International Rice Research Institute, South-Asia Hub, ICRISAT Campus, Hyderabad, India.
Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India.
Plant Biotechnol J. 2019 Aug;17(8):1612-1622. doi: 10.1111/pbi.13087. Epub 2019 Feb 15.
Though several genes governing various major traits have been reported in rice, their superior haplotype combinations for developing ideal variety remains elusive. In this study, haplotype analysis of 120 previously functionally characterized genes, influencing grain yield (87 genes) and grain quality (33 genes) revealed significant variations in the 3K rice genome (RG) panel. For selected genes, meta-expression analysis using already available datasets along with co-expression network provided insights at systems level. Also, we conducted candidate gene based association study for the 120 genes and identified 21 strongly associated genes governing 10-grain yield and quality traits. We report superior haplotypes upon phenotyping the subset of 3K RG panel, SD1-H8 with haplotype frequency (HF) of 30.13% in 3K RG panel, MOC1-H9 (HF: 23.08%), IPA1-H14 (HF: 6.64%), DEP3-H2 (HF: 5.59%), DEP1-H2 (HF: 37.53%), SP1-H3 (HF: 5.05%), LAX1-H5 (HF: 1.56%), LP-H13 (3.64%), OSH1-H4 (5.52%), PHD1-H14 (HF: 15.21%), AGO7-H15 (HF: 3.33%), ROC5-H2 (31.42%), RSR1-H8 (HF: 4.20%) and OsNAS3-H2 (HF: 1.00%). For heading date, Ghd7-H8 (HF: 3.08%), TOB1-H10 (HF: 4.60%) flowered early, Ghd7-H14 (HF: 42.60%), TRX1-H9 (HF: 27.97%), OsVIL3-H14 (HF: 1.72%) for medium duration flowering, while Ghd7-H6 (HF: 1.65%), SNB-H9 (HF: 9.35%) were late flowering. GS5-H4 (HF: 65.84%) attributed slender, GS5-H5 (HF: 29.00%), GW2-H2 (HF: 4.13%) were medium slender and GS5-H9 (HF: 2.15%) for bold grains. Furthermore, haplotype analysis explained possible genetic basis for superiority of selected mega-varieties. Overall, this study suggests the possibility for developing next-generation tailor-made rice with superior haplotype combinations of target genes suiting future food and nutritional demands via haplotype-based breeding.
尽管已经报道了几个控制各种主要性状的基因在水稻中，但它们用于开发理想品种的优异单倍型组合仍然难以捉摸。在这项研究中，对 120 个先前功能表征的基因的单倍型分析，这些基因影响谷物产量（87 个基因）和谷物品质（33 个基因），揭示了 3K 水稻基因组（RG）面板中的显著变化。对于选定的基因，使用已经可用的数据集进行的元表达分析以及共表达网络提供了系统水平的见解。此外，我们对 120 个基因进行了基于候选基因的关联研究，确定了 21 个与 10 粒产量和品质性状密切相关的基因。我们报告了在对 3K RG 面板的子集 SD1-H8 进行表型分析时的优异单倍型，其在 3K RG 面板中的单倍型频率（HF）为 30.13%，MOC1-H9（HF：23.08%），IPA1-H14（HF：6.64%），DEP3-H2（HF：5.59%），DEP1-H2（HF：37.53%），SP1-H3（HF：5.05%），LAX1-H5（HF：1.56%），LP-H13（3.64%），OSH1-H4（5.52%），PHD1-H14（HF：15.21%），AGO7-H15（HF：3.33%），ROC5-H2（31.42%），RSR1-H8（HF：4.20%）和 OsNAS3-H2（HF：1.00%）。对于抽穗期，Ghd7-H8（HF：3.08%），TOB1-H10（HF：4.60%）开花较早，Ghd7-H14（HF：42.60%），TRX1-H9（HF：27.97%），OsVIL3-H14（HF：1.72%）开花时间中等，而 Ghd7-H6（HF：1.65%），SNB-H9（HF：9.35%）开花较晚。GS5-H4（HF：65.84%）的穗粒细长，GS5-H5（HF：29.00%），GW2-H2（HF：4.13%）的穗粒中等细长，GS5-H9（HF：2.15%）的穗粒粗壮。此外，单倍型分析解释了选定巨型品种优异的可能遗传基础。总体而言，这项研究表明，通过基于单倍型的育种，有可能开发出具有优异目标基因单倍型组合的下一代定制型水稻，以满足未来的粮食和营养需求。
