WO2023245401A1 - Characteristic snp marker-based method for identifying litopenaeus vannamei breeds - Google Patents
Characteristic snp marker-based method for identifying litopenaeus vannamei breeds Download PDFInfo
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- the invention belongs to the technical field of aquaculture molecular markers, and specifically relates to a method for identifying cultured species of Litopenaeus vannamei based on characteristic SNP markers.
- Litopenaeus vannamei (Litopenaeus vannamei or Penaeus vannamei), also known as South American white shrimp, belongs to the phylum Arthropoda, the class Softshell, the family Penaeus, and the genus Litopenaeus.
- Litopenaeus vannamei has a bluish-blue or light bluish-gray body color and is naturally distributed in the eastern Pacific Ocean from Sonora, Mexico to Tumbes in northern Peru.
- Litopenaeus vannamei has been artificially cultured in the Americas since the 1970s. Initially, wild mated broodstock were artificially captured and hatched to produce nauplii for artificial breeding. With the expansion of breeding scale, its specific-pathogen-free (SPF) shrimp seedling technology is developing rapidly in Hawaii, Florida and other places. Due to its fast growth rate and strong stress resistance, Litopenaeus vannamei was introduced to various parts of Asia in the late 1980s and has gradually developed into one of the most important aquaculture species today, with great economic value.
- SPF specific-pathogen-free
- Litopenaeus vannamei was introduced to China in 1988 and has been cultivated locally for decades. At present, my country still needs to import more than 500,000 pairs of broodstock from the international market every year. However, imported Litopenaeus vannamei seed shrimp are not only expensive, but also have problems such as uneven quality and unclear genetic background. Therefore, identifying the species and origin of broodstock is crucial for the sustainable development of the Litopenaeus vannamei aquaculture industry.
- the purpose of the present invention is to provide a method for identification of Litopenaeus vannamei culture species based on characteristic SNP markers, that is, on the basis of providing characteristic SNP marker sets among Litopenaeus vannamei species and groups, an identification method is established at the molecular level. Methods of genetic background and species origin of Litopenaeus vannamei.
- the present invention first provides a SNP marker set.
- the SNP site in the SNP marker set is located at position 36 of any sequence of SEQ ID NO: 1-14974;
- SNP marker set provided by the present invention is to identify the species source of Litopenaeus vannamei
- the present invention also provides a method for identifying the source of Litopenaeus vannamei species, which uses the above-mentioned SNP marker set as a molecular marker for detection;
- the described method is based on the principal component cluster analysis method and includes the following steps:
- Step 1) Use the above SNP marker set to obtain the gene table corresponding to each SNP site of the sample to be tested;
- Step 2) Prepare the input file for principal component analysis, including reference set and test set;
- Step 3) Principal component analysis determines the feature vector
- Step 4) Visualize the feature vector and determine the source of the variety.
- the method of the present invention has the following advantages:
- the SNP markers used in this invention are derived from whole-genome scale SNP data sets. They are different from previous molecular markers in specific regions of the genome (such as mitochondria, microsatellite markers, etc.), and can more accurately identify the source of samples.
- the present invention applies principal component analysis to sample clustering, uses feature vectors to characterize the differences before samples, and realizes data quantification of fuzzy results of sample clustering.
- the present invention uses R scripts to visualize the sample clustering results, and uses 95% confidence intervals to classify the varieties to which the samples belong, making the classification results more intuitive.
- Figure 1 Cluster analysis results of 18 samples of Litopenaeus vannamei from known sources, where x and y represent the characteristic values of the sample on the first four principal component vectors, and the points of different shapes represent the main species of Litopenaeus vannamei. and the reference sample of the population, and the black round dots represent the target samples to be identified.
- RH and KH represent the two domestically selected varieties, Renhai No. 1 and Kehai No. 1, while TA, CP, BMK and SIS represent the selected varieties from four foreign companies: Dingfeng, Zhengda, BMK and SIS respectively;
- Figure 2 Cluster analysis results of 5 samples of Litopenaeus vannamei from unknown sources.
- SNP Single nucleotide polymorphism
- SNP molecular markers have the characteristics of large number, high density and simple type. Using differences in genetic components to identify the origin of shrimp requires a large number of genome-scale molecular markers, so SNP molecular markers are the most effective tool for source identification.
- genomic SNP markers include whole-genome resequencing, genome microarrays, simplified genome sequencing, restriction enzyme sequencing genotyping (GBS), PCR-based fluorescent labeling high-throughput methods, and high-resolution melting curves Analysis (HRM), TaqMan probe method fluorescence quantitative PCR, etc.
- GGS restriction enzyme sequencing genotyping
- HRM high-resolution melting curves Analysis
- TaqMan probe method fluorescence quantitative PCR etc.
- the density of SNP markers obtained by whole-genome resequencing is the highest.
- the invention brings together Renhai No. 1 (Yellow Sea Fisheries Research Institute of the Chinese Academy of Fisheries Sciences, Hairen Aquatic Seed Industry Technology Co., Ltd., RH) and Kehai No. 1 (Oceanic Research Institute of the Chinese Academy of Sciences, Northwest A&F University, Hainan Oriental Middle School Ke Marine Biological Breeding Co., Ltd., KH) two domestically selected varieties, Dingfeng (Dingfeng Aquaculture Co., Ltd., TA) and Zhengda (CP Charoen Pokphand Group, CP) broodstock groups of two Thai companies, as well as BMK ( Benchmark Genetics Shrimp Breeding Center, BMK) and SIS (Shrimp Improvement Systems, SIS) are the breeding groups of two American shrimp companies.
- the characteristic single nucleotide polymorphism (SNP) marker set among Litopenaeus vannamei species and populations obtained through screening in the present invention is used to identify the genetic background and species origin of the shrimp at the molecular level.
- SNP
- Example 1 Screening and identifying characteristic SNP marker collections from which shrimp species originate
- the SNP marker set of the present invention is selected from the whole genome of shrimp, and the screening steps are as follows:
- Sample and data collection First, all collected shrimp samples were vivisected, and DNA was extracted using SDS cleavage phenol chloroform extraction method to construct a 250-350bp genome resequencing library, and then Illumina paired-end sequencing was performed.
- Genome comparison After removing low-quality reads from all individual sequencing data, they are compared to the Litopenaeus vannamei reference genome, and then sorted according to genome coordinates to facilitate individual genotype detection.
- Genotype detection After PCR duplicate reads are removed, each individual mutation site is detected. After merging all individuals, perform SNP site filtering (filtering sites mainly include sequencing depth less than 4, alignment quality less than 20, minor allele frequency less than 0.05, and individual typing missing). After filtering out low-quality sequencing data and outlier samples, a total of 151 samples were used for subsequent analysis, including 25 Renhai 1, 35 Kehai 1, 23 Dingfeng, 25 Zhengda, and 16 SIS , 27 BMK. The whole-genome SNP data set is then quality tested and filtered to obtain high-quality SNP sets.
- the SNP marker set provided by the present invention is used to identify the species source of Litopenaeus vannamei, and can also be used in the genetic selection of Litopenaeus vannamei.
- the present invention also provides a method for identifying the source of Litopenaeus vannamei species, which is to use the above-mentioned SNP marker set as a molecular marker to perform principal component cluster analysis method detection.
- Step 1) Obtain the genotype information of the test sample through sample collection, whole-genome resequencing, and genotyping. Use the sequence list of the SNP set obtained through screening as a target reference for anchoring SNP site extraction to obtain the sample to be tested.
- SNP corresponding site gene table (take the test file Test.txt as an example, the sample names are letters plus numbers, such as "Test1, Test2,...,TestN")
- the file format requirements are as shown in Table 1 below.
- Table 1 Example table of test sample genotype file format
- Step 2) Prepare input files for principal component analysis, including reference set and test set: merge the genotype table of the test sample with the reference set (reference.txt), and use the command provided by this method to convert it into Plink format (including two files: analysis.ped and analysis.map).
- Step 3) Principal component analysis to determine the feature vector: Use Plink software under the Linux system to perform principal component analysis and obtain the feature vector file (merge.eigenvec) of each sample: the first two columns are the ID of the sample, and the following columns are features. Vector value on each principal component.
- Step 4) Visualize the feature vector and determine the source of the variety:
- the source of the test sample variety is determined ( Figure 1).
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Abstract
The present invention provides a characteristic SNP marker-based method for identifying litopenaeus vannamei breeds. On the basis of providing a characteristic SNP marker set of different litopenaeus vannamei breeds and populations, a method for identifying the genetic background and breed source of litopenaeus vannamei is established on the molecular level. The SNP site in the SNP marker set is position 36 in any of the sequences set forth in SEQ ID NOs: 1-14974.
Description
本发明属于水产养殖分子标记技术领域,具体涉及一种基于特征SNP标记的凡纳滨对虾养殖品种鉴定方法。The invention belongs to the technical field of aquaculture molecular markers, and specifically relates to a method for identifying cultured species of Litopenaeus vannamei based on characteristic SNP markers.
凡纳滨对虾(Litopenaeus vannamei或Penaeus vannamei),又称南美白对虾,属于节肢动物门,软甲纲,对虾科、滨对虾属动物。凡纳滨对虾体色为青蓝色或淡青灰色,自然分布于墨西哥的索诺拉到秘鲁北部的通贝斯东太平洋海域。Litopenaeus vannamei (Litopenaeus vannamei or Penaeus vannamei), also known as South American white shrimp, belongs to the phylum Arthropoda, the class Softshell, the family Penaeus, and the genus Litopenaeus. Litopenaeus vannamei has a bluish-blue or light bluish-gray body color and is naturally distributed in the eastern Pacific Ocean from Sonora, Mexico to Tumbes in northern Peru.
凡纳滨对虾自上世纪70年代开始在美洲进行人工养殖,最初是通过人工捕获野生已经交配过的亲虾进行孵化,产生无节幼体进行人工养殖。随着养殖规模的扩大,其无特定病原体(Specific-pathogen-free,SPF)的虾苗技术在夏威夷、佛罗里达等地快速发展。由于其生长速度快和抗逆性强,凡纳滨对虾于上个世纪80年代末引入亚洲各地,并逐渐发展为当今最重要的水产养殖物种之一,具有极大的经济价值。Litopenaeus vannamei has been artificially cultured in the Americas since the 1970s. Initially, wild mated broodstock were artificially captured and hatched to produce nauplii for artificial breeding. With the expansion of breeding scale, its specific-pathogen-free (SPF) shrimp seedling technology is developing rapidly in Hawaii, Florida and other places. Due to its fast growth rate and strong stress resistance, Litopenaeus vannamei was introduced to various parts of Asia in the late 1980s and has gradually developed into one of the most important aquaculture species today, with great economic value.
伴随着凡纳滨对虾产业的快速发展,对于优质种苗的需求越来越高。而随着常年的捕捞,在世界范围内野生凡纳滨对虾的种质资源都受到破坏;在这种情况下,对虾养殖业开始发展遗传改良和良种选育研究。相比于野生苗种,人工选育的优良苗种的后代表现出更好的生长速度和抗病性。With the rapid development of the Litopenaeus vannamei industry, the demand for high-quality seedlings is increasing. With years of fishing, the germplasm resources of wild Litopenaeus vannamei have been destroyed worldwide. Under this situation, the shrimp farming industry has begun to develop research on genetic improvement and breeding of improved species. Compared with wild seedlings, the offspring of artificially selected excellent seedlings show better growth speed and disease resistance.
凡纳滨对虾自1988年引进中国,已经过几十年的本地化养殖。目前我国每年仍需从国际进口亲虾超过50万对。而进口的凡纳滨对虾的种虾不仅价格昂贵,而且存在品质良莠不齐、遗传背景不清晰等问题。因此,鉴定亲虾的品种和来源对于凡纳滨对虾养殖业的持续发展至关重要。Litopenaeus vannamei was introduced to China in 1988 and has been cultivated locally for decades. At present, my country still needs to import more than 500,000 pairs of broodstock from the international market every year. However, imported Litopenaeus vannamei seed shrimp are not only expensive, but also have problems such as uneven quality and unclear genetic background. Therefore, identifying the species and origin of broodstock is crucial for the sustainable development of the Litopenaeus vannamei aquaculture industry.
然而不同来源的对虾的外观差异较小,仅凭技术人员的养殖经验无法对来 源进行判断。因此需要提供一种更有效的凡纳滨对虾品种鉴定方法。However, the differences in the appearance of shrimps from different sources are small, and the source cannot be judged based only on the breeding experience of technicians. Therefore, it is necessary to provide a more effective method for identification of Litopenaeus vannamei species.
发明内容Contents of the invention
本发明的目的是提供一种基于特征SNP标记的凡纳滨对虾养殖品种鉴定方法,即在提供凡纳滨对虾品种及群体间的特征SNP标记集的基础上,在分子水平上建立一种鉴定凡纳滨对虾的遗传背景和品种来源的方法。The purpose of the present invention is to provide a method for identification of Litopenaeus vannamei culture species based on characteristic SNP markers, that is, on the basis of providing characteristic SNP marker sets among Litopenaeus vannamei species and groups, an identification method is established at the molecular level. Methods of genetic background and species origin of Litopenaeus vannamei.
本发明首先提供一种SNP标记集合,所述的SNP标记集合中的SNP位点是位于序列为SEQ ID NO:1-14974的任意序列的第36位;The present invention first provides a SNP marker set. The SNP site in the SNP marker set is located at position 36 of any sequence of SEQ ID NO: 1-14974;
本发明所提供的SNP标记集合,其一种用途是用于鉴定凡纳滨对虾的品种来源;One use of the SNP marker set provided by the present invention is to identify the species source of Litopenaeus vannamei;
本发明还提供一种鉴定凡纳滨对虾品种来源的方法,是使用上述的SNP标记集合作为分子标记来进行检测;The present invention also provides a method for identifying the source of Litopenaeus vannamei species, which uses the above-mentioned SNP marker set as a molecular marker for detection;
所述的方法,作为实施例的具体记载,为基于主成分聚类分析方法,包括如下的步骤:The described method, as a specific description of the embodiment, is based on the principal component cluster analysis method and includes the following steps:
步骤1)利用上述的SNP标记集合,获取待测样本的每个SNP位点对应的基因表;Step 1) Use the above SNP marker set to obtain the gene table corresponding to each SNP site of the sample to be tested;
步骤2)准备主成分分析的输入文件,包括参考集和测试集;Step 2) Prepare the input file for principal component analysis, including reference set and test set;
步骤3)主成分分析确定特征向量;Step 3) Principal component analysis determines the feature vector;
步骤4)特征向量可视化,确定品种来源。Step 4) Visualize the feature vector and determine the source of the variety.
本发明方法与现有技术相比,具有以下优点:Compared with the existing technology, the method of the present invention has the following advantages:
1.本发明使用的SNP标记来源于全基因组尺度SNP数据集,不同于以往的基因组特定区域内(如线粒体,微卫星标记等)的分子标记,对样品来源鉴定更加精准。1. The SNP markers used in this invention are derived from whole-genome scale SNP data sets. They are different from previous molecular markers in specific regions of the genome (such as mitochondria, microsatellite markers, etc.), and can more accurately identify the source of samples.
2.本发明将主成分分析应用到样品聚类,使用特征向量表征样本之前的差 异,实现了样品聚类模糊结果的数据量化。2. The present invention applies principal component analysis to sample clustering, uses feature vectors to characterize the differences before samples, and realizes data quantification of fuzzy results of sample clustering.
3.本发明利用R脚本对样本聚类结果进行可视化,利用95%的置信区间,划分样本归属的品种,使分类结果更加直观。3. The present invention uses R scripts to visualize the sample clustering results, and uses 95% confidence intervals to classify the varieties to which the samples belong, making the classification results more intuitive.
图1:18个已知来源凡纳滨对虾样品的聚类分析结果图,其中x和y代表样品在前四个主成分向量上的特征值,不同形状的点代表凡纳滨对虾各主要品种和群体的参考样品,黑色圆形的点代表待鉴定的目标样品。RH,KH,代表壬海1号,科海1号两个国内选育品种,TA,CP,BMK,SIS分别代表顶丰,正大,BMK,SIS四个国外公司的选育品种;Figure 1: Cluster analysis results of 18 samples of Litopenaeus vannamei from known sources, where x and y represent the characteristic values of the sample on the first four principal component vectors, and the points of different shapes represent the main species of Litopenaeus vannamei. and the reference sample of the population, and the black round dots represent the target samples to be identified. RH and KH represent the two domestically selected varieties, Renhai No. 1 and Kehai No. 1, while TA, CP, BMK and SIS represent the selected varieties from four foreign companies: Dingfeng, Zhengda, BMK and SIS respectively;
图2:5个未知来源凡纳滨对虾样品的聚类分析结果图。Figure 2: Cluster analysis results of 5 samples of Litopenaeus vannamei from unknown sources.
单核苷酸多态性SNP是可遗传的变异中最常见的一种分子标记,是指个体或群体间在基因组水平上由单个核苷酸的变异所引起的DNA序列多态性。SNP分子标记具有数量大、密度高、类型简单的特征。利用遗传成分的差异进行鉴别对虾的来源,需要大量的基因组尺度的分子标记,因此SNP分子标记是进行来源鉴别最有效的工具。Single nucleotide polymorphism (SNP) is the most common molecular marker among heritable variations. It refers to the DNA sequence polymorphism caused by the variation of a single nucleotide at the genome level between individuals or groups. SNP molecular markers have the characteristics of large number, high density and simple type. Using differences in genetic components to identify the origin of shrimp requires a large number of genome-scale molecular markers, so SNP molecular markers are the most effective tool for source identification.
目前,获取基因组SNP标记的方法包括全基因组重测序,基因组芯片,简化基因组测序,限制性内切酶的测序基因分型(GBS),基于PCR的荧光标记高通量方法、高分辨率熔融曲线分析(HRM)、TaqMan探针法荧光定量PCR等。其中,全基因组重测序获取的SNP标记密度最高,Currently, methods for obtaining genomic SNP markers include whole-genome resequencing, genome microarrays, simplified genome sequencing, restriction enzyme sequencing genotyping (GBS), PCR-based fluorescent labeling high-throughput methods, and high-resolution melting curves Analysis (HRM), TaqMan probe method fluorescence quantitative PCR, etc. Among them, the density of SNP markers obtained by whole-genome resequencing is the highest.
本发明汇集了壬海1号(中国水产科学研究院黄海水产研究所、海壬水产种业科技有限公司,RH)和科海1号(中国科学院海洋研究所、西北农林科技大学、海南东方中科海洋生物育种有限公司,KH)两个国内选育品种,顶丰(顶丰水 产养殖有限公司,TA)和正大(正大卜蜂集团,CP)两个泰国公司的亲虾群体,以及BMK(Benchmark Genetics Shrimp育种中心,BMK)和SIS(Shrimp Improvement Systems公司,SIS)两个美国种虾公司的选育群体。利用本发明筛选获得的凡纳滨对虾品种及群体间的特征单核苷酸多态性(SNP)标记集,在分子水平鉴别对虾的遗传背景和品种来源。The invention brings together Renhai No. 1 (Yellow Sea Fisheries Research Institute of the Chinese Academy of Fisheries Sciences, Hairen Aquatic Seed Industry Technology Co., Ltd., RH) and Kehai No. 1 (Oceanic Research Institute of the Chinese Academy of Sciences, Northwest A&F University, Hainan Oriental Middle School Ke Marine Biological Breeding Co., Ltd., KH) two domestically selected varieties, Dingfeng (Dingfeng Aquaculture Co., Ltd., TA) and Zhengda (CP Charoen Pokphand Group, CP) broodstock groups of two Thai companies, as well as BMK ( Benchmark Genetics Shrimp Breeding Center, BMK) and SIS (Shrimp Improvement Systems, SIS) are the breeding groups of two American shrimp companies. The characteristic single nucleotide polymorphism (SNP) marker set among Litopenaeus vannamei species and populations obtained through screening in the present invention is used to identify the genetic background and species origin of the shrimp at the molecular level.
下面结合实施例和附图对本发明进行详细的描述。The present invention will be described in detail below with reference to the embodiments and drawings.
实施例1:筛选鉴定对虾品种来源的特征SNP标记集合Example 1: Screening and identifying characteristic SNP marker collections from which shrimp species originate
本发明的SNP标记集合选取自对虾的全基因组,其筛选的步骤如下:The SNP marker set of the present invention is selected from the whole genome of shrimp, and the screening steps are as follows:
a.样品及数据采集:首先对所有收集的对虾样本进行活体解剖,使用SDS裂解酚氯仿提取法进行DNA提取,构建250-350bp基因组重测序文库,之后进行Illumina双端测序。a. Sample and data collection: First, all collected shrimp samples were vivisected, and DNA was extracted using SDS cleavage phenol chloroform extraction method to construct a 250-350bp genome resequencing library, and then Illumina paired-end sequencing was performed.
b.基因组比对:所有个体测序数据去除低质量reads后,比对至凡纳滨对虾参考基因组,之后按照基因组坐标进行排序,便于个体基因型检测。b. Genome comparison: After removing low-quality reads from all individual sequencing data, they are compared to the Litopenaeus vannamei reference genome, and then sorted according to genome coordinates to facilitate individual genotype detection.
c.基因型检测:经过PCR重复reads去除后,进行每个个体变异位点检测。将所有个体合并后,进行SNP位点过滤(过滤位点主要包括测序深度小于4,比对质量小于20,次等位基因频率小于0.05,个体分型有缺失)。在过滤掉低质量测序数据和离群样品后,共151个样品用于后续分析,其中包括25个壬海1号,35个科海1号,23个顶丰,25个正大,16个SIS,27个BMK。随后对全基因组SNP数据集进行质量检测和筛选,以获取高质量的SNP集。c. Genotype detection: After PCR duplicate reads are removed, each individual mutation site is detected. After merging all individuals, perform SNP site filtering (filtering sites mainly include sequencing depth less than 4, alignment quality less than 20, minor allele frequency less than 0.05, and individual typing missing). After filtering out low-quality sequencing data and outlier samples, a total of 151 samples were used for subsequent analysis, including 25 Renhai 1, 35 Kehai 1, 23 Dingfeng, 25 Zhengda, and 16 SIS , 27 BMK. The whole-genome SNP data set is then quality tested and filtered to obtain high-quality SNP sets.
d.凡纳滨对虾品种及群体间的特征SNP集获取:利用主成分分析进行数据压缩和冗余噪音消除,计算了各位点在每个主成分上的特征值(eigenvalue)。筛选获得在前五个主成分方向上特征值最高的14974个SNP标记,作为鉴定品种来源的特征SNP集;其中的SNP位点是位于序列为SEQ ID NO:1-14974的任意 序列的第36位。d. Acquisition of characteristic SNP sets among Litopenaeus vannamei species and populations: Principal component analysis was used for data compression and redundant noise elimination, and the eigenvalues (eigenvalues) of each site on each principal component were calculated. The 14974 SNP markers with the highest characteristic values in the first five principal component directions were screened and used as a characteristic SNP set to identify the source of the variety; the SNP site is located at the 36th position of any sequence with the sequence SEQ ID NO: 1-14974 Bit.
本发明所提供的SNP标记集合用于鉴定凡纳滨对虾的品种来源,还可以用于凡纳滨对虾的遗传选育中。The SNP marker set provided by the present invention is used to identify the species source of Litopenaeus vannamei, and can also be used in the genetic selection of Litopenaeus vannamei.
本发明还提供一种鉴定凡纳滨对虾品种来源的方法,是使用上述的SNP标记集合作为分子标记来进行主成分聚类分析方法检测。The present invention also provides a method for identifying the source of Litopenaeus vannamei species, which is to use the above-mentioned SNP marker set as a molecular marker to perform principal component cluster analysis method detection.
实施例2:对已知来源样品进行鉴定Example 2: Identification of samples from known sources
于2021年7月自河北省黄骅县海壬对虾育苗公司获取了18个已知品种来源的凡纳滨对虾作为测试集,上述的6个品种各3只,并在实验室内进行活体解剖以获得鳃组织进行DNA提取,之后进行DNA重测序文库构建以及Illumina二代测序。经过基因组比对,基因型检测后,获取到测试集全部SNP位点集合。In July 2021, 18 Litopenaeus vannamei from known species were obtained from the Penaeus vannamei breeding company in Huanghua County, Hebei Province as a test set. Three of each of the above-mentioned six species were vivisected in the laboratory. Gill tissue was obtained for DNA extraction, followed by DNA resequencing library construction and Illumina second-generation sequencing. After genome comparison and genotype detection, the entire SNP site set of the test set was obtained.
步骤1):通过样品采集,全基因组重测序,基因分型获取到测试样本的基因型信息,利用筛选获得的SNP集合的序列表作为锚定SNP位点提取的靶标参考,获取待测样本的SNP对应位点基因表,(以测试文件Test.txt为例,样本名字命名为字母加数字,如“Test1,Test2,…,TestN”)文件格式要求参照按照下表1形式。Step 1): Obtain the genotype information of the test sample through sample collection, whole-genome resequencing, and genotyping. Use the sequence list of the SNP set obtained through screening as a target reference for anchoring SNP site extraction to obtain the sample to be tested. SNP corresponding site gene table, (take the test file Test.txt as an example, the sample names are letters plus numbers, such as "Test1, Test2,...,TestN") The file format requirements are as shown in Table 1 below.
表1:测试样本基因型文件格式示例表Table 1: Example table of test sample genotype file format
SNP_IDSNP_ID | Test1Test1 | Test2Test2 | …… | TestNTestN |
lg1-67279lg1-67279 | CCCC | CCCC | …… | CCCC |
lg1-414145lg1-414145 | GGGG | GAGA | …… | AAAA |
lg1-839392lg1-839392 | TTTT | TTTT | …… | CTCT |
lg1-1033093lg1-1033093 | AAAA | AAAA | …… | TTTT |
lg1-1033097lg1-1033097 | GGGG | GGGG | …… | CCCC |
lg1-1033101lg1-1033101 | TTTT | TTTT | …… | CCCC |
lg1-1214444lg1-1214444 | CCCC | TTTT | …… | CCCC |
步骤2):准备主成分分析的输入文件,包括参考集和测试集:将待测样品基因型表格与参考集合(reference.txt)合并,并利用本方法提供的命令转换为Plink格式(包括两个文件:analysis.ped和analysis.map)。Step 2): Prepare input files for principal component analysis, including reference set and test set: merge the genotype table of the test sample with the reference set (reference.txt), and use the command provided by this method to convert it into Plink format (including two files: analysis.ped and analysis.map).
a.准备Plink格式的ped文件基因型部分,将待测试样本的文件与本方法提供的参考集合横向合并,保留基因型部分并进行行列转置,作为Plink格式文件中的基因型部分(genotype):a. Prepare the genotype part of the ped file in Plink format, merge the file of the sample to be tested horizontally with the reference set provided by this method, retain the genotype part and transpose the rows and columns as the genotype part (genotype) in the Plink format file :
$$$awk'{$1=null;print$0}'Test.txt|paste reference.txt-|sed's//\t/g'$$$awk'{$1=null;print$0}'Test.txt|paste reference.txt-|sed's//\t/g'
|awk'{$1=null;print$0}'|sed'1d'|awk'{for(i=1;i<=NF;|awk'{$1=null; print$0}'|sed'1d'|awk'{for(i=1; i<=NF;
i++){if(NR==1){res[i]=$i;}else{res[i]=res[i]""$i}}}END{for(i=1;i++){if(NR==1){res[i]=$i;}else{res[i]=res[i]""$i}}}END{for(i=1;
i<=NF;i++){print res[i]}}'>genotype.txti<=NF;i++){print res[i]}}'>genotype.txt
b.准备Plink格式ped文件样品信息部分(sample.name.txt):b. Prepare the sample information part of the Plink format ped file (sample.name.txt):
$$$awk'{$1=null;print$0}'Test.txt|paste reference.txt-|sed's//\t/g'$$$awk'{$1=null;print$0}'Test.txt|paste reference.txt-|sed's//\t/g'
|awk'{$1=null;print$0}'|head-1|awk'{for(i=1;i<=NF;|awk'{$1=null;print$0}'|head-1|awk'{for(i=1;i<=NF;
i++){if(NR==1){res[i]=$i;}else{res[i]=res[i]""$i}}}END{for(i=1;i++){if(NR==1){res[i]=$i;}else{res[i]=res[i]""$i}}}END{for(i=1;
i<=NF;i++){print res[i]}}'>sample.name.txti<=NF;i++){print res[i]}}'>sample.name.txt
c.合并获得ped文件:c. Merge to obtain the ped file:
$$$awk'{print$1,$1,"0","0","0","-9"}'sample.name.txt|paste–$$$awk'{print$1,$1,"0","0","0","-9"}'sample.name.txt|paste–
genotype.txt|sed's/\t//'>analysis.pedgenotype.txt|sed's/\t//'>analysis.ped
d.准备Plink格式map文件:d. Prepare Plink format map file:
$$$sed'1d'reference.txt|cut-f 1|sed's/-//'|awk'{print$$$sed'1d'reference.txt|cut-f 1|sed's/-//'|awk'{print
$1,$1"-"$2,$2,$2}'>analysis.map$1,$1"-"$2,$2,$2}'>analysis.map
步骤3):主成分分析确定特征向量:利用linux系统下Plink软件,进行主成分分析,得到每个样品的特征向量文件(merge.eigenvec):前两列为样本的ID,后面的列为特征向量在每个主成分上的值。Step 3): Principal component analysis to determine the feature vector: Use Plink software under the Linux system to perform principal component analysis and obtain the feature vector file (merge.eigenvec) of each sample: the first two columns are the ID of the sample, and the following columns are features. Vector value on each principal component.
$$$plink--file analysis--pca tabs--allow-extra-chr--out merge$$$plink--file analysis--pca tabs--allow-extra-chr--out merge
步骤4)特征向量可视化,确定品种来源:Step 4) Visualize the feature vector and determine the source of the variety:
a.在输入文件merge.eigenvec中加入品种名称,和数据表头:a. Add the variety name and data header to the input file merge.eigenvec:
$$$cut-f 1-6merge.eigenvec|sed's/[0-9]*\t/\t/'>merge.pca$$$cut-f 1-6merge.eigenvec|sed's/[0-9]*\t/\t/'>merge.pca
$$$printf“TYPE\tINDV\tPC1\tPC2\tPC3\tPC4\n”|cat-merge.pca.ref>$$$printf“TYPE\tINDV\tPC1\tPC2\tPC3\tPC4\n”|cat-merge.pca.ref>
merge.PCA.txtmerge.PCA.txt
在文本编辑器中将merge.PCA.txt第一列(TYPE),参考样本填充为品种名,测试样本填充为“Test”。In the text editor, fill the first column (TYPE) of merge.PCA.txt with the reference sample as the variety name and the test sample as "Test".
启动R程序Start R program
install.packages("ggplot2")install.packages("ggplot2")
library(ggplot2)library(ggplot2)
setwd("/path/to/input/file/")setwd("/path/to/input/file/")
pdf("PCA.pdf",width=6,height=5)pdf("PCA.pdf",width=6,height=5)
all_vec<-read.table("val-pca.txt",header=T)all_vec<-read.table("val-pca.txt",header=T)
ref<-subset(all_vec,TYPE!='Test')ref<-subset(all_vec,TYPE!='Test')
test<-subset(all_vec,TYPE=='Test')test<-subset(all_vec,TYPE=='Test')
myplot1_2<-ggplot(ref,aes(x=PC1,y=PC2,shape=TYPE))+myplot1_2<-ggplot(ref,aes(x=PC1,y=PC2,shape=TYPE))+
geom_point(size=4,color="grey30")+geom_point(size=4,color="grey30")+
scale_shape_manual(values=c(6,5,2,0,3,4))+scale_shape_manual(values=c(6,5,2,0,3,4))+
stat_ellipse(type="norm",linetype=2)+stat_ellipse(type="norm",linetype=2)+
geom_point(size=4,data=test,shape=19)geom_point(size=4,data=test,shape=19)
myplot1_2+theme(panel.background=element_blank())+myplot1_2+theme(panel.background=element_blank())+
theme(axis.line=element_line(colour="black"))theme(axis.line=element_line(colour="black"))
myplot1_2<-ggplot(ref,aes(x=PC3,y=PC4,shape=TYPE))+myplot1_2<-ggplot(ref,aes(x=PC3,y=PC4,shape=TYPE))+
geom_point(size=4,color="grey30")+geom_point(size=4,color="grey30")+
scale_shape_manual(values=c(6,5,2,0,3,4))+scale_shape_manual(values=c(6,5,2,0,3,4))+
stat_ellipse(type="norm",linetype=2)+stat_ellipse(type="norm",linetype=2)+
geom_point(size=4,data=test,shape=19)geom_point(size=4,data=test,shape=19)
myplot1_2+theme(panel.background=element_blank())+myplot1_2+theme(panel.background=element_blank())+
theme(axis.line=element_line(colour="black"))theme(axis.line=element_line(colour="black"))
dev.off()dev.off()
根据样本特征向量分布图,确定测试样本品种来源(图1)。According to the sample feature vector distribution diagram, the source of the test sample variety is determined (Figure 1).
使用散点图分布的形式对主成分样本聚类结果进行可视化,根据各类群95%的置信区间,对样本来源进行辨别。如图1特征向量分布所示,18个黑色实心点对应18个测试样本,不同性状的灰色符号代表不同的参考样本,虚线椭圆为对应品种特征向量分布的95%置信区间。依据的每个样本特征向量的分布,参考样本中的六个品种在前四个主成分上分层清晰。来自6个品种的18个测试样本的在第一、第二主成分(1a)上与第三、第四主成分(1b)上的特征向量空间分布均与对应的参考样本相近,且向量分布落在各自95%置信区间内,表明样本鉴定结果可信度在95%以上。Use the scatter plot distribution form to visualize the principal component sample clustering results, and identify the source of the samples based on the 95% confidence interval of each group. As shown in the eigenvector distribution in Figure 1, 18 solid black points correspond to 18 test samples, the gray symbols of different traits represent different reference samples, and the dotted ellipse is the 95% confidence interval of the eigenvector distribution of the corresponding variety. According to the distribution of each sample feature vector, the six varieties in the reference sample are clearly stratified on the first four principal components. The spatial distribution of feature vectors on the first and second principal components (1a) and the third and fourth principal components (1b) of 18 test samples from 6 varieties are similar to the corresponding reference samples, and the vector distribution falling within their respective 95% confidence intervals, indicating that the sample identification results are more than 95% reliable.
实施例3:未知样本的品种鉴定:Example 3: Variety identification of unknown samples:
从市场上获取了5个未知来源的凡纳滨对虾进行实例分析展示。通过样品采集、全基因重测序、和基因型检测,抽取了待测样品的特征SNP集位点,分别将两组样品和参考样品的数据合并,进行主成分聚类分析(具体步骤同实例 2)。Five Litopenaeus vannamei from unknown sources were obtained from the market for case analysis and demonstration. Through sample collection, whole-gene resequencing, and genotype detection, the characteristic SNP set sites of the samples to be tested were extracted, and the data of the two groups of samples and the reference sample were merged to perform principal component cluster analysis (the specific steps are the same as Example 2 ).
如图2所示,5个黑色实心点代表5个测试样本,不同性状的灰色符号代表不同的参考样本,虚线椭圆为对应品种特征向量分布的95%置信区间。根据图示的每个特征向量的分布,参考样中的六个品种在前四个主成分上分层清晰。5个未知测试样品中2个测试样本的特征向量在空间上分布在壬海(RH)品种的95%置信区间内,3个测试样本分布在科海(KH)95%置信区间内,表明测试样本来自壬海和科海两个品种,鉴定结果可信度在95%以上。As shown in Figure 2, 5 solid black dots represent 5 test samples, gray symbols with different traits represent different reference samples, and the dotted ellipse is the 95% confidence interval of the corresponding variety characteristic vector distribution. According to the distribution of each eigenvector shown in the figure, the six varieties in the reference sample are clearly stratified on the first four principal components. The eigenvectors of 2 test samples among the 5 unknown test samples are spatially distributed within the 95% confidence interval of the Renhai (RH) variety, and the 3 test samples are distributed within the 95% confidence interval of the Kehai (KH) variety, indicating that the test The samples come from two varieties, Renhai and Kehai, and the identification results are more than 95% reliable.
Claims (6)
- 一种SNP标记集合,其特征在于,所述的SNP标记集合中的SNP位点位于序列为SEQ ID NO:1-14974中的任一序列的第36位。A SNP marker set, characterized in that the SNP site in the SNP marker set is located at position 36 of any sequence in SEQ ID NO: 1-14974.
- 权利要求1所述的SNP标记集合在鉴定凡纳滨对虾的品种来源中的应用。Application of the SNP marker set according to claim 1 in identifying the species origin of Litopenaeus vannamei.
- 权利要求1所述的SNP标记集合在凡纳滨对虾遗传育种中的应用。Application of the SNP marker set according to claim 1 in genetic breeding of Litopenaeus vannamei.
- 一种鉴定凡纳滨对虾品种来源的方法,其特征在于,所述的方法是使用权利要求1所述的SNP标记集合作为分子标记来进行鉴定凡纳滨对虾品种来源。A method for identifying the source of Litopenaeus vannamei species, characterized in that the method uses the SNP marker set described in claim 1 as a molecular marker to identify the source of Litopenaeus vannamei species.
- 如权利要求4所述的方法,其特征在于,所述的方法为主成分聚类分析方法。The method according to claim 4, characterized in that the method is a principal component cluster analysis method.
- 如权利要求5所述的方法,其特征在于,所述的方法包括如下的步骤:The method of claim 5, characterized in that the method includes the following steps:步骤1):利用权利要求1所述的SNP标记集合,获取待测样本的每个SNP位点对应的基因表;Step 1): Using the SNP marker set according to claim 1, obtain the gene table corresponding to each SNP site of the sample to be tested;步骤2):准备主成分分析的输入文件,所述的文件包括参考集和测试集;Step 2): Prepare the input file for principal component analysis. The file includes the reference set and the test set;步骤3):主成分分析确定特征向量;Step 3): Principal component analysis determines the feature vector;步骤4):特征向量可视化,确定品种来源。Step 4): Visualize the feature vector and determine the source of the variety.
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