Genome‐wide association coupled gene to gene interaction studies unveil novel epistatic targets among major effect loci impacting rice grain chalkiness. Issue 5 (9th December 2020)

• Record Type: Journal Article
• Authors: Misra, Gopal; Badoni, Saurabh; Parween, Sabiha; Singh, Rakesh Kumar; Leung, Hei; Ladejobi, OluFunmilayo; Mott, Richard; Sreenivasulu, Nese
• Is Part Of: Plant biotechnology journal. Volume 19:Issue 5(2021)
• Page Start: 910
• Page End: 925
• Publication Date: 2020-12-09
• Subjects: epistatic interactions -- genome‐wide association studies -- gene regulatory networks -- grain quality -- percent grain chalkiness -- quantitative trait loci; Plant biotechnology -- Periodicals; Plant genetic engineering -- Periodicals; 630.272
• DOI: 10.1111/pbi.13516
• Languages: English
• ISSNs: 1467-7644

Abstract

Abstract: Rice varieties whose quality is graded as excellent have a lower percent grain chalkiness (PGC) of two per cent and below with higher whole grain yields upon milling, leading to higher economic returns for farmers. We have conducted a genome‐wide association study (GWAS) using a combined population panel of indica and japonica rice varieties, and identified a total of 746 single nucleotide polymorphisms (SNPs) that were strongly associated with the chalk phenotype, covered 78 Quantitative Trait Loci (QTL) regions. Among them, 21 were high‐value QTLs, as they explained at least 10 % of the phenotypic variance for PGC. A combined epistasis and GWAS was applied to dissect the genetics of the complex chalkiness trait, and its regulatory cascades were validated using gene regulatory networks. Promising novel epistatic interactions were found between the loci of chromosomes 6 ( PGC6.1 ) and 7 ( PGC7.8 ) that contributed to lower PGC. Based on haplotype mining only a few modern rice varieties confounded with a lower chalkiness, and they possess several PGC QTLs. The importance of PGC6.1 was validated through multi‐parent advanced generation intercrosses and several low‐chalk lines possessing superior haplotypes were identified. The results of this investigation have deciphered the underlying genetic networks that can reduce PGC to 2%, and will thus support future breeding programs to improve the grain quality of elite genetic material with high‐yielding potentials.