Hinze Lori L, Hulse-Kemp Amanda M, Wilson Iain W, Zhu Qian-Hao, Llewellyn Danny J, Taylor Jen M, Spriggs Andrew, Fang David D, Ulloa Mauricio, Burke John J, Giband Marc, Lacape Jean-Marc, Van Deynze Allen, Udall Joshua A, Scheffler Jodi A, Hague Steve, Wendel Jonathan F, Pepper Alan E, Frelichowski James, Lawley Cindy T, Jones Don C, Percy Richard G, Stelly David M
USDA-ARS, Crop Germplasm Research Unit, College Station, TX, 77845, USA.
Department of Plant Sciences and Seed Biotechnology Center, University of California-Davis, Davis, CA, 95616, USA.
BMC Plant Biol. 2017 Feb 3;17(1):37. doi: 10.1186/s12870-017-0981-y.
Cotton germplasm resources contain beneficial alleles that can be exploited to develop germplasm adapted to emerging environmental and climate conditions. Accessions and lines have traditionally been characterized based on phenotypes, but phenotypic profiles are limited by the cost, time, and space required to make visual observations and measurements. With advances in molecular genetic methods, genotypic profiles are increasingly able to identify differences among accessions due to the larger number of genetic markers that can be measured. A combination of both methods would greatly enhance our ability to characterize germplasm resources. Recent efforts have culminated in the identification of sufficient SNP markers to establish high-throughput genotyping systems, such as the CottonSNP63K array, which enables a researcher to efficiently analyze large numbers of SNP markers and obtain highly repeatable results. In the current investigation, we have utilized the SNP array for analyzing genetic diversity primarily among cotton cultivars, making comparisons to SSR-based phylogenetic analyses, and identifying loci associated with seed nutritional traits.
The SNP markers distinctly separated G. hirsutum from other Gossypium species and distinguished the wild from cultivated types of G. hirsutum. The markers also efficiently discerned differences among cultivars, which was the primary goal when designing the CottonSNP63K array. Population structure within the genus compared favorably with previous results obtained using SSR markers, and an association study identified loci linked to factors that affect cottonseed protein content.
Our results provide a large genome-wide variation data set for primarily cultivated cotton. Thousands of SNPs in representative cotton genotypes provide an opportunity to finely discriminate among cultivated cotton from around the world. The SNPs will be relevant as dense markers of genome variation for association mapping approaches aimed at correlating molecular polymorphisms with variation in phenotypic traits, as well as for molecular breeding approaches in cotton.
棉花种质资源包含有益等位基因,可用于培育适应新出现的环境和气候条件的种质。传统上,种质材料和品系是根据表型特征进行鉴定的,但表型分析受到视觉观察和测量所需的成本、时间和空间的限制。随着分子遗传学方法的进步,由于能够测量的遗传标记数量增加,基因型分析越来越能够识别种质材料之间的差异。两种方法的结合将大大提高我们鉴定种质资源的能力。最近的努力最终确定了足够数量的单核苷酸多态性(SNP)标记,以建立高通量基因分型系统,如CottonSNP63K芯片,这使研究人员能够有效地分析大量SNP标记并获得高度可重复的结果。在本研究中,我们利用该SNP芯片主要分析棉花品种间的遗传多样性,与基于简单序列重复(SSR)的系统发育分析进行比较,并鉴定与种子营养性状相关的基因座。
SNP标记清晰地将陆地棉与其他棉属物种区分开来,并区分了陆地棉的野生类型和栽培类型。这些标记还有效地辨别了品种间的差异,这是设计CottonSNP63K芯片时的主要目标。该属内的群体结构与先前使用SSR标记获得的结果相比具有优势,并且关联研究确定了与影响棉籽蛋白质含量的因素相关的基因座。
我们的结果为主要栽培棉花提供了一个全基因组范围的大量变异数据集。代表性棉花基因型中的数千个SNP为精细区分来自世界各地的栽培棉花提供了机会。这些SNP将作为基因组变异的密集标记,用于旨在将分子多态性与表型性状变异相关联的关联作图方法,以及棉花的分子育种方法。