Rice Genomics and Genetics 2024, Vol.15, No.2, 48-57 http://cropscipublisher.com/index.php/rgg 57 genetics, 49(7): 1089-1098. https://doi.org/10.1038/ng.3887 Fang L., Wang Q., Chen J.D., Liu B.L., Zhang Z.Y., Guan X.Y., Chen S.Q., Zhou B.L., Mei G.F., Sun J.L., Pan Z.E., He S.P., Xiao S.H., Shi W.J., Gong W.F., Liu J.G., Ma J., Cai C.P., Zhu X.F., Guo W.Z., Du X.M., and Zhang T.Z., 2017, Genomic analyses in cotton identify signatures of selection and loci associated with fiber quality and yield traits, Nature Genetics, 49: 1089-1098. https://doi.org/10.1038/ng.3887 Klein R.J., Zeiss C., and Chew E.Y., 2005, Complement factor H polymorphism in age-related macular degeneration, Science, 308(5720): 385-389. https://doi.org/10.1126/science.1109557 Ma Z., He S., and Wang X., 2018, Resequencing a core collection of upland cotton identifies genomic variation and loci influencing fiber quality and yield, Nature Genetics, 50(6): 803-813. https://doi.org/10.1038/s41588-018-0119-7 Ming L.C., Fu D.B., Wu Z.N., Zhao H., Xu X.B., Xu T.T., Xiong X.H., Li M., Zheng Y., Li G., Yang L., Xia C.J., Zhou R.F., Liao K.Y., Yu Q., Chai W.Q., Li S.J., Liu Y.M., Wu X.K., Mao J.Q., Wei J.L., Li X., Wang L., Wu C.Y., and Xie W.B., 2023, Transcriptome-wide association analyses reveal the impact of regulatory variants on rice panicle architecture and causal gene regulatory networks, Nature Communications, 14(1): 7501. https://doi.org/10.1038/s41467-023-43077-6 Risch N., and Merikangas K., 1998, The future of genetic studies of complex human diseases, Epidemiology, 9(3): 350-354. https://doi.org/10.1097/00001648-199805000-00023 Song X.J., Kuroha T., Ayano M., Furuta T., Nagai K., Komeda N., Segami S., Miura K., Ogawa D., Kamura T., Su-zuki T., Higashiyama T., Yamasaki M., Mori H., Inukai Y., Wu J., Kitano H., Sakakibara H., Jacobsen S.E., Ashikari M., 2015, Rare allele of a previously unidentified histone H4 acetyltransferase enhances grain weight, yield, and plant biomass in rice, Proc. Natl. Acad. Sci. USA, 112: 76-81. https://doi.org/10.1073/pnas.1421127112 Tang F.F., Xu F. F., and Bao J.S., 2013, The application of genome-wide association study in genetics and breeding of rice, Journal of Nuclear Agricultural Sciences, 27(5): 598-606. Tian F., Bradbury P.J., and Brown P.J., 2011, Genome-wide as-sociation study of leaf architecture in the maize nested association mapping population, Nature Genetics, 43(2): 159-62. https://doi.org/10.1038/ng.746 Wang Y., Xiong G., Hu J., Jiang L., Yu H., Xu J., Fang Y., Zeng L., Xu E., Xu J., Ye W., Meng X., Liu R., Chen H., Jing Y., Wang Y., Zhu X., Li J., and Qian Q., 2015, Copy number variation at the GL7 locus contributes to grain size diversity in rice, Nat. Genet., 47: 944-948. https://doi.org/10.1038/ng.3346 Weng J., Wan X., Gao H., Guo T., Su N., Lei C., Zhang X., Cheng Z., Guo X., Wang J., Jiang L., Zhai H., and Wan J., 2018, Isolation and initial characterization of GW5, a major QTL associated with rice grain width and weight, Cell Res., 18: 1199-1209. https://doi.org/10.1038/cr.2008.307 Yano K., Yamamoto E., and Aya K., 2016, Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice, Nature Genetics, 48(8): 927-934. https://doi.org/10.1038/ng.3596 Yano K.L., Morinaka Y., Wang F.M., and Matsuoka M., 2019, GWAS with principal component analysis identifies a gene comprehensively controlling rice architecture, Proc. Natl. Acad. Sci. USA, 116(42): 21262-21267. https://doi.org/10.1073/pnas.1904964116
RkJQdWJsaXNoZXIy MjQ4ODYzNA==