Jernigan Kendra L, Godoy Jayfred V, Huang Meng, Zhou Yao, Morris Craig F, Garland-Campbell Kimberly A, Zhang Zhiwu, Carter Arron H
Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States.
Western Wheat Quality Laboratory, Agricultural Research Service, United States Department of Agriculture, Pullman, WA, United States.
Front Plant Sci. 2018 Mar 9;9:271. doi: 10.3389/fpls.2018.00271. eCollection 2018.
Soft white wheat is used in domestic and foreign markets for various end products requiring specific quality profiles. Phenotyping for end-use quality traits can be costly, time-consuming and destructive in nature, so it is advantageous to use molecular markers to select experimental lines with superior traits. An association mapping panel of 469 soft white winter wheat cultivars and advanced generation breeding lines was developed from regional breeding programs in the U.S. Pacific Northwest. This panel was genotyped on a wheat-specific 90 K iSelect single nucleotide polymorphism (SNP) chip. A total of 15,229 high quality SNPs were selected and combined with best linear unbiased predictions (BLUPs) from historical phenotypic data of the genotypes in the panel. Genome-wide association mapping was conducted using the Fixed and random model Circulating Probability Unification (FarmCPU). A total of 105 significant marker-trait associations were detected across 19 chromosomes. Potentially new loci for total flour yield, lactic acid solvent retention capacity, flour sodium dodecyl sulfate sedimentation and flour swelling volume were also detected. Better understanding of the genetic factors impacting end-use quality enable breeders to more effectively discard poor quality germplasm and increase frequencies of favorable end-use quality alleles in their breeding populations.
软质白小麦在国内外市场用于各种需要特定品质特征的终端产品。对最终用途品质性状进行表型分析成本高、耗时且具有破坏性，因此使用分子标记来选择具有优良性状的实验品系具有优势。一个由469个软质白冬小麦品种和高代育种系组成的关联作图群体是从美国太平洋西北地区的区域育种计划中培育出来的。该群体在一个小麦专用的90K iSelect单核苷酸多态性（SNP）芯片上进行了基因分型。共选择了15229个高质量的SNP，并与该群体中基因型的历史表型数据的最佳线性无偏预测（BLUPs）相结合。使用固定和随机模型循环概率统一法（FarmCPU）进行全基因组关联作图。在19条染色体上共检测到105个显著的标记-性状关联。还检测到了总面粉产量、乳酸溶剂保留能力、面粉十二烷基硫酸钠沉淀和面粉膨胀体积的潜在新位点。更好地了解影响最终用途品质的遗传因素，使育种者能够更有效地淘汰劣质种质，并提高其育种群体中有利的最终用途品质等位基因的频率。
