Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models.
Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models.
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使用单基因座和多基因座模型对玉米淀粉糊化特性进行全基因组关联作图
DOI：
10.3389/fpls.2018.01311
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发表时间：
2018
影响因子：
5.6
通讯作者：
Xu C
中科院分区：
文献类型：
--
作者：
Xu Y;Yang T;Zhou Y;Yin S;Li P;Liu J;Xu S;Yang Z;Xu C
玉米淀粉在食品加工和工业应用中起着至关重要的作用。糊化特性是淀粉最重要的特性，它对淀粉的加工性能、风味特性、储藏、蒸煮和烘焙都有很大的影响。了解淀粉糊化特性的遗传基础将有助于控制特定目的的淀粉特性。全基因组关联研究正成为剖析复杂性状的有力工具。在这里，我们利用一组230个自交系和145,232个SNPs，使用一个单基因座方法、全基因组高效混合模型关联(GEMA)和三个多基因座方法(FASTmrEMMA、FarmCPU和Lasso)对玉米淀粉的7个糊化特性进行了广义遗传分析。用这四种方法共鉴定了60个影响淀粉糊化特性的数量性状核苷酸(QTN)。FASTmrEMMA检测到的QTN最多(29个)，其次是FarmCPU(19个)和Lasso(12个)，Gema检测到的QTN最少(7个)。在这些QTN中，有7个QTN同时被一种以上的方法识别。我们进一步研究了这些显著相关的QTN的位置，以寻找可能的候选基因。这些候选基因和重要的QTN为进一步了解淀粉糊化特性的分子机制提供了指导。我们还利用蒙特卡罗模拟比较了四种GWAS方法的统计功率和I类误差。结果表明，多轨迹法比单轨迹法具有更强的检测能力，多轨迹法与单轨迹法相结合有助于提高广义遗传算法的检测能力。
Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pasting properties will be beneficial for manipulation of starch properties for a given purpose. Genome-wide association studies (GWAS) are becoming a powerful tool for dissecting the complex traits. Here, we carried out GWAS for seven pasting properties of maize starch with a panel of 230 inbred lines and 145,232 SNPs using one single-locus method, genome-wide efficient mixed model association (GEMMA), and three multi-locus methods, FASTmrEMMA, FarmCPU, and LASSO. We totally identified 60 quantitative trait nucleotides (QTNs) for starch pasting properties with these four GWAS methods. FASTmrEMMA detected the most QTNs (29), followed by FarmCPU (19) and LASSO (12), GEMMA detected the least QTNs (7). Of these QTNs, seven QTNs were identified by more than one method simultaneously. We further investigated locations of these significantly associated QTNs for possible candidate genes. These candidate genes and significant QTNs provide the guidance for further understanding of molecular mechanisms of starch pasting properties. We also compared the statistical powers and Type I errors of the four GWAS methods using Monte Carlo simulations. The results suggest that the multi-locus method is more powerful than the single-locus method and a combination of these multi-locus methods could help improve the detection power of GWAS.
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DOI：
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