Discovery of genomic regions and candidate genes for grain weight employing next generation sequencing based QTL-seq approach in rice (Oryza sativa L.).

Rice (Oryza sativa L.) yield enhancement is one of the prime objectives of plant breeders. Elucidation of the inheritance of grain weight, a key yield component trait, is of paramount importance for raising the yield thresholds in rice. In the present investigation, we employed Next-Generation Sequencing based QTL-seq approach to identify major genomic regions associated with grain weight using mapping populations derived from a cross between BPT5204 and MTU3626. QTL-seq analysis identified three grain weight quantitative trait loci (QTL) viz., qGW1 (35-40 Mb), qGW7 (10-18 Mb), and qGW8 (2-5 Mb) on chromosomes 1, 7 and 8, respectively and all are found to be novel. Further, qGW8 was confirmed through conventional QTL mapping in F2, F3 and BC1F2 populations and found to explain the phenotypic variance of 17.88%, 16.70% and 15.00%, respectively, indicating a major QTL for grain weight. Based on previous reports, two candidate genes in the qGW8 QTL were predicted i.e., LOC_Os08g01490 (Cytochrome P450), and LOC_Os08g01680 (WD domain, G-beta repeat domain containing protein) and through in silico analysis they were found to be highly expressed in reproductive organs during different stages of grain development. Here, we have demonstrated that QTL-seq is one of the rapid approaches to uncover novel QTLs controlling complex traits. The candidate genes identified in the present study undoubtedly enhance our understanding of the mechanism and inheritance of the grain weight. These candidate genes can be exploited for yield enhancement after confirmation through complementary studies.

Uncovering of natural allelic variants of key yield contributing genes by targeted resequencing in rice (Oryza sativa L.).

In rice (Oryza sativa L.), during the course of domestication, numerous beneficial alleles remain untapped in the progenitor wild species and landraces. This study aims at uncovering these promising alleles of six key genes influencing the yield, such as DEP1, Ghd7, Gn1a, GS3, qSW5 and sd1 by targeted resequencing of the 200 rice genotypes. In all, 543 nucleotide variations including single nucleotide polymorphisms and insertion and deletion polymorphisms were identified from the targeted genes. Of them, 225 were novel alleles, which identified in the present study only and 91 were beneficial alleles that showed significant association with the yield traits. Besides, we uncovered 128 population-specific alleles with indica being the highest of 79 alleles. The neutrality tests revealed that pleiotropic gene, Ghd7 and major grain size contributing gene, GS3 showed positive and balanced selection, respectively during the domestication. Further, the haplotype analysis revealed that some of the rice genotypes found to have rare haplotypes, especially the high yielding variety, BPT1768 has showed maximum of three genes such as Gn1a-8, qSW5-12 and GS3-29. The rice varieties with novel and beneficial alleles along with the rare haplotypes identified in the present study could be of immense value for yield improvement in the rice breeding programs.