WO2019047074A1 - 用于水稻基因分型的snp分子标记组合及其应用 - Google Patents

用于水稻基因分型的snp分子标记组合及其应用 Download PDF

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WO2019047074A1
WO2019047074A1 PCT/CN2017/100768 CN2017100768W WO2019047074A1 WO 2019047074 A1 WO2019047074 A1 WO 2019047074A1 CN 2017100768 W CN2017100768 W CN 2017100768W WO 2019047074 A1 WO2019047074 A1 WO 2019047074A1
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snp
rice
molecular marker
snp molecular
chip
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PCT/CN2017/100768
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French (fr)
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黎志康
王冰冰
王文生
徐建龙
傅彬英
王佳
高用明
许娜
熊艳文
张帆
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中国农业科学院作物科学研究所
华智水稻生物技术有限公司
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Priority to CN201780006971.9A priority Critical patent/CN109196123B/zh
Priority to PCT/CN2017/100768 priority patent/WO2019047074A1/zh
Publication of WO2019047074A1 publication Critical patent/WO2019047074A1/zh

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    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/156—Polymorphic or mutational markers

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  • the present invention relates to the fields of genomics, molecular biology, bioinformatics and molecular plant breeding, and in particular to SNP molecular marker combinations for rice genotyping and their use.
  • Molecular marker technologies are important tools in molecular breeding.
  • Traditional molecular marker technologies such as RFLP (Restriction Fragment Length Polymorphism) and SSR (Simple Sequence Repeat) techniques, have played an important role in functional genomics research.
  • the traditional molecular marker technology has many limitations, such as low throughput, small quantity, and cumbersome operation process, which cannot meet the needs of large-scale commercial breeding.
  • high-throughput molecular marker technology platforms include: second-generation sequencing technology, gene chip technology, and a single SNP marker detection system, such as Taqman and KASP markers.
  • Another object of the present invention is to provide a rice whole genome breeding chip.
  • the present invention provides a SNP molecular marker for rice genotyping, the nucleotide sequence of which is shown in any one of SEQ ID NOs: 1-56660, and the base 36 of each sequence The base is a SNP mutation site.
  • the invention then provides a SNP molecular marker combination for rice genotyping, the SNP molecular marker combination being any two or more combinations of the above SNP molecular markers.
  • the combination consists of 56606 SNP markers.
  • the invention utilizes second-generation DNA sequencing technology to perform genome-wide resequencing of 3024 rice samples from 89 countries and regions in the world, and obtains 17T sequencing data, the minimum sequencing depth is 4 ⁇ , and the sample of 10 ⁇ is 2322. The average sequencing depth is 14 ⁇ .
  • BWA soft was used for comparison, the average coverage was 94%, and the average alignment rate was 92.5%.
  • SNP detection was performed on 3024 samples using the GATK process (Fig. 1) to obtain 18.9M high quality SNPs and Indels, and 3024 rice phylogenetic trees were constructed (Fig.
  • Group1 421 Share
  • Group2 454 copies
  • Group3 250 copies
  • Group4 331 copies
  • Group5 310 copies
  • Group6 221 copies
  • Group7 223 copies
  • Group8 145 copies
  • Group9 266 copies
  • Group10 17.1 copies
  • Group11 101 copies
  • Group_Africa_cultivation 5 copies
  • Group_aro_G10_Ind 30 copies
  • Group_aro_G10_Jap 36 copies
  • Group_aus_aro 46 copies
  • Group_near7 7 copies
  • Group_near8 7 copies.
  • SNP polymorphisms based on 500 typical materials of 3K rice (rice functional genomic breeding database (RFGB): 3K rice SNP and InDel sub-database), and selected representative 192 rice varieties for high quality SNPs Further screening, 56606 core SNP loci were selected, and cluster analysis of 192 rice materials showed that the genotypic information of only 56606 SNP loci was sufficient to distinguish the above 192 rice germplasm resources. .
  • RFGB rice functional genomic breeding database
  • the invention also provides the use of the SNP molecular marker combination in preparing a rice whole genome breeding chip.
  • the present invention also provides a rice whole genome breeding chip (Rice 56K chip) comprising 56606 SNP sites having the nucleotide sequence set forth in SEQ ID NO: 1-56660.
  • the invention also provides the SNP molecular marker/combination or the application of the rice 56K chip in rice variety identification.
  • the invention also provides the SNP molecular marker/combination or the use of the rice 56K chip in detecting rice breeding materials.
  • the invention also provides the use of the SNP molecular marker/combination or the rice 56K chip in rice genome-wide association analysis.
  • the invention also provides the SNP molecular marker/combination or the application of the rice 56K chip in rice molecular marker-assisted breeding.
  • the invention also provides the SNP molecular marker/combination or the application of the rice 56K chip in genetic fingerprint analysis of rice germplasm resources.
  • the invention also provides the use of the SNP molecular marker/combination or the rice 56K chip for genotyping identification of rice hybrid progeny.
  • the present invention Compared with other molecular marker detection systems, the present invention has the following advantages and effects:
  • 1 is a basic flow chart of screening of a rice 56K chip of the present invention.
  • Figure 2 is a sputum type of 192 test samples of the present invention.
  • Figure 3 is a diagram showing the geographical origin distribution of 192 test samples of the present invention.
  • Figure 4 is a distribution and source of a rice 56K chip of the present invention.
  • Figure 5 is a distribution of SNP sites on the chromosome of the present invention (the number of SNP probes in the 10 Kb interval).
  • Figure 6 is a diagram showing the number distribution of SNP sites on 12 chromosomes of the present invention.
  • Figure 7 is a SNP efficacy annotation of the invention (using the snpeff tool).
  • FIG. 8 is a cluster analysis diagram of 192 test samples of the present invention; wherein A: cluster analysis is performed using 1100K SNP through QC; B: cluster analysis is performed using the selected 53K SNP.
  • the DNA sequences of 24 random samples were added to the 6 bp linker sequences, respectively, and mixed together to construct a mixed index library, which was used to distinguish the DNA sequence of each sample.
  • the constructed library was PE90 sequenced on a HiSeq2000 machine with at least 6 lanes per library to ensure that enough data was available for each sample. The data is then split according to the linker sequence.
  • the alignment parameter is "aln-m 10000-o 1-e 10-t 4", the other default.
  • the weight comparison is performed using the IndelRealigner command of the GATK software package, and the BaseRecalibrator performs base quality value calibration.
  • step 2 Based on the statistical results of step 2, the low-mass sites and the deletion sites are classified as missing data, and the polymorphic sites with missing data ⁇ 0.2 and MAF>0.05 are selected as the polymorphic sites of indica rice. There were 2910585 SNP polymorphisms in indica rice.
  • step 3 Based on the statistical results of step 3, the low-mass sites and the deletion sites were classified as missing data, and the polymorphic sites with missing data ⁇ 0.2 and MAF>0.05 were selected as the polymorphic sites of indica rice.
  • the 250bp (501bp 250+1+250) sequences upstream and downstream of the indica polymorphic loci were sequenced and mapped to the Nipponbare genome.
  • the unpmap locus was selected as the indica-specific (uniq) SNP polymorphism locus.
  • the number of sites is 4107.
  • Affymetrix's chip-based genotyping products provide a complete solution for a wide range of applications from genome-wide analysis to routine screening with the highest accuracy and repeatability, simple process and lowest cost.
  • the GeneTitan platform can easily customize the genetic SNP typing chips for different seeds, ranging from 1500 SNP/sample to 670,000 SNP/samples, which can be customized flexibly for different Research areas.
  • 500SNP/sample specifications are suitable for seed screening, transgenic identification, etc.
  • 5,000 SNP/sample specifications are suitable for molecular breeding and identification of good traits
  • 50,000 SNP/sample specifications are suitable for gene localization and confirmation of trait loci
  • 500,000 SNP/samples to 670,000 SNPs/samples are suitable for the localization of characteristic sites and the discovery of novel trait-related genes.
  • Affymetrix uses lithography technology, which uses laser grating to ensure the uniformity of all the sites of each similar chip, to avoid chip data loss caused by batch difference, which is unique in the gene chip platform.
  • the basic process for screening rice 56K chips is as follows:
  • the role of the Screening chip 1 to find the highest quality SNP site; 2 to screen out the false positive and singlet sites obtained by sequencing; 3 to estimate the MAF / LD value of the SNP site, etc., to find higher heritability
  • the location makes the final design of the chip more cost-effective; 4 only 192 samples to scan in the early stage, later can do more samples at the same cost; 5 get results faster, saving time and cost.
  • a representative 192 rice varieties were selected during the screening process, including 133 indica types, 47 indica types, 5 Aus/boro types, and 3 Basmati and intermediate types (Figure 2).
  • the Axiom_Rice3K55 custom project consists of 4 different designs, 2,467,017 probe sets, passed There were 1,142,678 (46.3%) probe groups detected by affy, of which 811 was the 931-1 specific reference genome-derived SNP locus, and the others were Nipponbare as the SNP locus of the reference genome (Table 1).
  • the four different designs of the Affy 3K2MAX chip contained approximately 2500K SNP sites, of which 192 samples eventually had a total of 178 samples that passed the QC test in all four designs (Table 2).
  • the four different designs of the Affy 3K2MAX chip contain approximately 2500K SNP sites, and approximately 1100K SNP sites are controlled by affymetrix SNP quality. The goal was to screen the 56K probes that met the criteria from all of the recommended SNP detection probes in the four chips.
  • 3SNP Annotation Information gives weights based on the genomic location of the SNP:
  • the distribution of the selected 56K chips on 12 chromosomes was statistically found.
  • the 56K SNPs were evenly distributed on 12 chromosomes of rice.
  • the average distance between SNPs on the chromosome was 6.84K.
  • the median value was 5.3K, the number of SNP loci designed near important agronomic loci is more (Fig. 5).
  • the number of selected 56K chips on 12 chromosomes was counted. It was found that 56K SNPs had more sites on the first and third chromosomes, respectively, 6833 and 6082; in the 9th and 10th The number on the 12 chromosomes is small, 3148, 3214, and 3329, respectively (Fig. 6).
  • the SNP molecular marker combination of the invention can be used for molecular marker fingerprint analysis of rice cultivars, genotypic identification of progeny of hybrid populations, identification of cultivar authenticity, analysis and screening of genetic background of breeding materials, and association of agronomic traits. Analysis has broad application prospects.

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Abstract

提供了用于水稻基因分型的SNP分子标记组合，由56606个SNP标记组成，所述SNP标记的编号分别为SNP1～SNP56606，它们的核苷酸序列分别如SEQ ID NO:1-56606所示。所述SNP分子标记组合可以应用于水稻品种资源的分子标记指纹分析、杂交群体后代的基因型鉴定、对品种真实性的鉴定、育种材料遗传背景的分析和筛选和农艺性状的关联分析。

Description

用于水稻基因分型的SNP分子标记组合及其应用 技术领域
本发明涉及基因组学、分子生物学、生物信息学和分子植物育种领域，具体地说，涉及用于水稻基因分型的SNP分子标记组合及其应用。
背景技术
分子标记技术(Molecular marker technologies)是分子育种中的重要工具。传统分子标记技术，如RFLP(Restriction Fragment Length Polymorphism，限制性片段长度多态性)和SSR(Simple Sequence Repeat，简单序列重复)技术曾在功能基因组研究中发挥着重要作用。但是，传统的分子标记技术存在许多局限性，如通量低、数量少、操作过程繁琐，不能满足大规模商业化育种的需求。为了对目标基因进行精确控制，对遗传背景进行有效选择，对育种品种进行准确分析和鉴定，需要开发和利用高通量分子标记技术。目前，高通量分子标记技术平台主要包括：第二代测序技术，基因芯片技术，以及单一SNP标记检测系统，例如Taqman和KASP标记。
发明内容
本发明的目的是提供用于水稻基因分型的SNP分子标记组合及其应用。
本发明的另一目的是提供一种水稻全基因组育种芯片。
为了实现本发明目的，本发明提供用于水稻基因分型的SNP分子标记，所述SNP分子标记的核苷酸序列如SEQ ID NO:1-56606任一所示，每条序列第36位碱基为SNP突变位点。
继而本发明提供用于水稻基因分型的SNP分子标记组合，所述SNP分子标记组合为上述SNP分子标记中的任意两个或多个组合。优选该组合由56606个SNP标记组成。
本发明利用二代DNA测序技术，对来自全球89个国家和地区的3024份水稻样本进行了全基因组重测序，得到17T的测序数据，最低测序深度为4×，达到10×的样本为2322份，平均测序深度为14×。以日本晴MSU7.0为参考序列，利用BWA软进行比对，平均覆盖度为94％，平均比对率为92.5％。使用GATK流程(图1)对3024份样品进行SNP检测，得到18.9M高质量的SNP及Indel，构建了3024份水稻的系统发育树(图2)，将水稻分为17个group：Group1(421份)，Group2(454份)，Group3(250份)，Group4(331份)，Group5(310份)，Group6(221份)， Group7(223份)，Group8(145份)，Group9(266份)，Group10(171份)，Group11(101份)，Group_Africa_cultivation(5份)，Group_aro_G10_Ind(30份)，Group_aro_G10_Jap(36份)，Group_aus_aro(46份)，Group_near7(7份)，Group_near8(7份)。基于3K水稻500份典型材料的SNP多态性位点筛选(水稻功能基因组育种数据库(RFGB):3K水稻SNP与InDel子数据库)，并选择了有代表性的192个水稻品种对高质量SNP位点做进一步筛选，从中挑选出56606个核心SNP位点，对192份水稻材料进行聚类分析的结果表明，仅用这56606个SNP位点的基因型信息足以区分出上述192份水稻种质资源。
本发明还提供所述SNP分子标记组合在制备水稻全基因组育种芯片中的应用。
本发明还提供水稻全基因组育种芯片(水稻56K芯片)，包含56606个SNP位点，其具有SEQ ID NO:1-56606所示的核苷酸序列。
本发明还提供所述SNP分子标记/组合或所述水稻56K芯片在水稻品种鉴定中的应用。
本发明还提供所述SNP分子标记/组合或所述水稻56K芯片在检测水稻育种材料中的应用。
本发明还提供所述SNP分子标记/组合或所述水稻56K芯片在水稻全基因组关联分析中的应用。
本发明还提供所述SNP分子标记/组合或所述水稻56K芯片在水稻分子标记辅助育种中的应用。
本发明还提供所述SNP分子标记/组合或所述水稻56K芯片在水稻种质资源基因指纹分析中的应用。
本发明还提供所述SNP分子标记/组合或所述水稻56K芯片在水稻杂交后代基因型鉴定中的应用。
与其他分子标记检测系统相比，本发明具有以下优点和效果：
(一)与传统分子标记如SSR标记相比，具有通量高、单个标记数据成本低等优势。
(二)基因分型数据准确可靠，遗传稳定性和重复性好。
(三)容易实现自动化检测，减少人力成本。
(四)可以满足多次基因分型数据结果的整合。
附图说明
图1为本发明水稻56K芯片的筛选基本流程图。
图2为本发明192个测试样品的籼粳类型。
图3为本发明192个测试样品的地理来源分布图。
图4为本发明水稻56K芯片的分布和来源。
图5为本发明SNP位点在染色体上的分布(10Kb区间内SNP探针的数目)。
图6为本发明SNP位点在12条染色体上的数目分布。
图7为本发明SNP功效注释(采用snpeff工具)。
图8为本发明192个测试样品的聚类分析图；其中，A:用通过QC的1100K SNP进行聚类分析；B:用筛选出的53K SNP进行聚类分析。
具体实施方式
以下实施例用于说明本发明，但不用来限制本发明的范围。若未特别指明，实施例均按照常规实验条件，如Sambrook等分子克隆实验手册(Sambrook J&Russell DW，Molecular Cloning:a Laboratory Manual，2001)，或按照制造厂商说明书建议的条件。
实施例1用于水稻基因分型的SNP分子标记组合的开发
一、3024份水稻种质资源的重测序和SNP位点的获得
1、3024份水稻种质资源的文库构建和测序：
将24个随机样本的DNA序列分别加上6个bp的接头序列，并且混合在一起构建混合index文库，接头序列用来区分每个样本的DNA序列。构建好的文库在HiSeq2000机器上进行PE90测序，每个文库至少测6个lane，以确保每个样本可以得到足够的数据。然后根据接头序列拆分数据，每个样本可以拆分后的read读长是83bp(83＝90-6-1，1是连接碱基“T”)。最后去掉被接头污染的reads和低质量的reads(碱基质量值≤5)，得到高质量的clean reads.
2、比对和SNP/Indel检测
2.1使用BWA软件将clean reads比对到日本晴(IRGSP-1.0)基因组上得到sam文件，比对参数为“aln-m 10000-o 1-e 10-t 4”，其他默认。使用samtools将每个样本的sam文件合并，加上index得到bam文件。使用Picard软件对bam文件进行排序，去除没有比对上的reads，同时标记重复的reads。使用GATK软件包的IndelRealigner命令进行重比对，BaseRecalibrator进行碱基质量值校准。
2.2使用GATK软件包的UnifiedGenotyper命令检测每个样本的基因型和Indel，使用参数为：-stand_call_conf 50.0，-stand_emit_conf 10.0，-dcov 50；使用如下参数对数据进行过滤：Mapping_quality>20，Variant quality>50，Read supported for every base>2。
2.3使用GATK软件包的UnifiedGenotyper命令检测群体SNP和Indel，使用参 数为：-stand_call_conf 50.0，-stand_emit_conf 30.0，-dcov 50；进一步使用Mapping_quality>20，Depth>2和MAF>0.001对群体SNP数据进行过滤，最后得到18.9M高质量的SNP及Indel。
利用二代DNA测序技术对来自全球89个国家和地区的3024份水稻样本进行了全基因组重测序，得到17T的测序数据，最低测序深度为4×，达到10×的样本为2322份，平均测序深度14×。以日本晴MSU7.0为参考序列，BWA软进行比对，平均覆盖度为94％，平均比对率92.5％。使用GATK流程对3024份样品进行SNP检测，得到18.9M SNP位点，构建了3024份水稻的系统发育树，将水稻分为17个group：Group1(421份)，Group2(454份)，Group3(250份)，Group4(331份)，Group5(310份)，Group6(221份)，Group7(223份)，Group8(145份)，Group9(266份)，Group10(171份)，Group11(101份)，Group_Africa_cultivation(5份)，Group_aro_G10_Ind(30份)，Group_aro_G10_Jap(36份)，Group_aus_aro(46份)，Group_near7(7份)，Group_near8(7份)。
二、SNP位点的初步筛选
基于3K水稻500份典型材料的SNP多态性位点筛选(水稻功能基因组育种数据库(RFGB):3K水稻SNP与InDel子数据库)，设计的标准与条件如下：
1、基于3K水稻的遗传背景和进化树信息，挑选500份典型材料来代表水稻群体的多态性。
2、以粳稻品种Nipponbare为参考序列，根据每个个体的VCF文件，计算每个位点的allele frequency，低质量位点和缺失位点。对于SNP位点，要求Variant quality>＝50，mapping quality>＝20；2<＝read depth<＝200；genotype quality>＝20；对于genotype位点，要求reference allele quality>＝30；mapping quality>＝20。
3、以籼稻品种9311为参考序列，按照步骤2中的条件，同样计算每个位点的allele frequency，低质量位点和缺失位点。
4、基于步骤2的统计结果，把低质量位点和缺失位点都归为missing data，选择missing data<0.2，MAF>0.05的多态性位点作为粳稻的多态性位点，共获得粳稻SNP多态性位点2910585个。
5、基于步骤3的统计结果，把低质量位点和缺失位点都归为missing data，选择missing data<0.2，MAF>0.05的多态性位点作为籼稻的多态性位点。提取籼稻多态性位点上下游250bp(共501bp＝250+1+250)序列比对到Nipponbare基因组上，挑选unpmap的位点作为籼稻特有的(uniq)SNP多态性位点，共获得这样的位点4107个。
6、提取SNP位点上下游35bp的侧翼序列用来设计芯片的探针，SNP位点保 留Major和minor碱基型。
共获得高质量的2.9MSNP多态性位点信息，以粳稻的遗传背景为主，同时加入了籼稻特有的多态性位点。
三、Affymetrix基因分型芯片的筛选
Affymetrix基于芯片的基因分型产品为从全基因组分析到常规筛查的各种应用提供了完整的解决方案，且准确性和重复性最高，流程简单，成本最低。
Affymetrix公司的GeneTitan基因芯片的用途和独特优势主要体现在：
在SNP领域(单核苷酸多态性)分析领域，GeneTitan平台可以方便地定制不同种子的基因SNP分型芯片，数目从1500SNP/样品，到67万SNP/样品均可以灵活定制，适合不同的研究领域。例如500SNP/样品的规格适合种子的筛选，转基因的鉴定等应用；5,000SNP/样品的规格适合分子育种以及优良性状的鉴定；50,000SNP/样品的规格适合基因的定位和性状位点的确认；500,000SNP/样品到67万SNP/样品适合特点位点的定位以及新型性状相关基因的发现。综上所述，各种规格的基因芯片有不同的应用领域、终端客户和市场，而Affymetrix公司的GeneTitan平台都可按照上述规格要求进行芯片的定制。并且Affymetrix采用的是光刻技术，即使用激光光栅确保每张同类芯片的所有位点的均一性，避免批间差造成芯片数据丢失，这在基因芯片平台方面是独一无二的。
水稻56K芯片的筛选基本流程如下：
根据前期从3K SNP中筛选获得的2.9MSNP位点，经过初步的筛选，获得2.5M的SNP位点用于前期的screening，选择有代表性的192个水稻品种对这2.5M的位点进行筛选，以获得高质量的SNP位点(图1)。
Screening芯片的作用：①找出最高质量的SNP位点；②筛除测序得来的假阳性和单态性的位点；③估算SNP位点的MAF/LD值等，找出更高遗传力的位点，使最终设计的芯片性价比更高；④前期只需192个样本做扫描，后期可以在同样的成本下做更多样本；⑤更快地得到结果，节约时间和成本。
四、Screening所用192个水稻样品的基本信息
在芯片screening过程中选择了有代表性的192个水稻品种，其中籼稻类型的133个，粳稻类型的47个，Aus/boro类型的5个，Basmati和中间类型各3个(图2)。从地理分布来看：192份材料来自于全球33个国家，主要以来源于中国的品种为主，来自于东南亚国家的品种次之，同时兼顾美洲、非洲、欧洲和大洋洲(图3)。来自于中国的品种中包括大面积推广品种、杂交稻亲本、分子育种亲本和微核心种质等。
五、192个水稻样品的Screening结果
Axiom_Rice3K55定制项目共包含4种不同的设计，2,467,017个探针组，通过 affy检测的探针组有1,142,678个(46.3％)，其中811为9311特异参考基因组来源SNP位点，其它均为日本晴作为参考基因组的SNP位点(表1)。
表1Affy四张芯片上探针数量及通过质量控制情况
类型 探针组数 通过质量控制
A 616595 294640
B 617004 283317
C 616742 289452
D 616676 275269
总计 2467017 1142678
Affy 3K2MAX芯片的4种不同的设计共包含约2500K SNP位点，其中192个样品最终共有178个样品在所有4种设计中都通过了QC检测(表2)。
表2Affy四张芯片上192个样品通过质量控制情况
Figure PCTCN2017100768-appb-000001
六、水稻56K芯片的最终筛选和SNP位点的确定
Affy 3K2MAX芯片的4种不同的设计共包含约2500K SNP位点，约1100K SNP位点通过affymetrix SNP质量控制。目标是从这4张芯片中所有的推荐SNP检测探针中筛选满足条件的56K探针。
1、筛选标准
1)已验证或公开的SNP位点
①华智实验室验证过的SNP位点
②其它公开数据/芯片中的SNP位点
③已克隆水稻基因(图位克隆、正向遗传学、反向遗传学等手段)的SNP
位点
④来源于水稻9311的SNP位点
2)其它通过质量控制的SNP位点
①创建打分系统，对所有通过质量控制的SNP进行综合评分：
a)碱基突变类型
b)PIC值(位点信息含量)
c)SNP注释信息
②LD block分析，去除冗余SNP
③加入其它SNP，使整体SNP位点在基因组均匀分布
2、详细筛选过程
1)已验证或公开的SNP位点
①华智实验室验证的SNP标记(3.1K)
a)2021通过affy质量测试
b)1085未被测试或未通过测试，加到最终芯片设计中。
②其它公开数据/芯片中的SNP位点
a)公开SNP数据集1:3000个位点中2161通过affy测试
b)公开SNP数据集2:6000个位点中3506通过affy测试
c)公开SNP数据集3:9000个位点中6251通过affy测试
以上数据合并后，共计获得10790个已验证或公开的SNP位点，这些位点都将入选芯片设计最终方案。
2)其它通过质量控制的SNP位点
对于其它通过质量控制的SNP位点，我们创建了一个打分系统，对所有通过质量控制的SNP进行综合评分：
①碱基突变类型
a)A/G；A/C；T/G；T/C之间的突变(权重20)；
b)A/T；G/C突变(权重0)，因为A/T,C/G使用相同的荧光信号，所以affy探针杂交如果要区分A/T；G/C之间的突变必须要放置2个探针组，因此其权重不同。
②PIC值(多态性信息含量，权重40)。
虽然检测样品192份，但4种芯片质检都通过的样品只有179个，最终根据这179个样品计算SNP的PIC值。该值类似于稀有等位基因频率MAF。
③SNP注释信息--SNP注释根据SNP所处的基因组位置给予权重：
基因间区(2)
内含子(3)
启动子(15)
5`-UTR(15)
3`-UTR(15)
如果SNP位于基因外显子区:
同义突变(4)
非同义突变(10)
无义突变(20)。
3、重要农艺基因SNP位点
我们筛选了近60个重要农艺性状基因，在其上下游2k与基因区选择得分最高20个SNP，不够20的则全部选择。按照该标准最终入选SNP位点940个(表3)。
表3重要农艺性状基因SNP探针数量
基因名 SNP数量 基因名 SNP数量
AG1 20 pi1 20
BADH2 20 pi2&9 20
Bph14 20 Pi21 20
Bph15 20 pi5 20
Bph3 20 PPKL1 20
Bphi008a 8 qLTG3-1 14
ChALK5 20 Rf17|RMS 8
CKX2/Gn1a 20 Rf1a|Rf5 20
COLD1 20 Rf1b 20
DEP1 20 Rf2 20
Ghd7 1 RF2a|OsbZIP75 20
Ghd7.1|Hd2|OsPRR37|DTH7 20 RF2b|OsbZIP30 20
GS3 20 Rf4 16
GS5 20 S27 2
GW2 20 S28 2
GW7|GL7|SLG7 20 S5(ORF3) 2
MOC1 20 S5(ORF5) 20
NRAT1 5 SaM 20
OsAPP6 15 sd1|GA20ox2 20
OsglHAT1 20 SKC1 20
OsHMA3 11 SLR1|OsGAI 17
SPL14 20 Xa1 18
SPL16 20 XA10 4
STV11 5 xa21 20
Sub1B 20 Xa23 4
SUB1C 28 Xa25 20
TGW6 20 Xa5 20
TT1 20 Waxy 20
4、已克隆的功能基因SNP位点
我们收集了通过图位克隆、正向遗传学和反向遗传学等手段克隆发表的基因约2372个。从每个基因(包括上下游2k)的SNP位点中选择得分最高的2个SNP位点，总计获得4729个SNP位点。
5、来源于9311的SNP位点
这些位点存在于最初的设计中，总计811个SNP通过质量控制，全部入选。
6、LD block区间内标签SNP筛选
1)为去除冗余SNP，我们用178份检测材料分型结果对通过质量检测的SNP 探针进行了LD block计算，共获得1,012,772个与其相邻SNP存在LD的SNP位点。如果LD block区间小于10kb，我们将在其内部选择得分最高的SNP作为标签SNP；如果LD block大于10k，将在其内部每10kb选择一个得分最高的SNP作为这个区间的标签SNP。按照这种方法，总共选择了43005个位于LD block中的SNP位点。
2)通过分析每10Kb区间内SNP分布，我们发现有2312个区间>2个SNP。为了平衡芯片位点总量、基因组平均分布、LD block区间信息。我们将在2312个区间内每5kb选择一个得分高的SNP位点作为代表。所以最终获得LD区间内36510个SNP位点。
7、基因组均匀分布SNP筛选
为确保SNP芯片设计在水稻全基因组范围内均匀分布，从128,620个未划入任何LD block的SNP位点进行了补缺筛选。通过将染色体分成10k的区间，如果该区域内不含有任何1-5步筛选出的SNP，则在该区域内选择得分最高的一个非LD block的SNP位点。这样可以保证每10Kb区间将会有至少一个SNP入选(前提是1M SNP库在该区间有SNP的存在)。按照该标准共补缺选择1736个SNP位点。
七、水稻56K芯片设计结果
1、56K芯片SNP位点的来源分布
通过以上各种方法，我们总共筛选到55,312个SNP位点，各步骤所贡献的SNP位点及比例情况如图4所示。
2、56K芯片SNP位点的染色体分布
对筛选到的56K芯片在12条染色体上的分布进行了统计，发现56K的SNP位点均匀的分布在水稻12条染色体上，SNP位点在染色体上间距平均值为6.84K，中位值为5.3K，重要农艺基因位点附近设计的SNP位点数较多(图5)。
对筛选到的56K芯片在12条染色体上的数目进行了统计，发现56K的SNP位点在第一和第三染色体上的位点较多，分别为6833个和6082个；在第9、10和12染色体上的数目较少，分别为3148、3214和3329个(图6)。
3、56K芯片SNP位点在不同基因区域的分布见图4。采用snpeff工具对SNP进行功效注释，结果见图7。
4、筛选前后SNP位点聚类分析
用筛选前(1.1M)和筛选后(56K)的SNP位点对192个测试样品进行聚类分析，发现筛选前后得到的结果非常相似。选择K＝5，均可将测试样品分为5个亚群，2个粳稻(温带和热带)和3个籼稻群。表明筛选出的56K的SNP位点具有较高的代表性(图8)。
虽然，上文中已经用一般性说明及具体实施方案对本发明作了详尽的描述，但在本发明基础上，可以对之作一些修改或改进，这对本领域技术人员而言是显 而易见的。因此，在不偏离本发明精神的基础上所做的这些修改或改进，均属于本发明要求保护的范围。
工业实用性
利用本发明的SNP分子标记组合可以对水稻品种资源进行分子标记指纹分析、对杂交群体后代进行基因型鉴定、对品种真实性进行鉴定、对育种材料遗传背景进行分析和筛选、对农艺性状进行关联分析，具有广阔的应用前景。

Claims (10)

  1. 用于水稻基因分型的SNP分子标记，其特征在于，所述SNP分子标记的核苷酸序列如SEQ ID NO:1-56606任一所示，每条序列第36位碱基为SNP突变位点。
  2. 用于水稻基因分型的SNP分子标记组合，其特征在于，所述SNP分子标记组合为权利要求1所述SNP分子标记中的任意两个或多个组合。
  3. 权利要求2所述SNP分子标记组合在制备水稻全基因组育种芯片中的应用。
  4. 水稻全基因组育种芯片，其特征在于，包含56606个SNP位点，其具有SEQ ID NO:1-56606所示的核苷酸序列。
  5. 权利要求1所述SNP分子标记、权利要求2所述SNP分子标记组合或权利要求4所述芯片在水稻品种鉴定中的应用。
  6. 权利要求1所述SNP分子标记、权利要求2所述SNP分子标记组合或权利要求4所述芯片在检测水稻育种材料中的应用。
  7. 权利要求1所述SNP分子标记、权利要求2所述SNP分子标记组合或权利要求4所述芯片在水稻全基因组关联分析中的应用。
  8. 权利要求1所述SNP分子标记、权利要求2所述SNP分子标记组合或权利要求4所述芯片在水稻分子标记辅助育种中的应用。
  9. 权利要求1所述SNP分子标记、权利要求2所述SNP分子标记组合或权利要求4所述芯片在水稻种质资源基因指纹分析中的应用。
  10. 权利要求1所述SNP分子标记、权利要求2所述SNP分子标记组合或权利要求4所述芯片在水稻杂交后代基因型鉴定中的应用。
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