Germplasm collections are rich sources of genetic variation to improve crops for many valuable traits. Nested association mapping (NAM) populations can overcome the limitations of genome‐wide association studies (GWAS) in germplasm collections by reducing the effect of population structure. We exploited the genetic diversity of the USDA‐ARS wheat (Triticum aestivum L.) core collection by developing the Spring Wheat Multiparent Introgression Population (SWMIP). To develop this population, twenty‐five core parents were crossed and backcrossed to the Minnesota spring wheat cultivar RB07. The NAM population and 26 founder parents were genotyped using genotyping‐by‐sequencing and phenotyped for heading date, height, test weight, and grain protein content. After quality control, 20,312 markers with physical map positions were generated for 2,038 recombinant inbred lines (RILs). The number of RILs in each family varied between 58 and 96. Three GWAS models were utilized for quantitative trait loci (QTL) detection and accounted for known family stratification, genetic kinship, and both covariates. GWAS was performed on the whole population and also by bootstrap sampling of an equal number of RILs from each family. Greater power of QTL detection was achieved by treating families equally through bootstrapping. In total 16, 15, 12, and 13 marker‐trait associations (MTAs) were identified for heading date, height, test weight, and grain protein content, respectively. Some of these MTAs were coincident with major genes known to control the traits, but others were novel and contributed by the wheat core parents. The SWMIP will be a valuable source of genetic variation for spring wheat breeding.

中文翻译：

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嵌套关联映射的春小麦群体农艺和品质性状的遗传结构

种质资源是遗传变异的丰富来源，可以改善作物的许多宝贵性状。嵌套关联映射（NAM）种群可以通过减少种群结构的影响来克服种质资源集合中的全基因组关联研究（GWAS）的局限性。我们利用了USDA‐ARS小麦（Triticum aestivum）的遗传多样性L.）通过开发春小麦多亲基因渗入种群（SWMIP）进行核心收藏。为了发展这一种群，将二十五名核心父母与明尼苏达州春小麦品种RB07进行了杂交和回交。使用测序对NAM人群和26个创始父母进行基因分型，并根据分型表对抽穗期，身高，体重和谷物蛋白含量进行分型。经过质量控制后，为2038个重组自交系（RIL）生成了20312个具有物理图谱位置的标记。每个家庭的RIL数量在58至96之间。三种GWAS模型用于定量性状基因座（QTL）检测，并解释了已知的家庭分层，遗传亲属关系和这两个协变量。GWAS是在整个人群中进行的，并且还通过对每个家庭的相同数量的RIL进行自举采样。通过自举平等对待家庭，可以实现更高的QTL检测能力。共确定了16、15、12和13个标记性状关联（MTA），分别用于抽穗期，身高，体重和谷物蛋白质含量。这些MTA中的一些与已知控制该性状的主要基因相吻合，但其他一些则是新颖的，由小麦核心亲本贡献。SWMIP将成为春小麦育种遗传变异的宝贵来源。但另一些则是新颖的，是小麦核心父母的贡献。SWMIP将成为春小麦育种遗传变异的宝贵来源。但另一些则是新颖的，是小麦核心父母的贡献。SWMIP将成为春小麦育种遗传变异的宝贵来源。