[关键词]
[摘要]
玉米籽粒氮浓度与品质紧密相关,其遗传机制的解析对玉米品质育种具有重要意义。本研究利用 253 份玉米自交系为关联群体,利用一般线性模型(GLM)、混合线性模型(MLM)、固定和随机模型交替概率统一(FarmCPU)和基因组相关预测集成工具(GAPIT)分别对其籽粒氮浓度进行全基因组关联分析。共鉴定 25 个与籽粒氮浓度显著关联的 SNP(P<1.72E-05)。其中,GLM 、FarmCPU 和 GAPIT 方法分别检测到 12 个、15 个和 1 个位点。S3_202120604、S1_2007087 47 和 S5_10258682 在 GLM 和 FarmCPU 两种方法中均能检测到。Bin1.06、Bin3.07、Bin5.04、Bin1.07和Bin5.02可能是影响籽粒氮浓度的重要区段。共挖掘30个相关候选基因,其中 Zm00001d031747、Zm00001d031749、Zm00001d031753、Zm00001d043502和Zm00001d01339等可能是影响玉米籽粒氮浓度的关键候选基因。
[Key word]
[Abstract]
Nitrogen concentration in maize grains is closely related to maize quality, and the analysis of its genetic mechanism is great significance for maize quality breeding. In this study, we used 253 maize inbred lines as an association population, and used general linear model (GLM), mixed linear model (MLM), fixed and random model alternation probability Unification (FarmCPU) and Genome-wide correlation Prediction Integration (GAPIT) to conduct genome-wide association analysis for grain nitrogen concentration. A total of 25 SNPS (P<1.72E-05) were identified. Twelve,fifteen and one SNPs were detected by GLM, FarmCPU and GAPIT methods, respectively. S3_202120604, S1_200708747 and S5_10258682 can be detected in both GLM and FarmCPU methods. Bin1.06, Bin3.07, Bin5.04, Bin1.07 and Bin5.02 may be the important genomic regions for grain nitrogen concentration. A total of 30 candidate genes were identified, among which Zm00001d031747, Zm00001d031749, Zm00001d031753, Zm00001d043502 and Zm00001d01339 may be the key candidate genes for maize grain nitrogen concentration.
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[基金项目]
国家重点研发计划(2021YFD1200703)、河南省重大科技专项(201300111100)、中央引导地方科技发展专项资金(YDZX20214100003985)和河南省科技攻关计划项目(222102110471)共同资助。