Genome-Wide Association Mapping of Complex Traits in Rice

Chapter

Abstract

In rice varieties, there are many naturally occurring genetic variations. Most of morphological, developmental, and physiological variations in rice belong to complex quantitative traits controlled by dozens of genetic variants. One of the most important aims in rice genetic studies is to identify individual genes and their allelic mutations underlying some phenotypic variations in rice through the way of genetic mapping. In this chapter, we begin by addressing the potential difficulties in genetic dissections of complex traits. We then discuss recent progresses on high-resolution quantitative trait locus mapping and genome-wide association study in rice. Finally, some prospects in the future to enhance the mapping power and resolution of complex traits in rice are discussed.

Keywords

Rice Complex traits Germplasm resources Genetic mapping Next-generation sequencing Genome-wide association 

Notes

Acknowledgments

We thank Mr. Jiashun Miao for the helps in formatting the references in the manuscript preparations. Rice genetic studies in our labs are supported by the Ministry of Science and Technology of China (2016YFD0100902) and the National Natural Science Foundation of China (91535202 and 91635302).

References

  1. Altshuler D, Daly MJ, Lander ES (2008) Genetic mapping in human disease. Science 322:881–888CrossRefPubMedPubMedCentralGoogle Scholar
  2. Bai X, Luo L, Yan W et al (2010) Genetic dissection of rice grain shape using a recombinant inbred line population derived from two contrasting parents and fine mapping a pleiotropic quantitative trait locus qGL7. BMC Genet 11(1):1–11CrossRefGoogle Scholar
  3. Buckler ES, Holland JB, Bradbury PJ et al (2009) The genetic architecture of maize flowering time. Science 325:714–718CrossRefPubMedGoogle Scholar
  4. Chen W, Gao Y, Xie W et al (2014) Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Nat Genet 46(7):714–721CrossRefPubMedGoogle Scholar
  5. Cheng SH, Zhuang JY, Fan YY et al (2007) Progress in research and development on hybrid rice: a super-domesticate in China. Ann Bot 100:959–966CrossRefPubMedPubMedCentralGoogle Scholar
  6. Elshire RJ, Glaubitz JC, Sun Q et al (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6(5):e19379CrossRefPubMedPubMedCentralGoogle Scholar
  7. Gamuyao R, Chin JH, Pariasca-Tanaka J et al (2012) The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency. Nature 488:535–539CrossRefPubMedGoogle Scholar
  8. Haines JL, Hauser MA, Schmidt S et al (2005) Complement factor H variant increases the risk of age-related macular degeneration. Science 308:419–421CrossRefPubMedGoogle Scholar
  9. Hua JP, Xing YZ, Xu CG et al (2002) Genetic dissection of an elite rice hybrid revealed that heterozygotes are not always advantageous for performance. Genetics 162(4):1885–1895PubMedPubMedCentralGoogle Scholar
  10. Huang X, Feng Q, Qian Q et al (2009) High-throughput genotyping by whole-genome resequencing. Genome Res 19:1068–1076CrossRefPubMedPubMedCentralGoogle Scholar
  11. Huang X, Wei X, Sang T et al (2010) Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet 42(11):961–967CrossRefPubMedGoogle Scholar
  12. Huang X, Paulo MJ, Boer M et al (2011) Analysis of natural allelic variation in Arabidopsis using a multiparent recombinant inbred line population. Proc Natl Acad Sci U S A 108(11):4488–4493CrossRefPubMedPubMedCentralGoogle Scholar
  13. Huang X, Zhao Y, Wei X et al (2012) Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nat Genet 44(1):32–39CrossRefGoogle Scholar
  14. Huang X, Yang S, Gong J et al (2015) Genomic analysis of hybrid rice varieties reveals numerous superior alleles that contribute to heterosis. Nat Commun 6:6258CrossRefPubMedPubMedCentralGoogle Scholar
  15. Huang X, Yang S, Gong J et al (2016) Genomic architecture of heterosis for yield traits in rice. Nature 537:629–633CrossRefPubMedGoogle Scholar
  16. International Rice Genome Sequencing Project (2005) The map-based sequence of the rice genome. Nature 436:793–800CrossRefGoogle Scholar
  17. Kang HM, Sul JH, Service SK et al (2010) Variance component model to account for sample structure in genome-wide association studies. Nat Genet 42(4):348–354CrossRefPubMedPubMedCentralGoogle Scholar
  18. Kojima S, Takahashi Y, Kobayashi Y et al (2002) Hd3a, a rice ortholog of the Arabidopsis FT gene, promotes transition to flowering downstream of Hd1 under short-day conditions. Plant Cell Physiol 43(10):1096–1105CrossRefPubMedGoogle Scholar
  19. Kover PX, Valdar W, Trakalo J et al (2009) A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana. PLoS Genet 5(7):e1000551CrossRefPubMedPubMedCentralGoogle Scholar
  20. Kump KL, Bradbury PJ, Wisser RJ et al (2011) Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population. Nat Genet 43(2):163–168CrossRefPubMedGoogle Scholar
  21. Li H, Peng Z, Yang X et al (2013) Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels. Nat Genet 45(1):43–50CrossRefPubMedGoogle Scholar
  22. Liu T, Mao D, Zhang S et al (2009) Fine mapping SPP1, a QTL controlling the number of spikelets per panicle, to a BAC clone in rice (Oryza sativa). Theor Appl Genet 118(8):1509–1517CrossRefPubMedGoogle Scholar
  23. Lu T, Lu G, Fan D et al (2010) Function annotation of the rice transcriptome at single-nucleotide resolution by RNA-seq. Genome Res 20:1238–1249CrossRefPubMedPubMedCentralGoogle Scholar
  24. Marouli E, Graff M, Medina-Gomez C et al (2017) Rare and low-frequency coding variants alter human adult height. Nature 542:186–190CrossRefPubMedPubMedCentralGoogle Scholar
  25. Mather KA, Caicedo AL, Polato NR et al (2007) The extent of linkage disequilibrium in rice (Oryza sativa L.) Genetics 177:2223–2232CrossRefPubMedPubMedCentralGoogle Scholar
  26. Matsubara K, Hori K, Ogiso-Tanaka E et al (2014) Cloning of quantitative trait genes from rice reveals conservation and divergence of photoperiod flowering pathways in Arabidopsis and rice. Front Plant Sci 5:193CrossRefPubMedPubMedCentralGoogle Scholar
  27. McCouch SR, Teytelman L, Xu Y et al (2002) Development and mapping of 2,240 new SSR markers for rice (Oryza sativa L.) DNA Res 9:199–207CrossRefPubMedGoogle Scholar
  28. McMullen MD, Kresovich S, Villeda HS et al (2009) Genetic properties of the maize nested association mapping population. Science 325:737–740CrossRefPubMedGoogle Scholar
  29. Miura K, Ashikari M, Matsuouka M (2011) The role of QTLs in the breeding of high-yielding rice. Trends Plant Sci 16:319–326CrossRefPubMedGoogle Scholar
  30. Myles S, Peiffer J, Brown PJ et al (2009) Association mapping: critical considerations shift from genotyping to experimental design. Plant Cell 21(8):2194–2202CrossRefPubMedPubMedCentralGoogle Scholar
  31. Nordborg M, Weigel D (2008) Next-generation genetics in plants. Nature 456:720–723CrossRefPubMedGoogle Scholar
  32. Picelli S, Björklund AK, Reinius B et al (2014) Tn5 transposase and tagmentation procedures for massively scaled sequencing projects. Genome Res 24(12):2033–2040CrossRefPubMedPubMedCentralGoogle Scholar
  33. Poland JA, Bradbury PJ, Buckler ES et al (2011) Genome-wide nested association mapping of quantitative resistance to northern leaf blight in maize. Proc Natl Acad Sci U S A 108(17):6893–6898CrossRefPubMedPubMedCentralGoogle Scholar
  34. Reig-Valiente JL, Viruel J, Sales E et al (2016) Genetic diversity and population structure of rice varieties cultivated in temperate regions. Rice 9:58CrossRefPubMedPubMedCentralGoogle Scholar
  35. Riedelsheimer C, Czedikeysenberg A, Grieder C et al (2012) Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat Genet 44(2):217–220CrossRefPubMedGoogle Scholar
  36. Sadhu MJ, Bloom JS, Day L et al (2016) CRISPR-directed mitotic recombination enables genetic mapping without crosses. Science 352:1113–1116CrossRefPubMedPubMedCentralGoogle Scholar
  37. Shomura A, Izawa T, Ebana K et al (2008) Deletion in a gene associated with grain size increased yields during rice domestication. Nat Genet 40(8):1023–1028CrossRefPubMedGoogle Scholar
  38. Si L, Chen J, Huang X et al (2016) OsSPL13 controls grain size in cultivated rice. Nat Genet 48:447–456CrossRefPubMedGoogle Scholar
  39. Song XJ, Kuroha T, Ayano M et al (2015) Rare allele of a previously unidentified histone H4 acetyltransferase enhances grain weight, yield, and plant biomass in rice. Proc Natl Acad Sci U S A 112(1):76–81CrossRefPubMedGoogle Scholar
  40. Summerfield RJ, Collinson ST, Ellis RH et al (1992) Photothermal responses of flowering in rice (Oryza sativa). Ann Bot 69(2):101–112CrossRefGoogle Scholar
  41. The Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447:661–678CrossRefPubMedCentralGoogle Scholar
  42. Tian F, Bradbury PJ, Brown PJ et al (2011) Genome-wide association study of leaf architecture in the maize nested association mapping population. Nat Genet 43(2):159–162CrossRefPubMedGoogle Scholar
  43. Wei X, Liu K, Zhang Y et al (2015) Genetic discovery for oil production and quality in sesame. Nat Commun 6:8609CrossRefPubMedPubMedCentralGoogle Scholar
  44. Xiao J, Li J, Yuan L et al (1995) Dominance is the major genetic basis of heterosis in rice as revealed by QTL analysis using molecular markers. Genetics 140(2):745–754PubMedPubMedCentralGoogle Scholar
  45. Xu X, Chen H, Fujimura T et al (2008) Fine mapping of a strong QTL of field resistance against rice blast, Pikahei-1(t), from upland rice Kahei, utilizing a novel resistance evaluation system in the greenhouse. Theor Appl Genet 117(6):997–1008CrossRefPubMedGoogle Scholar
  46. Yamamoto T, Yonemaru J, Yano M (2009) Towards the understanding of complex traits in rice: substantially or superficially? DNA Res 16(3):141–154CrossRefPubMedPubMedCentralGoogle Scholar
  47. Yang J, Zhao X, Cheng K et al (2012) A killer-protector system regulates both hybrid sterility and segregation distortion in rice. Science 337:1336–1340CrossRefPubMedGoogle Scholar
  48. Yano K, Yamamoto E, Aya K et al (2016) Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nat Genet 48(8):927–934CrossRefPubMedGoogle Scholar
  49. Yu J, Pressoir G, Briggs WH et al (2005) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38(2):203–208CrossRefPubMedGoogle Scholar
  50. Yu B, Lin Z, Li H et al (2008) TAC1, a major quantitative trait locus controlling tiller angle in rice. Plant J 52:891–898CrossRefGoogle Scholar
  51. Zhang Q, Li J, Xue Y et al (2008) Rice 2020: a call for an international coordinated effort in rice functional genomics. Mol Plant 1(5):715–719CrossRefPubMedGoogle Scholar
  52. Zhang Z, Ersoz E, Lai CQ et al (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42(4):355–360CrossRefPubMedPubMedCentralGoogle Scholar
  53. Zhao K, Tung CW, Eizenga GC et al (2011) Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nat Commun 2:467CrossRefPubMedPubMedCentralGoogle Scholar
  54. Zhou G, Chen Y, Yao W et al (2012) Genetic composition of yield heterosis in an elite rice hybrid. Proc Natl Acad Sci USA 109(39):15847–15852CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.College of Life and Environmental SciencesShanghai Normal UniversityShanghaiChina
  2. 2.National Center for Gene Research, CAS Center for Excellence of Molecular Plant SciencesInstitute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of SciencesShanghaiChina

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