欢迎访问作物学报,今天是

作物学报 ›› 2018, Vol. 44 ›› Issue (01): 32-42.doi: 10.3724/SP.J.1006.2018.00032

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

全基因组关联定位籼稻种质资源外观和加工品质QTL

方雅洁1,2,朱亚军2,3,吴志超2,陈凯2,3,申聪聪3,石英尧1,*,徐建龙2,3,4,*   

  1. 1安徽农业大学,安徽合肥 230036; 2中国农业科学院作物科学研究所,北京 100081; 3中国农业科学院农业基因组研究所,广东深圳 518210;4中国农业科学院深圳生物育种创新研究院,广东深圳 518210
  • 收稿日期:2017-04-05 修回日期:2017-09-10 出版日期:2018-01-12 网络出版日期:2017-09-28
  • 基金资助:

    本研究由国家高技术研究发展计划(863计划)项目(2014AA10A601),农业部引进国际先进农业科学技术(948)项目(2016-X16),深圳孔雀团队计划(20130415095710361)和中国农业科学院科技创新工程团队项目资助。

Genome-wide Association Study of Grain Appearance and Milling Quality in a Worldwide Collection of Indica Rice Germplasm

FANG Ya-Jie1,2,ZHU Ya-Jun2,3,WU Zhi-Chao2,CHEN Kai2,3,SHEN Cong-Cong3,SHI Ying-Yao1,*,XU Jian-Long2,3,4,*   

  1. 1 Anhui Agricultural University, Hefei 230036, China; 2 Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 3 Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen 518210, China; 4 Shenzhen Institute of Breeding & Innovation, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
  • Received:2017-04-05 Revised:2017-09-10 Published:2018-01-12 Published online:2017-09-28
  • Supported by:

    This study was supported by National High-Tech Research & Development Plan (863) (2014AA10A601), Introduction of International Advanced Agricultural Science and Technology of Ministry of Agriculture (948) (2016-X16), ShenZhen Peacock Plan (20130415095710361), and Scientific and Technological Innovation Project of Chinese Academy of Agricultural Sciences.

摘要:

以400份籼稻变异丰富的种质资源材料在2个环境下考察外观与加工品质性状表型,利用404K高密度SNP基因型进行全基因组关联分析,挖掘影响外观与加工品质性状的重要位点。结果表明,粒型和籼米的外观和加工品质密切相关,垩白性状降低稻米的精米率和整精米率,除粒型外,籼稻的外观和加工品质明显受到环境影响。全基因组关联分析共鉴定到39个QTL,其中17个为新位点,6个新位点(qMRR9、qGL2、qGL10、qGW1、qGLWR1和qGLWR2.1)在2个环境下均被检测到,暗示这6个位点在水稻外观与加工品质上可能是不依赖于环境稳定表达的QTL。此外,21个控制稻米外观品质的位点很可能具一因多效。结合前人研究结果,我们推论qSW5、GSE5和GS3在籼稻外观和加工品质性状上扮演着关键性角色。研究结果为克隆新的外观与加工品质基因以及通过分子手段加速培育优质高产籼稻新品种提供了指导信息。

关键词: 籼稻种质资源, 外观与加工品质, 全基因组关联分析, 数量性状座位

Abstract:

Appearance and milling quality are two crucial properties of rice affecting their market acceptability. Understanding the genetic basis of rice grain quality could improve the efficiency of breeding for high quality. Here we carried out genome-wide association analysis using the 404K SNP genotype and data of grain appearance and milling quality for a diverse panel of 400 indica accessions selected from 3K Rice Genome Project collected in two environments. These were closely correlation between grain shape and quality (appearance and milling) of indica rice. The chalk trait reduced milled rice rate and high milled rice rate. In addition to grain shape, the phenotype value of appearance and milling quality traits was obviously affected by environments. Total of 39 QTL were detected which was significantly associated with grain appearance and milling quality in two environments and 17 of them were new QTL. Six new QTL (qMRR9, qGL2, qGL10, qGW1, qGLWR1, and qGLWR2.1) with minor or small effect were considered as stably expressed QTL because they were simultaneously identified in two environments. In addition, we found 21 QTL probably having multiple-effect in appearance and milling quality of indica rice. Combined with the results of previous studies, we concluded that qSW5, GSE5 and GS3 play important role in affecting appearance and milling quality. This research provides valuable information for cloning QTL controlling appearance and milling quality and breeding rice with high yield and good quality by molecular techniques.

Key words: Indica germplasms, Appearance and milling quality, GWAS, Quantitative trait loci/locus (QTL)

[1]梅德勇, 朱玉君, 樊叶杨. 籼稻稻米碾磨与外观品质性状的QTL定位. 遗传, 2012, 34: 1591–1598 Mei D Y, Zhu Y J, Fan Y Y. Mapping QTL for rice milling and appearance quality traits in indica rice. Hereditas (Beijing), 2012, 34: 1591–1598 (in Chinese with English abstract) [2]王丹英, 章秀福, 朱智伟, 陈能, 闵捷, 姚青, 严建立, 廖西元. 食用稻米品质性状间的相关性分析. 作物学报, 2005, 31: 1086-1091 Wang D Y, Zhang X F, Zhu Z W, Chen N, Min J, Yao Q, Yan J L, Liao X Y. Correlation analysis of rice grain quality characteristics. Acta Agron Sin, 2005, 31: 1086–1091(in Chinese with English abstract) [3]Wang X Q, Pang Y L, Wang C C, Chen K, Zhu Y J, Shen C C, Ali J, Xu J L, Li Z K. New candidate genes affecting rice grain appearance and milling quality detected by genome-wide and gene-based association analyses. Front Plant Sci, 2017, 7: 1998 [4]Xu J L, Yu S B, Luo L J , Zhong D B, Sanchez A, Mei H W, Khush G S , Li Z K. Molecular dissection of the primary sink size and its related traits in rice. Plant Breed, 2004, 123: 43–50 [5]周立军, 江玲, 翟虎渠, 万建民. 水稻垩白的研究现状与改良策略. 遗传, 2009, 31: 563–572 Zhou L J, Jiang L, Zhai H Q, Wan J M. Current status and strategies for improvement of rice grain chalkiness. Hereditas (Beijing), 2009, 31: 563–572 (in Chinese with English abstract) [6]Qiu X J, Chen K, Lv W K, Qu X X, Zhu Y J, Xing D Y, Yang L W, Fan F J, Yang J, Xu J L. Examining two sets of introgression lines reveals background-independent and stably expressed QTL that improve grain appearance quality in rice (Oryza sativa L.). Theor Appl Genet, 2017, doi: 101007/s00122-017-2862-z [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 [8]Shomura A, Izawa T, Ebana K, Ebitani T, Kanegae H, Konishi S, Yano M. Deletion in a gene associated with grain size increased yields during rice domestication. Nat Genet, 2008, 40: 1023–1028 [9]Yan S, Zou G H, Li S J, Wang H, Liu H Q, Zhai G W, Guo P, Song H M, Yan C J, Tao Y Z. Seed size is determined by the combinations of the genes controlling different seed characteristics in rice. Theor Appl Genet, 2011, 123: 1173–1181 [10]Fan C C, Xing Y Z, Mao H L, Lu T T, Han B, Xu C G, Li X H, Zhang Q F. 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 [11]Wang Y X, Xiong G S, Hu J, Jiang L, Yu H, Xu J, Fang Y X, Zeng L J, Xu E B, Xu J, Ye W J, Meng X B, Liu R F, Chen H Q, Jing Y H, Wang Y H, Zhu X D, Li J Y, Qian Q. Copy number variation at the GL7 locus contributes to grain size diversity in rice. Nat Genet, 2015, 47: 944-948 [12]Wang S K, Li S, Liu Q, Wu K, Zhang J Q, Wang S S, Wang Y, Chen X B, Zhang Y, Gao C X, Wang F, Huang H X, Fu X D. The OsSPL16-GW7 regulatory module determines grain shape and simultaneously improves rice yield and grain quality. Nat Genet, 2015, 47: 949–954 [13]Sun L J, Li X J, Fu Y C, Zhu Z G, Tan L B, Liu F X, Sun X Y, Sun X W, Sun C Q. GS6, a member of the GRAS gene family, negatively regulates grain size in rice. J Integr Plant Biol, 2013, 55: 938–949 [14]Guo L B, Ma L L, Jiang H, Zeng D L, Hu J, Wu L W, Gao Z Y, Zhang G Z, Qian Q. Genetic analysis and fine mapping of two genes for grain shape and weight in rice. J Integr Plant Biol, 2009, 51: 45–51 [15]Singh R, Singh A K, Sharma T R, Singh A, Singh N K. Fine mapping of grain length QTLs on chromosomes 1 and 7 in Basmati rice (Oryza sativa L.). J Plant Biochem Biotechnol, 2012, 21: 157–166 [16]Li Y B, Fan C H, Xing Y Z, Yun P, Luo L J, Yan B, Peng B, Xie W B, Wang G W, Li X H, Xiao J H, Xu C G, He Y Q. Chalk5 encodes a vacuolar H(+)-translocating pyrophosphatase influencing grain chalkiness in rice. Nat Genet, 2014, 46: 398–404 [17]Wang E T, Wang J J, Zhu X D, Hao W, Wang L Y, Li Q, Zhang L X, He W, Lu B R, Lin H X, Ma H, Zhang G Q, He Z H. Control of rice grain-filling and yield by a gene with a potential signature of domestication. Nat Genet, 2008, 40: 1370–1374 [18]Zhang Y, Verhoeff N I, Chen Z, Chen S, Wang M, Zhu Z, Ouwerkerk P B F. Functions of OsDof25 in regulation of OsC4PPDK. Plant Mol Biol, 2015, 89: 229–242 [19]Ryoo N, Yu C, Park C S, Baik M Y, Park I M, Cho M H, Bhoo S h, An G, Hahn T R, Jeon J S. Knockout of a starch synthase gene OsSSIIIa/Flo5 causes white-core floury endosperm in rice (Oryza sativa L.). Plant Cell Rep, 2007, 26: 1083–1095 [20]Zhou L J, Chen L M, Jiang L, Zhang W W, Liu L J, Liu X, Zhao Z G, Liu S J , Zhang L J, Wang J K, Wan J M. Fine mapping of the grain chalkiness QTL qPGWC-7 in rice (Oryza sativa L.). Theor Appl Genet, 2009, 118: 581–590 [21]Ren D Y, Rao Y H, Huang L C, Leng Y J, Hu J, Lu M, Zhang G H, Zhu L, Gao Z Y, Dong G J, Guo L B, Qian Q, Zeng D L. Fine mapping identifies a new QTL for brown rice rate in rice (Oryza sativa L.). Rice, 2016, 9: 4–14 [22]Qiu X J, Pang Y L, Yuan Z H, Xing D Y, Xu J L, Dingkuhn M, Li Z K, Ye G Y. Genome-wide association study of grain appearance and milling quality in a worldwide collection of indica rice germplasm. PLoS One, 2015, 10: e0145577 [23]Zhao K Y, Tung C W, Eizenga G C, Wright M H, Ali ML, Price A H, Norton G J, Islam M R, Reynolds A, Mezey J, McClung A M, Bustamante C D, McCouch S R. Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nat Commun, 2011, 2: 467–478 [24]唐富福, 徐非非, 包劲松. 全基因组关联分析在水稻遗传育种中的应用. 核农学报, 2013, 27: 598–606 Tang F F, Xu F F, Bao J S. Application of genome-wide association analysis in rice. Acta Agric Nucl Sin, 2013, 27: 598-606(in Chinese) [25]侯青青, 司丽珍, 黄学辉, 韩斌. 水稻复杂性状研究的新途径: 水稻重要农艺性状全基因组关联分析. 生命科学, 2016, 28: 1250–1257 Hou Q Q, Si L Z, Huang X H, Han B. Progress on genome-wide association study of important agronomic traits in rice. Chin Bull Life Sci, 2016, 28: 1250–1257 (in Chinese with English abstract) [26]邱先进, 袁志华, 陈凯, 杜斌, 何文静, 杨隆维, 徐建龙, 邢丹英, 吕文恺. 用全因组关联分析解析籼稻垩白的遗传基础. 作物学报, 2015, 41: 1007-1016 Qiu X J, Yuan Z H, Chen K, Du B, He W J, Yang W L, Xu J L, Xing D Y, Lyu W K. Genetic dissection of grain chalkiness in indica mini-core germplasm using genome-wide association method. Acta Agron Sin, 2015, 41: 1007–1016 (in Chinese with English abstract) [27]The 3,000 rice genomes project. The 3,000 rice genomes project. GigaScience, 2014, 3: 7–13 [28]Alexandrov N, Tai S, Wang W S, Mansueto L, Palis K, Fuentes RR, Ulat VJ, Chebotarov D, Zhang G Y, Li Z K. SNP-Seek database of SNPs derived from 3000 rice genomes. Nucleic Acids Res, 2015, 43: D1023 [29]Hu J, Wang Y X, Fang Y X, Zeng L J, Xu J, Yu H P, Shi Z T, Pan J J, Zhang D, Kang S J, Zhu L, Dong G J, Guo L B, Zeng D L, Zhang G H, Xie L H, Xiong G S, Li J Y, Qian Q. A rare allele of GS2 enhances grain size and grain yield in rice. Mol Plant, 2015, 8: 1455–1465 [30]Matsushima R, Maekawa M, Kusano M, Tomita K, Kondo H, Nishimura H, Crofts N, Fujita N, Sakamoto W. Amyloplast membrane protein SUBSTANDARD STARCH GRAIN6 controls starch grain size in rice endosperm. Plant Physiol, 2016, 170: 1445–1459 [31]Song X J, Kuroha T, Ayano M, Furuta T, Nagai K, Komeda N, Segami S, Miura K, Ogawa D, Kamura T, Suzuki T, Higashiyama T, Yamasaki M, Mori H, Inukai Y, Wu J Z, Kitano H, Sakakibara H, Jacobsen S E, Ashikari M. Rare allele of a previously unidentified histone H4 acetyltransferase enhances grain weight, yield, and plant biomass in rice. Proc Natl Acad Sci USA, 2015, 112: 76–81 [32]Feng Z M, Wu C Y, Wang C M, Roh J, Zhang L, Chen J, Zhang S Z, Zhang H, Yang C Y, Hu J L. SLG controls grain size and leaf angle by modulating brassinosteroid homeostasis in rice. J Exp Bot, 2016, 67: erw204 [33]Zhang X J, Wang J F, Huang J, Lan H X, Wang C L, Yin C F, Wu Y Y, Tang H J, Qian Q, Li J Y. Rare allele of OsPPKL1 associated with grain length causes extra-large grain and a significant yield increase in rice. Proc Natl Acad Sci USA, 2012, 109: 21534–21543 [34]Tan Y F, Xing Y Z, Li J X, Yu S B, Xu C G, Zhang Q F. Genetic bases of appearance quality of rice grains in Shanyou 63, an elite rice hybrid. Theor Appl Genet, 2000, 101: 823–829 [35]Zhao X Q, Zhou L J, Ponce K, Ye G Y. The usefulness of known genes/QTLs for grain quality traits in an indica population of diverse breeding lines tested using association analysis. Rice. 2015, 8: 29–42 [36]张云康, 林榕辉, 闵捷, 吴戍君, 朱智伟, 葛进平. 浙江水稻品种资源的品质研究. 作物品种资源, 1992, (4): 23–25 Zhang Y K, Lin R H, Min J, Wu S J, Zhu Z W, Ge J P. The research of germplasm on rice quality in Zhejiang province. Crop Variety Germplasm Res, 1992, (4): 23–25 (in Chinese) [37]徐正进, 陈温福, 马殿荣, 吕英娜, 周淑清, 刘丽霞. 稻谷粒形与稻米主要品质性状的关系. 作物学报, 2004, 30: 894–900 Xu Z J, Chen W F, Ma D R, Lyu Y N, Zhou S Q, Liu L X. Correlations between rice grain shapes and main qualitative characteristics. Acta Agron Sin, 2004, 30: 894–900 (in Chinese with English abstract) [38]Duan P G, Xu J S, Zeng D L, Zhang B L, Geng M F, Zhang G Z, Huang K, Huang L J, Xu R, Ge S, Qian Q, Li Y H. Natural variation in the promoter of GSE5 contributes to grain size diversity in rice. Mol Plant, 2017, doi: http: //dxdoiorg/101016/jmolp201703009 [39]Xu Y B, Lu Y K, Xie C X, Gao S B, Wan J M, Prasanna B M. Whole-genome strategies for marker-assisted plant breeding. Mol Breed, 2012, 29: 855–855 [40]Feng Y, Lu Q, Zhai R R, Zhang M C, Xu Q, Yang Y L, Wang S, Yuan X P, Yu H Y, Wang Y P, Wei X H. Genome wide association mapping for grain shape traits in indica rice. Planta, 2016, 244: 819–830 [41]Nagata K, Ando T, Nonoue Y, Mizubayashi T, Kitazawa N, Shomura A, Matsubara K, Ono N, Mizobuchi R, Shibaya T, Ogiso-Tanaka E, Hori K, Yano M, Fukuoka S. Advanced backcross QTL analysis reveals complicated genetic control of rice grain shape in a japonica × indica cross. Breed Sci, 2015, 65: 308–318

[1] 陈玲玲, 李战, 刘亭萱, 谷勇哲, 宋健, 王俊, 邱丽娟. 基于783份大豆种质资源的叶柄夹角全基因组关联分析[J]. 作物学报, 2022, 48(6): 1333-1345.
[2] 孙思敏, 韩贝, 陈林, 孙伟男, 张献龙, 杨细燕. 棉花苗期根系分型及根系性状的关联分析[J]. 作物学报, 2022, 48(5): 1081-1090.
[3] 渠建洲, 冯文豪, 张兴华, 徐淑兔, 薛吉全. 基于全基因组关联分析解析玉米籽粒大小的遗传结构[J]. 作物学报, 2022, 48(2): 304-319.
[4] 赵海涵, 练旺民, 占小登, 徐海明, 张迎信, 程式华, 楼向阳, 曹立勇, 洪永波. 水稻协优9308重组自交系群体白叶枯病抗性的全基因组关联分析[J]. 作物学报, 2022, 48(1): 121-137.
[5] 耿腊, 黄业昌, 李梦迪, 谢尚耿, 叶玲珍, 张国平. 大麦籽粒β-葡聚糖含量的全基因组关联分析[J]. 作物学报, 2021, 47(7): 1205-1214.
[6] 马娟, 曹言勇, 李会勇. 玉米穗轴粗全基因组关联分析[J]. 作物学报, 2021, 47(7): 1228-1238.
[7] 陈灿, 农保选, 夏秀忠, 张宗琼, 曾宇, 冯锐, 郭辉, 邓国富, 李丹婷, 杨行海. 广西水稻地方品种核心种质稻瘟病抗性位点全基因组关联分析[J]. 作物学报, 2021, 47(6): 1114-1123.
[8] 靳义荣, 刘金栋, 刘彩云, 贾德新, 刘鹏, 王雅美. 普通小麦氮素利用效率相关性状全基因组关联分析[J]. 作物学报, 2021, 47(3): 394-404.
[9] 魏丽娟, 申树林, 黄小虎, 马国强, 王曦彤, 杨怡玲, 李洹东, 王书贤, 朱美晨, 唐章林, 卢坤, 李加纳, 曲存民. 锌胁迫下甘蓝型油菜发芽期下胚轴长的全基因组关联分析[J]. 作物学报, 2021, 47(2): 262-274.
[10] 蒋伟, 潘哲超, 包丽仙, 周福仙, 李燕山, 隋启君, 李先平. 马铃薯资源晚疫病抗性的全基因组关联分析[J]. 作物学报, 2021, 47(2): 245-261.
[11] 雷维, 王瑞莉, 王刘艳, 袁芳, 孟丽姣, 邢明礼, 徐璐, 唐章林, 李加纳, 崔翠, 周清元. 甘蓝型油菜容重及其相关性状的全基因组关联分析[J]. 作物学报, 2021, 47(11): 2099-2110.
[12] 谢磊, 任毅, 张新忠, 王继庆, 张志辉, 石书兵, 耿洪伟. 小麦穗发芽性状的全基因组关联分析[J]. 作物学报, 2021, 47(10): 1891-1902.
[13] 王小雷, 李炜星, 曾博虹, 孙晓棠, 欧阳林娟, 陈小荣, 贺浩华, 朱昌兰. 基于染色体片段置换系对水稻粒形及千粒重QTL检测与稳定性分析[J]. 作物学报, 2020, 46(10): 1517-1525.
[14] 荐红举, 霍强, 高玉敏, 李阳阳, 谢玲, 魏丽娟, 刘列钊, 卢坤, 李加纳. 用全基因组关联分析筛选甘蓝型油菜叶片叶绿素含量候选基因[J]. 作物学报, 2020, 46(10): 1557-1565.
[15] 邹伟伟,路雪丽,王丽,薛大伟,曾大力,李志新. 不同氮水平下水稻钾吸收及全基因组关联分析[J]. 作物学报, 2019, 45(8): 1189-1199.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!