Document Type

Article

Publication Date

12-1-2020

Abstract

Rice is an important cereal for human consumption. Identification of QTLs for important agronomic traits with high resolution is essential to the identification of genes and marker-assisted breeding to improve rice productivity. A genotyping by sequencing (GBS)-based high-resolution SNP linkage developed in a recombinant inbred lines (RIL) population of a japonica (Bengal) × indica (Pokkali) cross was used for QTL analysis of traits such as days to heading, plant height, panicle length, flag leaf length, 1000 kernel weight, number of unfilled grains, number of filled grains, grain width, grain length, and awns using interval mapping and inclusive composite interval mapping approaches. Among the 102 additive QTLs identified for the ten traits, 23 QTLs were major effect QTLs. A chromosomal region flanking the sd-1 gene colocalized the QTLs for plant height, panicle length, and flag leaf length, suggesting possible pleiotropic effects on the expression of these traits. Our study not only reduced confidence intervals of previously identified QTLs but also validated several known genes for heading date (Hd1), panicle length (APO1), grain width (GW2, GW5) and awn length (An-1). Furthermore, candidate genes for several agronomic traits were identified. Annotations of genes within novel QTLs for yield-related traits revealed that RCN4 (LOC_Os06g45460), expansin precursor (LOC_Os02g51040), and RGB1 (LOC_Os03g46650) are promising candidates for yield enhancement. Our study provided genetic insights into the important agronomic and yield enhancing traits through identification of QTLs and candidate genes for future validation and molecular breeding to improve rice yield potential.

Publication Source (Journal or Book title)

Plant Gene

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