Genomic regions and candidate genes selected during the breeding of rice in Vietnam. (9th July 2022)

• Record Type: Journal Article
• Authors: Higgins, Janet; Santos, Bruno; Khanh, Tran Dang; Trung, Khuat Huu; Duong, Tran Duy; Doai, Nguyen Thi Phuong; Hall, Anthony; Dyer, Sarah; Ham, Le Huy; Caccamo, Mario; De Vega, Jose
• Is Part Of: Evolutionary applications. Volume 15:Number 7(2022)
• Page Start: 1141
• Page End: 1161
• Publication Date: 2022-07-09
• Subjects: allele mining -- genome scan -- landraces -- rice -- selection; Evolution (Biology) -- Periodicals; Genetics -- Periodicals; Natural selection -- Periodicals; Ecology -- Periodicals; 576.8
• DOI: 10.1111/eva.13433
• Languages: English
• ISSNs: 1752-4571

Abstract

Abstract: Vietnam harnesses a rich diversity of rice landraces adapted to a range of conditions, which constitute a largely untapped source of diversity for the continuous improvement of cultivars. We previously identified a strong population structure in Vietnamese rice, which is captured in five Indica and four Japonica subpopulations, including an outlying Indica‐5 group. Here, we leveraged that strong differentiation and 672 native rice genomes to identify genomic regions and genes putatively selected during the breeding of rice in Vietnam. We identified significant distorted patterns in allele frequency (XP‐CLR) and population differentiation scores ( F ST ) resulting from differential selective pressures between native subpopulations, and later annotated them with QTLs previously identified by GWAS in the same panel. We particularly focussed on the outlying Indica‐5 subpopulation because of its likely novelty and differential evolution, where we annotated 52 selected regions, which represented 8.1% of the rice genome. We annotated the 4576 genes in these regions and selected 65 candidate genes as promising breeding targets, several of which harboured alleles with nonsynonymous substitutions. Our results highlight genomic differences between traditional Vietnamese landraces, which are likely the product of adaption to multiple environmental conditions and regional culinary preferences in a very diverse country. We also verified the applicability of this genome scanning approach to identify potential regions harbouring novel loci and alleles to breed a new generation of sustainable and resilient rice.