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作物学报 ›› 2022, Vol. 48 ›› Issue (7): 1813-1821.doi: 10.3724/SP.J.1006.2022.12047

• 研究简报 • 上一篇    下一篇

水稻产量相关性状的全基因组关联分析及候选基因筛选

杨飞1(), 张征锋2(), 南波1, 肖本泽1,*()   

  1. 1华中农业大学植物科学技术学院, 湖北武汉 430070
    2华中师范大学生命科学学院, 湖北武汉 430079
  • 收稿日期:2021-07-13 接受日期:2021-11-30 出版日期:2022-07-12 网络出版日期:2021-12-24
  • 通讯作者: 肖本泽
  • 作者简介:杨飞, E-mail: 1044708754@163.com
    张征锋, E-mail: zhengfeng@mail.ccnu.edu.cn第一联系人：

    ** 同等贡献

  • 基金资助:
    国家转基因生物新品种培育重大专项(2016ZX 08001-003)

Genome-wide association analysis and candidate gene selection of yield related traits in rice

YANG Fei1(), ZHANG Zheng-Feng2(), NAN Bo1, XIAO Ben-Ze1,*()   

  1. 1College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
    2School of Life Sciences, Central China Normal University, Wuhan 430079, Hubei, China
  • Received:2021-07-13 Accepted:2021-11-30 Published:2022-07-12 Published online:2021-12-24
  • Contact: XIAO Ben-Ze
  • About author:First author contact:

    ** Contributed equally to this work

  • Supported by:
    National Major Project for Developing New GM Crops(2016ZX 08001-003)

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摘要：

水稻是最重要的粮食作物之一, 培育高产稳产的水稻品种对于维护粮食安全至关重要, 对产量相关性状的遗传解析是提高水稻产量的基础。本文从“3000份水稻核心种质重测序项目” (3K Rice Genome Project)中挑选生育期较为一致的226份核心种质资源材料考察生育期(rice growing period, RGP)、株高(plant height, PH)、有效穗数(effective panicle number, EPN)、穗长(panicle length, PL)、穗着粒密度(spikelet density, SD)、结实率(seed setting rate, SSR)、千粒重(thousand grains weight, TGW)、单株产量(yield per plant, YP)、每穗颖花数(spikelet per panicle, SP)、每穗实粒数(grains per panicle, GP) 10个主要农艺性状, 结合2429 kb的高密度基因型数据进行全基因组关联分析(genome-wide association study, GWAS)。共定位到显著相关位点43个, 除了qRGP7.2、qPH12、qPL6.2、qSD6.2、qTGW1.1、qGP1、qGP5.2 7个QTLs以外, 其余36个QTL为本研究中定位到的新位点。此外, 本研究利用单核苷酸位点功能评估的方式筛选到6个主要农艺性状相关候选基因。分别为株高相关基因LOC_Os12g18760、有效穗数相关基因LOC_Os03g33530、穗长相关基因LOC_Os06g30940、千粒重相关基因LOC_Os01g49810、单株产量相关基因LOC_Os09g25260、穗着粒密度和每穗颖花数相关基因LOC_Os09g32620。本研究结果将为水稻产量遗传改良提供理论参考与重要基因资源。

关键词: 水稻, 产量, 关联分析, 候选基因, 遗传改良

Abstract:

Rice is the most important food crop for more than half of the world’s population, and the cultivation of rice varieties with high and stable yield is crucial for solving the world’s food problems. In this study, 226 rice core materials with relatively consistent growth stage were selected from “3K Rice Genome Project” and 2429 kb of high density genotype and 10 agronomic traits including growth period, plant height, effective panicle number, panicle length, spikelet density, seed setting rate, thousand-grains weight, yield per plant, spikelet per panicle, and grains per panicle were investigated by genome-wide associate study combined with 2429 kb of high-density genotype data. A total of 43 loci significantly associated with main agronomic traits were identified, including seven known loci, such as qRGP7.2, qPH12, qPL6.2, qSD6.2, qTGW1.1, qGP1, and qGP5.2. Six candidate genes were screened out, including LOC_Os12g18760 related to plant height, LOC_Os03g33530 related to effective panicle number, LOC_Os06g30940 related to panicle length, LOC_Os01g49810 related to thousand grains weight, LOC_Os09g25260 related to yield per plant, and LOC_Os09g32620 related to spikelet density and spikelet per panicle. These results provide important gene resources and the theoretical reference for genetic improvement of rice yield.

Key words: rice, yield, GWAS, candidate genes, genetic improvement

图1

材料不同类别群体的LD衰减图"

图2

系统发育树以及亲缘关系热图"

表1

群体产量相关性状的表现"

性状
Trait		 最小值
Max.		 最大值
Min.		 平均值±标准差
Mean±SD		 变异系数
CV		 偏度
Skewness		 峰度
Kurtosis
生育期RGP 88.00 141.00 113.69±12.49 0.11 -0.22 -0.33
株高PH 70.83 212.52 125.40±29.63 0.24 0.47 -0.70
有效穗数EPN 1.50 30.00 11.26±4.01 0.36 0.75 2.58
穗长PL 12.19 35.32 24.93±3.78 0.15 -0.12 0.82
穗着粒密度SD 26.71 125.40 55.79±15.95 0.29 0.95 1.45
结实率SSR 2.72 94.48 54.35±21.74 0.40 -0.37 -0.68
千粒重TGW 13.63 34.67 21.48±3.07 0.14 0.52 1.52
单株产量YP 2.09 55.62 18.91±10.26 0.54 0.47 -0.23
每穗颖花数SP 32.56 320.96 139.25±42.67 0.31 0.62 1.28
每穗实粒数GP 10.20 182.85 76.00±37.61 0.49 0.41 -0.35

表2

群体主要农艺性状相关系数"

性状
Trait		 生育期
RGP		 株高
PH		 有效穗数
EPN		 穗长
PL		 穗着粒密度SD 结实率
SSR		 千粒重
TGW		 单株产量YP 每穗颖花数SP
株高PH 0.334**
有效穗数EPN -0.322** -0.118
穗长PL 0.409** 0.592** -0.068
穗着粒密度SD 0.285** -0.141* -0.194** -0.035
结实率SSR -0.114 0.117 0.265** 0.013 -0.003
千粒重TGW -0.043 0.127 -0.014 0.017 -0.357** -0.064
单株产量YP 0.006 0.148* 0.536** 0.247** 0.242** 0.740** -0.045
每穗颖花数SP 0.419** 0.137* -0.208** 0.420** 0.878** 0.008 -0.299** 0.340**
每穗实粒数GP 0.145* 0.191** 0.067 0.274** 0.459** 0.780** -0.246** 0.799** 0.560**

图3

主要农艺性状的曼哈顿图和QQ (分位数-分位数)图"

表3

水稻主要农艺性状全基因组关联分析检测到的位点"

性状
Trait		 位点
Loci		 染色体
Chr.		 峰值SNP位置
Lead SNP location		 等位基因
Allele		 P值
P-value		 表型解释率
R2 (%)		 已知基因或QTL
Known gene/QTL
着粒密度SD qSD2 2 23,186,794 G/A 4.62E-08 13.70
qSD3.1 3 1,157,127 G/T 2.32E-07 13.21
qSD3.2 3 1,237,405 C/T 3.23E-07 12.91
qSD4.1 4 624,883 A/G 3.95E-07 12.45
qSD4.2 4 21,988,379 A/T 9.13E-07 11.99
qSD6.1 6 1,288,379 C/G 3.95E-07 13.73
qSD6.2 6 4,195,628 A/C 4.43E-07 13.08 qSD-6[12]
qSD8 8 4,256,879 G/A 5.45E-07 11.94
qSD9 9 19,467,675 C/T 3.61E-10 18.35
qSD11 11 21,384,141 A/T 4.47E-07 13.46
结实率SSR qSSR1 1 5,869,453 C/T 3.99E-07 13.12
qSSR5 5 1,034,218 G/A 7.89E-07 14.62
千粒重TGW qTGW1.1 1 23,551,474 G/T 3.66E-07 12.34 gw1.6[9]
qTGW1.2 1 28,602,321 C/T 1.09E-07 14.27
单株产量YP qYP9 9 15,090,090 C/T 2.05E-07 15.40
每穗颖花数SP qSP9 9 19,467,675 C/T 2.25E-08 15.37
每穗实粒数GP qGP1 1 5,016,026 C/T 4.74E-07 12.88 Gn1a[5]
qGP4 4 4,823,582 A/T 8.26E-08 14.67
qGP5.1 5 4,768,623 G/C 1.70E-07 14.00
qGP5.2 5 24,181,775 G/C 6.36E-07 13.76 qFGP-5[12]
qGP7 7 19,529,904 A/T 9.90E-07 11.90
qGP10 10 1,461,247 C/G 7.41E-07 13.35
qGP12 12 18,869,520 C/T 5.68E-07 13.19
生育期RGP qRGP3 3 9,022,002 G/A 9.18E-08 8.00
qRGP7.1 7 8,213,977 C/T 6.75E-07 8.89
qRGP7.2 7 10,550,765 T/C 5.47E-07 4.61 Ghd7[10]
qRGP7.3 7 26,977,462 G/T 8.28E-07 8.39
qRGP9.1 9 5,217,056 G/A 2.15E-07 7.09
qRGP9.2 9 9,452,746 C/T 4.25E-07 9.68
株高PH qPH12 12 10,850,670 A/G 9.52E-09 13.74 rs10809004[26]
有效穗数EPN qEPN2.1 2 8,414,057 T/G 5.52E-07 12.87
qEPN2.2 2 21,565,076 G/A 4.42E-07 8.32
qEPN2.3 2 23,524,522 G/A 9.55E-08 14.15
qEPN3 3 19,153,885 A/C 3.25E-07 14.46
qEPN4 4 8,551,259 G/A 2.36E-07 13.85
qEPN7 7 9,522,613 C/A 6.85E-07 11.96
qEPN9 9 11,661,903 C/T 4.08E-07 13.23
qEPN10 10 11,248,685 G/A 1.89E-07 12.11
qEPN12 12 23,941,955 C/G 3.44E-07 14.09
穗长PL qPL3 3 4,492,601 A/G 1.31E-07 7.10
qPL6.1 6 7,837,937 G/A 7.68E-07 11.20
qPL6.2 6 18,006,896 C/T 2.95E-07 4.87 PL6-4[13]
qPL10 10 22,711,072 C/T 2.35E-08 4.22

表4

主要农艺性状相关候选基因"

性状
Trait		 染色体
Chr.		 Block区间
Block interval		 SNP位置
SNP location		 P值
P-value		 突变类型
Mutation type		 候选基因
Candidate gene
株高PH 12 9,980,244-10,892,970 10,850,670 9.52E-09 Ile341Val LOC_Os12g18760
10,852,412 2.62E-07 Arg427Trp LOC_Os12g18760
有效穗数EPN 3 18,869,017-19,653,830 19,153,885 3.25E-07 His1596Gln LOC_Os03g33530
穗长PL 6 17,508,688-18,018,169 17,998,194 6.38E-07 Arg145Trp LOC_Os06g30940
17,998,633 5.87E-07 Val291Ala LOC_Os06g30940
17,998,980 5.42E-07 Ser407Pro LOC_Os06g30940
着粒密度SD 9 19,299,911-19,490,308 19,465,897 1.78E-09 Gln242* LOC_Os09g32620
千粒重TGW 1 28,102,929-28,992,862 28,600,008 4.75E-07 Asp238Glu LOC_Os01g49810
单株产量YP 9 14,973,503-15,128,976 15,126,639 3.38E-07 Ser89Leu LOC_Os09g25260
每穗实粒数SP 9 19,299,911-19,490,308 19,465,897 4.89E-08 Gln242* LOC_Os09g32620
[1] Godfray H C, Beddington J R, Crute I R, Haddad L, Lawrence D, Muir J F, Pretty J, Robinson S, Thomas S M, Toulmin C. Food security: the challenge of feeding 9 billion people. Science, 2010, 327: 812-818.
doi: 10.1126/science.1185383
[2] Takahashi Y, Shomura A, Sasaki T, Yano M. Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the alpha subunit of protein kinase CK2. Proc Natl Acad Sci USA, 2001, 98: 7922-7927.
doi: 10.1073/pnas.111136798
[3] Kojima S, Takahashi Y, Kobayashi Y, Monna L, Sasaki T, Araki T, Yano M. Hd3a, a rice ortholog of the Arabidopsis FT gene, promotes transition to flowering downstream of Hd1 under short-day conditions. Plant Cell Physiol, 2002, 43: 1096-1105.
pmid: 12407188
[4] Doi K, Izawa T, Fuse T, Yamanouchi U, Kubo T, Shimatani Z, Yano M, Yoshimura A. Ehd1, a B-type response regulator in rice, confers short-day promotion of flowering and controls FT-like gene expression independently of Hd1. Genes Dev, 2004, 18: 926-936.
doi: 10.1101/gad.1189604
[5] Ashikari M, Sakakibara H, Lin S, Yamamoto T, Takashi T, Nishimura A, Angeles E R, Qian Q, Kitano H, Matsuoka M. Cytokinin oxidase regulates rice grain production. Science, 2005, 309: 741-745.
doi: 10.1126/science.1113373
[6] Fan C, Xing Y, Mao H, Lu T, Han B, Xu C, Li X, Zhang Q. GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor Appl Genet, 2006, 112: 1164-1171.
doi: 10.1007/s00122-006-0218-1
[7] Song X J, Huang W, Shi M, Zhu M Z, Lin H X. A QTL for rice grain width and weight encodes a previously unknown RING- type E3 ubiquitin ligase. Nat Genet, 2007, 39: 623-630.
doi: 10.1038/ng2014
[8] 赵芳明, 朱海涛, 丁效华, 曾瑞珍, 张泽民, 李文涛, 张桂权. 基于SSSL的水稻重要性状QTL的鉴定及稳定性分析. 中国农业科学, 2007, 40: 447-456.
Zhao F M, Zhu H T, Ding X H, Zeng R Z, Zhang Z M, Li W T, Zhang G Q. Detection of QTLs for traits of agronomic importance and analysis of their stabilities using SSSLs in rice. Sci Agric Sin, 2007, 40: 447-456. (in Chinese with English abstract)
[9] Kaladhar K, Swamy B, Babu A P, Reddy C S, Sarla N. Mapping quantitative trait loci for yield traits in BC2F2 population derived from Swarna × O. nivara cross. Rice Genet News, 2009, 24: 34-36.
[10] Xue W, Xing Y, Weng X, Zhao Y, Tang W, Wang L, Zhou H, Yu S, Xu C, Li X, Zhang Q. Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nat Genet, 2008, 40: 761-767.
doi: 10.1038/ng.143
[11] Li Y, Fan C, Xing Y, Jiang Y, Luo L, Sun L, Shao D, Xu C, Li X, Xiao J, He Y, Zhang Q. Natural variation in GS5 plays an important role in regulating grain size and yield in rice. Nat Genet, 2011, 43: 1266-1269.
doi: 10.1038/ng.977
[12] 陈燕华, 黄大辉, 邱永福, 张月雄, 刘芳, 马增凤, 刘驰, 李容柏. 水稻主要农艺性状的QTL分析. 华南农业大学学报, 2014, 35: 42-51.
Chen Y H, Huang D H, Qiu Y F, Zhang Y X, Liu F, Ma Z F, Liu C, Li R B. A QTL analysis of main agronomic characters in rice,Oryza sativa. J South China Agric Univ, 2014, 35: 42-51. (in Chinese with English abstract)
[13] Sun Z, Yin X, Ding J, Yu D, Hu M, Sun X, Tan Y, Sheng X, Liu L, Mo Y, Ouyang N, Jiang B, Yuan G, Duan M, Yuan D, Fang J. QTL analysis and dissection of panicle components in rice using advanced backcross populations derived from Oryza sativa cultivars HR1128 and ‘Nipponbare’. PLoS One, 2017, 12: e0175692.
doi: 10.1371/journal.pone.0175692
[14] Yu J, Buckler E S. Genetic association mapping and genome organization of maize. Curr Opin Biotechnol, 2006, 17: 155-160.
doi: 10.1016/j.copbio.2006.02.003
[15] Huang X, Wei X, Sang T, Zhao Q, Feng Q, Zhao Y, Li C, Zhu C, Lu T, Zhang Z, Li M, Fan D, Guo Y, Wang A, Wang L, Deng L, Li W, Lu Y, Weng Q, Liu K, Huang T, Zhou T, Jing Y, Li W, Lin Z, Buckler E S, Qian Q, Zhang Q F, Li J, Han B. Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet, 2010, 42: 961-967.
doi: 10.1038/ng.695
[16] Zhou L, Liu S, Wu W, Chen D, Zhan X, Zhu A, Zhang Y, Cheng S, Cao L, Lou X, Xu H. Dissection of genetic architecture of rice plant height and heading date by multiple-strategy-based association studies. Sci Rep, 2016, 6: 29718.
doi: 10.1038/srep29718
[17] Begum H, Spindel J E, Lalusin A, Borromeo T, Gregorio G, Hernandez J, Virk P, Collard B, McCouch S R. Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa). PLoS One, 2015, 10: e0119873.
doi: 10.1371/journal.pone.0119873
[18] Li X, Chen Z, Zhang G, Lu H, Qin P, Qi M, Yu Y, Jiao B, Zhao X, Gao Q, Wang H, Wu Y, Ma J, Zhang L, Wang Y, Deng L, Yao S, Cheng Z, Yu D, Zhu L, Xue Y, Chu C, Li A, Li S, Liang C. Analysis of genetic architecture and favorable allele usage of agronomic traits in a large ppub of Chinese rice accessions. Sci China Life Sci, 2020, 63: 1688-1702.
doi: 10.1007/s11427-019-1682-6
[19] Wang W, Mauleon R, Hu Z, Chebotarov D, Tai S, Wu Z, Li M, Zheng T, Fuentes R R, Zhang F, Mansueto L, Copetti D, Sanciangco M, Palis K C, Xu J, Sun C, Fu B, Zhang H, Gao Y, Zhao X, Shen F, Cui X, Yu H, Li Z, Chen M, Detras J, Zhou Y, Zhang X, Zhao Y, Kudrna D, Wang C, Li R, Jia B, Lu J, He X, Dong Z, Xu J, Li Y, Wang M, Shi J, Li J, Zhang D, Lee S, Hu W, Poliakov A, Dubchak I, Ulat V J, Borja F N, Mendoza J R, Ali J, Li J, Gao Q, Niu Y, Yue Z, Naredo M E B, Talag J, Wang X, Li J, Fang X, Yin Y, Glaszmann J C, Zhang J, Li J, Hamilton R S, Wing R A, Ruan J, Zhang G, Wei C, Alexandrov N, McNally K L, Li Z, Leung H. Genomic variation in 3010 diverse accessions of Asian cultivated rice. Nature, 2018, 557: 43-49.
doi: 10.1038/s41586-018-0063-9
[20] Kawahara Y, de la Bastide M, Hamilton J P, Kanamori H, McCombie W R, Ouyang S, Schwartz D C, Tanaka T, Wu J, Zhou S, Childs K L, Davidson R M, Lin H, Quesada-Ocampo L, Vaillancourt B, Sakai H, Lee S S, Kim J, Numa H, Itoh T, Buell C R, Matsumoto T. Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data. Rice (New York), 2013, 6: 4.
[21] Alexander D H, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res, 2009, 19: 1655-1664.
doi: 10.1101/gr.094052.109 pmid: 19648217
[22] Bradbury P J, Zhang Z, Kroon D E, Casstevens T M, Ramdoss Y, Buckler E S. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 2007, 23: 2633-2635.
pmid: 17586829
[23] Preacher K J, Hayes A F. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Res Meth Instrum Comp, 2004, 36: 717-731.
[24] Si L, Chen J, Huang X, Gong H, Luo J, Hou Q, Zhou T, Lu T, Zhu J, Shang-Guan Y, Chen E, Gong C, Zhao Q, Jing Y, Zhao Y, Li Y, Cui L, Fan D, Lu Y, Weng Q, Wang Y, Zhan Q, Liu K, Wei X, An K, An G, Han B. OsSPL13 controls grain size in cultivated rice. Nat Genet, 2016, 48: 447-456.
doi: 10.1038/ng.3518
[25] Cingolani P, Platts A, Wang L, Coon M, Nguyen T, Wang L, Land S J, Lu X, Ruden D M. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin), 2012, 6: 80-92.
doi: 10.4161/fly.19695 pmid: 22728672
[26] Li N, Li Y. Ubiquitin-mediated control of seed size in plants. Front Plant Sci, 2014, 5: 332.
[27] 阮成江, 何祯祥, 钦佩. 我国农作物QTL定位研究的现状和进展. 植物学通报, 2003, 20: 10-22.
Ruan C J, He Z X, Qin P. Research advancements on crop QTL mapping in China. Chin Bull Bot, 2003, 20: 10-22. (in Chinese with English abstract)
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