WO2020082314A1 - 水稻绿色基因芯片与应用 - Google Patents

水稻绿色基因芯片与应用 Download PDF

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WO2020082314A1
WO2020082314A1 PCT/CN2018/111983 CN2018111983W WO2020082314A1 WO 2020082314 A1 WO2020082314 A1 WO 2020082314A1 CN 2018111983 W CN2018111983 W CN 2018111983W WO 2020082314 A1 WO2020082314 A1 WO 2020082314A1
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chip
snp
rice
gene
sites
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陆青
周发松
邱树青
雷昉
谢为博
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武汉双绿源创芯科技研究院有限公司
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Priority to PCT/CN2018/111983 priority Critical patent/WO2020082314A1/zh
Priority to CN201880083605.8A priority patent/CN111684113B/zh
Publication of WO2020082314A1 publication Critical patent/WO2020082314A1/zh

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  • the present invention relates to the fields of molecular biology, genomics, bioinformatics, and plant molecular breeding, and in particular, to green rice gene chips and applications.
  • SNP markers are based on DNA sequencing (Davey et al., Genome-wide genetic marker discovery and generic typing using next-generation sequencing. Nat Rev Genet. 12: 499-510.), Since the advent of the 454 sequencer in 2005, the second-generation sequencing technology has been continuously improved, the genome sequencing efficiency has been greatly improved, the sequencing cost has dropped significantly, and the complete genome sequence of a large number of species has been completed, which has greatly advanced the progress of functional genome research.
  • Rice is a model plant for the study of monocotyledonous plants, and it is also the most important food crop in the world. It re-sequences different varieties and uses the SNP markers found by resequencing to construct a high-density rice haplotype map (HapMap).
  • Genome-wide association mapping (GWAS) performs association analysis on important agronomic traits, determines candidate gene loci related to important agronomic traits, and establishes a set of efficient, fast, mature and stable genotypes with low cost and high throughput Identification methods (Huang et al., Genome-wide associations of 14 agronomic traits in rice landraces. Nat Genet. 2010, 42: 961-967) are the priority directions for molecular biology researchers.
  • the object of the present invention is to provide a rice green gene chip, which includes a total of 44,263 polynucleotides shown in SEQ ID No. 1 to 44263.
  • Another object of the present invention is to provide the application of rice green gene chips.
  • the present invention adopts the following technical measures:
  • the application of the rice green gene chip includes using the SNP chip provided by the present invention to identify or locate functional genes of rice; using the SNP chip provided by the present invention to analyze rice genetic diversity; and using the SNP chip provided by the present invention to analyze rice varieties.
  • the present invention has the following advantages:
  • the invention has better variety representativeness than Rice6K and Rice60K of the same type of China Seed Group Co., Ltd. and 56K rice SNP chip of Huazhi Rice Biotechnology Co., Ltd.
  • the SNP loci of the Rice6K chip are identified and screened from the sequencing data of more than 520 rice local varieties.
  • the SNP loci on the Rice60K chip are derived from more than 730 rice varieties, and the 56K rice SNP chip is represented by 89 countries and regions around the world. 3024 rice genomic whole genome resequencing sequence information was excavated, and the SNP site of the GSR40K rice whole genome chip of the present invention was derived from the resequencing results of 4726 cultivated rice cultivars all over the world.
  • the present invention is further optimized, the ratio of excellent marks is greater, the indica-japonica differential marks are reduced, and the indica-indica and japonica-japonica marks are added to make the typing of different subgroups Effectiveness is more reasonable.
  • Fig. 1 is a schematic diagram of the distribution of all SNP sites on a whole genome genome of a rice whole genome breeding chip GSR40K.
  • FIG. 2 is a schematic diagram showing the frequency distribution of polymorphic SNP among indica rice, indica-japonica, and japonica rice at all sites of a rice genome-wide breeding chip GSR40K.
  • Figure 3 shows the results of genetic diversity analysis of 120 rice varieties using a rice-based whole-genome breeding chip GSR40K. Among them, a in Figure 3 is the whole genome distribution of the number of differential markers per 100 kb of Nipponbare / Minghui 63;
  • b is the statistics of the number of difference markers per 100kb of Nipponbare / Minghui 63;
  • c is the genome-wide distribution of 9311 / Basla differential markers per 100 kb;
  • d is the number of difference markers per 100 kb of 9311 / Balila.
  • the invention utilizes the resequencing results of 4726 rice varieties to identify 14,541,446 SNP sites and 2,855,580 InDel sites (http://ricevarmap.ncpgr.cn/v2/), and applies LD-KNN to imputation it to fill in the gaps After filtering out SNP sites with a missing value ratio greater than 30%, the selection steps for SNP sites are as follows:
  • Score3 is 0 when SNP is in the intergenic region; Score3 is 0.5 when SNP is in the promoter region; Score3 is 1 when SNP is in 5 ⁇ -UTR or 3 ⁇ -UTR; SNP is in the gene Score3 is 1 when the synonymous mutation is on the top; Score3 is 4 when the SNP is on the gene and is a nonsynonymous mutation; Score3 is 8 when the SNP is on the gene and is a large effect mutation.
  • Total score Score Score1 + Score2 + Score3.
  • All 44263 SNP sites are 1 to 44263 DNA sequences listed in the sequence table, and these sequences are submitted to Illumina company, and the SNP chip GSR40K is manufactured by Infinium chip manufacturing technology. The distribution of all SNP loci on the whole genome of GSR40K is shown in Figure 1. Overall, the whole genome is evenly distributed, and at the same time it is densely distributed in important functional gene regions, which can meet the genetic diversity analysis and genetic relationship analysis of rice germplasm resources. Functional gene identification and gene mapping of rice can meet the needs of authenticity identification of rice varieties and genetic background analysis of rice breeding materials.
  • the method for detecting rice samples using the GSRK40K rice genome breeding chip includes the following steps:
  • the comparative data is divided into seven groups, namely: indica (Ind) Jap (Jep), indica 1 (IndI) and indica 2 (IndII), temperate japonica rice (TeJ) and tropical japonica rice (TrJ), Inside Indica 1 group (IndI), Indica 2 group (IndII), temperate japonica rice group (TeJ), tropical japonica rice group (TrJ).
  • indica (Ind) Jap (Jep) indica 1
  • IndIII temperate japonica rice
  • TrJ tropical japonica rice
  • Table 2 temperate japonica rice group
  • the average number of polymorphic markers between indica and japonica populations is about 22,000, the average number of polymorphic markers between indica 1 and indica 2 is about 14,000, and the average number of polymorphic markers between temperate and tropical japonica subgroups is about 10,000. When the genetic background within the subgroup is very similar, the number of polymorphic markers still reaches an average of about 7000.
  • the Rice6K breeding chip contains 5636 SNP markers, and the number of polymorphic markers between indica and japonica, indica and indica rice and japonica and japonica rice is 2600, 1000 and 800 respectively, which is far lower than the GSR40K chip of the invention; Rice60K breeding chip 58290 SNP sites, the number of sites is much higher than the GSR40K chip, but the average number of polymorphic markers between indica and japonica rice, between indica and indica rice, and between japonica and japonica rice is about 19,000, 10000 and 8000, respectively. Lower than GSR40K.
  • GSR40K chip used in rice genetic background selection was used in rice genetic background selection:
  • the GSR40K chip was used to detect the parents of Nipponbare / Minghui 63 and 9311 / Ballila groups, Nipponbare, Minghui 63 and Ballila, to determine whether they can be used for background selection of the progeny groups of the above two hybrid combinations .
  • the strategy of molecular design breeding is to decompose the overall breeding goal into several unit goals, design and cultivate a batch of breeding material that meets the unit goal according to each unit, and finally combine the genes possessed by each unit material according to the overall goal to obtain compliance.
  • the overall target variety It is particularly important to analyze the existence of important functional genes in varieties.
  • the GSR40K chip can analyze the functional genes of important agronomic traits such as rice blast resistance, brown planthopper resistance, and bacterial blight resistance, and provide an information basis for design breeding.
  • the GSR40K chip was used to detect the rice variety IRBB-60 and analyze its resistance to rice blast, brown planthopper, and bacterial blight resistance. The results are as follows:

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Abstract

本发明公开了水稻绿色基因芯片与应用，芯片命名为GSR40K，是基于Illumina芯片制造技术制作的SNP芯片，包含44263个位点，SNP位点来源于全世界各地的4726份栽培稻品种的重测序结果，每张芯片同时检测24个样品，可用于种质资源遗传多样性分析和亲缘关系分析、功能基因鉴定和基因定位、品种真实性鉴定、育种材料遗传背景分析。

Description

水稻绿色基因芯片与应用 技术领域
本发明涉及分子生物学、基因组学、生物信息学及植物分子育种领域，具体地，涉及水稻绿色基因芯片与应用。
背景技术
SNP标记的开发是基于DNA测序基础上的(Davey等，Genome-wide genetic marker discovery and genotyping using next-generation sequencing.Nat Rev Genet.12:499-510.)，自从2005年454测序仪问世以来的十多年时间，二代测序技术不断完善，基因组测序效率大大提高，测序成本大幅度下降，大量物种的全基因组序列完成，极大地推进了功能基因组研究的进展。
水稻作为单子叶植物研究的模式植物，同时也是全球最重要的粮食作物，对不同的品种进行重测序，利用重测序发现的SNP标记，构建高密度的水稻单倍型图谱(HapMap)，利用全基因组关联分析(Genome-wide Association Mapping,GWAS)对重要农艺性状进行关联分析，确定重要农艺性状相关的候选基因位点，建立起一套高效快速、成熟稳定、成本低、通量高的基因型鉴定方法(Huang等，Genome-wide association studies of 14 agronomic traits in rice landraces.Nat Genet.2010,42:961-967)，是分子生物学研究人员优先考虑的方向。
目前多个作物物种中都开发出了SNP基因芯片，水稻的Illumina Infinium Rice6K(Yu等，A whole genome SNP array(RICE6K)for genomic breeding in rice.Plant Biotech J,2014,12:28-37)、Cornell_6K_Array_Infinium_Rice(Thomson等，Large-scale deployment of a rice 6K SNP array for genetics and breeding applications.Rice(N Y),2017,10:40)、Illumina GoldenGate(Parida等，SNPs in stress-responsive rice genes:validation,genotyping,functional relevance and population structure.BMC Genomics.2012,13:426-443；)、Affyme trix GeneChip Rice 44K(Zhao等，Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa.Nat Commun.2011,13:467)已经广泛的应用于种质资源筛选、品种真实性和纯度鉴定、育种材料遗传背景分析等工作；Ganal等(Alarge maize(Zea mays L.)SNP genotyping array:development and germplasm genotyping,and genetic mapping to compare with the B73reference genome.PLos One.2011,6:e28334)利用Illumina Infinium maize SNP50基因芯片对两个玉米重组自交系群体进行分析，获得了分别包含20913和14524个标记的高密度遗传连锁图；在大豆的驯化历史研究中，Affymetrix Axiom全基因组SNP芯片NJAU 355K SoySNP分析了105个野生和262个栽培品种，得出大豆栽培品种起源于中国的中部和北部的结论(Wang等，Development and application of a novel genome-wide SNP array reveals domestication history in soybean.Sci Rep.2016,6:20728-20737)；为构建小麦的高密度遗传连锁图，以小麦90KInfinium iSelec t SNP芯片对4个小麦群体进行了扫描，将29692个SNP标记定位到了6倍体小麦的21条染色体上(Wen等，A high-density consensus map of common wheat integrating four mapping populations scanned by the 90K SNP array.Front Plant Sci.2017,doi:10.3389/fpls.2017.01389)。
发明内容
本发明的目的在于提供了水稻绿色基因芯片，所述的芯片包括SEQ ID No.1～44263所示的共44263个多核苷酸。
本发明的另一个目的在于提供了水稻绿色基因芯片的应用。
为了达到上述目的，本发明采取以下技术措施：
申请人利用4726份水稻品种重测序结果，鉴定出14,541,446个SNP位点和2,855,580个InDel位点(http://ricevarmap.ncpgr.cn/v2/)，并应用LD-KNN对其进行imputation，补缺后过滤掉缺失值比例大于30％的SNP位点，最终筛选得到44263个多核苷酸，将这些序列提交给Illumina公司，利用Infinium芯片制造技术制作SNP芯片，命名为GSR40K；所述的44263个多核苷酸为SEQ ID NO.1～44263所示。
水稻绿色基因芯片的应用，包括利用本发明提供的SNP芯片进行水稻功能基因鉴定或定位；利用本发明提供的SNP芯片进行水稻遗传多样性分析；利用本发明提供的SNP芯片进行水稻品种分析。
与现有技术相比，本发明具有以下优点：
本发明与同类型的中国种子集团有限公司的Rice6K和Rice60K以及华智水稻生物技术有限公司的56K水稻SNP芯片相比具有更好的品种代表性。Rice6K芯片的SNP位点是从520多份水稻地方品种的测序数据中鉴定筛选出来的，Rice60K芯片上的SNP位点来源于730多份水稻品种，56K水稻SNP芯片从全球89个国家和地区代表性的3024份水稻品种全基因组重测序序列信息中挖掘出来，本发明的GSR40K水稻全基因组芯片SNP位点来源于全世界各地的4726份栽培稻品种的重测序结果。
本发明与上述10中的其它芯片相比：进行了进一步优选，优异标记的比例更多，减少了籼-粳差异标记，增加了籼-籼和粳-粳标记，使得不同亚群的分型效能更加合理。
附图说明
图1为一种水稻全基因组育种芯片GSR40K所有SNP位点在全基因组上的分布示意图。
图2为一种水稻全基因组育种芯片GSR40K所有位点籼稻之间、籼粳之间以及粳稻之间多态性SNP频率分布示意图。
图3为一种水稻全基因组育种芯片GSR40K对120个水稻品种进行遗传多样性分析的结果；其中图3中a为日本晴/明恢63每100kb差异标记数全基因组分布情况；
b为日本晴/明恢63每100kb差异标记数统计；
c为9311/Balila每100kb差异标记数全基因组分布情况；
d为9311/Balila每100kb差异标记数统计。
具体实施方式
本发明所述技术方案，如未特别说明，均为本领域的常规方案；所述试剂或材料，如未特别说明，均来源于商业渠道。
实施例1：
水稻全基因组育种芯片GSR40K的获得：
本发明利用4726份水稻品种重测序结果，鉴定出14,541,446个SNP位点和2,855,580个InDel位点(http://ricevarmap.ncpgr.cn/v2/)，并应用LD-KNN对其进行imputation，补缺后过滤掉缺失值比例大于30％的SNP位点，对SNP位点的选择步骤如下：
1)应用Illumina评分系统对所有SNP位点进行评分，过滤分值小于0.6的位点。
2)过滤掉剩余SNP中第二种(按照等位基因频率降序排列)等位基因频率≤5％的位点。
3)判断剩余SNP位点是否存在两种以上基因型，并过滤掉存在两种以上基因型且第三种(按照等位基因频率降序排列)等位基因频率大于2％的位点。
4)判断剩余每个SNP位点上下游50bp中是存在第二等位基因频率大于10％的的SNP/InDel位点，并过滤掉存在上述情况的SNP位点。
5)判断剩余SNP位点是否处于重复区间中，提取SNP上下游50bp序列，计算该段序列在水稻基因组中出现的次数(相似度≥80％)，过滤出现次数≥2的SNP位点。
6)将水稻全基因组每100kb分为一个区段，计算每区段内SNP两两间的相关系数,以相关系数(R 2≥0.60)为阈值将SNP分组。
7)构建一种综合评分策略，对剩余SNP效能进行评价，具体如下：
(1)分别计算SNP在All/All_Indica/All_Japonica/Aus/IndicaI/IndicaII/Indica_Intermediate/Temperate_Japonica/Tropical_Japonica/Japonica_Intermediate/GroupVI-Aromatic/Intermediate亚群中等位基因频率。构建打分策略Score1＝MAFAll*WAll+MAFAll_Ind*WAll_Ind+MAFAll_Jap*WAll_Jap+MAFIndI*WIndI+MAFIndII*WIndII+MAFInd_Int*WInd_Int+MAFTeJ*WTeJ+MAFTrJ*WTrJ+MAFJap_Int*WJap_Int。
按照每SNP illumina合成探针类型计算Score2＝TypeinfiniumI*0.5+TypeinfiniumII*25。
(2)按照SNP位置计算Score3：SNP位于基因间区时Score3为0；SNP位于启动子区域时，Score3为0.5；SNP位于5`-UTR或3`-UTR时，Score3为1；SNP位于基因上且为同义突变时，Score3为1；SNP位于基因上且为非同义突变时，Score3为4；SNP位于基因上且为大效应突变时，Score3为8。总分值Score＝Score1+Score2+Score3。
(3)按照每个SNP的Score值由大至小对12中每组SNP进行排序，依次选择组中分值最高SNP，进行合并，最终选择出44263个SNP位点。
所有44263个SNP位点为序列表所列的1～44263条DNA序列，将这些序列提交给Illumina公司，利用Infinium芯片制造技术制作SNP芯片GSR40K。GSR40K所有SNP位点在 全基因组上的分布如图1所示，总体上在全基因组均匀分布，同时在重要功能基因区域分布密集，能满足水稻种质资源遗传多样性分析和亲缘关系分析、满足水稻的功能基因鉴定和基因定位、满足水稻品种真实性鉴定和水稻育种材料遗传背景分析的需求。
实施例2：
利用GSRK40K水稻全基因组育种芯片检测水稻样品的方法，包括以下步骤：
1)水稻样品DNA的制备：根据检测需要利用天根生化科技(北京)有限公司的植物基因组DNA抽提试剂盒，按照试剂盒标准流程抽提不同组织、器官或个体的DNA，
2)水稻样品DNA的质量控制：用1％的琼脂糖凝胶电泳，检测基因组DNA的完整性；按照仪器使用说明，用Nanodrop2000分光光度计测定DNA的浓度，判断蛋白质和RNA的污染程度。
3)基因芯片检测：按照Illumina Infinium基因芯片检测标准流程操作。芯片扫描使用Illumina HiScan芯片扫描仪。
4)基因芯片数据分析：Illumina HiScan扫描结果用Genome Studio软件分析基因型，并用R语言编程获得基因型比较结果。
实施例3：
GSR40K芯片标记分型效果评估
533水稻种质资源(http://ricevarmap.ncpgr.cn/v1/cultivars_information/)中随机选取亚群(IndI 98份、IndII 105份、TeJ 91份、TrJ 44份)品种，利用GSR40K芯片进行分析，比较亚群内和亚群间芯片多态性标记比例。比较数据分为七组，分别为：籼(Ind)粳(Jep)间、籼1群(IndI)和籼2(IndII)群间、温带粳稻群(TeJ)和热带粳稻群(TrJ)间、籼1群内部(IndI)、籼2群(IndII)内部、温带粳稻群(TeJ)内部、热带粳稻群(TrJ)内部。每组随机选取10份共140份数据进行比较，结果见图2。籼粳群间平均多态性标记数约22000个，籼1和籼2平均多态性标记数约14000个，温带粳稻和热带粳稻亚群间平均多态性标记数约10000个，在温带粳稻亚群内部遗传背景极为相似的情况下，多态性标记数仍然达到平均约7000个。Rice6K育种芯片包含5636个SNP标记，其籼稻与粳稻、籼稻与籼稻已经粳稻与粳稻之间多态性标记数分别平均为2600、1000和800，远低于本发明的GSR40K芯片；Rice60K育种芯片包含58290个SNP位点，位点数远高于GSR40K芯片，但其籼稻与粳稻之间、籼稻与籼稻之间以及粳稻与粳稻之间多态性标记数分别平均约为19000、10000和8000个，均低于GSR40K。
实施例4：
GSR40K芯片应用于水稻遗传背景选择：
利用实施例2所述的方法，应用GSR40K芯片对日本晴/明恢63及9311/Ballila群体的 亲本日本晴、明恢63以及Ballila进行检测，确定是否可用于对上述两个杂交组合后代群体的背景选择。
分析结果显示日本晴/明恢63每1000kb平均差异标记数为56，9311/Balila每1000kb平均差异标记数为59，相当于约平均每20kb有一个可区分双亲的多态性标记，差异标记在全基因组上分布均匀，可有效满足分子育种中对背景进行精确选择的标记需求(图3)。
利用日本晴、明恢63和Ballila的测序数据，分析Rice6K和Rice60K芯片SNP位点在上述两个群体对应亲本之间的差异标记分布情况，发现Rice6K芯片SNP位点在日本晴/明恢63和9311/Ballila两个杂交组合亲本之间每1000kb的平均差异性标记数分别为7.5和8.0个，Rice60K芯片SNP位点在日本晴/明恢63和9311/Ballila两个杂交组合亲本之间每1000kb的平均差异性标记数分别为49.6和51.8个，均低于本发明的GSR40K芯片。
实施例5：
利用GSR40K芯片进行重要基因功能分析
分子设计育种的策略是将育种总体目标分解成若干个单元目标，根据每个单元设计并培育一批符合单元目标的育种材料，最后按照整体目标将各单元材料具备的基因组合在一起，获得符合总体目标的品种。解析品种中重要功能基因的存在情况尤为重要。
GSR40K芯片可解析品种抗稻瘟病、抗褐飞虱、抗白叶枯等重要农艺性状功能基因，为设计育种提供信息基础。
应用GSR40K芯片检测水稻品种IRBB-60，分析其抗稻瘟病、抗褐飞虱以及抗白叶枯基因情况，结果如下:
Figure PCTCN2018111983-appb-000001
Figure PCTCN2018111983-appb-000002
同时对上述基因进行Sanger测序，对比芯片分析与测序的结果，发现二者对功能基因的判断结果完全一致，即IRBB-60含有白叶枯抗性基因xa5，xa13，Xa21，说明GSR40K 芯片可有效进行重要功能基因等位基因的分析。

Claims (4)

  1. 一种水稻绿色基因芯片，所述的芯片包括SEQ ID No.1～44263所示的共44263个多核苷酸。
  2. 权利要求1所述的芯片在进行水稻功能基因鉴定或定位中的应用。
  3. 权利要求1所述的芯片在进行水稻遗传多样性分析中的应用。
  4. 权利要求1所述的芯片在进行水稻品种分析中的应用。
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