Abstract:
The sunflower (Helianthus annuus L.) is one of the most essential oil crops in the world. Several component traits, including flowering time, plant height, stem diameter, seed weight, and kernel weight, determine sunflower seed and oil yield. Although the genetic mechanisms governing the variation of these yield-related traits have been studied using various approaches, genome-wide association studies (GWAS) have not been widely applied to sunflowers. In this study, a set of 342 sunflower accessions was evaluated in 2019 and 2020 using an incomplete randomized block design, and GWAS was conducted utilizing two complementary approaches: the mixed linear model (MLM) and the fixed and random model circulating probability unification (farmCPU) model by fitting 226,779 high-quality SNPs. As a result, GWAS identified a number of trait-associated SNPs. Those SNPs were located close to several genes that may serve as a basis for further molecular characterization and provide promising targets for sunflower yield improvement.
摘要:
向日葵(HelianthusannuusL.)是世界上最重要的油料作物之一。几个成分特征,包括开花时间,植物高度,阀杆直径,种子重量,和内核重量,确定葵花籽和油的产量。尽管已经使用各种方法研究了控制这些产量相关性状变异的遗传机制,全基因组关联研究(GWAS)尚未广泛应用于向日葵。在这项研究中,2019年和2020年,使用不完全随机区组设计对342份向日葵种质进行了评估,和GWAS利用两种互补的方法进行:混合线性模型(MLM)和固定和随机模型循环概率统一(farmCPU)模型,通过拟合226,779个高质量的SNP。因此,GWAS鉴定了许多性状相关的SNP。这些SNP位于几个基因附近,这些基因可以作为进一步分子表征的基础,并为向日葵产量的提高提供有希望的目标。