five

Development of an Alfalfa SNP Array and Its Use to Evaluate Patterns of Population Structure and Linkage Disequilibrium

收藏
Figshare2016-01-18 更新2026-04-29 收录
下载链接:
https://figshare.com/articles/dataset/_Development_of_an_Alfalfa_SNP_Array_and_Its_Use_to_Evaluate_Patterns_of_Population_Structure_and_Linkage_Disequilibrium_/898946
下载链接
链接失效反馈
官方服务:
资源简介:
A large set of genome-wide markers and a high-throughput genotyping platform can facilitate the genetic dissection of complex traits and accelerate molecular breeding applications. Previously, we identified about 0.9 million SNP markers by sequencing transcriptomes of 27 diverse alfalfa genotypes. From this SNP set, we developed an Illumina Infinium array containing 9,277 SNPs. Using this array, we genotyped 280 diverse alfalfa genotypes and several genotypes from related species. About 81% (7,476) of the SNPs met the criteria for quality control and showed polymorphisms. The alfalfa SNP array also showed a high level of transferability for several closely related Medicago species. Principal component analysis and model-based clustering showed clear population structure corresponding to subspecies and ploidy levels. Within cultivated tetraploid alfalfa, genotypes from dormant and nondormant cultivars were largely assigned to different clusters; genotypes from semidormant cultivars were split between the groups. The extent of linkage disequilibrium (LD) across all genotypes rapidly decayed to 26 Kbp at r2 = 0.2, but the rate varied across ploidy levels and subspecies. A high level of consistency in LD was found between and within the two subpopulations of cultivated dormant and nondormant alfalfa suggesting that genome-wide association studies (GWAS) and genomic selection (GS) could be conducted using alfalfa genotypes from throughout the fall dormancy spectrum. However, the relatively low LD levels would require a large number of markers to fully saturate the genome.
创建时间:
2016-01-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作