Genome-wide analysis of polymorphisms identified domestication-associated polymorphism desert carrying important rice grain size/weight QTL
Kumar, A.; Daware, A.; Kumar, A.; Kumar, V.; Krishnan S, G.; Mondal, S.; Patra, B. C.; Singh, A. K.; Tyagi, A. K.; Parida, S. K.; Thakur, J. K.
Show abstract
Rice grain size and weight are major determinant of grain quality and yield and so have been under rigorous selection since domestication. However, genetic basis for contrasting grain size/weight trait among indian germplasm, and their association with domestication shaped evolutionary region is not studied before. To identify genetic basis of grain size/weight two long (LGG) and two short grain genotypes (SGG) were resequenced. LGG (LGR and Pusa Basmati 1121) differentiated from SGG (Sonasal and Bindli) by 504439 SNPs and 78166 InDels. The LRK gene cluster was significantly affected and a truncation mutation in the LRK8 kinase domain was uniquely associated with LGG. Phylogeny with 3000 diverse rice accessions revealed four sequenced genotypes belonged to japonica group and were at the edge of clades indicating source of genetic diversity available in Asian rice population. Five SNPs significantly were associated with grain size/weight and top three SNPs were validated in RIL mapping populations, suggesting this study as a valuable resource for high-throughput genotyping. A contiguous [~]6 Mb polymorphism desert region carrying a major grain weight QTL was identified on chromosome 5 in four sequenced genotypes. Further, among 3000, this region was identified as evolutionary important site with significant positive selection, elevated LD, and multiple selection sweeps, stabilising many domestication-related traits including grain size/weight. The aus group genotype retained more allelic variations in the desert region than japonica and indica, and likely to be one of the differentiation point for aus group. We suggest this desert region as an important evolutionary node that can be selected in breeding programs for improvement of grain yield and quality. All data and analysis can be accessed from RiceSzWtBase database.\n\nSignificance statementBeing an important trait, rice grain size/weight has been under rigorous selection since domestication. However, a link between this trait and domestication is not so directly established. In addition to characterization of novel grain size/weight-associated SNPs, in this study, [~] 6 Mb polymorphism desert region harboring major grain weight QTL was identified on chromosome 5, which turned out to be an evolutionary important site with multiple selection sweeps and introgression events, significantly correlated with domestication-related traits.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Sorghum pan-genome explores the functional utility to accelerate the genetic gain 96%
- Identification of QTLs for Internode Length and Diameter Associated with Lodging Resistance in Rice 96%
- A Combinatorial Approach of Biparental QTL Mapping and Genome-Wide Association Analysis Identifies Candidate Genes for Phytophthora Blight Resistance in Sesame 95%
Similar papers in this journal
- Impact of pre-anthesis drought stress on physiology, yield-related traits and drought responsive genes in green super rice 95%
- Codon Usage Bias Analysis of the WRKY Gene Family in Musa acuminata 93%
- A recently formed triploid Cardamine insueta inherits leaf vivipary and submergence tolerance traits of parents 93%
Similar papers in this journal
Similar papers in this journal
- Whole-genome polymorphisms and relatedness of rice varieties circulating in the Mediterranean market 96%
- Salt tolerance QTL derived from the Bangladeshi landrace Horkuch 96%
- TaAPO-A1, an ortholog of rice ABERRANT PANICLE ORGANIZATION 1, is associated with total spikelet number per spike in elite hexaploid winter wheat varieties (Triticum aestivum L.) 96%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.