中国农业科学 ›› 2022, Vol. 55 ›› Issue (1): 219-232.doi: 10.3864/j.issn.0578-1752.2022.01.018

• 研究简报 • 上一篇    

芝麻产量相关性状的多位点全基因组关联分析及候选基因预测

崔承齐1(),刘艳阳1(),江晓林1,孙知雨2,杜振伟1,武轲1,梅鸿献1(),郑永战1()   

  1. 1河南省农业科学院芝麻研究中心,郑州 450008
    2华南师范大学生命科学学院,广州 510631
  • 收稿日期:2021-06-23 接受日期:2021-09-18 出版日期:2022-01-01 发布日期:2022-01-07
  • 通讯作者: 梅鸿献,郑永战
  • 作者简介:崔承齐,E-mail: chengqicui_1986@126.com。|刘艳阳,E-mail: liuyanyang001@163.com
  • 基金资助:
    财政部和农业农村部:国家现代农业产业技术体系(CARS-14-1-01);河南省重大科技专项(201300110600);河南省重点研发与推广专项(202102110026);河南省农业科学院优秀青年科技基金(2020YQ26);河南省农业科学院科技创新创意项目(2020CX25);河南省农业科学院基础性科研项目(2020JC008);河南省农业科学院基础性科研项目(2021JC013);河南省农业科学院基本科研业务费(2021ZC69)

Multi-Locus Genome-Wide Association Analysis of Yield-Related Traits and Candidate Gene Prediction in Sesame (Sesamum indicum L.)

CUI ChengQi1(),LIU YanYang1(),JIANG XiaoLin1,SUN ZhiYu2,DU ZhenWei1,WU Ke1,MEI HongXian1(),ZHENG YongZhan1()   

  1. 1Henan Sesame Research Center, Henan Academy of Agricultural Sciences, Zhengzhou 450008
    2College of Life Sciences, South China Normal University, Guangzhou 510631
  • Received:2021-06-23 Accepted:2021-09-18 Online:2022-01-01 Published:2022-01-07
  • Contact: HongXian MEI,YongZhan ZHENG

摘要:

【目的】通过对芝麻产量相关性状的全基因组关联分析,挖掘与产量性状关联的SNP位点及预测候选基因,为通过分子标记辅助选择育种等方式提高芝麻产量提供技术基础。【方法】以363份不同遗传背景和地理来源的芝麻种质资源构成的自然群体为研究对象,调查2年2点4环境下8个产量相关性状(单株产量、单株蒴数、蒴粒数、千粒重、株高、主茎果轴长、始蒴高度和表观收获指数)的表型值,借助覆盖全基因组的42 781个SNP标记,利用多位点SNP随机效应混合线性模型(multi-locus random-SNP-effect mixed linear model,mrMLM)对8个产量相关性状进行全基因组关联分析,检测与产量相关性状显著关联的SNP位点,并预测候选基因。【结果】在4个不同环境下,8个产量相关性状表现出广泛的表型变异,变异系数为6.51%—33.57%;相关性分析表明单株产量与单株蒴数、株高、主茎果轴长、表观收获指数呈极显著正相关;方差分析表明产量相关性状的基因型效应、环境效应、基因型与环境互作效应均达到了极显著水平。通过多位点全基因组关联分析共检测到210个与产量相关性状显著关联的SNP,在2018年南阳环境下检测到47个SNP,解释表型变异的1.63%—17.29%;在2019年南阳环境下检测到35个SNP,解释表型变异的1.94%—11.90%;在2018年平舆环境下检测到35个SNP,解释表型变异的2.15%—15.90%;在2019年平舆环境下检测到53个SNP,解释表型变异的1.25%—11.13%;在4个环境的综合BLUP条件下检测到75个SNP,解释表型变异的1.44%—13.58%。上述210个SNP涉及到175个位点,其中10个位点在3个及以上环境中被重复检测到。在这10个位点基因组区域内,共鉴定到214个候选基因,其中156个候选基因具有功能注释,主要涉及植物代谢、生物调控、生长发育等生物学过程。根据功能注释筛选出4个可能与芝麻产量相关的候选基因,其中SIN_1006338编码1-氨基环丙烷-1-羧酸合酶3(1-aminocyclopropane-1-carboxylate synthase 3-like),参与乙烯的生物合成;SIN_1024330编码碱性螺旋-环-螺旋(basic helix-loop-helix)转录因子,负向调控植物细胞和器官的伸长;SIN_1014512编码吲哚-3-乙酸-酰胺合成酶GH3.6(indole-3-acetic acid-amido synthetase GH3.6),参与调控茎和下胚轴细胞的伸长生长;SIN_1011473编码泛素受体蛋白DA1(protein DA1-like),参与调节植物细胞增殖周期。【结论】通过多位点SNP随机效应混合线性模型的全基因组关联分析,检测到175个与产量相关性状显著关联的位点,筛选出4个可能与产量相关的重要候选基因。

关键词: 芝麻, 产量性状, 多位点全基因组关联分析, 功能注释, 候选基因

Abstract:

【Objective】 Genome-wide association studies (GWAS) were performed using multi-locus random-SNP-effect mixed linear (mrMLM) model to identify the significantly associated SNPs and candidate genes with yield traits, and lay a foundation for molecular marker-assisted selection breeding for sesame high yield.【Method】 In this study, 363 diverse sesame lines were assembled into an association-mapping panel. Eight yield-related traits, including seed yield per plant, capsule number per plant, seed number per capsule, 1000-seed weight, plant height, capsule axis length, first capsule height and apparent harvest index, were investigated. Genome-wide association studies were performed using mrMLM to detect significantly associated SNPs and predict important candidate genes related to yield traits.【Result】 Eight yield-related traits measured in four environments exhibited extensive phenotypic variation with 1.63%-17.29% of phenotypic variation coefficients. The seed yield per plant was positively correlated with capsule number per plant, plant height, capsule axis length, and apparent harvest index respectively. Analysis of variance indicated that significant variations were observed across environment, genotype, and the genotype × environment interaction. GWAS were performed and a total of 210 SNPs were detected for yield traits. Among these SNPs, 47, 35, 35, 53, and 75 SNPs were detected in 2018NY, 2019NY, 2018PY, 2019PY and BLUP, explaining 1.63%-17.29%, 1.94%-11.90%, 2.15%-15.90%, 1.25%-11.13% and 1.44%-13.58% of phenotypic variation, respectively. These 210 SNPs corresponded to 175 loci, and 10 loci were detected in more than 3 environments. A total of 214 candidate genes were identified, including 156 genes involved in metabolism, biological regulation, and developmental and growth process. Among these genes, 4 genes were selected as important candidate genes. SIN_1006338, encoding 1-aminocyclopropane-1-carboxylate synthase 3-like protein, was involved in ethylene biosynthesis. SIN_1024330, encoding transcription factor IBH1-like 1, was involved in regulating cell and organ elongation. SIN_1014512, encoding indole-3-acetic acid-amido synthetase GH3.6, was involved in shoot and hypocotyl cell elongation. SIN_1011473, encoding protein DA1-like, was involved in restricting the period of cell proliferation.【Conclusion】 One hundred and seventy-five loci were identified by mrMLM, and 4 important genes related to yield traits were selected.

Key words: Sesamum indicum L., yield-related traits, genome-wide association studies, function annotation, candidate gene