Details

Autor(en) / Beteiligte

• Islam, A. S. M. Faridul

Titel

Genome-Wide Association Mapping for Rice Grain Quality and Nutrition

Ort / Verlag

ProQuest Dissertations & Theses

Erscheinungsjahr

2021

Quelle

ProQuest Dissertations & Theses A&I

Beschreibungen/Notizen

• Being a staple food for half of the world population, rice plays a crucial role in terms of food security, economic impact, and nutrition. Superior rice grain quality is considered as one of the key characteristics selected by rice breeders during variety development and demanded by consumers when buying the rice product. Rice grain quality has four facets, including milling, appearance, eating and cooking, and nutritional quality. Genetically, grain quality traits are complex and quantitatively inherited, controlling by pleiotropic genes/QTLs with environmental effect. The present study was conducted to identify the genetic basis (QTLs) of grain quality traits by using single-locus (three models) and multilocus (six models) methods of genome-wide association studies (GWAS) using 174 diverse rice accessions and 6,565 SNP markers. A total of 147 QTLs were identified for mineral elements, 216 QTLs were identified for grain appearance, milling, eating and nutritional traits, and 17 QTLs for resistant starch (RS) content. While 43 (29%), 28 (13%) and 1 (5%) of the identified QTLs co-located with the positions of known genes, QTLs, and markers reported previously, the remaining 104, 188 and 16 QTLs were novel. While single-locus methods alone detected 110, 106 and 9 SNPs for minerals, appearance and nutritional and RS content, respectively, 22, 64 and 3 SNPs were found by multi-locus methods alone, and 15, 46 and 5 QTLs were found by both GWAS methods. By conducting in silico gene expression analysis to identify candidate genes for the respective traits, 792 of 3129, 1329 of 4609 and 122 of 381 genes that were mined within the linkage disequilibrium distance of significant SNPs (250kb) were found being expressed in the rice reproductive stage. This study demonstrated the usefulness of using multiple GWAS methods as a complement to each other to identify as accurate QTLs for the corresponding traits. This study also suggests that there are still many QTLs yet to be discovered across the diversity of rice accessions. The identified common QTLs along with novel QTLs will be valuable resources for further gene functional characterization that can help accelerate the genetic improvement of rice grain quality traits.