OsLG3 contributing to rice grain length and yield was mined by Ho-LAMap
Jianping Yu
OsLG3 contributing to rice grain length and yield was mined by Ho-LAMap [Electronic Resource] - London, United Kingdom : BioMed Central Ltd, 2017.
Open Access Peer review
Background Most agronomic traits in rice are complex and polygenic. The identification of quantitative trait loci (QTL) for grain length is an important objective of rice genetic research and breeding programs. Results Herein, we identified 99 QTL for grain length by GWAS based on approximately 10 million single nucleotide polymorphisms from 504 cultivated rice accessions (Oryza sativa L.), 13 of which were validated by four linkage populations and 92 were new loci for grain length. We scanned the Ho (observed heterozygosity per locus) index of coupled-parents of crosses mapping the same QTL, based on linkage and association mapping, and identified two new genes for grain length. We named this approach as Ho-LAMap. A simulation study of six known genes showed that Ho-LAMap could mine genes rapidly across a wide range of experimental variables using deep-sequencing data. We used Ho-LAMap to clone a new gene, OsLG3, as a positive regulator of grain length, which could improve rice yield without influencing grain quality. Sequencing of the promoter region in 283 rice accessions from a wide geographic range identified four haplotypes that seem to be associated with grain length. Further analysis showed that OsLG3 alleles in the indica and japonica evolved independently from distinct ancestors and low nucleotide diversity of OsLG3 in indica indicated artificial selection. Phylogenetic analysis showed that OsLG3 might have much potential value for improvement of grain length in japonica breeding. Conclusions The results demonstrated that Ho-LAMap is a potential approach for gene discovery and OsLG3 is a promising gene to be utilized in genomic assisted breeding for rice cultivar improvement.
Text in English
https://doi.org/10.1186/s12915-017-0365-7
Rice
Quantitative Trait Loci
Genetic code
Chromosome mapping
Artificial Selection
OsLG3 contributing to rice grain length and yield was mined by Ho-LAMap [Electronic Resource] - London, United Kingdom : BioMed Central Ltd, 2017.
Open Access Peer review
Background Most agronomic traits in rice are complex and polygenic. The identification of quantitative trait loci (QTL) for grain length is an important objective of rice genetic research and breeding programs. Results Herein, we identified 99 QTL for grain length by GWAS based on approximately 10 million single nucleotide polymorphisms from 504 cultivated rice accessions (Oryza sativa L.), 13 of which were validated by four linkage populations and 92 were new loci for grain length. We scanned the Ho (observed heterozygosity per locus) index of coupled-parents of crosses mapping the same QTL, based on linkage and association mapping, and identified two new genes for grain length. We named this approach as Ho-LAMap. A simulation study of six known genes showed that Ho-LAMap could mine genes rapidly across a wide range of experimental variables using deep-sequencing data. We used Ho-LAMap to clone a new gene, OsLG3, as a positive regulator of grain length, which could improve rice yield without influencing grain quality. Sequencing of the promoter region in 283 rice accessions from a wide geographic range identified four haplotypes that seem to be associated with grain length. Further analysis showed that OsLG3 alleles in the indica and japonica evolved independently from distinct ancestors and low nucleotide diversity of OsLG3 in indica indicated artificial selection. Phylogenetic analysis showed that OsLG3 might have much potential value for improvement of grain length in japonica breeding. Conclusions The results demonstrated that Ho-LAMap is a potential approach for gene discovery and OsLG3 is a promising gene to be utilized in genomic assisted breeding for rice cultivar improvement.
Text in English
https://doi.org/10.1186/s12915-017-0365-7
Rice
Quantitative Trait Loci
Genetic code
Chromosome mapping
Artificial Selection