Comparative Genetics of Seed Size Traits in Divergent Cereal Lineages Represented by Sorghum (Panicoidae) and Rice (Oryzoidae). Issue 6 (1st June 2015)

• Record Type: Journal Article
• Authors: Zhang, Dong; Li, Jingping; Compton, Rosana O; Robertson, Jon; Goff, Valorie H; Epps, Ethan; Kong, Wenqian; Kim, Changsoo; Paterson, Andrew H
• Is Part Of: G3. Volume 5:Issue 6(2015)
• Page Start: 1117
• Page End: 1128
• Publication Date: 2015-06-01
• Subjects: quantitative trait locus -- genome-wide association studies; Genetics -- Research -- Periodicals; Genomics -- Periodicals; Genetics; Genomics; Genes; Genetics -- Research; Genomics; Electronic journals; Periodical; Periodicals; Fulltext; Internet Resources; Periodicals; 572.8
• DOI: 10.1534/g3.115.017590
• Languages: English
• ISSNs: 2160-1836

Abstract

Abstract: Seed size is closely related to fitness of wild plants, and its modification has been a key recurring element in domestication of seed/grain crops. In sorghum, a genomic and morphological model for panicoid cereals, a rich history of research into the genetics of seed size is reflected by a total of 13 likelihood intervals determined by conventional QTL (linkage) mapping in 11 nonoverlapping regions of the genome. To complement QTL data and investigate whether the discovery of seed size QTL is approaching "saturation, " we compared QTL data to GWAS for seed mass, seed length, and seed width studied in 354 accessions from a sorghum association panel (SAP) that have been genotyped at 265, 487 SNPs. We identified nine independent GWAS-based "hotspots" for seed size associations. Targeted resequencing near four association peaks with the most notable linkage disequilibrium provides further support of the role(s) of these regions in the genetic control of sorghum seed size and identifies two candidate causal variants with nonsynonymous mutations. Of nine GWAS hotspots in sorghum, seven have significant correspondence with rice QTL intervals and known genes for components of seed size on orthologous chromosomes. Identifying intersections between positional and association genetic data are a potentially powerful means to mitigate constraints associated with each approach, and nonrandom correspondence of sorghum (panicoid) GWAS signals to rice (oryzoid) QTL adds a new dimension to the ability to leverage genetic data about this important trait across divergent plants.