CN113284551A - Method for positioning leaf color character of rosa davurica pall - Google Patents
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Abstract
The invention belongs to the technical field of biological analysis and discloses a method for positioning the leaf color character of rosa davurica, which comprises the following steps: constructing a genetic population, namely obtaining an F1 progeny population by artificial cross pollination by using rosa labrata as a female parent and rosa davurica (R.davurica) as a male parent, and testing the leaf color separation condition of the F1 progeny through chi-square test, wherein the leaf color separation condition accords with 1: 1, separation, namely, supposing that the leaf color character of rosa davurica pall is controlled by dominant single gene; BSA-Seq analysis locates the position and region of the golden leaf character genome; and (3) developing SNP molecular markers by carrying out MassARRAY high-throughput sequencing technical means based on the BSA-Seq result, and further finely positioning candidate genes. The invention uses BSA-Seq to develop SNP markers in the positioning interval and construct a genetic linkage map of the positioning interval, so that the leaf color positioning interval can be narrowed, and candidate genes related to leaf color characters can be screened.
Description
Technical Field
The invention belongs to the field of molecular biology and plant molecular breeding, and particularly relates to precise positioning of leaf color traits of rosa davurica pall and development and application of a high-throughput SNP molecular marker.
Background
Rosa davurica (Rosa bengeriana) belongs to Rosa (Rosa) plants in Rosaceae (Rosaceae), is one of representative species of wild rose resources in northwest of China, has excellent characteristics of drought resistance, cold resistance, barren resistance and the like, and is a high-quality germplasm resource for modern rose breeding. The rosa flexuosa is a bud-change material generated on a seedling branch after rosa flexuosa seeds are radiated by gamma rays, and a mutant plant of the rosa flexuosa can stably keep the characteristics of golden leaves, has the characteristics of long ornamental period and bright color, increases the seasonal phase change of leaf color, can also play a role of replacing flowers with leaves in a light flower season, has special garden use and high ornamental value, and makes up the defect of monotonous garden landscape color.
A mixed sample grouping analysis (BSA-seq) based on a high-throughput sequencing technology is characterized in that two groups of individuals with extreme phenotypic differences in a separation population are utilized to respectively construct an equal-amount mixed pool, and a Single Nucleotide Polymorphism (SNP) marker and an Insertion/absence marker (InDel) which are related to a detected property are screened out between the two mixed pools, so that the method is an effective method for rapidly obtaining a molecular marker linked with a target gene. In recent years, BSA-seq has been widely used in marker screening and gene mapping of fertility genes, resistance genes and forms, physiological genes of various plants, but BSA-seq only carries out molecular marking on target genes and cannot determine the degree of linkage between the target genes and the molecular markers and the positions of the target genes and the molecular markers on a genetic linkage map. Therefore, a BSA-seq and MassARRAY combined analysis method is adopted, firstly, a molecular marker linked with a target gene is obtained through the BSA-seq, then, the developed molecular marker is subjected to cosegregation analysis between the marker and characters in an analysis population by using the MassARRAY, a genetic linkage map is constructed, whether linkage is carried out or not and the genetic distance between the marker and the character are determined, and gene positioning is carried out.
Disclosure of Invention
(1) Construction of genetic populations
The method is characterized in that rosa labrata (R.beggeria 'Aurea') is used as a female parent, rosa davurica (R.davurica) is used as a male parent, artificial hybridization and pollination are carried out to obtain an F1 progeny population, and the leaf color separation condition of the F1 progeny is tested by Chi 2, and the method meets the following conditions that 1: 1, the leaf color character of the rosa davurica is presumed to be controlled by dominant single gene.
In the invention, a separated population of 'rosa labrata' X 'rosa davurica pall' F1 is used as a material, wherein 27 strains of rosa labrata and 34 strains of green labrata are consigned to Biomarker Technologies CO, LTD to extract genomic DNA of fresh leaves and equally mix, two extreme mixing pools of rosa labrata and green leaves are constructed, DNA quality of the two mixing pools is detected, the sample DNA is used for constructing a sequencing library after being qualified, and genome re-sequencing is carried out through Illumina HiSeq X after the library quality is detected.
(2) BSA-Seq analysis for locating genomic positions and regions of golden leaf traits
Taking the genome of 'moon powder' (R. chinensis 'Old Blush') of China Old China rose, namely, RchiOBHm-V2, as a reference genome, comparing obtained reads to the reference genome by using BWA software, detecting SNP and InDel between a sample and the reference genome by using GATK software, and extracting variation sites which are different between two sample mixing pools to obtain an SNP and InDel variation site set between the two extreme mixing pools; and then calculating the SNP-index of each mixing pool by using the SNP data of the two parents, comparing the SNP-index of each mixing pool, calculating the delta SNP-index, fitting the delta SNP-index by adopting an Euclidean distance algorithm, and finally drawing a distribution graph of the ED value of the SNP on the color body, wherein the distribution graph is shown in figure 2.
The method is characterized in that an ED fitting algorithm is used for calculating that a positioning region related to the gold leaf character is 4,040,000bp-8,850,000bp of chromosome CM009586.1 of an ancient China rose (R.Chinese 'Old Blush') genome in a reference genome, the total length is 4.81Mb, 492 genes are annotated in the positioning region, 540 SNPs are annotated as non-synonymous mutations, 100 InDel are annotated as frameshift mutations, and the sites are possibly directly related to the character.
(3) And developing the SNP molecular marker by adopting a MassARRAY high-throughput technical means based on the BSA-Seq result.
By combining all the technical schemes, the invention has the advantages and positive effects that: the method for positioning the leaf color character of rosa davurica pall provided by the invention utilizes rosa davurica (R.beggarana 'Aurea') as a female parent and rosa davurica (R.davurica) as a male parent, and obtains an F1 progeny population through artificial cross pollination as a mapping population of a genetic linkage map. Leaf color separation of F1 progeny is determined by chi square2) And (4) checking, and according to the following conditions: 1, the leaf color character of rosa davurica is presumed to be controlled by dominant single gene. The plum super-grade uses the golden leaf rosa davurica x rosa davurica F1 generation population as a mapping population, the leaf color trait is positioned on the 4 th linkage group of the golden leaf rosa davurica by using AFLP molecular markers, the marker point is 17.4cM away from the upstream M3E4-1760 marker point, and the marker point is 18.0cM away from the downstream M3E1-1990 marker point. On the basis of the initial positioning, the SNP markers in the positioning interval are developed by using BSA-Seq, and the genetic linkage map of the positioning interval is constructed, so that the leaf color positioning interval can be narrowed, and candidate genes related to the leaf color character can be screened.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for locating the leaf color trait of rosa davurica pall according to an embodiment of the present invention.
FIG. 2 is a BSA-Seq and MassARRAY based joint analysis provided by an embodiment of the present invention.
FIG. 3 is a diagram showing the result of typing of the partial SNP molecular markers rna28536a, rna28674a and rna28757b in the present invention.
FIG. 4 is a genetic linkage map of a golden leaf trait candidate region of Rosa davurica of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a method for positioning the leaf color character of rosa davurica pall.
As shown in fig. 1, the method for locating the leaf color trait of rosa davurica includes the following steps:
s101: constructing a genetic population, namely obtaining a F1 progeny population by artificial cross pollination by using rosa labrata (R.beggerana 'Aurea') as a female parent and rosa davurica (R.davurica) as a male parent, and obtaining a Ka square (chi) for the leaf color separation condition of the F1 progeny2) And (4) checking, and according to the following conditions: 1, the leaf color character of the rosa davurica is presumed to be controlled by dominant single gene.
S102: BSA-Seq analysis localizes the genomic position and region of the gold leaf trait.
S103: and (3) developing the SNP molecular marker by carrying out MassARRAY high-throughput sequencing technical means based on the BSA-Seq result.
S104: constructing a genetic map of a leaf color candidate region of rosa davurica, and finely positioning the leaf color trait gene of rosa davurica.
The method for positioning the leaf color character of rosa davurica pall provided by the embodiment of the invention specifically comprises the following steps:
(1) constructing a genetic population, namely obtaining a F1 progeny population by artificial cross pollination by using rosa labrata (R.beggerana 'Aurea') as a female parent and rosa davurica (R.davurica) as a male parent, and obtaining a Ka square (chi) for the leaf color separation condition of the F1 progeny2) And (4) checking, and according to the following conditions: 1, the leaf color character of the rosa davurica is presumed to be controlled by dominant single gene.
In the invention, a separated population of 'rosa labrata' X 'rosa davurica pall' F1 is used as a material, wherein 27 strains of rosa labrata and 34 strains of green labrata are consigned to Biomarker Technologies CO, LTD to extract genomic DNA of fresh leaves and equally mix, two extreme mixing pools of rosa labrata and green leaves are constructed, DNA quality of the two mixing pools is detected, the sample DNA is used for constructing a sequencing library after being qualified, and genome re-sequencing is carried out through Illumina HiSeq X after the library quality is detected.
(2) BSA-Seq analyzes and positions the position and the region of a gold leaf character genome, uses the genome of China Old China rose 'moon powder' (R. chinensis 'Old Blush') RchiOBHm-V2 as a reference genome, uses BWA software to compare obtained reads to the reference genome, uses GATK software to detect SNP and InDel between a sample and the reference genome, extracts the differential variation sites between two sample mixing pools, and obtains an SNP and InDel variation site set between the two extreme mixing pools; and then calculating the SNP-index of each mixing pool by using the SNP data of the two parents, comparing the SNP-index of each mixing pool, calculating the delta SNP-index, fitting the delta SNP-index by adopting an Euclidean distance algorithm, and finally drawing a distribution graph of the ED value of the SNP on the color body, wherein the distribution graph is shown in figure 2.
The method is characterized in that an ED fitting algorithm is used for calculating that a positioning region related to the gold leaf character is 4,040,000bp-8,850,000bp of chromosome CM009586.1 of an ancient China rose (R.Chinese 'Old Blush') genome in a reference genome, the total length is 4.81Mb, 492 genes are annotated in the positioning region, 540 SNPs are annotated as non-synonymous mutations, 100 InDel are annotated as frameshift mutations, and the sites are possibly directly related to the character.
(3) And developing the SNP molecular marker by adopting a MassARRAY high-throughput technical means based on the BSA-Seq result.
(4) Carrying out genotyping detection on the developed molecular marker in parent and offspring based on MassARRAY high-throughput technical means, and constructing a rosa labrata leaf color candidate region genetic linkage map by using a genotyping detection result. The leaf color mutant gene of rosa davurica is finely positioned.
A person skilled in the art can also perform other steps by using the method for locating the leaf color trait of rosa davurica provided by the present invention, and the method for locating the leaf color trait of rosa davurica provided by the present invention shown in fig. 1 is only one specific example.
The technical effects of the present invention will be described in detail with reference to experiments.
1. Experimental materials: the parent Rosa davurica and Rosa davurica are respectively used as a strain, and 44 strains of an F1 generation golden leaf individual and a green leaf individual are respectively used as materials. The experimental material is planted in a Chinese rose germplasm resource garden of vegetable and flower institute of Chinese agricultural academy of sciences.
2. Extraction of genomic DNA: 100mg of fresh rosa davurica and mature rosa davurica leaves are quickly ground into powder in liquid nitrogen, and the operation is carried out according to the instruction of a DNAquick Plant System rapid Plant genome DNA extraction kit (DP 321). The absorbance and concentration of total RNA at 260nm and 280nm were determined by Nanodrop 2000, and the quality and integrity of the DNA was checked by 1% agarose gel electrophoresis, ensuring a DNA concentration of >50 ng/. mu.L. And (5) using the DNA sample qualified for quality inspection for a mass spectrum detection experiment.
3. Designing a primer: based on the SNP site sequence information, PCR reaction and single base extension primer were designed and synthesized using primer design software Assay design3.1 of sequenom.
4. And (3) PCR reaction: the method adopts a multiplex PCR amplification technology, and is carried out in a 384-well plate, wherein the reaction system of each well is 5 mu L, and the reaction system and the reaction conditions are as follows:
A) PCR reaction system
| Name of reagent | Each reaction system (. mu.L) |
| H2O | 1.75 |
| PCR Buffer with 15 mM MgCl2 | 0.625 |
| MgCl2(25mM) | 0.325 |
| dNTP Mix(25mM) | 0.1 |
| Primer Mix(0.5uM) | 1 |
| HotStar Taq(5U/μL) | 0.2 |
| DNA template(10ng/uL) | 1 |
| Total | 5 |
B) Circulation parameter
SAP digestion:
A) reaction system
| Reagent | Volume(uL) |
| H2O | 1.53 |
| SAP Buffer(10×) | 0.17 |
| SAP(1.7U/uL) | 0.3 |
| Total | 2 |
The total reaction volume was 7. mu.L for each alkaline phosphatase treated well, 5. mu.L of PCR product and 2. mu.L of SAP mixture.
B) Circulation parameter
| Temperature(℃) | Time(minute) | Cycle |
| 37 | 40 | 1 |
| 85 | 5 | 1 |
| 4 | forever | 1 |
And (3) extension reaction:
A) reaction System (384-well PCR plate + 38% reagent loss)
| Reagent | Volume(uL) |
| H2O | 0.75 |
| iPLEX buffer plus(10×) | 0.2 |
| iPLEX terminator | 0.2 |
| Primer Mix(0.6-1.3uM) | 0.80 |
| iPlex enzyme | 0.05 |
| total | 2 |
For each reaction well, the single-base extension reaction system contained 7. mu.L of the PCR product after SAP treatment and 2. mu.L of the extension reaction solution, and the total volume of the reaction system was 9. mu.L.
B) Circulation parameter
A) The reaction product (total 9uL) was diluted 3-fold and desalted using a resin
B) Dropping the desalted sample on a sample target for natural crystallization
C) Performing mass spectrum detection on the computer, and collecting data
Through the PCR reaction system, in 540 possibly-linked SNPs which are excavated by visual analysis and analysis of mixed pool sequencing data of gold leaf individuals and green leaf individuals in the gold leaf gene positioning interval of the rosa labrocarpa and are possibly linked with gold leaf phenotypes, 248 SNPs are selected for MassARRAY mass spectrum genotyping detection on the basis of selecting one SNP every 15kb, and finally 248 SNP markers are developed in total.
The invention provides a Rosa davurica gold leaf character SNP molecular marker developed by partial MassARRAY high-throughput sequencing technical means, and also provides a specific PCR primer and a single base extension primer for detecting the molecular marker by mass spectrum.
SEQ ID NO: 1, molecular marker rna28531 a: GAGTAACTAAAAGGCAACAACCAAAGTCAGCTATGTGGAAAGTATGACCATATCACAAGCTTAAGGAAAAAGCAATGCCAAAAATATGGATGGAAGCACCAAATTGGAATAAAACCAACAAAAAAAAAAAAAAGTTGACAGGAAACGATATAAACTTACAATCAACATATATGTTCTTTATTTCCTCTGTGTCATAATCAGGAGACATACAGCGCAAACCCGGACTCCTTATACCAGTCTCTACTTCTCCATGATTCCTTGCAACTTTACATGAGATTTCTCATCTAGACAGTCATTTTGCTCAGGTGTTGAACCAGCTCCATATGGCTTAATAAGCTGACACAGAAAGAGATAAAATAGGACCAATAACTCTCAGTCAAAGGTGTCAGGGATAATACTGCCTAAAATTATGAAGAGGTACAAGAGAAGTAACATGATGTTTAAGGTAAGGTGAATACCGACACATCTGCAAGACTGCAACCCAGAATCCAATAGAATTT [ C/T ] GATAGTAAGAGCATCCCAATAGCTTCCCGTCATGAATGCATAAGTCAGCAAGTCTTGACCATCCCATATCAACAGAATCATGGGATATTACAGGCTCCCATGAATAAACCAGCAAATAGGGATCTTAAGTTTACATGTTAACTCAATTCAATCCCCTAGAGTACTAAGACAAACAAATGAAAACCTTCAAACTGTCATCCAATCCAGAAAATATTGTCCTCCCATCAGGGTGGAAAGTAATTGCGCGTACTCCCCTTGTAGGCTGGAAACAAGAAAAAAAAATTGTCAGACTAACTGGATGAAAGTCACATTACAAGAAAAACATAGCTACAGGAATATATGATGCTCTATCAATCTGAGTGAGAGAGAGAGAGAGAGAAAGAGAGATATATATATATATATATATATATATTCAATTAATAACATAAATTACCTCAGGCCTGCTAGATCCAATCAGTTCAAAAGTTTCCAAATCCCAGAATTTCACAGTTCTGTCTGCT
SEQ ID NO: 2, PCR primer 1: ACGTTGGATGTGGTTTTCATTGTAGGAAC
SEQ ID NO: 3, PCR primer 2: ACGTTGGATGTAACATCCAGAATGAGGCCC
SEQ ID NO: 4, extending primer direction: f (Forward)
Single base extension primer: GCCAGCTGGTTCTTCT
SEQ ID NO: 5, molecular marker rna28823 a: AGTTTCCTAAAGCCACACTAACCCAGAGCTTTGATCACTCTCTATATATACCTAACCACCTTCAAAACCTCcctaaaaacccagaaaccataAATCAGCAACACTCATTTCTTTGGTTAACACTTTTATACATGGAACCTTCTACACTCATCGGTGCAACGCCTCGGCCCACCTCGGCTCTACTTCCGGTGGTCCCCGCCGCCGCCTGCAGCGGCACGCTGGGCCGCCACCTGGCTCGGCGGCTGGTCGAGATTGGCGTTCATGACGTGTTCTCAGTCCCCGGCGACTTCAACTTGACCCTCTTGGACCACCTGATCGCCGAGCCGGAGCTCAACCTCATCGGCTGCTGCAACGAGCTCAACGCCGGCTACGCCGCCGACGGCTACGCGCGCGCCAGGGGCGTCGGCGCGTGTGTCGTAACTTTCACGGTGGGTGGGCTCAGCGTCTTGAACGCCATCGCCGGTGCTTACAGTGAGAACTTGCCGGTGATTTGTATCGTC G/A GTGGGCCCAACTCCAATGATTACGGGACCAATCGGATCCTCCACCACACGATCGGGTTACCCGATTTCACTCAGGAGCTCCGGTGCTTCCAAACTGTTACTTGTCACCAGGTAAAAGCTTCACAGCTAAGACAGTAGAGTGTTCTAGTCTCAAGGTCTTAAACCTCTATAATATTCTCGAATTTTTTTTTTTTTTTTTTTTAGTATCATTGTTAAATATAACATGTTTTGAATATTTTATTTTAGTATATTTCCTCGATATTTTGGTCACCTGTTACTATGTTATGCTCAAAGATGTTGGATTTAATGTTGCTGAAGACATTTTCGTGCATTGTGTGACAGGCAGTGGTGAGTCATTTGGAAGATGCGCATGAGCTTATAGACACGGCAATTTCGACAGCATTGAAGGAGAGCAAGCCGGTTTACATTAGCATAAGTTGTAATTTGCCTGCAATTCCTCACCCCACATTTGGTAGAGACCCTGTTCCCTTCTTTATTGCA
SEQ ID NO: 6, PCR primer 1: ACGTTGGATGTGATTTGTATCGTCGGTGGG
SEQ ID NO: 7, PCR primer 2: ACGTTGGATGCCTGAGTGAAATCGGGTAAC
SEQ ID NO: 8, extending primer direction: f (Forward)
Single base extension primer: ACAATACCTTATCATACAAATTCT
SEQ ID NO: 9, molecular marker rna29070 a: GACAACCTTGCACCAATAGCACCACTACAAGTACAAAAGATTAATTAAATATCTTAAAGAATTTAAAGCTTATAAAAGTTTCTGTCTATTTTTATCACACCTTGAATTTGCAGGATCATCAAACCAACTAATTTGCTGGTGTACAACTTTTTGGAATGTCAAGGCACGAATTCGCTCTATCAGCTTCCCACCTGCAATTCCAAAGAAGAAATTTTGCCCTGGAATAACAAACAACCCAAAGAAACCTATACCAACATACACTCCTGCCCAAACTTTGGAGTCTTTTCGCAGCTCATTATGCGGTTCATAGAACATCTTGATGGCTTTTGAGAGTAGTAAGCCGAAGACAGGAAAAATCACTCCATGACCTGCTGCAGCAATAGATCCAAGCAGCAAAACTGGAAGCTCAGGTTTATTCAAATAGGCCAGCCTTTTGATGGAAACTTTTTTGCGTTGCTCCGGATCAACCTTCGTTTTCACACGGTTCTCCTCATCTTCTT [ C/T ] TTCTACTTGTACTTCACAATTAACTGGAGCAGGAACACCAAAGCTAGTAATAGTGAATGAGCGCCGACTACCTGATGAACCTTTGCTTAAAGATCTCACTGCTGAAAGTCTCTGGCTCCCAGATCTACTCATTGTCCTATCTATATTCAAACCATTATCTGGATCAGAGGGCTCTGCACCTTTTTCTTTAGCTCTTTCTTGCAGGCGGATTAGTTGGCTATAAGCTCCTTCTGGGTTTTGGGTCAAGTCATCATGAGTTCCTACAATACAAAACGATGATGTTACTTGAGGAACAAGTTTATTGTACGAATGAGAATGATGGTGTACCTTATGGAAATGCTCTTACCTATTTCAACAATTTTCCCTTTATGCACCACAGCTATTGCATCAGCATTCCTAATCGTTGTTAAGCGATGTGCAACAACTATAGTCGTTCTATTTGACATCAATCTCACCAGTGCATCTTGAACAATTCTCTCCGACTCAGCATCCAAGGCGCT
SEQ ID NO: 10, PCR primer 1: ACGTTGGATGTAGCTTTGGTGTTCCTGCTC
SEQ ID NO: 11, PCR primer 2: ACGTTGGATGCCTTCGTTTTCACACGGTTC
SEQ ID NO: 12, direction of extension primer: f (Forward)
Single base extension primer: ACGGTTCTCCTCATCTTCTT
The genotype frequency was calculated by using the mass spectrometry result, and the molecular marker was rna28531a, the SNP polymorphism of which was CC/CT, wherein in the parent Rosa davurica was CC genotype, the parent Rosa davurica was CT genotype, and in the F1 progeny, 44 golden leaf individuals and 44 green leaf individuals were typed, the CT genotype of the green leaf individual accounted for 81.8% (36/44), and the CT genotype of the golden leaf individual accounted for 63.6% (28/44) of (a) of FIG. 3. The molecular marker rna28823a has SNP polymorphism of AA/GA, wherein the parent Rosa flexuosa is AA genotype, the parent Rosa flexuosa is GA genotype, and in F1 progeny, 44 golden leaf individuals and 44 green leaf individuals are typed, the green leaf individual AA genotype accounts for 84.9% (37/44), and the golden leaf individual CT genotype accounts for 86.4% (38/44) in (b) of FIG. 3. The molecular marker rna29070a has the SNP polymorphism of CC/CT, wherein the parent rosa spinalis is CC genotype, the parent rosa spinalis is CT genotype, and in F1 offspring, 44 golden-leaf individuals and 44 green-leaf individuals are typed, wherein the AA genotype of the green-leaf individuals accounts for 86.4 percent (38/44), and the CT genotype of the golden-leaf individuals accounts for 70.5 percent (31/44) in (c) of figure 3.
The 114 SNP typing situations detected by MassArray are converted into 5 genotype segregation modes of < nnxnp >, < lmxll >, < efxeg >, < hkxhk > and < abxcd > according to the CP mapping mode of JoinMap 4.0 software, the leaf color phenotype character "YL" is converted into < nnxnp > type markers, and a mapping group with the LOD of 3.0 is selected for map construction by adopting the calculation of a Kosambi mapping function. Finally, 36 markers are used to construct a genetic linkage map with the total map distance of 34.4cM, as shown in FIG. 3, wherein the golden leaf character "YL" of the rosa flexuosa is positioned at 22.7cM of the map and is 0.2cM away from the rna28746 marker at the upstream, and is 0.4cM away from the rna28800 marker at the downstream, and the golden leaf character of the rosa flexuosa is positioned between 6,290,023bp and 6,581,773bp of chromosome CM009586.1 of the 'lunar powder' (R.chinensis 'Old Blush') genome by referring to the physical positions of the upstream and downstream markers on the genome of the Old rosa flexuosa 'lunar powder' (R.chinensis 'Old Blush'), and the total length of the interval is 0.28 Mb.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Sequence listing
<110> vegetable and flower institute of Chinese academy of agricultural sciences
<120> positioning method for leaf color character of rosa davurica
<160> 12
<170> SIPOSequenceListing 1.0
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gagtaactaa aaggcaacaa ccaaagtcag ctatgtggaa agtatgacca tatcacaagc 60
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tttcctctgt gtcataatca ggagacatac agcgcaaacc cggactcctt ataccagtct 240
ctacttctcc atgattcctt gcaactttac atgagatttc tcatctagac agtcattttg 300
ctcaggtgtt gaaccagctc catatggctt aataagctga cacagaaaga gataaaatag 360
gaccaataac tctcagtcaa aggtgtcagg gataatactg cctaaaatta tgaagaggta 420
caagagaagt aacatgatgt ttaaggtaag gtgaataccg acacatctgc aagactgcaa 480
cccagaatcc aatagaattt cgatagtaag agcatcccaa tagcttcccg tcatgaatgc 540
ataagtcagc aagtcttgac catcccatat caacagaatc atgggatatt acaggctccc 600
atgaataaac cagcaaatag ggatcttaag tttacatgtt aactcaattc aatcccctag 660
agtactaaga caaacaaatg aaaaccttca aactgtcatc caatccagaa aatattgtcc 720
tcccatcagg gtggaaagta attgcgcgta ctccccttgt aggctggaaa caagaaaaaa 780
aaattgtcag actaactgga tgaaagtcac attacaagaa aaacatagct acaggaatat 840
atgatgctct atcaatctga gtgagagaga gagagagaga aagagagata tatatatata 900
tatatatata tattcaatta ataacataaa ttacctcagg cctgctagat ccaatcagtt 960
caaaagtttc caaatcccag aatttcacag ttctgtctgc t 1001
<210> 2
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acgttggatg tggttttcat tgtaggaac 29
<210> 3
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acgttggatg taacatccag aatgaggccc 30
<210> 4
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gccagctggt tcttct 16
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tacttccggt ggtccccgcc gccgcctgca gcggcacgct gggccgccac ctggctcggc 240
ggctggtcga gattggcgtt catgacgtgt tctcagtccc cggcgacttc aacttgaccc 300
tcttggacca cctgatcgcc gagccggagc tcaacctcat cggctgctgc aacgagctca 360
acgccggcta cgccgccgac ggctacgcgc gcgccagggg cgtcggcgcg tgtgtcgtaa 420
ctttcacggt gggtgggctc agcgtcttga acgccatcgc cggtgcttac agtgagaact 480
tgccggtgat ttgtatcgtc ggtgggccca actccaatga ttacgggacc aatcggatcc 540
tccaccacac gatcgggtta cccgatttca ctcaggagct ccggtgcttc caaactgtta 600
cttgtcacca ggtaaaagct tcacagctaa gacagtagag tgttctagtc tcaaggtctt 660
aaacctctat aatattctcg aatttttttt tttttttttt ttagtatcat tgttaaatat 720
aacatgtttt gaatatttta ttttagtata tttcctcgat attttggtca cctgttacta 780
tgttatgctc aaagatgttg gatttaatgt tgctgaagac attttcgtgc attgtgtgac 840
aggcagtggt gagtcatttg gaagatgcgc atgagcttat agacacggca atttcgacag 900
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<213> Artificial Sequence (Artificial Sequence)
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cggttcatag aacatcttga tggcttttga gagtagtaag ccgaagacag gaaaaatcac 360
tccatgacct gctgcagcaa tagatccaag cagcaaaact ggaagctcag gtttattcaa 420
ataggccagc cttttgatgg aaactttttt gcgttgctcc ggatcaacct tcgttttcac 480
acggttctcc tcatcttctt cttctacttg tacttcacaa ttaactggag caggaacacc 540
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tgctgaaagt ctctggctcc cagatctact cattgtccta tctatattca aaccattatc 660
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ataagctcct tctgggtttt gggtcaagtc atcatgagtt cctacaatac aaaacgatga 780
tgttacttga ggaacaagtt tattgtacga atgagaatga tggtgtacct tatggaaatg 840
ctcttaccta tttcaacaat tttcccttta tgcaccacag ctattgcatc agcattccta 900
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<210> 10
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<212> DNA
<213> Artificial Sequence (Artificial Sequence)
<400> 10
acgttggatg tagctttggt gttcctgctc 30
<210> 11
<211> 30
<212> DNA
<213> Artificial Sequence (Artificial Sequence)
<400> 11
acgttggatg ccttcgtttt cacacggttc 30
<210> 12
<211> 20
<212> DNA
<213> Artificial Sequence (Artificial Sequence)
<400> 12
acggttctcc tcatcttctt 20
Claims (4)
1. A method for locating a leaf color trait of rosa davurica, which is characterized by comprising the following steps:
constructing a genetic population, namely obtaining an F1 progeny population by artificial cross pollination by using rosa labrata as a female parent and rosa davurica (R.davurica) as a male parent, and testing the leaf color separation condition of the F1 progeny through chi-square test, wherein the leaf color separation condition accords with 1: 1, separation, namely, supposing that the leaf color character of rosa davurica pall is controlled by dominant single gene;
BSA-Seq analysis locates the position and region of the golden leaf character genome;
and (3) developing the SNP molecular marker by carrying out MassARRAY high-throughput sequencing technical means based on the BSA-Seq result.
2. The method for locating the leaf color trait of rosa canina according to claim 1, wherein the isolated population of rosa canina ' F1 is used as a material, 27 individual rosa canina ' x ' rosa davurica ' F1 is extracted from fresh leaves of the isolated population, 34 individual rosa canina ' F1 are extracted from fresh leaves of the isolated population, genomic DNA of the fresh leaves are mixed in equal amount, two extreme mixed pools of rosa canina and green leaves are constructed, DNA quality of the two mixed pools is detected, the sample DNA is used for constructing a sequencing library after being qualified, and genomic re-sequencing is performed by Illumina HiSeqX after being qualified in library quality detection.
3. The method for locating the leaf color trait of rosa flexuosa according to claim 1, wherein BSA-Seq analysis locates the position and region of the gold leaf trait genome, uses the 'lunar powder' genome RchiOBHm-V2 of ancient chinese rose as a reference genome, uses BWA software to compare obtained reads to the reference genome, uses GATK software to detect SNP and InDel between a sample and the reference genome, extracts the variation sites with difference between two sample mixing pools, and obtains a set of SNP and InDel variation sites between the two extreme mixing pools; and then calculating the SNP-index of each mixing pool by using the SNP data of the two parents, comparing the SNP-index of each mixing pool, calculating the delta SNP-index, fitting the delta SNP-index by adopting an Euclidean distance algorithm, and finally drawing a distribution map of the ED value of the SNP on the color body.
4. The method for mapping leaf color trait of rosa flexuosa according to claim 3, wherein the ED fitting algorithm is used to calculate that the mapping region related to the gold leaf trait is 4,040,000bp-8,850,000bp and 4.81Mb in total length of chromosome CM009586.1 of the ancient China rose 'lunar powder' genome in the reference genome, 492 genes are annotated in the mapping region, 540 SNPs are annotated as non-synonymous mutations and 100 InDel are annotated as frameshift mutations.
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| CN109360606A (en) * | 2018-11-19 | 2019-02-19 | 广西壮族自治区农业科学院水稻研究所 | A kind of method of low-density SNP genome area Accurate Prediction BSA-seq candidate gene |
| US20200407805A1 (en) * | 2017-05-05 | 2020-12-31 | Tianjin Kernel Agricultural Science And Technology Corporation Ltd. Cucumber Research Institute | Cucumber Male Sterility Gene, Molecular Marker, Screening Method and Application Thereof |
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| US20200407805A1 (en) * | 2017-05-05 | 2020-12-31 | Tianjin Kernel Agricultural Science And Technology Corporation Ltd. Cucumber Research Institute | Cucumber Male Sterility Gene, Molecular Marker, Screening Method and Application Thereof |
| CN109360606A (en) * | 2018-11-19 | 2019-02-19 | 广西壮族自治区农业科学院水稻研究所 | A kind of method of low-density SNP genome area Accurate Prediction BSA-seq candidate gene |
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