes, which are then recombined by the derivative group. Produces a range of phenotypic values. For example, assume a trait controlled by four genes, in which a capitalized dual gene increases the trait value and a lowercase dual gene reduces the trait value. Here, if the dual genes of the four genes have similar influences, individuals with the AABBccdd and aabbCCDD genotypes should have approximately the same phenotype. Members of the F 1 generation ( AaBbCcDd ) are unchanged and have intermediate phenotypes. However, F 2 generations or progeny from a backcross F 1 individuals of any one of the parental, it will change. F 2 progeny in any one will have zero to eight uppercase allele, backcross progeny in any one will have four to eight uppercase allele.
因此,用於本文之術語「效應大小(effect size)」係關於給予一個或兩個或一個科的指數名字,其用於量測處理效果的大小。這些指數獨立於樣本大小。效應大小的度量為整合來自研究的特定領域之發現的匯總分析研究之普遍潮流。舉例而言,效應大小可被量測作為兩個平均值之間之標準化差異,像是兩個群之間的標準化平均數差異或作為自變量的分類與對應變量之個別分數之間的相互關係。此相互關係稱之為「相互關係效應大小(effect size corrlation)」。換句話說,效應大小為現象強度的度量。Thus, the term "effect size" as used herein relates to an index name given to one or two or one family, which is used to measure the magnitude of the treatment effect. These indices are independent of the sample size. The measure of effect size is the general trend of pooled analytical research that integrates findings from specific areas of research. For example, the effect size can be measured as a normalized difference between two means, such as the normalized mean difference between two populations or the correlation between the classification as an independent variable and the individual scores of the corresponding variables. . This relationship is called "effect size corrlation." In other words, the effect size is a measure of the intensity of the phenomenon.
從資料計算而來的效應大小為敘述性統計,其傳達了關係的預估大小,而不對數據表面關係是否反映出族群的真實關係做任何說明。在那樣的狀況下,效應大小與推論統計像是P -值互補。在遺傳研究中,效應大小可定義為SNP的係數(β),當其與結果的關聯藉由迴歸模組(像是對數量性狀的線性迴歸或是對性質性狀的邏輯式迴歸)模擬時,假設每一對偶基因之拷貝的線性趨勢。數量性狀的迴歸係數可以性狀之標準差(SD)單位來表示,所以其為可比較的跨性狀。The magnitude of the effect calculated from the data is a narrative statistic that conveys the estimated size of the relationship without any explanation as to whether the data surface relationship reflects the true relationship of the ethnic group. In that case, the magnitude of the effect and the inference statistics are complementary to the P -value. In genetic studies, the magnitude of the effect can be defined as the coefficient of the SNP (β), and when its association with the result is modeled by a regression module (such as a linear regression of quantitative traits or a logistic regression of qualitative traits), A linear trend in the copy of each pair of genes is assumed. The regression coefficient of the quantitative trait can be expressed as the standard deviation (SD) unit of the trait, so it is a comparable cross-trait.
QTL分析的首要目標已解答表現型的不同是否主要是由於具有相當大效應的少量基因座,或是由於各具有小量的效應之多個基因座。這顯示出了在許多數量性狀中相當比例之表現型變異可以解釋為巨大效應的少量基因座,其餘則是微小效應的許多基因座。一但QTL被識別,便可使用分子技術將QTL縮小至候選基因(其過程稍後描述於下面的第1及2例)。其可能得以利用本文敘述的方法,使用分析預測調節基因或編碼成轉錄因子的基因及其他信號蛋白的角色。The primary goal of QTL analysis has been to answer whether the difference in phenotype is mainly due to a small number of loci with considerable effects, or multiple loci with small effects. This shows that a significant proportion of phenotypic variants in many quantitative traits can be interpreted as a small number of loci with large effects, while the rest are many loci with minor effects. Once the QTL is identified, molecular techniques can be used to narrow the QTL to candidate genes (the process is described later in Examples 1 and 2 below). It may be possible to use the methods described herein to use assays to predict the role of regulatory genes or genes encoding transcription factors and other signaling proteins.
如同所有的統計分析,樣本大小是一個關鍵因素。小的樣本大小可使得微小效應之QTL的偵測失敗,並導致高估被識別到的QTL之效應大小。已提出用於將偵測到的QTL與預期數值的分佈做比較以估計有多少基因座可能被遺漏之方法。As with all statistical analyses, sample size is a key factor. The small sample size can cause the detection of small effect QTLs to fail and lead to overestimation of the effect size of the identified QTL. Methods have been proposed for comparing the detected QTL to the expected value distribution to estimate how many loci may be missed.
在某些例子中,如同本文所述的關聯性定位方法,其關聯性定位包括應用了與混合統計線性模型(mixed statistical linear model, MLM)結合之一般統計線性模型(general statistical linear model, GLM)。In some instances, as with the association positioning method described herein, the relevance of the location includes the application of a general statistical linear model (GLM) combined with a mixed statistical linear model (MLM). .
當考慮性狀與分類群之間的QTL時,可以注意到表現型常常被各種交互作用效應(例如被環境影響的基因型及QTL之間的上位相互作用),儘管不是所有的QTL研究都被設計為偵測這些交互作用。此外,在生命週期中亦紀錄顯著的顯性、上位性及被環境影響的基因型作用。When considering the QTL between traits and taxa, it can be noted that phenotypes are often influenced by various interactions (eg, environmentally affected genotypes and epistatic interactions between QTLs), although not all QTL studies are designed. To detect these interactions. In addition, significant dominant, epistatic, and environmentally affected genotype effects were recorded throughout the life cycle.
同樣地,檢查了作物之間作物構造差異之QTL研究,已重複地表現顯著的上位相互作用。也可能利用雜種、同胞關係 (半同胞或全同胞科) 及/或譜系訊息來執行對不可操控之自然族群的QTL分析。Similarly, QTL studies examining crop structural differences between crops have repeatedly demonstrated significant superior interactions. It is also possible to perform QTL analysis of uncontrollable natural populations using hybrid, sibling relationships (semi-sib or full sibling) and/or pedigree messages.
因此有很多統計分析在關聯性定位中之基因標記 方法。,在某些例子中,本文敘述的關聯性定位可利用包含,但不侷限於以樣本簡單迴歸的最大概似法(maximum-likelihood)、在標記基因座的變異數分析(analysis of variance, ANOVA)、最小平方法(methods of least square)、Wright’s F統計(Wright’s F statistics)、結構結合(structured association)、基因體控制(genomic control)、數量傳遞不平衡檢測(quantitative transmission disequilibrium test, QTDT)、族群結構(population structure)及相關親屬(relative kinship)的這些方法來分析。在基因體控制中,隨機標記被用以估計和調整由族群結構產生之試驗統計的膨脹。基因體控制和結構結合為控制由族群結構引起之偽陽性(第一型誤差)的普遍方法。Therefore, there are many statistical methods for genetic mapping in association mapping. In some instances, the association positioning described herein may include, but is not limited to, the most approximate-likelihood of simple regression of samples, and the analysis of variance (ANOVA) at the marker locus. ), methods of least square, Wright's F statistics, structured association, genomic control, quantitative transmission disequilibrium test (QTDT), These methods of population structure and relative kinship are analyzed. In genomic control, random markers are used to estimate and adjust the expansion of experimental statistics generated by the population structure. Genome control and structural integration are common methods for controlling false positives (type 1 errors) caused by ethnic structures.
在某些例子,敘述的方法中,其中關連性定位包括應用了與混合統計線性模型(MLM)結合之一般統計線性模型(GLM)。一般統計線性模型混和了數個不同的統計模型像是ANOVA、ANCOVA、 MANOVA、 MANCOVA、普通線性迴歸、t試驗及F試驗。一般統計線性模型係為對一個以上應變數之例子的多元線性迴歸模型的概括。In some examples, the described methods, where the relevance of the location includes the application of a general statistical linear model (GLM) combined with a mixed statistical linear model (MLM). The general statistical linear model is a mixture of several different statistical models such as ANOVA, ANCOVA, MANOVA, MANCOVA, ordinary linear regression, t test and F test. A general statistical linear model is a generalization of a multiple linear regression model for an example of more than one strain number.
混合統計線性模型可被用以認定與藉由隨機基因標記同步偵測到的多階層關係。有利的是,發明者應用GLM及MLM結合的發明者可更準確地預測結合。A mixed statistical linear model can be used to identify multi-level relationships detected by random genetic markers. Advantageously, the inventors of the inventors applying GLM and MLM combinations can more accurately predict binding.
在下面的某些例子中,發明者利用STRUCTURE來執行分析。STRUCTURE係利用基因型資料來推論族群結構的軟體。個體叢的數量之偵測基於給定族群的事後機率資料,利用貝氏方法(Bayesian approach)來獲得(Evanno, G., Regnaut, S., Goudet, J.; Molecular Ecology; 2005; 14: 2611-2620)。相關親屬矩陣,定義個體對之間的基因變積程度,可利用SPAGeDi軟體計算。結構結合法(Pritchard, J. K., Stephens, M., Rosenberg, N. A., Donnelly,Am. J. Hum. Genet. ; 2000; 67: 170-181)與統一混合模型法藉由考慮族群間的族群結構及家族相關性以減少偽陽性(Yu, et. al.,Nature Genetics , 2006, vol.38, no. 2, pp.203)。這些假結合可發生於相關標記沒有連結至使役基因座,而是偏往該亞族群,於任意標記對偶基因以高頻率存在於亞族群中時。In some of the examples below, the inventor used STRUCTURE to perform the analysis. STRUCTURE uses genotype data to infer the software of ethnic structure. The detection of the number of individual plexes is based on the posterior probability of a given population, using the Bayesian approach (Evanno, G., Regnaut, S., Goudet, J.; Molecular Ecology; 2005; 14: 2611 -2620). The relative family matrix, which defines the degree of gene degeneration between individual pairs, can be calculated using the SPAGeDi software. Structural Binding (Pritchard, JK, Stephens, M., Rosenberg, NA, Donnelly, Am. J. Hum. Genet .; 2000; 67: 170-181) and the Unified Mixed Model Method by considering the ethnic group structure between ethnic groups and Family correlation to reduce false positives (Yu, et. al., Nature Genetics , 2006, vol. 38, no. 2, pp. 203). These pseudo-bindings can occur when the relevant marker is not linked to the causal locus, but rather to the sub-population, when any of the labeled dual genes are present in the subpopulation at a high frequency.
也可加入輔助因子資料的利用以增加偵測連結的能力。舉例而言,當執行FFB關聯性定位時我們可以包含果實大小作為輔助因子以助於增加關聯性定位以挑出連結至性狀標記的能力。The use of cofactor data can also be added to increase the ability to detect links. For example, when performing FFB association positioning, we can include the fruit size as a cofactor to help increase the association location to pick the ability to link to the trait tag.
要理解的是,根據分析的緊迫性可以使用不同的截止值,而且效率高的截止值是由族群類型、生物體、樣品大小及其他考量來決定的。舉例而言,帶有p-值的多型性基因標記根據經驗推論大約低於5%、或大約低於4%、或大約低於3%、或大約低於2%、或大約低於1%、或大約低於0.5%、或大約低於0.1%被認為與感興趣之表現型具有統計上顯著地相關。It is to be understood that different cutoff values can be used depending on the urgency of the analysis, and that the high cutoff values are determined by the type of population, organism, sample size, and other considerations. For example, a polymorphic gene signature with a p-value is empirically inferred to be less than about 5%, or less than about 4%, or less than about 3%, or less than about 2%, or about less than one. %, or approximately less than 0.5%, or approximately less than 0.1% is considered to be statistically significantly correlated with the phenotype of interest.
在某些例子中,描述方法,其中為關聯性定位帶有低於5%經驗推論之p-值的多型性基因標記之方法,其被認為與合意表現型具有統計上的顯著相關。在進一步的例子中,如同本文所描述之方法為對關聯性定位帶有低於1%經驗推論之p-值的多型性基因標記之方法,其被認為與合意表現型具有統計上的顯著相關。In some examples, methods are described in which a method of localizing a polymorphic gene marker with a p-value of less than 5% empirical inference for association is considered to be statistically significantly correlated with a desirable phenotype. In a further example, a method as described herein is a method of locating a polymorphic gene marker with a p-value of less than 1% empirical inference for association, which is considered to be statistically significant with a desirable phenotype Related.
在某些例子中,方法已描述於本文中,係有關於根據標記效應之表現型的迴歸來定位QTL的方法。當在後敘標題「驗證(Validation)」下解釋進一步的細節時,判定的係數(R平方或R2 ),使用標記評估表現型變異的比例。也就是說可用R2 判定或預測標記或對偶基因的效應,預期有多少感興趣之性狀受到特定對偶基因存在的影響。在某些例子中,R平方值可應用於具有p-值小於0.01的標記組。因此在某些例子中,R平方截止值可為多於大約0.01、或多於大約0.02、或多於大約0.03、或多於大約0.04、或多於大約0.05、或多於大約0.06、或多於大約0.07、或多於大約0.08、或多於大約0.09、或多於大約0.1、或多於大約0.15、或多於大約0.2。在某些例子中,用於具有p-值小於0.01的標記組,其被描述為有多於大約0.1的R平方截止值。In some instances, methods have been described herein, along with methods for locating QTLs based on phenotypic regression of marker effects. When further details are explained under the heading "Validation", the coefficient of the decision (R square or R 2 ) is used to evaluate the proportion of the phenotypic variation using the marker. That is to say, the effect of R 2 can be used to determine or predict a marker or a dual gene, and how many traits of interest are expected to be affected by the presence of a particular dual gene. In some examples, the R-squared value can be applied to a set of markers having a p-value of less than 0.01. Thus, in some examples, the R square cutoff value can be more than about 0.01, or more than about 0.02, or more than about 0.03, or more than about 0.04, or more than about 0.05, or more than about 0.06, or more. It is about 0.07, or more than about 0.08, or more than about 0.09, or more than about 0.1, or more than about 0.15, or more than about 0.2. In some examples, for a set of markers having a p-value of less than 0.01, which is described as having an R-squared cutoff of more than about 0.1.
當與樣本組中性狀的總變異數做比較時,R平方值顯示了有多少對偶基因或對偶基因的組合可以解釋該性狀中的變方。舉例而言,如果某組標記的R平方值為0.8,那麼該組標記可以預測80%之感興趣性狀。其同時也意味著還有另外未知或未發現的標記影響20%性狀。換句話說,R平方值可以視作一個、兩個、三個、四個或以上標記準確預測表現型性狀的能力指標。然而效應大小則是關於對偶基因對表現型之數值影響的大小。舉例而言,如果對果實重量的效應大小為50,那麼該對偶基因會影響該性狀50公斤。換句話說,效應大小可以視作對偶基因控制之數量變化的指標。When compared to the total variance of traits in the sample set, the R-squared value shows how many pairs of dual or dual genes can interpret the variants in the trait. For example, if a set of markers has an R-squared value of 0.8, then the set of markers can predict 80% of the trait of interest. It also means that there are additional unknown or undiscovered markers affecting 20% traits. In other words, the R-squared value can be viewed as one, two, three, four or more markers that accurately predict phenotypic traits. However, the magnitude of the effect is about the magnitude of the effect of the dual gene on the phenotype. For example, if the effect on the weight of the fruit is 50, then the dual gene will affect 50 kg of the trait. In other words, the magnitude of the effect can be seen as an indicator of the change in the number of dual gene controls.
在某些例子中,敘述進一步地提供方法,其中多型性標記包括具有小於0.1的判定係數,當後驗測試時,帶有最重要的負向效應之多型性標記為那些具有評估效應大小為<-10、<-15、<-20或<-30者。In some examples, the description further provides a method wherein the polytype marker comprises a decision coefficient having a magnitude of less than 0.1, and when the posterior test, the polytype marker with the most important negative effect is those having an evaluation effect size For <-10, <-15, <-20 or <-30.
在某些例子中,描述利用於本文中所述之方法,預測還沒顯示出感興趣之表現型之作物之感興趣之作物表現型之方法以篩查及選擇那些擁有感興趣之表現型的作物以與同種的其他植物栽種或培育。換句話說,此方法不用等待至性狀可被量測便能預期感興趣之表現型。有利的是,藉由通過判定表現型而能夠預測表現型,發明者能夠節省時間及花費。In some instances, methods for predicting crop phenotypes of interest for a phenotypic crop of interest are described using the methods described herein to screen and select those having a phenotype of interest. Crops are planted or cultivated with other plants of the same species. In other words, this method does not wait until the trait can be measured to anticipate the phenotype of interest. Advantageously, the inventor can save time and money by being able to predict phenotype by determining phenotype.
在進一步的例子中,描述方法,其中預測的表現型為產量。可預測其他感興趣之表現型。某些例子已於本文中描述。在另一例中,所述之方法其中的作物為油棕櫚且預測的表現型為新鮮果串產量、串之數目或其組合。在進一步的例子中,所述之方法其中感興趣之作物表現型為選自於由新鮮果串重、串之大小、果實大小、油之萃取比例、串之數目及其組合組成之群組之產量構成要素。In a further example, a method is described in which the predicted phenotype is yield. Other phenotypes of interest can be predicted. Some examples are described in this article. In another example, the crop wherein the crop is oil palm and the predicted phenotype is fresh fruit bunch yield, number of strands, or a combination thereof. In a further example, the method wherein the crop phenotype of interest is selected from the group consisting of fresh fruit bunch weight, string size, fruit size, oil extraction ratio, number of strings, and combinations thereof. The components of production.
在另一例中,感興趣之表現型與新鮮果串重或串之數目產量有關。In another example, the phenotype of interest is related to the number of fresh fruit bunches or strings.
本揭露也提供其他產量構成要素包括,但不侷限於增加作物一個或多個部位的生質量(重量),特別是地表以上的(可收穫的)部分、增加根部生質量或增加其他任意可收獲部分的生質量、增加總種子產量,其包括增加種子生質量(種子重量)及可為以每單位作物或個別種子為基準地增加種子重量、增加每單位花穗的花朵(小花(florets))數目、增加(飽滿的)種子數目、增加種子大小,其也可影響種子的組成、增加種子體積,其也可影響種子的組成(包括油、蛋白質及碳水化合物總含量及組成)、增加個別種子面積、增加個別種子長度及/或寬度、增加收獲指數,其以可收獲部分的產量比例表示像是種子、整體的生質量及增加千粒重(thousand kernel weight, TKW),其由計算飽滿種子數目與飽滿種子總重量推斷而來。種子大小及/或種子體重的增加會導致TKW的增加。The disclosure also provides other yield components including, but not limited to, increasing the quality (weight) of one or more parts of the crop, particularly the (harvestable) portion above the surface, increasing the root mass or adding any other harvest. Part of the raw mass, increasing total seed yield, including increasing seed quality (seed weight) and increasing the seed weight per unit crop or individual seed, increasing the flowers per unit of flowering (florets) The number, the number of (full) seeds, and the increase in seed size can also affect seed composition, increase seed volume, and can also affect seed composition (including total oil and protein and carbohydrate content and composition), and increase individual seeds. Area, increase individual seed length and / or width, increase harvest index, which represents the yield of the harvestable part, such as seed, overall raw mass and increase of thousand weight (TKW), which is calculated by counting the number of full seeds and The total weight of the full seed is inferred. An increase in seed size and/or seed weight results in an increase in TKW.
在一例中,所述的一個或多個多型性標記之存在與新鮮果串(FFB)表現型有關,其中標記包括,但不侷限於,SEQ ID NOs: 1至79。在另一例中,方法包括偵測兩個或多個、三個或多個、四個或多個、五個或多個、六個或多個、七個或多個、八個或多個、九個或多個、十個或多個、十一個或多個或全部的多型性基因標記存在與否,多型性標基因誌包括,但不侷限於SEQ ID NOs: 1至79。在另一例中所述的一個或多個多型性標記之存在與串之數目產量(bunch number yield, BNO)表現型有關,其中多型性標記包括,但不侷限於SEQ ID NO:8、SEQ ID NO: 27、SEQ ID NO: 48、SEQ ID NO: 53、SEQ ID NO: 56、SEQ ID NO: 57、SEQ ID NO: 58、SEQ ID NO: 62、SEQ ID NO: 80、SEQ ID NO: 81、SEQ ID NO: 82、SEQ ID NO: 83、SEQ ID NO: 84、SEQ ID NO: 85、SEQ ID NO: 86、SEQ ID NO: 87、SEQ ID NO: 88、SEQ ID NO: 89、SEQ ID NO: 90、SEQ ID NO: 91、SEQ ID NO: 92、SEQ ID NO: 93、SEQ ID NO: 94、SEQ ID NO: 95、SEQ ID NO: 96、SEQ ID NO: 97、SEQ ID NO: 98、SEQ ID NO: 99、SEQ ID NO: 100、SEQ ID NO: 101、SEQ ID NO: 102、SEQ ID NO: 103、SEQ ID NO: 104、SEQ ID NO: 105、SEQ ID NO: 106、SEQ ID NO: 107、SEQ ID NO: 108、SEQ ID NO: 109、SEQ ID NO: 110、SEQ ID NO: 111、SEQ ID NO: 112、SEQ ID NO: 113、SEQ ID NO: 114及SEQ ID NO: 115。此多型性標記是根據本文所述之方法來選擇。標記的例示性組合與其於判定作物表現型之用途可於本說明書中找到,例如於表6、表7及表12中。In one example, the presence of the one or more polymorphic markers is associated with a fresh fruit bunch (FFB) phenotype, wherein the markers include, but are not limited to, SEQ ID NOs: 1 to 79. In another example, the method includes detecting two or more, three or more, four or more, five or more, six or more, seven or more, eight or more , nine or more, ten or more, eleven or more or all of the polymorphic gene markers are present or not, and the polymorphic gene signature includes, but is not limited to, SEQ ID NOs: 1 to 79 . The presence of one or more polymorphic markers in another example is related to a bunch number yield (BNO) phenotype, wherein the polymorphic marker includes, but is not limited to, SEQ ID NO: 8. SEQ ID NO: 27, SEQ ID NO: 48, SEQ ID NO: 53, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 62, SEQ ID NO: 80, SEQ ID NO: 81, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 84, SEQ ID NO: 85, SEQ ID NO: 86, SEQ ID NO: 87, SEQ ID NO: 88, SEQ ID NO: 89, SEQ ID NO: 90, SEQ ID NO: 91, SEQ ID NO: 92, SEQ ID NO: 93, SEQ ID NO: 94, SEQ ID NO: 95, SEQ ID NO: 96, SEQ ID NO: SEQ ID NO: 98, SEQ ID NO: 99, SEQ ID NO: 100, SEQ ID NO: 101, SEQ ID NO: 102, SEQ ID NO: 103, SEQ ID NO: 104, SEQ ID NO: 105, SEQ ID NO: 106, SEQ ID NO: 107, SEQ ID NO: 108, SEQ ID NO: 109, SEQ ID NO: 110, SEQ ID NO: 111, SEQ ID NO: 112, SEQ ID NO: 113, SEQ ID NO: 114 and SEQ ID NO: 115. This polymorphic marker is selected according to the methods described herein. Exemplary combinations of markers and their use in determining crop phenotypes can be found in this specification, for example in Table 6, Table 7, and Table 12.
在一個例子中,如同本文所述之方法提供與增加/減少新鮮果串產量有關的SNPs,其SNPs為一個或兩個或以上基因標記,其包括,但不侷限於SEQ ID NO: 1、SEQ ID NO: 3、SEQ ID NO: 6、SEQ ID NO: 7、SEQ ID NO: 8、SEQ ID NO: 10、SEQ ID NO: 12、SEQ ID NO: 13、SEQ ID NO: 14、SEQ ID NO: 18、SEQ ID NO: 19、SEQ ID NO: 20、SEQ ID NO: 21、SEQ ID NO: 23、SEQ ID NO: 26、SEQ ID NO: 27、SEQ ID NO: 30、SEQ ID NO: 33、SEQ ID NO: 34、SEQ ID NO: 35、SEQ ID NO: 36、SEQ ID NO: 37、SEQ ID NO: 39、SEQ ID NO: 40、SEQ ID NO: 41、SEQ ID NO: 43、SEQ ID NO: 44、SEQ ID NO: 45、SEQ ID NO: 46、SEQ ID NO: 47、SEQ ID NO: 48、SEQ ID NO: 51、SEQ ID NO: 52、SEQ ID NO: 53、SEQ ID NO: 54、SEQ ID NO: 56、SEQ ID NO: 57、SEQ ID NO: 58、SEQ ID NO: 60、SEQ ID NO: 62、SEQ ID NO: 63、SEQ ID NO: 64、SEQ ID NO: 65、SEQ ID NO: 66、SEQ ID NO: 67、SEQ ID NO: 70、SEQ ID NO: 71、SEQ ID NO: 72、SEQ ID NO: 73、SEQ ID NO: 75、SEQ ID NO: 76、SEQ ID NO: 77及SEQ ID NO: 79。In one example, a method as described herein provides SNPs associated with increasing/decreasing the yield of fresh fruit bunches, the SNPs of which are one or two or more gene markers including, but not limited to, SEQ ID NO: 1, SEQ ID NO: 3. SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 10, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO : 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 23, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 30, SEQ ID NO: 33 SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37, SEQ ID NO: 39, SEQ ID NO: 40, SEQ ID NO: 41, SEQ ID NO: 43, SEQ ID NO: 44, SEQ ID NO: 45, SEQ ID NO: 46, SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO: 51, SEQ ID NO: 52, SEQ ID NO: 53, SEQ ID NO 54. SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 60, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64, SEQ ID NO: 65 SEQ ID NO: 66, SEQ ID NO: 67, SEQ ID NO: 70, SEQ ID NO: 71, SEQ ID NO: 72, SEQ ID NO: 73, SEQ ID NO: 75, SEQ ID NO: 76, SEQ ID NO : 77 and SEQ ID NO: 79.
在一個例子中,如同本文所述之方法提供的SNPs,其中SNPs的存在與新鮮果串產量之增加或減少有關,且其中SNPs包括,但不侷限於標記號1(SEQ ID NO: 10)、標記號2(SEQ ID NO: 20)、標記號3(SEQ ID NO: 13)、標記號4(SEQ ID NO: 8)、標記號5(SEQ ID NO: 19)、標記號6(SEQ ID NO: 34)及其組合。在進一步的例子中,包括但不侷限於標記號1(SEQ ID NO: 10)、2(SEQ ID NO: 20)、3(SEQ ID NO: 13)、4(SEQ ID NO: 8)、5(SEQ ID NO: 19)、6(SEQ ID NO: 34)之至少一個、至少兩個、至少三個、至少四個、至少五個或全部標記之存在與新鮮果串重量產量之增加有關。在另一例中,包括但不侷限於標記號1(SEQ ID NO: 10)、3(SEQ ID NO: 13)、5(SEQ ID NO: 19)、6(SEQ ID NO: 34)之至少一個、兩個、三個或全部標記之存在與新鮮果串重量產量之減少有關。標記運用的例子可於本說明書的表4、表6及表7中見到。In one example, the SNPs provided by the methods described herein, wherein the presence of SNPs is associated with an increase or decrease in the yield of fresh fruit bunches, and wherein the SNPs include, but are not limited to, marker number 1 (SEQ ID NO: 10), Marker 2 (SEQ ID NO: 20), marker number 3 (SEQ ID NO: 13), marker number 4 (SEQ ID NO: 8), marker number 5 (SEQ ID NO: 19), marker number 6 (SEQ ID) NO: 34) and combinations thereof. In further examples, including but not limited to marker number 1 (SEQ ID NO: 10), 2 (SEQ ID NO: 20), 3 (SEQ ID NO: 13), 4 (SEQ ID NO: 8), 5 The presence of at least one, at least two, at least three, at least four, at least five or all of the markers (SEQ ID NO: 19), 6 (SEQ ID NO: 34) is associated with an increase in the weight yield of fresh fruit bunches. In another example, including but not limited to at least one of marker number 1 (SEQ ID NO: 10), 3 (SEQ ID NO: 13), 5 (SEQ ID NO: 19), 6 (SEQ ID NO: 34) The presence of two, three or all of the markers is associated with a decrease in the weight yield of the fresh fruit bunch. Examples of marking applications can be found in Tables 4, 6, and 7 of this specification.
在一個例子中,描述如前述的SNPs,其SNPs與串之數目(BNO)產量的增加或減少有關的為標記號7(SEQ ID NO: 90)、8(SEQ ID NO: 105)、9(SEQ ID NO: 106)、10(SEQ ID NO: 99)、11(SEQ ID NO: 80)及其組合。在進一步的例子中,其SNPs為一個或兩個或以上的基因標記包括,但不侷限於SEQ ID NO: 48、SEQ ID NO: 53、SEQ ID NO: 58、SEQ ID NO: 80、SEQ ID NO: 82、SEQ ID NO: 83、SEQ ID NO: 84、SEQ ID NO: 86、SEQ ID NO: 90、SEQ ID NO: 92、SEQ ID NO: 94、SEQ ID NO: 96、SEQ ID NO: 99、SEQ ID NO: 100、SEQ ID NO:105、SEQ ID NO: 106及SEQ ID NO:113。在進一步的例子中,其SNPs為包括,但不侷限於SEQ ID NO: 80、SEQ ID NO: 90、SEQ ID NO:99、SEQ ID NO:105及SEQ ID NO:106之一個或兩個或以上的基因標記。In one example, the SNPs are described as described above, and the SNPs associated with the increase or decrease in the number of strands (BNO) are labeled 7 (SEQ ID NO: 90), 8 (SEQ ID NO: 105), 9 ( SEQ ID NOs: 106), 10 (SEQ ID NO: 99), 11 (SEQ ID NO: 80), and combinations thereof. In a further example, the SNPs are one or two or more gene markers including, but not limited to, SEQ ID NO: 48, SEQ ID NO: 53, SEQ ID NO: 58, SEQ ID NO: 80, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 84, SEQ ID NO: 86, SEQ ID NO: 90, SEQ ID NO: 92, SEQ ID NO: 94, SEQ ID NO: 96, SEQ ID NO: 99. SEQ ID NO: 100, SEQ ID NO: 105, SEQ ID NO: 106, and SEQ ID NO: 113. In a further example, the SNPs thereof are, but are not limited to, one or two of SEQ ID NO: 80, SEQ ID NO: 90, SEQ ID NO: 99, SEQ ID NO: 105, and SEQ ID NO: 106 or The above gene markers.
在一個例子中,如同本文所述之方法提供標記號8(SEQ ID NO: 105)及標記號11(SEQ ID NO: 80)的組合之存在與串之數目產量的改變有關。在另一例中,標記號7(SEQ ID NO: 90)、標記號9(SEQ ID NO: 106)及標記號10(SEQ ID NO: 99)的組合之存在與串之數目產量的改變有關。在另一例中,標記號11(SEQ ID NO: 80)之存在與串之數目產量的改變有關。標記運用的例子可於本說明書的表10及表12中見到。In one example, the presence of a combination of marker number 8 (SEQ ID NO: 105) and marker number 11 (SEQ ID NO: 80) as described herein is related to a change in the number of strands produced. In another example, the presence of a combination of marker number 7 (SEQ ID NO: 90), marker number 9 (SEQ ID NO: 106), and marker number 10 (SEQ ID NO: 99) is associated with a change in the number of strands produced. In another example, the presence of marker number 11 (SEQ ID NO: 80) is related to a change in the number of strands produced. Examples of marking applications can be found in Tables 10 and 12 of this specification.
亦描述於本文中的是一個或多個多型性基因標記作為作物的選種準則的用途,其中選種係根據一個或多個多型性基因標記存在與否。Also described herein is the use of one or more polymorphic gene markers as a selection criterion for crops, wherein the selection is based on the presence or absence of one or more polymorphic gene markers.
範例example
本發明的不受限例子包括最佳模式及比較例子將會參考特定例子進一步地詳細描述,其特定例子不應理解為對本發明範圍有任何形式的限制。The non-limiting examples of the present invention, including the best mode and the comparative examples, are further described in detail with reference to the specific examples, which are not to be construed as limiting the scope of the invention.
材料及方法Materials and methods
用於「新鮮果串產量」及「串之數目」標記識別方法的作物材料係由三個油棕櫚族群取得,每個族群皆包含Deli、Nigerian及AVROS背景的雜交,並因此具有不同遺傳背景的混合體。在這三個族群中發現的對偶基因組合係為這些對偶基因存在於商業油棕櫚遺傳物質中的表現。舉例而言,在馬來西亞販售及種植的商業材料為限制起源的培育族群(BPROs)的不同雜交組合,用以產生關聯性定位用的族群之全部親代BPROs涵蓋所有常見遺傳背景,其藉由培育者基因移入以生產栽種於馬來西亞及印尼之商業油棕櫚。這些油棕櫚在特定的時段裡被個別地記錄產量。The crop material used in the identification method of "fresh fruit bunch yield" and "number of bunches" is obtained from three oil palm groups, each of which contains a hybrid of Deli, Nigerian and AVROS backgrounds, and thus has different genetic backgrounds. Mixture. The dual gene combinations found in these three ethnic groups are the expression of these dual genes in commercial oil palm genetic material. For example, commercial materials sold and grown in Malaysia are different hybrid combinations of restricted origin breeding groups (BPROs), and all parental BPROs used to generate association-targeted populations cover all common genetic backgrounds, The breeder's genes are moved in to produce commercial palm oil grown in Malaysia and Indonesia. These oil palms are individually recorded for production over a specific period of time.
DNADNA 提取extract
嫩莖葉,為從最高葉而來的第一未綻開年輕幼葉,得自於油棕櫚樹。在放置於冷凍庫(-80°C)貯藏之前,清潔這些葉子並用液態氮冷凍。當需要DNA樣本時,秤取並從貯藏庫移出大約3至5克的葉片樣本,用液態氮處理並用研缽和研杵磨成粉末,磨好的葉片接著移至加有15毫升改良溴化十六烷基三甲基銨(cetyl trimethyl ammonium bromide, CTAB)緩衝液的試管中。CTAB緩衝液包含2%(重量/體積)CTAB、20 nM EDTA(pH 8.0)、1.4 M 氯化鈉、100 mM Tris-HCL (pH 8.0)、5 mM 抗壞血酸(ascorbic acid)、4 mM 二乙基二硫代氨基甲酸鈉鹽(diethyldithiocarbamic acid sodium salt)、2%聚乙烯四氫吡咯烷酮(polyvinylpyrolidone-40, PVP40)及100 µl 2-巰基乙醇(β-mercaptoethanol)。將該混合物以60°C培養30分鐘,接著在完全混和之前加入等體積的氯仿:異戊醇。將混合物以10,000 rpm離心15分鐘,並把上層液相移至乾淨試管中。然後加入冰冷的異丙醇以沉澱DNA。接著將此溶液於-20°C貯藏數個小時之後以12,000 rpm離心15分鐘以 5 ml的包含70%乙醇及10 mM 醋酸銨之洗滌緩衝液沖洗在試管底部見到的DNA片狀沉澱。接著離心樣本使DNA沉澱,使之乾燥並溶於含有10 mM Tris-HCL (pH 8.0)及1 mM EDTA (pH 8.0)之Tris-EDTA(TE)緩衝液。此DNA溶液接著以RNAse處理以除去RNA。The tender stems and leaves, the first unopened young leaves from the highest leaves, are derived from oil palm trees. The leaves were cleaned and frozen in liquid nitrogen prior to storage in a freezer (-80 °C). When DNA samples are required, approximately 3 to 5 grams of leaf samples are removed and removed from the reservoir, treated with liquid nitrogen and ground into a powder using a mortar and pestle, and the ground leaves are then moved to 15 ml of modified bromination. Cetyl trimethyl ammonium bromide (CTAB) buffer in a test tube. CTAB buffer contains 2% (w/v) CTAB, 20 nM EDTA (pH 8.0), 1.4 M sodium chloride, 100 mM Tris-HCL (pH 8.0), 5 mM ascorbic acid, 4 mM diethyl Diethyldithiocarbamic acid sodium salt, 2% polyvinylpyrolidone-40 (PVP40) and 100 μl of 2-mercaptoethanol. The mixture was incubated at 60 ° C for 30 minutes, followed by an equal volume of chloroform:isoamyl alcohol before complete mixing. The mixture was centrifuged at 10,000 rpm for 15 minutes and the upper liquid phase was transferred to a clean tube. Ice cold isopropanol was then added to precipitate the DNA. The solution was then stored at -20 ° C for several hours and then centrifuged at 12,000 rpm for 15 minutes to rinse the DNA pellets seen at the bottom of the tube with 5 ml of wash buffer containing 70% ethanol and 10 mM ammonium acetate. The sample was then centrifuged to precipitate DNA, which was dried and dissolved in Tris-EDTA (TE) buffer containing 10 mM Tris-HCL (pH 8.0) and 1 mM EDTA (pH 8.0). This DNA solution is then treated with RNAse to remove RNA.
標記識別Tag recognition
接著利用Illumina Genome Analyser按照各製造商的指示將萃取出的DNA定序。利用生物資訊工具例如但不侷限於Burrows-Wheeler Aligener及SAMTOOLS分析資料以偵測可能的SNPs。將SNPs的清單傳送給Illumina公司,且1208個SNP標記排列成GoldenGate™分析格式。使用Illumina的方法以執行利用269棵棕櫚DNA的GoldenGate™分析,這269棵棕櫚來自上述定義的三個族群,其中96棵棕櫚來自第一族群,96棵棕櫚來自第二族群,77棵棕櫚來自第三族群。The extracted DNA was then sequenced using an Illumina Genome Analyser according to the manufacturer's instructions. Biometric information tools such as, but not limited to, Burrows-Wheeler Aligener and SAMTOOLS analysis data are used to detect possible SNPs. The list of SNPs was transmitted to Illumina and 1208 SNP markers were arranged in the GoldenGateTM analysis format. Illumina's method was used to perform GoldenGateTM analysis using 269 palm DNA from the three populations defined above, 96 palms from the first population, 96 palms from the second population, and 77 palms from the first Three ethnic groups.
接著利用Illumina的Genome Studio™ Genotyping Module解譯分析的結果。顯示對偶基因的叢集的結果,並被轉移至展開表上且如下述進一步分析。The results of the analysis were then interpreted using Illumina's Genome StudioTM Genotyping Module. The results of the cluster of dual genes are displayed and transferred to the expansion table and further analyzed as described below.
關聯性定位Relevance targeting
前面識別的SNP標記接著被統計試驗以確認它們是否與表現型資料連結,且藉由延展便能預測表現型表現及哪些分異的基因型會影響性狀,哪些不會。統計線性模型被用以估算基因型與受測表現型之間是否有顯著的連結。基因型資料係由上述的GoldenGate™分析獲得,而表現型資料是由54個月的期間收集而來以增加資料準確性,用於此分析的表現型為新鮮果串產量及串之數目。The previously identified SNP markers are then statistically tested to confirm whether they are linked to phenotypic data, and by extension, phenotypic performance can be predicted and which differentiated genotypes will affect traits and which will not. A statistical linear model was used to estimate whether there was a significant link between the genotype and the phenotype being tested. Genotype data was obtained from the above GoldenGateTM analysis, and phenotypic data was collected over a 54-month period to increase data accuracy. The phenotype used for this analysis was the number of fresh fruit bunches and the number of strings.
此分析是利用一般統計線性模型(GLM)來實施,以識別連結至兩個表現型(新鮮果串產量及串之數目)的SNP基因標記。為了改進準確性,混合統計線性模型(MLM)與GLM模型一起被使用。與產量性狀顯著地相關的SNP標記使用一般統計線性模型(GLM)和混合模型關聯(MLM)分析與TASSEL(Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES. Bioinformatics; 2007; 23:2633-2635.)而入選結合了基因型、包括新鮮果串產量資料和串之數目的表現型資料以及由SPAGeDi(Hardy OJ, Vekemans X; 2002)衍生的兩個成對親屬係數(K-矩陣)程式。SPAGeDi:多功能的電腦程式,用以分析個體或族群層上的空間遺傳結構(Molecular Ecology Notes 2; 618-620)以及來自STRUCTURE軟體(Pritchard, J. K., Stephens, M., Rosenberg, N. A., Donnelly, Am. J. Hum. Genet.; 2000; 67: 170-181)的結構資訊(Q-value)來降低由於群體分層之假結合的可能性。用於執行STRUCTURE的參數對於BURN-IN及MCMC同為 10,000次重複的參數。K值使用由Evanno等人(Evanno, G., Regnaut, S., Goudet, J.; Molecular Ecology; 2005; 14: 2611-2620)提出的分析來判定。標獲得並研究誌的P-值。越低的p-值代表標記與感興趣之性狀連結的機會越大。帶有低於5%或1%經驗推論值之P-值的多型性位置被認為與性狀具有統計性顯著的結合(Greenhalgh T; BMJ 315; 1997; 540-543.; Tommasini L., Schnurbusch T., Fossati D., Mascher F., Keller B. , Theor. Appl. Genet.;2007; 115: 697–708.)。因此,截止點被判定為0.01且選擇帶有可接受P值的最好的幾個標記以進一步地分析。This analysis was performed using a general statistical linear model (GLM) to identify SNP gene markers linked to two phenotypes (fresh fruit bunch yield and number of strands). To improve accuracy, a mixed statistical linear model (MLM) is used along with the GLM model. SNP markers that are significantly correlated with yield traits use general statistical linear model (GLM) and mixed model correlation (MLM) analysis with TASSEL (Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES. Bioinformatics; 2007; 23:2633-2635.) and selected phenotype data combining genotypes, including fresh fruit bunch yield data and string numbers, and two paired relative coefficients derived from SPAGeDi (Hardy OJ, Vekemans X; 2002) (K - Matrix) program. SPAGeDi: A versatile computer program for analyzing spatial genetic structures at the individual or ethnic level (Molecular Ecology Notes 2; 618-620) and from STRUCTURE software (Pritchard, JK, Stephens, M., Rosenberg, NA, Donnelly, Am. J. Hum. Genet.; 2000; 67: 170-181) Structural information (Q-value) to reduce the possibility of false combinations due to group stratification. The parameters used to perform STRUCTURE are the same as 10,000 repetitions for BURN-IN and MCMC. The K value was determined using an analysis proposed by Evanno et al. (Evanno, G., Regnaut, S., Goudet, J.; Molecular Ecology; 2005; 14: 2611-2620). The P-value of the syllabus was obtained and studied. The lower the p-value, the greater the chance that the marker will be linked to the trait of interest. A polymorphic position with a P-value below 5% or 1% of the empirical inference value is considered to have a statistically significant binding to the trait (Greenhalgh T; BMJ 315; 1997; 540-543.; Tommasini L., Schnurbusch T., Fossati D., Mascher F., Keller B., Theor. Appl. Genet.; 2007; 115: 697–708.). Therefore, the cutoff point is judged to be 0.01 and the best few markers with acceptable P values are selected for further analysis.
對於被選擇的標記,將作物的基因型與感興趣之性狀比較。計算效應評估以判定與感興趣之性狀關聯之不論正向或負向的對偶基因效應。For the selected marker, the genotype of the crop is compared to the trait of interest. The effect assessment is calculated to determine the dual gene effect, whether positive or negative, associated with the trait of interest.
驗證verification
來自油棕櫚農場的商業性可用植栽材料之油棕櫚上驗證藉由執行關聯性定位步驟而來之入選標記。樣本為使用「開放陣列(OpenArray)」平台並利用上述的關聯性定位來分析之基因型。其分析結果提供了一系列的標記、標記可被偵測到的不同之對偶基因及可被用來預測感興趣之性狀(p-值)的標記有多準確之計量、對其連結至的性狀影響有多強(對偶基因效應)以及標記對於解釋由標記所引起的全部受測性狀之變異的數學模式有多吻合(R平方)。The inclusion marker was performed on the oil palm of a commercially available plant material from the Oil Palm Farm by performing an associated positioning step. The sample is a genotype analyzed using the OpenArray platform and using the correlation mapping described above. The results of the analysis provide a series of markers, different pairs of genes that can be detected, and how accurately the markers can be used to predict the trait of interest (p-value), and the traits to which they are linked How strong is the influence (dual gene effect) and how well the labeling is to explain the mathematical pattern of the variation of all tested traits caused by the marker (R square).
標記根據<0.01的截止p-值、<0.1的R平方(R2 )截止值及其預測有多少油棕櫚受到特定對偶基因之存在影響之預測的對偶基因效應而入選。R平方值可利用標準統計方法推導,該值越接近1,則在受測性狀的整體所有效應上之標記影響就越強。對偶基因效應預測特定的對偶基因組合,相較於平均的油棕櫚,將會給受測作物正向或負向的改變。越大的正向及負向值越有利於篩查及選擇具有合意對偶基因及缺少不合意對偶基因的油棕櫚。The markers were selected based on a cut-off p-value of <0.01, an R-squared (R 2 ) cutoff value of <0.1, and a predicted dual gene effect that predicts how much oil palm is affected by the presence of a particular dual gene. The R-squared value can be derived using standard statistical methods. The closer the value is to 1, the stronger the effect of the marker on all of the effects of the overall trait of the test trait. The dual gene effect predicts a specific dual gene combination that will give a positive or negative change to the tested crop compared to the average oil palm. The greater the positive and negative values, the better the screening and selection of oil palms with desirable dual genes and lack of undesired dual genes.
被選出的理想油棕櫚應該只包含被預測給予正向影響的對偶基因。應注意避免帶有受測性狀被預測為負向影響之對偶基因的油棕櫚,但此在實務上是很困難的,因此像這樣理想的基因型組合非常稀少。為了選擇對偶基因,選出對於對偶基因影響給予最佳預測值的對偶組合,並且該對偶組合被預測對於被移除的受測性狀給予最強的負面影響。分析由基因型鑑定而來的資料和與基因型一起的關聯性定位之預測資料,以確定入選之標記的預測是否準確,以及油棕櫚的表現型表現是否可根據該基因型而被預測。The ideal oil palm selected should contain only the dual genes that are predicted to give positive effects. Care should be taken to avoid oil palms with dual genes whose predicted traits are predicted to be negatively affected, but this is practically difficult, so an ideal genotype combination like this is very rare. In order to select a dual gene, a dual combination that gives the best predictive value for the effect of the dual gene is selected, and the dual combination is predicted to give the strongest negative impact on the removed test trait. The data from the genotype identification and the predictive data of the association with the genotype are analyzed to determine whether the prediction of the selected marker is accurate and whether the phenotypic performance of the oil palm can be predicted based on the genotype.
根據執行驗證試驗,分析確認對於受測性狀為優等的棕櫚,且將它們的性狀資料與該性狀的平均值比較以顯示以這些標記選擇將得以準確預測油棕櫚,而該油棕櫚具有增加待評估性狀表現的潛力。上述的方法用以識別連結至兩個表現型性狀(新鮮果串產量及串之數目)的基因標記,其結果在以下的第1及2例中描述。According to the performance verification test, the analysis confirmed that the palms were superior for the tested traits, and compared their trait data with the average of the traits to show that the selection of these markers would accurately predict the oil palm, and the oil palm had an increase to be evaluated. The potential for trait performance. The above method is used to identify gene markers linked to two phenotypic traits (fresh fruit bunch yield and number of strands), the results of which are described in the following first and second examples.
結果result
第First 11 例:example: FFBFFB 產量相關標記Yield related mark
執行預測與FFB產量有關之作物表現的標記識別,以選出高產量作物以植栽及培育。Marking identification of crop performance predicting FFB production is performed to select high yield crops for planting and cultivating.
將前述三個族群的269棵棕櫚如同上述地執行基因型鑑定。藉由測量個別油棕櫚產出的果串重量來執行FFB產量的表現型鑑定。執行應用GLM及MLM的關聯性定位。Genotype identification was performed as described above for 269 palms of the aforementioned three ethnic groups. Phenotypic identification of FFB production was performed by measuring the weight of fruit bunches produced by individual oil palms. Perform correlation positioning using GLM and MLM.
為了判定與FFB產量有正相關的標記,需要一個截止值使得選擇標記的數目為可管理的。如果截止值太高,會很難找到滿足此準則的足夠作物,但是在表現型上的效應會比較高。反過來說,如果截止值太低,便能夠輕易地找到符合此準則的作物,但將會有太多標記,其中的一些標記對於受測性狀僅具有微小的改良(增加)。在此例中使用的截止值為<0.01的p-值,係為了產生包含79個入選標記,其被推定與新鮮果串(FFB)產量性狀有關。這79個入選標記被預測與FFB有關,與p-值的GLM及MLM預測值一併列於以下的表2中。In order to determine the mark that is positively correlated with the FFB yield, a cutoff value is required such that the number of select marks is manageable. If the cutoff is too high, it will be difficult to find enough crops to meet this criterion, but the phenotypic effect will be higher. Conversely, if the cutoff is too low, crops that meet this criteria can be easily found, but there will be too many markers, some of which have only minor improvements (increased) for the tested trait. The p-value used in this example with a cut-off value of <0.01 is intended to produce 79 inclusion markers that are presumed to be associated with fresh fruit bunch (FFB) yield traits. These 79 inclusion markers are predicted to be associated with FFB and are listed in Table 2 below along with the p-valued GLM and MLM predictions.
表2:與新鮮果串(FFB)產量性狀相關之受測標記的一般統計線性模型(GLM)及混合統計線性模型(MLM)值
以被種植成以75棵每區地種植於3個分離的實驗區塊上之225棵棕櫚的族群,驗證這79個標記。當這三個區塊的種植作物是來自不同來源時,這三個區塊不應被認為是複製物,而是不同油棕櫚族群的多樣性代表,其為在油棕櫚產業的商業材料中所找到的多樣性之象徵。The 79 markers were validated with a population of 225 palms planted in 75 separate plots on each of the three experimental plots. When the crops in these three blocks are from different sources, these three blocks should not be considered as replicas, but rather representative of the diversity of different oil palm groups, which are in commercial materials in the oil palm industry. Find the symbol of diversity.
實施基因型鑑定以識別個別油棕櫚的對偶性內容。收集這些棕櫚的表現型資料。利用上述表2所列的79個已識別標記執行基因型鑑定,並以個別的樹為基準,識別連結至標記的不同的對偶基因與。如同對於79個標記的其中一個而言多個對偶基因可能為可行的,根據R平方(R2 )值應用截止。為了減少資料的複雜度並簡化分析,刪除所有提供R2 值<0.1的對偶基因。R2 值係為多少特定對偶基因解釋資料點與用以預測被判定的性狀或表現型變異的統計模型有多吻合之描述。因此具有小R2 值的對偶基因將不會特別地準確,且因此對本文敘述之目的沒有用處。對此例來說,我們以0.1作為截止點,所有低於0.1的對偶基因被認為對進一步的選擇是無用的。然而,已知可以接受R2 值的不同值,端視有多少標記可用於性狀的選擇,或是對於預測需要多少的精確度。Genotype identification was performed to identify the dual content of individual oil palms. Collect phenotypic data for these palms. Genotyping was performed using the 79 identified markers listed in Table 2 above, and the different pairs of genes linked to the markers were identified based on individual trees. Multiple dummy genes may be feasible as for one of the 79 markers, applying a cutoff based on the R square (R 2 ) value. To reduce the complexity of the data and simplify the analysis, delete all dual genes that provide an R 2 value of <0.1. The R 2 value is a description of how many specific dual gene interpretation data points are consistent with the statistical model used to predict the trait or phenotypic variation being determined. Thus a dual gene with a small R 2 value will not be particularly accurate and therefore not useful for the purposes described herein. For this example, we use 0.1 as the cutoff point, and all of the dual genes below 0.1 are considered useless for further selection. However, it is known to accept different values of R 2 values, and it depends how much selective trait markers can be used, or how much the prediction accuracy required.
判定R2 值並應用於個別族群上,其中當在不同族群中測試時會導致不同的R2 值。這是因為某些標記在某些族群中為較好的性狀預測,而某些標記在跨族群時運作良好。藉由根據對族群特定性狀的族群標記來判定標記的R2 值,便能識別出普遍性狀的標記,使得在給定族群中判定用以預測性狀的標記組合有更大的自由度。The R 2 values are determined and applied to individual ethnic groups, where different R 2 values are induced when tested in different ethnic groups. This is because some markers are better trait predictions in certain ethnic groups, while some markers work well across ethnic groups. By determining the R 2 value of the marker based on the population marker for the specific trait of the ethnic group, the marker of the universal trait can be identified such that the combination of markers used to predict the trait is determined to have greater degrees of freedom in a given population.
在採用了小於0.01的p值截止之後,79個標記之中保留下來的53個為FFB性狀的良好預測者。After the p-value cutoff of less than 0.01 was used, 53 of the 79 markers remained a good predictor of the FFB trait.
表3:在三個受測族群中具有小於0.01p-值的標記 值
來自關聯性定位樣本組的作物之基因型可為正向同型接合、負向同型接合或異型接合的對偶基因,這些資料係由分析存在於族群中之不同的對偶基因所獲得。此資料用以預測FFB產量表現。The genotype of the crop from the associated localized sample set can be a positive homozygous junction, a negative homozygous junction, or a heterozygous duplex, obtained from the analysis of different dual genes present in the population. This data is used to predict FFB production performance.
不像品質性狀,其中表現型性狀係由單一基因影響,產量係為數量性狀,受許多組成性狀(多重基因)的交互作用及整合所影響,其可與環境條件的變異像是降雨、地域、土壤類型、溫度和日照度互相影響。因此,為了增加選擇高產量油棕櫚的準確度以增加種植區域的整體平均產量,利用了多重標記。帶有被認為是次要的之對偶基因效應的標記也被包含作為可用以預測至期待值的顯著改變之「次要」變異體的組合。Unlike quality traits, phenotypic traits are affected by a single gene, yield is a quantitative trait, influenced by the interaction and integration of many constitutive traits (multiple genes), which can vary with environmental conditions like rainfall, area, Soil type, temperature and sunshine affect each other. Therefore, in order to increase the accuracy of selecting high yield oil palms to increase the overall average yield of the planted area, multiple markers were utilized. Markers with dual gene effects that are considered secondary are also included as a combination of "minor" variants that can be used to predict significant changes to the expected value.
已識別的標記接著用以篩查被預測為高產量作物的油棕櫚族群。至少一個、至少兩個、至少三個或以上標記被選出,象徵正向/負向對偶基因效應。此影響隨著越多標記而越提升且使用的標記數目取決於R平方值的全部總和。藉由將連接至眾多標記的花費與利用大量標記的準確性作對比來納入考量以選出截止點。換句話說,在越多標記數目的情況下,預測會越準確,但執行實驗的花費也會越高。The identified markers are then used to screen oil palm populations that are predicted to be high yield crops. At least one, at least two, at least three or more markers are selected to symbolize the positive/negative dual gene effect. This effect increases with more markers and the number of markers used depends on the total sum of the R-squared values. The cut-off point is selected by taking into account the cost of connecting to a plurality of tags in comparison to the accuracy of utilizing a large number of tags. In other words, the more the number of tags, the more accurate the prediction will be, but the higher the cost of executing the experiment.
R平方值的總和表示有多少的變異可以被迴歸模型中的對偶基因組合解釋。舉例而言,如果標記組合給予為1的R平方值總和,那麼標記組合將準確地預測表現型的改變。例如,如果R平方總和為0.3,意指根據該性狀的回歸模型標記的預測可有30%的準確度。The sum of the R-squared values indicates how many variations can be explained by the combination of dual genes in the regression model. For example, if the combination of markers gives a sum of R squared values of 1, then the combination of markers will accurately predict the change in phenotype. For example, if the sum of R squares is 0.3, it means that the prediction of the regression model marker according to the trait can have an accuracy of 30%.
帶有最高的R平方值的理想標記,例如R平方值為1、或R平方值為0.9、或R平方值為0.8、或R平方值為0.7、或R平方值為0.6、或R平方值為0.5、或R平方值為0.4、或R平方值為0.3、或R平方值為0.2、或R平方值為0.1將隨著最高的標記效應被選出,且可選出遞迴的額外標記直到R平方總和達到合理且可再現的預測準確度。然而此如同其取決於實際的量測地主觀。An ideal mark with the highest R-squared value, such as an R-squared value of 1, or an R-squared value of 0.9, or an R-squared value of 0.8, or an R-squared value of 0.7, or an R-squared value of 0.6, or an R-squared value. A value of 0.5, or an R-squared value of 0.4, or an R-squared value of 0.3, or an R-squared value of 0.2, or an R-squared value of 0.1 will be selected with the highest mark effect, and optional additional marks for recursion up to R The sum of squares achieves reasonable and reproducible prediction accuracy. However, this is as subjective as it depends on the actual measurement.
如果效應大小的範圍非常小,例如100公斤到110公斤的差別(換句話說,10公斤是效應大小的效應大小),那麼當準確度無法去選擇作物時,像是對於感興趣之性狀具有顯著增加/減少的棕櫚,便不能合意地使用許多標記。如果變異的範圍非常大(例如50公斤到150公斤之間的差異),那麼就可以合意地選擇更多的標記從而將選擇帶有最顯著增加或減少性狀的作物。If the range of effect sizes is very small, such as a difference of 100 kg to 110 kg (in other words, 10 kg is the effect size effect), then when the accuracy cannot be selected, it is as significant as the trait of interest. With the increased/decreased palm, many markers cannot be used desirably. If the range of variation is very large (eg, a difference between 50 kg and 150 kg), then more markers can be desirably selected to select the crop with the most significant increase or decrease in traits.
選擇至少一個、至少兩個、至少三個、至少四個或以上表示正向對偶基因效應的標記。標記為遞迴式地增加以平衡最高可能R平方值與最少可能標記。篩查受測族群以得到帶有連結至良好對偶基因效應的對偶基因作物,並挑選出帶有該對偶基因的作物。在此例中,如表4所示選出了六個標記,其也顯示了與標記相關的不同對偶基因及每一個觀察到的對偶基因的評估GLM值。At least one, at least two, at least three, at least four or more markers indicating the effect of the forward dual gene are selected. The mark is added recursively to balance the highest possible R-squared value with the least likely mark. The tested population is screened to obtain a dual gene crop with an effect linked to a good dual gene, and the crop with the dual gene is selected. In this example, six markers were selected as shown in Table 4, which also shows the estimated GLM values for the different dual genes associated with the markers and for each of the observed dual genes.
表4:被選擇用以篩查棕櫚族群的入選標記
為了驗證標記,這六個標記被選為最佳例並用於基因型鑑定全部225棵不同背景油棕櫚,其背景包括Deli、AVROS及Nigerian譜系的混合體。紀錄這些作物的個別產量54個月並計算出每一棵作物的平均FFB產量六個標記中的每一個討論中的對偶基因列於表5。To validate the markers, these six markers were selected as the best example and used for genotyping to identify all 225 different background oil palms, the background of which included a mixture of Deli, AVROS and Nigerian lineages. The individual yields of these crops were recorded for 54 months and the average FFB yield for each crop was calculated. The dual genes in each of the six markers discussed are listed in Table 5.
表5:對225棵棕櫚之驗證族群的六個標記之基因型鑑定結果
根據上述表4中標記的對偶基因準則選出作物,並且重新計算被選出作物的的FFB平均,以判定對於整體未選擇的族群的平均FFB是否有增進。未選擇的225棵棕櫚其平均新鮮果串為233.8公斤/棕櫚/年。Crops were selected according to the dual gene criteria labeled in Table 4 above, and the FFB average of the selected crops was recalculated to determine if there was an increase in the average FFB for the overall unselected population. The unselected 225 palms had an average fresh fruit bunch of 233.8 kg/palm/year.
如果根據標記1來選擇棕櫚,其藉由挑出含有正向效應之對偶基因組合C:C的棕櫚,摒棄具有負向效應之對偶基因組合T:T的棕櫚和無效應之對偶基因組合C:T的棕櫚,那麼將會從225棵棕櫚中挑出45棵棕櫚且其平均產量為255.77公斤/棕櫚/年,FFB的增進為21.97公斤/棕櫚/年。If palm is selected according to marker 1, it is to discard the palm of the dual gene combination C:C containing the positive effect, and discard the palm combination of the dual gene combination T:T with negative effect and the dual combination of effectless C: The palm of T, then 45 palms will be picked from 225 palms with an average yield of 255.77 kg/palm/year and an increase in FFB of 21.97 kg/palm/year.
如果根據標記2來選擇棕櫚,其藉由挑出含有正向效應之對偶基因組合A:T或A:A的棕櫚,那麼將會從225棵棕櫚中挑出161棵棕櫚且其平均產量為239.66公斤/棕櫚/年,FFB的增進為5.86公斤/棕櫚/年。If the palm is selected according to marker 2, by picking the palm of the dual gene combination A:T or A:A containing the positive effect, then 161 palms will be picked from 225 palms and the average yield is 239.66. In kg/palm/year, the increase in FFB is 5.86 kg/palm/year.
為了選擇棕櫚,使用僅具有負向效應的對偶基因組合之標記,包含這些對偶基因組合的棕櫚將從選擇之中被排除。例子微利用標記3,其包含負向效應之對偶基因組T:T及A:T而從225棵棕櫚中被排出的棕櫚有208棵,且將挑出17棵棕櫚,其平均產量為271.58公斤/棕櫚/年,其增進為37.7公斤/棕櫚/年。In order to select palms, markers of a combination of dual genes with only negative effects are used, and palms containing these dual gene combinations will be excluded from selection. The example micro-use marker 3, which contains the dual-genome T:T and A:T of the negative effect, has 208 palms discharged from 225 palms, and will pick 17 palms with an average yield of 271.58 kg/ Palm/year, its promotion is 37.7 kg / palm / year.
如果根據標記4來選擇棕櫚,其藉由包含正向效應之對偶基因組合A:G,並摒棄包含負向效應之對偶基因組合G:G的棕櫚,那麼將會從225棵棕櫚中挑出67棵棕櫚且其平均產量為249.71公斤/棕櫚/年,其增進為15.91公斤/棕櫚/年。If palms are selected according to marker 4, which combines A:G with a dual gene comprising a positive effect and discards the palm of the dual gene combination G:G containing a negative effect, then 67 out of 225 palms will be picked. The palm has an average yield of 249.71 kg/palm/year, which is an increase of 15.91 kg/palm/year.
如果根據標記5來選擇棕櫚,其藉由包含正向效應之對偶基因組合A:A,並摒棄包含負向效應之對偶基因組合G:G及中性效應之對偶基因組合A:G的棕櫚,那麼將會從225棵棕櫚中挑出45棵棕櫚且其平均產量為252.91公斤/棕櫚/年,其增進為19.11公斤/棕櫚/年。If the palm is selected according to the marker 5, it combines A:A with the dual gene comprising the positive effect, and discards the palm of the dual gene combination G:G containing the negative effect and the dual combination of the neutral effect A:G, Then 45 palms will be picked from 225 palms and the average yield is 252.91 kg/palm/year, which is an increase of 19.11 kg/palm/year.
如果根據標記6來選擇棕櫚,其藉由包含正向效應之對偶基因組合C:T,並摒棄包含負向效應之對偶基因組合C:C及中性效應之對偶基因組合T:T的棕櫚,那麼將會從225棵棕櫚中挑出161棵棕櫚且其平均產量為238.97公斤/棕櫚/年,其增進為5.1公斤/棕櫚/年。If palm is selected according to marker 6, it combines C:T with a dual gene comprising a positive effect, and discards the palm of the dual gene combination C:C containing a negative effect and the dual effect of the neutral effect T:T, Then 161 palms will be picked from 225 palms and the average yield is 238.97 kg/palm/year, which is an increase of 5.1 kg/palm/year.
棕櫚的選擇可以利用單一標記或複數個標記來實行。表6顯示了如果利用複數個標記來選擇225棵棕櫚之驗證族群的FFB獲得產量。The selection of palms can be carried out using a single marker or a plurality of markers. Table 6 shows that if a plurality of markers are used to select the FFB of the 255 palm verification population, yield is obtained.
表6:利用複數個標記以選擇之驗證
為了進一步判定獲得的標記是否能預測在油棕櫚的選擇中必須要避免之對偶基因,相同的試驗在相同的驗證族群上實行,其中選擇負向對偶基因效應代替選擇正向對偶基因效應。這與上述例子中以標記3實行的對偶基因選擇相似。結果顯示在表7,從中可以觀察到選擇負向對偶基因效應對受測性狀具有不利的效應。To further determine whether the obtained marker predicted a dual gene that must be avoided in the selection of oil palm, the same experiment was performed on the same validation population, with the negative dual gene effect being chosen instead of the positive dual gene effect. This is similar to the dual gene selection performed with marker 3 in the above example. The results are shown in Table 7, from which it can be observed that the selection of the negative dual gene effect has an adverse effect on the tested trait.
表7:利用複數個標記以選擇之驗證
上述的例子很清楚地顯示了,可以藉由尋找那些帶有被預測為對受測性狀有助益(正向對偶基因效應)之對偶基因的作物,並且避免對受測性狀帶有不利效應(負向對偶基因效應)的對偶基因來達成油棕櫚性狀的預測。The above examples clearly show that by looking for crops with dual genes predicted to be beneficial for the tested trait (positive dual gene effect), and avoiding adverse effects on the tested traits ( The dual gene of the negative dual gene effect) is predicted to achieve oil palm traits.
第二例:串之數目相關標記The second example: the number of strings related to the mark
用以預測油棕櫚串之數目的標記識別係利用與描述於第1例的相同方法執行。The marker recognition used to predict the number of oil palm strings is performed using the same method as described in the first example.
利用上述的方法,入選的44個標記(P值小於0.01)被推定有關於油棕櫚的串之數目,其油棕櫚與第1例中的作物材料相同。其列於下述的表8。Using the above method, the selected 44 markers (P value less than 0.01) were presumed to have the number of strings of oil palm, the oil palm of which was identical to the crop material in the first example. It is listed in Table 8 below.
表8:與串之數目(BNO)產量性狀相關之受測標記的GLM及MLM值
接著測試標記以確認其具有R2 >0.1值,如於表8中所示。除了被測之表現型為串之數目(BNO)外,利用上述步驟執行驗證,其結果列於下述表9中。The label was then tested to confirm that it had a R 2 >0.1 value as shown in Table 8. Except for the number of strings to be tested (BNO), the verification was performed using the above procedure, and the results are shown in Table 9 below.
表9:在三個受測族群中具有<0.01p-值之標籤的R2
值
已識別的標籤以說明於上述第1例中的方式測試。顯示這些標籤能夠預測串之性狀。The identified tags are tested in the manner described in the first example above. Displaying these tags can predict the traits of the string.
表10:選擇具有其之入選標記以篩查棕櫚族群
如表10中的這五個標記,列出了對串之數目性狀具有效應的對偶基因組合,並且可以藉由其本身或組合來選擇出被預測比平均串之數目高或低的作物。這些標記被命名為標記7、8、9、10及11。對於標記7、8、9、10及11於225棵棕櫚的基因型鑑定結果顯示如表11,其選擇能力的驗證顯示如表12。As with the five markers in Table 10, the dual gene combinations having an effect on the number of traits of the string are listed, and the crops predicted to be higher or lower than the number of average strings can be selected by themselves or in combination. These markers are named as markers 7, 8, 9, 10 and 11. The genotype identification results for 225 palms for markers 7, 8, 9, 10 and 11 are shown in Table 11, and the validation of their selection ability is shown in Table 12.
表11:對225棵棕櫚之驗證族群的五個標記之基因型鑑定結果
表12:利用用於選擇之複數個標記之驗證
表12顯示了已識別以連結至串之數目的標記可用以選出包含統計上連結至相較於未選擇族群的平均值不論是較高串之數目或較低串之數目的最佳對偶組合之作物。此例用作為證實揭露於此之方法可被用以連結不同的表現型至基因型並由此偵測有助益或合意的對偶組合。Table 12 shows that the markers identified to be linked to the number of strings can be used to select the best dual combination that includes statistically linked to the average compared to the unselected population, whether the number of higher strings or the number of lower strings. crop. This example serves as a demonstration that the method disclosed herein can be used to link different phenotypes to genotypes and thereby detect useful or desirable dual combinations.
表13:新鮮果串的Sequence ID No.及SNP
表14:BNO的Sequence ID No.及SNP
無。no.
<110> 雲頂種植有限公司(Genting Plantations Berhad) <120> 用於選擇表現型性狀的基因標記 <130> 28896SG2 <160> 115 <170> PatentIn version 3.5 <210> 1 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 1 ctagcctaga gcttgaatat tttctttgaa ttggctctag ggtgcataga aacctgaccc 60 rgagcctaat tctagcatta tttgtgccta ctgtttactt taaaaaataa aataatagta 120 a 121 <210> 2 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 2 atgtatagag gatagttcct cttccagtgg ccctgtttct tgcaaaaaaa gcactctgcc 60 wagctctggt cgggcttgtg cttctcggac tcacgcttct tggtctgacc atgtgcagac 120 a 121 <210> 3 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 3 tcatgtcagt gtctacaata ttgtttttgt gtttcttgtt tcctatatta taattttcaa 60 ygaaacttgt ggtgtgacat agttactcca ccttggaatt ttaaattgct ttagctgaaa 120 a 121 <210> 4 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 4 ttcgcaactc attgtcagac aatactgagg agaatgtgca gcctgagatc ctgttctctc 60 yagatactta caaagcttaa gtctctacaa tcgtattttg attattttaa aatttctcac 120 a 121 <210> 5 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 5 tatatataac ttcttggcct gagactcaat taaaaaccaa attgagacat ggcttgaatg 60 yattagttaa attgacttgt gaagtaatgc cggatcaaca tgcacatgga caagaaaatt 120 a 121 <210> 6 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 6 catatatacc aactattatt ccagcatgca tcttctaagc tggtcatgct ggtccatctg 60 waaaggatca tggttcgcac atggccttgt tttctccaat gaaaaacaaa aaagaaaaaa 120 g 121 <210> 7 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 7 gtccatttaa agatgatggg ggctgatgac cacatcgagg ctgatggaaa agagggactt 60 ragaattggg taggggagga gataaaaaga gaaggaaaga cttgttgcaa cgaagtttga 120 g 121 <210> 8 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 8 atccaggtta tggactttga tgatgatgaa accattgggc caatctctga tgagattaaa 60 rtacttgctc aagggccaaa ccatattgca agaaggttta aagcttttgc tatggataat 120 g 121 <210> 9 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 9 agaatttttt gccttcaagg ttttcttggt ttttatcatg tattttgcca tttctattgg 60 yagcctgatc aatgcaaaca ttatggtcac gtaattgtct ttgccgaacc ccttccacaa 120 a 121 <210> 10 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 10 ttgctttctc taccccttta tataagttcc ttccagcaga tctctatctc tctctcccat 60 yttgttagac cctactctgt ggcccgtctt tctatacctc tctctcccct ccccaccaca 120 c 121 <210> 11 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 11 gcatgattca gattaaaagt attttaatct tatattctgc tttgatattt aaaaaataaa 60 rttttgaaat acacatgcat gccccaaacc tctaattcca acagtggtat cagagccacg 120 a 121 <210> 12 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 12 ctttatgagg aatcatttcg agccgagctt cgattacctg tacacccttt tgtcatagag 60 ktctttcatt ttttcaatat tttttcttat tctttagttt ccaactcttt tcatttcatt 120 a 121 <210> 13 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 13 tcattgtgct tgccagattt tagcctaaac atctctgaaa atagaggtaa gatcctctag 60 wcatcaagat aatttagttt gctatcttcc tcagccttta aaacctcaat ttcagtcgac 120 a 121 <210> 14 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 14 gaatatgggt ataaatgtcc cttcgatctg agatcaccat agtgacttgc aagcaactca 60 ytatgcttta gtattggact atttaaattt ttaattcagt gatgaaaaat ttttaggcac 120 a 121 <210> 15 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 15 gtacttggat taagttgatc accaggccgt ccggtcatag gagcaaaaag atttaaaagc 60 ygtctcttcc tattcgatag ggtgctctta tggtgtgtag gggtgccatg tgatttgatc 120 c 121 <210> 16 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 16 agctcgattg gacctaaatc aattagattg aaatctaatc aaatttgatc aacttatatt 60 yggacctact gccagttaga tatggaaccc aatgagacac acacatatag aaattggcca 120 a 121 <210> 17 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 17 gctcgattgg acctaaatcg attagattga aatctaatca aatttgatca acttatatct 60 rgacctattg ccaactagat gtggaaccca atgggtcaca cacatataga aattggccaa 120 g 121 <210> 18 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 18 taaggggcta tttgattttg aataagattc aaaccttttg cctatttaaa gggatcttct 60 ytaaggctct aagcatcaca ttttcaacag ccccacgcct ccctctcttc tctcctttgg 120 t 121 <210> 19 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 19 tagcttatat aggaagagac tatttttttc atgtgaggtg tctttgaaga gcaaaactgt 60 raggctctaa atgacaaagg cccactgaag tccaaagatg gtcatgtgct ttttaaagag 120 c 121 <210> 20 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 20 tgatccatca agttgtgttt atggaagggt aacgtaactt tggcgatggc tttaaaacca 60 wtgaatatat atattttttt catttctctt cctctctttc tccctctctg tttcttcctt 120 c 121 <210> 21 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 21 ctaaaactga gccatcaacc tctttctgat accagttgaa agaaaaaaaa ttatcttttt 60 ycttgtagga tctttcagat ttcatcaaat ctgaggtgaa ataattttaa aaaaaattta 120 t 121 <210> 22 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 22 tatatagttg ttagcattgt tgtaagtaat ttagtattac catagtagct aatcacattc 60 yatctttgtc aggagcttta aagtttgggc gggaagtttg tctcacttgg tgtcccaatg 120 g 121 <210> 23 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 23 cttgagctac ccaagagttg gtttcttacc atgtcataac tcatatagtg tggtaaaaaa 60 wgatttaaaa aaaatctgat tcaaaaaatg aatcacaata aataatatat atccctagag 120 a 121 <210> 24 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 24 gatgccgata ttaatattct cagtcattat taaaattcac tgaatagata ttagtaatga 60 yagtatcaat gcactcgacc atcaataaag tcattattta aaatgcacca aaaatttggc 120 t 121 <210> 25 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 25 ccaaacttcc tattttaaaa aacagcgtca tgcctggatg atggtatcat gtcccttctt 60 ygttttcgac gaacataggt ttccatgcag ccggaaatta ttcagaaatt tgatcattat 120 t 121 <210> 26 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 26 ggggagagag aacagtctcc cctttaaata gggtcagagg ggaggagttt gactcctcct 60 yagggtgttt tttgactccg attaggagtc ggtcgggaag aagaagaaga ctctcaggag 120 t 121 <210> 27 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 27 aaattaaggc catacaggag atgactccct caagaacgat caaagaagtg caacatcata 60 ygggaagact tgttgctttg aaccgatttg tcttgagatc gacagaatgg tgcttaccct 120 t 121 <210> 28 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 28 ctcaaccatt tcatgatgtt cagtcaattt taaagacaac ccatgcagtg atagtaaaga 60 kgtaaatgtg tgtataagaa tataaaagga ctactcatgt tgatatgcac aagttagacg 120 a 121 <210> 29 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 29 gaatgtatgg atatcgagca gatggtctgc cgatggctgg agggttggca ggcccgtgca 60 ytgtctatga tggatcggat caccttgatg aggtctgttc tcagctttat ttcagtgtac 120 c 121 <210> 30 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 30 tcttcaattt atgaccactc tccttttcta ccatagtatt aaatgcttta aaaatagaaa 60 stgtagcagg cttttcttga aggaaataaa ctcatagttt tatagtgtaa ttatcaatga 120 a 121 <210> 31 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 31 caatgaatgg acaggtgctg ttacatatct aaacactgaa aatttgatcc attatacttc 60 yttatcagct gaagttttaa aattatatgc aatactctct agattgtaga gtgaaagaaa 120 t 121 <210> 32 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 32 cattcttatt ttaaaaaaga aaaaaccttt atgagactct ttgatacaac actgacctat 60 kgtaagctat gaaggcattg cagtggttta ggtgcagtct agatagcttt atttcttgtt 120 t 121 <210> 33 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 33 atagtagtga gtaaaattaa ttttgatgta ctacgatatg tatcaaattt tggtaccatt 60 rtcggagatc ttagcacgat tgttttaaaa aaaatcaaaa aaaaatttat aaaataataa 120 a 121 <210> 34 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 34 ccttggtcag aaggctatca gtttcaactc ctagtcgaca tacaacactc tctgattttt 60 yctcagaagc atatcgaaaa gctcaagttc aaagtgcagg caccaactgg ccacagctct 120 c 121 <210> 35 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 35 actgcatggt taacaaggaa cttttctatt gctcaacttt gaactaatct tatgtaggtt 60 rctagcctac cgagagagac actatcatgg tctttttgca tgaacctttt aaagacatgt 120 t 121 <210> 36 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 36 tattgttttt aaaatacagt tactaatttg tcactagtct ctctccaata ttttgtttga 60 raatacatat ccattgataa tcgatcgcta ttcagtcgct aaaaaaaaac tattcgggac 120 a 121 <210> 37 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 37 aaaacagacg gatgaaacaa ttatttagaa ggctataatt cgaggaattc atggtgttat 60 mtaaaggcct ttgtttgcag ttttcacatt ctattttctt gccatttttc ttcttgttat 120 a 121 <210> 38 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 38 tttaaacatc actataagca taaacatcat atcttatcct aaccagtcac cgagctactc 60 rtgtgaatat ttggattgga ccaattgagc ttcttctcat attttgaata cttcatagaa 120 a 121 <210> 39 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 39 catgtcatat aacaaatacc cacgactaac aacttagtga gtgggtggat ttcctatcct 60 wgctacctat agattcagac ataacaaact ctggtacttc tctatataaa ggtaacaaga 120 g 121 <210> 40 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 40 tttttttttt tgggtaaacg tgtactagtc ttgtttgatt tgtcttgcag aagaggcatc 60 watttgtgga tcttttaaat aaaagtttga tgaaagagta gaccattata atgggtcaaa 120 t 121 <210> 41 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 41 ctcagctttt aaaaattcaa ccttctatct tttgctgccc tttgagacat agtcggctaa 60 ytttctgact tagtcgacta agtttgcgtg ccaagcgtac gaagggttct ttgaaatgtt 120 t 121 <210> 42 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 42 atccgtttaa cattggccaa aaacatcaca ttcaacatcc tggaggaaaa gacgatagct 60 ratttgatga aggctctatc taacatgtat aaaaaacctt cgacttccaa caagatatac 120 c 121 <210> 43 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 43 gatgtatgct gtggtgtgtt gtagattaca tcttgcccat gcagtgagtc agatcagcag 60 rtttatggta tggcctagca agaagcattg acgagcactg aaggagatct tcagatatat 120 g 121 <210> 44 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 44 ttatgcttga aaggatatag aagatgttga agaagattat ttttgaagac ttgctgaaat 60 ytgtgcataa ctttcctctc tctttatttt ttggatattc aatgtttttc acaaaaataa 120 a 121 <210> 45 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 45 aacgagaagt tcgggcccca agctcgaaca ccgagagaaa gcacaaattt gaagggtctc 60 raaaggacct tcggtcatga acaaaaagga tgaatcaatg tggcgatgac cagaaacctt 120 c 121 <210> 46 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 46 ttggagcctt tgcatctact ttttcatgtg tcacatagag cctaggggat gccccatgct 60 rgtcccacat gtcctcttta aaatgggcat gtccaacttg atcaaatcaa gtgacgcccc 120 t 121 <210> 47 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 47 tttaaaaaaa gctgtgcatt acagatgact gcatctaaaa ccatcatttt ggtaacaaaa 60 magtcacatt atttccgaac catgaacagc aaatggtgca ggataacttt cgttagattg 120 c 121 <210> 48 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 48 aatatttatt atttaaaatt aattttgcag catatttaca gaaagctcta tgcctcgtgt 60 kattaccgag atcatctaac gattgatgtc gggcccagtg aacgagttct ctacttgacc 120 a 121 <210> 49 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 49 ttatagataa ttctcatgat ctaataagta taggagttct aacccaaatc taatttaaat 60 yagtccaata cttataaaaa aaaatttcta catgagatag aattgccatc acatatgaca 120 a 121 <210> 50 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 50 atattttcat caaattttaa atctttcgga tagtcatgac ttattgctaa acatcaatct 60 kgacttatgg attcatcaaa attaaaaaaa tttaattcaa gaattaatta ggaagaatct 120 t 121 <210> 51 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 51 agtaaaatgt aaaaatgcag tttggaaagt tacataattt tttaaacaca aaagaaaact 60 ygatatggtc tttcttggtt tgtgacataa acacgaaata tgtacccaaa gttttattag 120 t 121 <210> 52 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 52 ttttctgact ttcccaatgc tgctagtttt gcctggtgct gctcagcttc tcttgctgcc 60 rtcgctgaat ttttttcaag ttcttcttgg tttcacactt ccgcttggcc tcccccggtg 120 c 121 <210> 53 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 53 aagggtctag ccactgtagc ggaccctcat caccctactc cacaaacagt ccgattggat 60 ygagaatcta actgcatgcc taatgatcaa aacctccctc ctcatcaaca aggagtggat 120 c 121 <210> 54 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 54 atatgtctaa cgatcctcct ggatcaaagg atgataaata ctcatacact agtgtttttc 60 yagtgacccc tcatgctcca tccaataatt ttaattatca tgtaaattta aatatttttt 120 t 121 <210> 55 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 55 tcagaaaaat agcaaaatta aagcttaata gtaaacattt ttaatggaaa tcaaaccctc 60 raccaaacct gaaggcattt aaatataggg gacaccaatg ggtaagaaat ttaagcccat 120 g 121 <210> 56 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 56 tctttctcct caactgactg tcctgcacta tcaggaatat ctttgtcctt gtagaggctt 60 ytttcattga agatcatggc cttgcttctg atgaatttcc tatcctgctc attccagaac 120 t 121 <210> 57 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 57 catggctggg tttggaggtc gaggacgcct gcggccaaga aagcgagaga gaaacaagga 60 rcttctccga gatggggcgg ggggatagcg gatcgatcga gatttttctg gaatggaatt 120 g 121 <210> 58 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 58 taatcttaat tagtttacga ttgtcatata tcctaatttt ttaaaactta ttttaagaac 60 raaagggatt ctaatccctc ccactactct atacccactc tcctaacata gattgaagtt 120 t 121 <210> 59 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 59 aagggctcac ttggttgagg ctctacattg gccgacctcg atggcctttg gcttcctcaa 60 wgaaccttgg gcagtcgacg ctaccctctt cttagggata tgttgcgcca agatccaata 120 c 121 <210> 60 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 60 aaagctatga tgattgttca gcaattgtct attaatggaa ataatatcag tcaccgaata 60 wgagagtgca actattgtct ggcgtgatat attgaagctg gcctaacaac catgaatgtg 120 a 121 <210> 61 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 61 ttttcattat tcatcatcat ggaaaagatc gtgcagcacc cctacatacc ataggagatc 60 ycatcgaatt ggtaaataag attatgaaat cttgatttct tctaggatcg gatatctacg 120 a 121 <210> 62 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 62 ccttatgttg ggtaatgtac ttggggtggc atagtgtagg cttgaatctg acttaagcct 60 rtgataggag ggcctattag gattagtttt aaatggctag atcccctctc caatttctat 120 a 121 <210> 63 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 63 accaaccaaa atcttacaag tccaattcta ggtttggatg ggcctaatcc aaatttcttt 60 yatccccaag aaacttgaaa agaaaacaag aatataagat gcagaatttc agaataaatt 120 a 121 <210> 64 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 64 ttgttccaat catgtatgga tttatctcaa tgattttttt gacagtttga gaagctgcaa 60 raaaaatagg tatccaatgg taagactaat gttttaaacc agatcattga caaaactgga 120 a 121 <210> 65 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 65 aagagtacgc cagcttactg aaccatggcc gatcagcaca agatccaatt ccgatacggc 60 raaccttact tctagtttca tcaaagtaat aagtaacaag caaaggggta gagcactgat 120 g 121 <210> 66 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 66 tatccctttt aaagtactat gatatctctc actaactaat agaccttaaa ggctatttat 60 rtcatcaaaa actacatagc atatgacttg gtatgcttca aataggtgtg ttgatggttt 120 t 121 <210> 67 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 67 ttaaacttat caaagacttt ggatttatgt ttcattaaat ccatatatcc aaaccttgat 60 raatcattta taaaagtgat gaaataggag catcctcttc tgatttgagt tgtcattgac 120 c 121 <210> 68 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 68 tgtcattaaa gtaacactaa ctatggcttt accaaccact atcttatcta atttaaagtc 60 yttttcatca caattaccaa tgtgccgtaa cataaaacgc tgcaaaatga tcttttaatg 120 c 121 <210> 69 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 69 ataacgactg gatcatcatt tgagtcacaa aagggtgctc ttcgattcat tgattaataa 60 wttttgtaaa gccaccatat agtctttgta tttttaaaag tttcctcccc tattttctca 120 a 121 <210> 70 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 70 tcaaggtttc aagctatcaa gctagcttga caagttggtg gaagatgttg atggatagag 60 rgacttaatc tcgggcaaaa taacaactag gatttgggcc ggtccacttt aaaaatactt 120 t 121 <210> 71 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 71 agtatcatat tagataagtg tcattattgt ccttctttga tgatgaatgt catttctaca 60 rgttttttgg ccaaatttaa ttttaaattt ttaataaaag ataatttttg tgatatcatt 120 a 121 <210> 72 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 72 tcttcaaaat atctctctca atattcaaaa aatttaaaga taaaacgtca tgattatgat 60 wtttaaatcc ctaaaattag tttcaaggag tgaacattga acacctaccg agcacatcgc 120 c 121 <210> 73 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 73 atacatggcc attagggaca cactaaagta gtaaacacta aaataaaatt ttaaaaaatg 60 rtcaaaagtc ctgaagggta acaataaagg tttatgaacc tcaaaggtct cacatagtgg 120 a 121 <210> 74 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 74 tacatttcca gtcagtgtag gcttcataac aatgattcag attgtgtgag gcacggcatc 60 mtggttttcc catgaaacaa gacacgatgc catctcggcc catcctgaca taatgccttt 120 g 121 <210> 75 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 75 ccaaaagctc ttgcttccta tttattgcat gcaactgatt aacccatatg agttctattt 60 rgactcttct tctctctttt tttctttttt atttaaaaaa aatgtagtcc cacatgagga 120 g 121 <210> 76 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 76 accccctttt aaggccagtt gttgatagca atttttggat ggtttaaaaa gaaaatgatt 60 yttagtgaaa gaaggctgta taccctcttt ccttttctta tgctccctct tcttttcctt 120 t 121 <210> 77 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 77 gcaaaagagt agtggtacag actgtgaatt aaaccatatt caagttattt aaagatgtca 60 ygtcttcttc tatgaactaa agcgaagatg ttcccttgtt gtacaagtat tattttttca 120 t 121 <210> 78 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 78 agtaaaaacc tctgcctcca gtttgctgac gatactattg ttttttgaga agcgaaaaag 60 raagttgctg gccatctcaa gttcatatta tactcatatg aattggtatc tgatctcaaa 120 a 121 <210> 79 <211> 121 <212> DNA <213> 人工序列 <220> <223> 新鮮果串(FFB)之SNP <400> 79 tattttctac tatctcataa gctgatgcta tggcacatcc tattggttga tcactcctat 60 rgatagcatg ctgaaaaata tgcttgataa attctcaaaa gctgacaagt tggtttaaaa 120 t 121 <210> 80 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 80 gtccatgaag cttagaagtc agtatcccaa agttgcatca actagttggt cgatctttga 60 yaaagaaaaa ctgtccttcg gatgagcttc atttaaattt gtatagtcga tgtaaattct 120 c 121 <210> 81 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 81 ctaagtgtgg gggcgtgcgg gatgcccaaa gaagagggag aaggaagagg aagagagggc 60 rtgggaagag cttttgggca taaggggctg ctaggtttta tgccctaagg atcttaaggg 120 a 121 <210> 82 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 82 ctgctgaact gtatggtttt aattctccaa atcattgaat atgggggctc acaacctaag 60 kgtcatgtat gttatatcct ttcgaaaagt cttttagagg tttcatgtag ggccaaattt 120 g 121 <210> 83 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 83 tatcccaata aatgcggtcc aggtaagttt ttatcagagg caagagtcac caaagaaaag 60 rtagagagaa caactagccc aaggaaattt tgcagcactt tttcatttag aagagaagga 120 t 121 <210> 84 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 84 tatcaacatg tcagagtcaa cttgaaatct cttgaagttg actttaaggc tttttcactt 60 rattttttat gaaaaatctt tatctaatca tcctttttta ctttcaaaat actttaaata 120 c 121 <210> 85 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 85 ctgtggccag tatggccagt ccattaattt gaaagctgtt ggaatccata cacctcataa 60 kttaaatttt tgagaaatag aaatcacact tttagatgaa ttcatgtgct tcaagaaagt 120 c 121 <210> 86 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 86 acctcctctc ctggacctcc gaggaggtac ttgatgttag tcttgttcgc cgtctcagct 60 rtatcattgc tgggcctcgt ctctccgttt taccatggag gagaattggc gtccgaccgg 120 g 121 <210> 87 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 87 tagatttgat tattttattg gccatccgaa tccgaatcta actcatttaa aatagaattg 60 ractatattt ttcgatccaa tggatggggt cgagcctaaa attcaaatcc cattggtgaa 120 g 121 <210> 88 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 88 agatgaaatt tactagtagt caaagtcggg gacgaagtct gactcccgta ggagtccaga 60 yggagtttcc ccatggccag agtcagagat gatgtccggc tcccgtagga gtccggacgg 120 a 121 <210> 89 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 89 tgggttattt ggttggccat gacttgtttt taaacaggtt aaacagttgg gaaaggatca 60 sctcacctgg gcaataaaca ggttagttag ggtttgactg tctaacctac ttagggtccg 120 t 121 <210> 90 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 90 atgaaaggaa acattcctta tgcagttcac ataaagatga gtaataagac ctgaggcctg 60 rgcaacagtg atgctcacat taagaaggtc aaattgttgc tcatagttac caaggtacta 120 t 121 <210> 91 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 91 catatctgta cttttttgcc tgaatagcga agacatgaat ttgatgttac tattccatat 60 wtgtttaaaa tgaagatgaa tatgagctgg atataaatac ttctttttta attgaatgtg 120 a 121 <210> 92 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 92 acggctccac cctcttctcc agattgcctg ctcctgggct ggggttggga cttggataca 60 raaacatgtc ttatcaatgc tatagcagtc tgtgaactta aaggttcatg cgggacggta 120 c 121 <210> 93 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 93 caactcgtgg gctaggcatg gcctgacatg gtccaggcct agtccaagcc ctgcttgatc 60 yttttttctg aatttaaaaa atatattttt ttataaatta taaaagtgtt aaggagtaaa 120 a 121 <210> 94 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 94 tacataatag tgagtaggtt taattttggt atgctacgac acatataaaa ttttgacatc 60 rttatcggag atcttggtat gattgtttta aaaaaaatca aaaaatatat atttactact 120 t 121 <210> 95 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 95 aaaagcggga tgaattgaat tctttaaaaa tttttactaa atccaaatct gaacaattat 60 rtgcttcaat ttaagctaaa ttgagtgttt gtgaagtatt tgatatgtgt agcagcaaaa 120 t 121 <210> 96 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 96 gtaaatgcaa aatttaataa ctaaaattta aatccatggt tcaaaaaaaa gtcaaagata 60 wtttttgatt tttaagaccg atgctagaaa tcgatgcaac aatttggcaa aatatgaatt 120 a 121 <210> 97 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 97 catctccatg ctatctttct aattcaaatt gaacctatga ttctctagca aaacagtaat 60 mgcatttgct tacaccattg atgaattatg tttgttttta aaactcaaag agcattctcg 120 t 121 <210> 98 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 98 gtggtgcagc tccaaggggc taataaatga gaatgctgga tctcctgatg tttgtccgta 60 ygaaagttat gaaccgcaac aggggcctta aagtcattta acatgctggg tagggtaaag 120 g 121 <210> 99 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 99 agtgtcctgc acatcaggca cgcctttaaa tgccccttta acaacatgat tccagcaaca 60 ragagaagca gaaaatcacg aaaaccatgt aaattactcc aattcttgat caacctccca 120 t 121 <210> 100 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 100 cctctctctt ggactatctc aagaaaattc aattctctca ccaagaatgt tttctctttt 60 mttccctctt ggatcacttc cctaattgat tttatatctt aacttagttg aagtatactg 120 g 121 <210> 101 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 101 ttaatcggcc acatacaaca cgtaccagat taggaggatt gaaaactgta atggctgaga 60 yaactttata tgaaaatgaa gccgctgtta gttatgatcc taatcctact gatgatgaag 120 a 121 <210> 102 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 102 tttaaatcgc gatttcagga cacatagtac tgttgtgtgg ccatcttttt tgactttgtt 60 satgcaatta tacagggtaa taattaaaaa tagggtaata attaaccaga gtctacaaaa 120 t 121 <210> 103 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 103 atcattaatt gtcatcctaa ccaaacactt tcttgatcag ttccttttct tggtttctga 60 yatccaaatc ttccatgaca caattaaaga aaatcaagaa tgaacagata atctcatgtt 120 t 121 <210> 104 <211> 121 <212> DNA <213> 人工序列 <220> <223> SNP for Bunch Number (BNP) <400> 104 atgggtcatt tcttctaaga tccttttttt tcaactactc cattttgttg tggtattttt 60 katgctaaaa agttgggttg aatcccattt tcattattga aattttcaaa atttttattt 120 t 121 <210> 105 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 105 taacagttaa tgagtcccct caatccacct gattggattc tgtttttcca agctaccggg 60 ycttaaattg ggatgccttc tattaaagtt gtgcaataat ctgagattta aattagtatc 120 t 121 <210> 106 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 106 aaatgtgtct gacttatcca aaacatctct taggctgcat aatgagctcc agatggccag 60 ytgaaaaact cattcaccgt tcccgacatc aagtattgga tgatgtcagt aaccacatga 120 g 121 <210> 107 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 107 tttcatcgat atatattata tggttggatg attcatgctt gttgattttc tgatatatac 60 ygcaagtttc tttggtatat actcagtagc aattcaatac acacctcgga taaatcgata 120 a 121 <210> 108 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 108 gaggcctaaa cgatttcctg tttccattga tgatgactta catcatgatg aaaggagatg 60 wataatggtt taaaaatata tattgagtgc tgtcaataat cagggtcacc ttctagaggg 120 t 121 <210> 109 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 109 ccactcctta gttaagcttg acccgccgtt cacaggcagg tgtgaagccg tcattgagtc 60 yctcagacaa cacattcggg ccaacctcat ctttaccctg gagcaactct ttgctagtaa 120 a 121 <210> 110 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 110 ctgatctgat cagtcttctc gggagtgcta gtttgcatga agaccttctt cttaactgat 60 ytggatcttt ttctcaaatt tttaaaattt ttttagagat tgaagataga cttctagagg 120 a 121 <210> 111 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 111 gaagaaaaga aagaaccaga tgaaaaatct gaagggtact aagcatctga agaggtcaat 60 raatagtgct gctcgcttgc gatgaacatt cccacctctg actcatttta aatacttatc 120 t 121 <210> 112 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 112 caattcatgc gccagcttgt aatcccccaa agtcgaagcc tcaagcttcg ggccagttga 60 ygcaatccca aaagcaccag ctgtctcgac tgatgcctct tctagggaaa ggtcgacaac 120 t 121 <210> 113 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 113 ctatgatgag cttcattgat ttatctttat ttctttgggg acatgtctca cttatcgtaa 60 kgcatatttt aaataggatt ccttctaaat ccattcctac tataccatat gagatatggc 120 a 121 <210> 114 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 114 ctttgtcact gaggccagga tctcttgcct catacttcag cagttctaaa acatccacag 60 yggagacacc acctagtgtt agtgctgcaa tagctggtgc acgggctgca gctgcacagt 120 t 121 <210> 115 <211> 121 <212> DNA <213> 人工序列 <220> <223> 串之數目之SNP <400> 115 cgttctattt taaataaata aataaataaa tatttaggga ggcaagacta cgctgagtcg 60 yggtgtcggt ttggtagatt acgtgcggta taccgcaggc aaaactggaa ccaggcgagc 120 t 121<110> Genting Plantations Berhad <120> Gene markers for selection of phenotypic traits <130> 28896SG2 <160> 115 <170> PatentIn version 3. 5 <210> 1 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 1 Ctagcctaga Gcttgaatat Tttctttgaa Ttggctctag Ggtgcataga Aacctgaccc 60 Rgagcctaat Tctagcatta Tttgtgccta Ctgtttactt Taaaaaataa Aataatagta 120 a 121 <210> 2 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 2 Atgtatagag Gatagttcct Cttccagtgg Ccctgtttct Tgcaaaaaaa Gcactctgcc 60 Wagctctggt Cgggcttgtg Cttctcggac Tcacgcttct Tggtctgacc Atgtgcagac 120 a 121 <210> 3 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 3 Tcatgtcagt Gtctacaata Ttgtttttgt Gtttcttgtt Tcctatatta Taattttcaa 60 Ygaaacttgt Ggtgtgacat Agttactcca Ccttggaatt Ttaaattgct Ttagctgaaa 120 a 121 <210> 4 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 4 Ttcgcaactc Attgtcagac Aatactgagg Agaatgtgca Gcctgagatc Ctgttctctc 60 Yagatactta Caaagcttaa Gtctctacaa Tcgtattttg Attattttaa Aatttctcac 120 a 121 <210> 5 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 5 Tatatataac Ttcttggcct Gagactcaat Taaaaaccaa Attgagacat Ggcttgaatg 60 Yattagttaa Attgacttgt Gaagtaatgc Cggatcaaca Tgcacatgga Caagaaaatt 120 a 121 <210> 6 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 6 Catatatacc Aactattatt Ccagcatgca Tcttctaagc Tggtcatgct Ggtccatctg 60 Waaaggatca Tggttcgcac Atggccttgt Tttctccaat Gaaaaacaaa Aaagaaaaaa 120 g 121 <210> 7 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 7 Gtccatttaa Agatgatggg Ggctgatgac Cacatcgagg Ctgatggaaa Agagggactt 60 Ragaattggg Taggggagga Gataaaaaga Gaaggaaaga Cttgttgcaa Cgaagtttga 120 g 121 <210> 8 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 8 Atccaggtta Tggactttga Tgatgatgaa Accattgggc Caatctctga Tgagattaaa 60 Rtacttgctc Aagggccaaa Ccatattgca Agaaggttta Aagctttgc Tatggataat 120 g 121 <210> 9 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 9 Gaaatttttt Gccttcaagg Ttttcttggt Ttttatcatg Tattttgcca Tttctattgg 60 Yaggctgatc Aatgcaaaca Tttaggtcac Gtaattgtct Ttgccgaacc Ccttccacaa 120 a 121 <210> 10 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 10 Ttgctttctc Taccccttta Tataagttcc Ttccagcaga Tctctatctc Tctctcccat 60 Yttgttagac Cctactctgt Ggcccgtctt Tctatacctc Tctctcccct Ccccaccaca 120 c 121 <210> 11 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 11 Gcatgattca Gattaaaagt Attttaatct Tatattctgc Tttgatattt Aaaaaataaa 60 Rttttgaaat Acacatgcat Gccccaaacc Tctaattcca Acagtggtat Cagagccacg 120 a 121 <210> 12 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 12 Ctttatgagg Aatcatttcg Agccgagctt Cgattacctg Tacacccttt Tgtcatagag 60 Ktctttcatt Ttttcaatat Tttttcttat Tctttagttt Ccaactcttt Tcatttcatt 120 a 121 <210> 13 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 13 Tcattgtgct Tgccagattt Tagcctaaac Atctctgaaa Atagaggtaa Gatcctctag 60 Wcatcaagat Aatttagttt Gctatcttcc Tcagccttta Aaacctcaat Ttcagtcgac 120 a 121 <210> 14 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 14 Gaatatgggt Ataaatgtcc Cttcgatctg Agatcaccat Agtgacttgc Aagcaactca 60 Ytatgcttta Ggttggact Atttaaattt Ttaattcagt Gatgaaaaat Ttttaggcac 120 a 121 <210> 15 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 15 Gtacttggat Taagttgatc Accaggccgt Ccggtcatag Gagcaaaaag Atttaaaagc 60 Ygtctcttcc Tattcgatag Ggtgctctta Tggtgtgtag Gggtgccatg Tgatttgatc 120 c 121 <210> 16 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 16 Agctcgattg Gacctataatc Aattagattg Aaatctaatc Aaatttgatc Aacttatatt 60 Yggacctact Gccagttaga Tatggaaccc Aatgagacac Acacatatag Aaattggcca 120 a 121 <210> 17 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 17 Gctcgattgg Acctaaatcg Attagattga Aatctaatca Aatttgatca Acttatatct 60 Rgacctattg Ccaactagat Gtggaaccca Atgggtcaca Cacatataga Aattggccaa 120 g 121 <210> 18 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 18 Taaggggcta Tttgattttg Aataagattc Aaaccttttg Cctatttaaa Gggatcttct 60 Ytaaggctct Aagcatcaca Ttttcaacag Ccccaccccct Ccctctcttc Tctcctttgg 120 t 121 <210> 19 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 19 Tagcttatat Aggaagagac Tatttttttc Atgtgaggtg Tctttgaaga Gcaaaactgt 60 Raggctctaa Atgacaaagg Cccactgaag Tccaaagatg Gtcatgtgct Ttttaaagag 120 c 121 <210> 20 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 20 Tgatccatca Agttgtgttt Atggaagggt Aacgtaactt Tggcgatggc Tttaaaacca 60 Wtgaatatat Atattttttt Catttctctt Cctctctttc Tccctctctg Tttcttcctt 120 c 121 <210> twenty one <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> twenty one Ctaaaactga Gccatcaacc Tctttctgat Accagttgaa Agaaaaaaaa Tttatttttt 60 Ycttgtagga Tctttcagat Ttcatcaaat Ctgaggtgaa Ataattttaa Aaaaaattta 120 t 121 <210> twenty two <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> twenty two Tatatagttg Ttagcattgt Tgtaagtaat Ttagtattac Catagtagct Aatcacattc 60 Yatctttgtc Aggagcttta Aagtttgggc Gggaagtttg Tctcacttgg Tgtcccaatg 120 g 121 <210> twenty three <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> twenty three Cttgagctac Ccaagagttg Gtttcttacc Atgtcataac Tcatatagtg Tggtaaaaaa 60 Wgatttaaaa Aaaatctgat Tcaaaaaatg Aatcacaata Aataatatat Atccctagag 120 a 121 <210> twenty four <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> twenty four Gatgccgata Ttaatattct Cagtcattat Taaaattcac Tgaatagata Ttagtaatga 60 Yagtatcaat Gcactcgacc Atcaataaag Tcattattta Aaatgcacca Aaaatttggc 120 t 121 <210> 25 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 25 Ccaaacttcc Tattttaaaa Aacagcgtca Tgcctggatg Atggtatcat Gtcccttctt 60 Ygttttcgac Gaacataggt Ttccatgcag Ccggaaatta Ttcagaaatt Tgatcattat 120 t 121 <210> 26 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 26 Ggggagagag Aacagtctcc Cctttaaata Gggtcagagg Ggaggagttt Gactcctcct 60 Yagggtgttt Tttgactccg Attaggagtc Ggtcgggaag Aagaagaaga Ctctcaggag 120 t 121 <210> 27 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 27 Aaattaaggc Catacaggag Atgactccct Caagaacgat Caaagaagtg Caacatcata 60 Ygggaagact Tgttgctttg Aaccgatttg Tcttgagatc Gacagaatgg Tgcttaccct 120 t 121 <210> 28 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 28 Ctcaaccatt Tcatgatgtt Cagtcaattt Taaagacaac Ccatgcagtg Atagtaaaga 60 Kgtaaatgtg Tgtataagaa Tataaaagga Ctactcatgt Tgatatgcac Aagttagacg 120 a 121 <210> 29 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 29 Gaatgtatgg Atatcgagca Gatggtctgc Cgatggctgg Aggtgtggca Ggcccgtgca 60 Ytgtctatga Tggatcggat Caccttgatg Aggtctgttc Tcagctttat Ttcagtgtac 120 c 121 <210> 30 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 30 Tcttcaattt Atgaccactc Tccttttcta Ccatagtatt Aaatgcttta Aaaatagaaa 60 Stgtagcagg Cttttcttga Aggaaataaa Ctcatagttt Tatagtgtaa Tttacaatga 120 a 121 <210> 31 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 31 Caatgaatgg Acaggtgctg Ttacatatct Aaacactgaa Aatttgatcc Attatacttc 60 Yttatcagct Gaagttttaa Aattatatgc Aatactctct Agattgtaga Gtgaaagaaa 120 t 121 <210> 32 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 32 Cattcttatt Ttaaaaaaga Aaaaaccttt Atgagactct Ttgatacaac Actgacctat 60 Kgtaagctat Gaaggcattg Cagtggttta Ggtgcagtct Agatagcttt Atttcttgtt 120 t 121 <210> 33 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 33 Atagtagtga Gtaaaattaa Ttttgatgta Ctacgatatg Tatcaaattt Tggtaccatt 60 Rtcggagatc Ttagcacgat Tgttttaaaa Aaaatcaaaa Aaaaatttat Aaaataataa 120 a 121 <210> 34 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 34 Cctgtgcag Aaggctatca Gtttcaactc Ctagtcgaca Tacaacactc Tctgattttt 60 Yctcagaagc Atatcgaaaa Gctcaagttc Aaagtgcagg Caccaactgg Ccacagctct 120 c 121 <210> 35 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 35 Actgcatggt Taacaaggaa Cttttctatt Gctcaacttt Gaactaatct Tatgtaggtt 60 Rttagcctac Cgagagagac Actatcatgg Tctttttgca Tgaacctttt Aaagacatgt 120 t 121 <210> 36 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 36 Tattgttttt Aaaatacagt Tactaatttg Tcactagtct Ctctccaata Ttttgtttga 60 Raatacatat Ccattgataa Tcgatcgcta Ttcagtcgct Aaaaaaaaac Tattcgggac 120 a 121 <210> 37 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 37 Aaaacagacg Gatgaaacaa Tttattagaa Ggctataatt Cgaggaattc Atggtgttat 60 Mtaaaggcct Ttgtttgcag Ttttcacatt Ctattttctt Gccatttttc Ttcttgttat 120 a 121 <210> 38 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 38 Tttaaacatc Actataagca Taaacatcat Atcttatcct Aaccagtcac Cgagctactc 60 Rtgtgaatat Ttggattgga Ccaattgagc Ttcttctcat Attttgaata Cttcatagaa 120 a 121 <210> 39 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 39 Catgtcatat Aacaaatacc Cacgactaac Aacttagtga Gtgggtggat Ttcctatcct 60 Wgctacctat Agattcagac Ataacaaact Ctggtacttc Tctatataaa Ggtaacaaga 120 g 121 <210> 40 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 40 Tttttttttt Tgggtaaacg Tgtactagtc Ttgtttgatt Tgtcttgcag Aagaggcatc 60 Wattgtgga Tcttttaaat Aaaagtttga Tgaaagagta Gaccattata Atgggtcaaa 120 t 121 <210> 41 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 41 Ctcagctttt Aaaaattcaa Ccttctatct Tttgctgccc Tttgagacat Agtcggctaa 60 Ytttctgact Ttagcgacta Agtttgcgtg Ccaagcgtac Gaagggttct Ttgaaatgtt 120 t 121 <210> 42 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 42 Atccgtttaa Cattggccaa Aaacatcaca Ttcaacatcc Tggaggaaaa Gacgatagct 60 Ratttgatga Aggctctatc Taacatgtat Aaaaaacctt Cgacttccaa Caagatatac 120 c 121 <210> 43 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 43 Gatgtatgct Gtggtgtgtt Gtagattaca Tcttgcccat Gcagtgagtc Agatcagcag 60 Rtttatggta Tggcctagca Agaagcattg Acgagcactg Aaggagatct Tcagatatat 120 g 121 <210> 44 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 44 Tttagcttga Aaggatatag Aagatgttga Agaagattat Ttttgaagac Ttgctgaaat 60 Ytgtgcataa Ctttcctctc Tctttatttt Ttggatattc Aatgtttttc Acaaaaataa 120 a 121 <210> 45 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 45 Aacgagaagt Tcgggcccca Agctcgaaca Ccgagagaaa Gcacaaattt Gaagggtctc 60 Raaaggacct Tcggtcatga Acaaaaagga Tgaatcaatg Tggcgatgac Cagaaacctt 120 c 121 <210> 46 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 46 Ttggagcctt Tgcatctact Ttttcatgtg Tcacatagag Ctagagggat Gccccatgct 60 Rgtcccacat Gtcctcttta Aaatgggcat Gtccaacttg Atcaaatcaa Gtgacgcccc 120 t 121 <210> 47 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 47 Tttaaaaaaa Gctgtgcatt Acagatgact Gcatctaaaa Ccatcatttt Ggtaacaaaa 60 Magtcacatt Atttccgaac Catgaacagc Aaatggtgca Ggataacttt Cgttagattg 120 c 121 <210> 48 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 48 Aatatttatt Atttaaaatt Aattttgcag Catatttaca Gaaagctcta Tgcctcgtgt 60 Kattaccgag Atcatctaac Gattgatgtc Gggcccagtg Aacgagttct Ctacttgacc 120 a 121 <210> 49 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 49 Ttatagataa Ttctcatgat Ctaataagta Taggagttct Aacccaaatc Taatttaaat 60 Yagtccaata Cttataaaaa Aaaatttcta Catgagatag Aattgccatc Acatatgaca 120 a 121 <210> 50 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 50 Atattttcat Caaattttaa Atctttcgga Tagtcatgac Ttattgctaa Acatcaatct 60 Kgacttatgg Attcatcaaa Attaaaaaa Tttaattcaa Gaattaatta Ggaagaatct 120 t 121 <210> 51 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 51 Agtaaaatgt Aaaaatgcag Tttggaaagt Tacataattt Tttaaacaca Aaagaaaact 60 Ygatatggtc Tttcttggtt Tgtgacataa Acacgaaata Tgtacccaaa Gttttattag 120 t 121 <210> 52 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 52 Ttttctgact Ttcccaatgc Tgctagtttt Gcctggtgct Gctcagcttc Tcttgctgcc 60 Rtcgctgaat Ttttttcaag Ttcttcttgg Tttcacactt Ccgcttggcc Tcccccggtg 120 c 121 <210> 53 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 53 Aagggtctag Ccactgtagc Ggaccctcat Caccctactc Cacaaacagt Ccgattggat 60 Ygagaatcta Actgcatgcc Taatgatcaa Aacctccctc Ctcatcaaca Aggagtggat 120 c 121 <210> 54 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 54 Atatgtctaa Cgatcctcct Ggatcaaagg Atgataaata Ctcatacact Agtgttttc 60 Yagtgacccc Tcatgctcca Tccaataatt Ttaattatca Tgtaaattta Aatatttttt 120 t 121 <210> 55 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 55 Tcagaaaaat Agcaaaatta Aagcttaata Gtaaacattt Tatatggaaa Tcaaaccctc 60 Raccaaacct Gaaggcattt Aaatataggg Gacaccaatg Ggtaagaaat Ttaagcccat 120 g 121 <210> 56 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 56 Tctttctcct Caactgactg Tcctgcacta Tcaggaatat Ctttgtcctt Gtagaggctt 60 Ytttcattga Agatcatggc Cttgcttctg Atgaatttcc Tatcctgctc Attccagaac 120 t 121 <210> 57 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 57 Catggctggg Tttggaggtc Gaggacgcct Gcggccaaga Aagcgagaga Gaaacaagga 60 Rcttctccga Gatggggcgg Ggggatagcg Gatcgatcga Gatttttctg Gaatggaatt 120 g 121 <210> 58 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 58 Taatcttaat Tagtttacga Ttgtcatata Tcctaatttt Ttaaaactta Ttttaagaac 60 Raaagggatt Ctaatccctc Cactactct Atacccactc Tcctaacata Gattgaagtt 120 t 121 <210> 59 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 59 Aagggctcac Ttggttgagg Ctctacattg Gccgacctcg Atggcctttg Gcttcctcaa 60 Wgaaccttgg Gcagtcgacg Ctaccctctt Cttagggata Tgttgcgcca Agatccaata 120 c 121 <210> 60 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 60 Aaagctatga Tgattgttca Gcaattgtct Atatagtgaa Ataatatcag Tcaccgaata 60 Wgagagtgca Actattgtct Ggcgtgatat Attgaagctg Gcctaacaac Catgaatgtg 120 a 121 <210> 61 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 61 Ttttcattat Tcatcatcat Ggaaaagatc Gtgcagcacc Cctatacc Ataggagatc 60 Ycatcgaatt Ggtaaataag Attattagaat Cttgatttct Tctaggatcg Gatatctacg 120 a 121 <210> 62 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 62 Ccttatgttg Ggtaatgtac Ttggggtggc Arggtgtagg Cttgaatctg Acttaagcct 60 Rtgataggag Ggcctattag Gattagtttt Aaatggctag Atcccctctc Caatttctat 120 a 121 <210> 63 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 63 Accaaccaaa Atcttacaag Tccaattcta Ggtttggatg Ggcctaatcc Aaatttcttt 60 Yatccccaag Aaacttgaaa Agaaaacaag Aatataagat Gcagaatttc Agaataaatt 120 a 121 <210> 64 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 64 Ttgttccaat Catgtatgga Tttatctcaa Tgattttttt Gacagtttga Gaagctgcaa 60 Raaaaatagg Tatccaatgg Taagactaat Gttttaaacc Agatcattga Caaaactgga 120 a 121 <210> 65 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 65 Aagagtacc Cagcttactg Aaccatggcc Gatcagcaca Agatccaatt Ccgatacggc 60 Raaccttact Tctagtttca Tcaaagtaat Aagtaacaag Caaaggggta Gagcactgat 120 g 121 <210> 66 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 66 Tatccctttt Aaagtactat Gatatctctc Actaactaat Agacttaaa Ggctatttat 60 Rtcatcaaaa Actacatagc Atatgacttg Gtatgcttca Aataggtgtg Ttgatggttt 120 t 121 <210> 67 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 67 Ttaaacttat Caaagacttt Ggatttatgt Ttcattaaat Ccatatatcc Aaaccttgat 60 Raatcattta Taaaagtgat Gaaataggag Catcctcttc Tgatttgagt Tgtcattgac 120 c 121 <210> 68 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 68 Tgtcattaaa Gtaacactaa Ctatagggtt Accaaccact Atcttatcta Atttaaagtc 60 Yttttcatca Caattaccaa Tgtgccgtaa Cataaaacg Tgcaaaatga Tcttttaatg 120 c 121 <210> 69 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 69 Ataacgactg Gatcatcatt Tgagtcacaa Aagggtgctc Ttcgattcat Tgattaataa 60 Wttttgtaaa Gccaccatat Agtctttgta Tttttaaaag Tttcctcccc Tattttctca 120 a 121 <210> 70 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 70 Tcaaggtttc Aagctatcaa Gctagcttga Caagttggtg Gaagatgttg Atggatagag 60 Rgacttaatc Tcgggcaaaa Taacaactag Gatttgggcc Ggtccacttt Aaaaatactt 120 t 121 <210> 71 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 71 Agtatcatat Tagataagtg Tcattattgt Ccttctttga Tgatgaatgt Catttctaca 60 Rgttttttgg Ccaaatttaa Ttttaaattt Tattaaaaag Ataatttttg Tgatatcatt 120 a 121 <210> 72 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 72 Tcttcaaaat Atctctctca Atattcaaaa Aatttaaaga Taaaacgtca Tgattatgat 60 Wtttaaatcc Ctaaaattag Tttcaaggag Tgaacattga Acacctaccg Agcacatcgc 120 c 121 <210> 73 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 73 Atacatggcc Attagggaca Cactaaagta Gtaaacacta Aaataaaatt Ttaaaaaatg 60 Rtcaaaagtc Ctgaagggta Acaataaagg Tttatgaacc Tcaaaggtct Cacatagtgg 120 a 121 <210> 74 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 74 Tacatttcca Gtcagtgtag Gcttcataac Aatgattcag Attgtgtgag Gcacggcatc 60 Mtggttttcc Catgaaacaa Gacacgatgc Catctcggcc Catcctgaca Taatgccttt 120 g 121 <210> 75 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 75 Ccaaaagctc Ttgcttccta Tttattgcat Gcaactgatt Aacccatatg Agttctattt 60 Rgactcttct Tctctctttt Tttctttttt Atttaaaaaa Aatgtagtcc Cacatgagga 120 g 121 <210> 76 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 76 Accccctttt Aaggccagtt Gttgatagca Atttttggat Ggtttaaaaa Gaaaatgatt 60 Yttagtgaaa Gaaggctgta Taccctcttt Ccttttctta Tgctccctct Tcttttcctt 120 t 121 <210> 77 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 77 Gcaaaagagt Aggtgtacag Actgtgaatt Aaaccatatt Caagttattt Aaagatgtca 60 Ygtcttcttc Tatgaactaa Agcgaagatg Ttcccttgtt Gtacaagtat Tattttttca 120 t 121 <210> 78 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 78 Agtaaaaacc Tctgcctcca Gtttgctgac Gatactattg Ttttttgaga Agcgaaaaag 60 Raagttgctg Gccatctcaa Gttcatatta Tactcatatg Aattggtatc Tgatctcaaa 120 a 121 <210> 79 <211> 121 <212> DNA <213> Artificial sequence <220> <223> Fresh fruit bunch (FFB) SNP <400> 79 Tattttctac Tatctcataa Gctgatgcta Tggcacatcc Tattggttga Tcactcctat 60 Rgatagcatg Ctgaaaaata Tgcttgataa Attctcaaaa Gctgacaagt Tggtttaaaa 120 t 121 <210> 80 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 80 Gtccatgaag Cttagaagtc Agtatcccaa Agttgcatca Actagttggt Cgatctttga 60 Yaaagaaaaa Ctgtccttcg Gatgagcttc Atttaaattt Gtatagtcga Tgtaaattct 120 c 121 <210> 81 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 81 Ctaagtgtgg Gggcgtgcgg Gatgcccaaa Gaagagggag Aaggaagagg Aagagagggc 60 Rtgggaagag Cttttgggca Taaggggctg Ctaggtttta Tgccctaagg Atcttaaggg 120 a 121 <210> 82 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 82 Ctgctgaact Gtatggtttt Aattctccaa Atcattgaat Atgggggctc Acaacctaag 60 Kgtcatgtat Gttatatcct Ttcgaaaagt Cttttagagg Tttcatgtag Ggccaaattt 120 g 121 <210> 83 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 83 Tatcccaata Aatgcggtcc Aggtaagttt Ttatcagagg Caagagtcac Caaagaaaag 60 Rtagagagaa Caactagccc Aaggaaattt Tgcagcactt Tttcatttag Aagagaagga 120 t 121 <210> 84 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 84 Tatcaacatg Tcagagtcaa Cttgaaatct Cttgaagttg Actttaaggc Tttttcactt 60 Rattttttat Gaaaaatctt Tatctaatca Tcctttttta Ctttcaaaat Actttaaata 120 c 121 <210> 85 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 85 Ctgtggccag Tatggccagt Ccattaattt Gaaagctgtt Ggaatccata Cacctcataa 60 Kttaaatttt Tgagaaatag Aaatcacact Tttagatgaa Ttcatgtgct Tcaagaaagt 120 c 121 <210> 86 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 86 Acctcctctc Ctggacctcc Gaggaggtac Ttgatgttag Tcttgttcgc Cgtctcagct 60 Rtacattgc Tgggcctcgt Ctctccgttt Taccatggag Gagaattggc Gtccgaccgg 120 g 121 <210> 87 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 87 Tagatttgat Tattttattg Gccatccgaa Tccgaatcta Actcatttaa Aatagaattg 60 Ractatattt Ttcgatccaa Tggatggggt Cgagcctaaa Attcaaatcc Cattggtgaa 120 g 121 <210> 88 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 88 Agatgaaatt Tactagtagt Caaagtcggg Gacgaagtct Gactcccgta Ggagtccaga 60 Yggagtttcc Ccatggccag Agtcagagat Gatgtccggc Tcccgtagga Gtccggacgg 120 a 121 <210> 89 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 89 Tgggttattt Ggttggccat Gacttgtttt Taaacaggtt Aaacagttgg Gaaaggatca 60 Sctcacctgg Gcaataaaca Ggttagttag Ggtttgactg Tctaacctac Ttagggtccg 120 t 121 <210> 90 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 90 Atgaaaggaa Acattcctta Tgcagttcac Ataaagatga Gtaataagac Ctgaggcctg 60 Rgcaacagtg Atgctcacat Taagaaggtc Aaattgttgc Tcatagttac Caaggtacta 120 t 121 <210> 91 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 91 Catatctgta Cttttttgcc Tgaatagcga Agacatgaat Ttgatgttac Tattccatat 60 Wtgtttaaaa Tgaagatgaa Tatgagctgg Atataaatac Ttctttttta Attgaatgtg 120 a 121 <210> 92 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 92 Acggctccac Cctcttctcc Agattgcctg Ctcctgggct Ggggttggga Cttggataca 60 Raaacatgtc Ttatcaatgc Tatagcagtc Tgtgaactta Aaggttcatg Cgggacggta 120 c 121 <210> 93 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 93 Caactcgtgg Gctaggcatg Gcctgacatg Gtccaggcct Agtccaagcc Ctgcttgatc 60 Yttttttctg Aatttaaaaa Atatattttt Ttataaatta Taaaagtgtt Aaggagtaaa 120 a 121 <210> 94 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 94 Tacataatag Tgagtaggtt Taattttggt Atgctacgac Acatataaaa Ttttgacatc 60 Rttatcggag Atcttggtat Gattgtttta Aaaaaaatca Aaaaatatat Atttactact 120 t 121 <210> 95 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 95 Aaaagcggga Tgaattgaat Tctttaaaaa Tttttactaa Atccaaatct Gaacaattat 60 Rtgcttcaat Ttaagctaaa Ttgagtgttt Gtgaagtatt Tgatatgtgt Agcagcaaaa 120 t 121 <210> 96 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 96 Gtaaatgcaa Aatttaataa Ctaaaattta Aatccatggt Tcaaaaaaaa Gtcaaagata 60 Wtttttgatt Tttaagaccg Atgctagaaa Tcgatgcaac Aatttggcaa Aatatgaatt 120 a 121 <210> 97 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 97 Catctccatg Ctatctttct Aattcaaatt Gaacctatga Ttctctagca Aaacagtaat 60 Mgcatttgct Tacaccattg Atgaattatg Tttgttttta Aaactcaaag Agcattctcg 120 t 121 <210> 98 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 98 Gtggtgcagc Tccaaggggc Taataaatga Gaatgctgga Tctcctgatg Tttgtccgta 60 Ygaaagttat Gaaccgcaac Agggggtta Aagtcattta Acatgctggg Tagggtaaag 120 g 121 <210> 99 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 99 Agtgtcctgc Acatcaggca Cgcctttaaa Tgccccttta Acacacatgat Tccagcaaca 60 Ragagaagca Gaaaatcacg Aaaaccatgt Aaattactcc Aattcttgat Caacctccca 120 t 121 <210> 100 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 100 Cctctctctt Ggactatctc Aagaaaattc Aattctctca Ccaagaatgt Tttctctttt 60 Mttccctctt Ggatcacttc Cctaattgat Tttatatctt Aacttagttg Aagtatactg 120 g 121 <210> 101 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 101 Tatatcggcc Acatacaaca Cgtaccagat Taggaggatt Gaaaactgta Atggctgaga 60 Yaactttata Tgaaaatgaa Gccgctgtta Gttatgatcc Taatcctact Gatgatgaag 120 a 121 <210> 102 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 102 Tttaaatcgc Gatttcagga Cacatagtac Tgttgtgtgg Ccatcttttt Tgactttgtt 60 Satgcaatta Tacagggtaa Taattaaaaa Tagggtaata Attaaccaga Gtctacaaaa 120 t 121 <210> 103 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 103 Atcattaatt Gtcatcctaa Ccaaacactt Tcttgatcag Ttccttttct Tggtttctga 60 Yatccaaatc Ttccatgaca Caattaaaga Aaatcaagaa Tgaacagata Atctcatgtt 120 t 121 <210> 104 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP For Bunch Number (BNP) <400> 104 Atgggtcatt Tcttctaaga Tccttttttt Tcaactactc Cattttgttg Tggtattttt 60 Katgctaaaa Agttgggttg Aatcccattt Tcattattga Aattttcaaa Atttttattt 120 t 121 <210> 105 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 105 Taacagttaa Tgagtcccct Caatccacct Gattggattc Tgtttttcca Agctaccggg 60 Ycttaaattg Ggatgccttc Tattaaagtt Gtgcaataat Ctgagattta Aattagtatc 120 t 121 <210> 106 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 106 Aaatgtgtct Gacttatcca Aaacatctct Taggctgcat Aatgagctcc Agatggccag 60 Ytgaaaaact Catcaccgt Tcccgacatc Aagtattgga Tgatgtcagt Aaccacatga 120 g 121 <210> 107 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 107 Tttcatcgat Atatattata Tggttggatg Attcatgctt Gttgattttc Tgatatatac 60 Ygcaagtttc Tttggtatat Actcagtagc Aattcaatac Acacctcgga Taaatcgata 120 a 121 <210> 108 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 108 Gaggcctaaa Cgatttcctg Tttccattga Tgatgactta Catcatgatg Aaaggagatg 60 Wataatggtt Taaaaatata Tattgagtgc Tgtcaataat Cagggtcacc Ttctagaggg 120 t 121 <210> 109 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 109 Ccactcctta Gttaagcttg Acccgccgtt Cacaggcagg Tgtgaagccg Tcattgagtc 60 Yctcagacaa Cacattcggg Ccaacctcat Ctttaccctg Gagcaactct Ttgctagtaa 120 a 121 <210> 110 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 110 Ctgatctgat Cagtcttctc Gggagtgcta Gtttgcatga Agacttctt Cttaactgat 60 Ytggatcttt Ttctcaaatt Tttaaaattt Ttttagagat Tgaagataga Cttctagagg 120 a 121 <210> 111 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 111 Gaagaaaaga Aagaaccaga Tgaaaaatct Gaagggtact Aagcatctga Agaggtcaat 60 Raatagtgct Gctcgcttgc Gatgaacatt Cccacctctg Actcatttta Aatacttatc 120 t 121 <210> 112 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 112 Caattcatgc Gccagcttgt Aatcccccaa Agtcgaagcc Tcaagcttcg Ggccagttga 60 Ygcaatccca Aaagcaccag Ctgtctcgac Tgatgcctct Tctagggaaa Ggtcgacaac 120 t 121 <210> 113 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 113 Ctatgatgag Cttcattgat Tttactttat Ttctttgggg Acatgtctca Cttatcgtaa 60 Kgcatatttt Aaataggatt Ccttctaaat Ccattcctac Tataccatat Gagatatggc 120 a 121 <210> 114 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 114 Ctttgtcact Gaggccagga Tctcttgcct Catacttcag Cagttctaaa Acatccacag 60 Yggagacacc Acctagtgtt Agtgctgcaa Tagctggtgc Acgggctgca Gctgcacagt 120 t 121 <210> 115 <211> 121 <212> DNA <213> Artificial sequence <220> <223> SNP of the number of strings <400> 115 Cgttctattt Taaataaata Aataaataaa Tatttaggga Ggcaagacta Cgctgagtcg 60 Yggtgtcggt Ttggtagatt Acgtgcggta Taccgcaggc Aaaactggaa Ccaggcgagc 120 t 121
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