Dataset Information

Genetic Diversity and Elite Allele Mining for Grain Traits in Rice (Oryza sativa L.) by Association Mapping.

ABSTRACT: Mining elite alleles for grain size and weight is of importance for the improvement of cultivated rice and selection for market demand. In this study, association mapping for grain traits was performed on a selected sample of 628 rice cultivars using 262 SSRs. Grain traits were evaluated by grain length (GL), grain width (GW), grain thickness (GT), grain length to width ratio (GL/GW), and 1000-grain weight (TGW) in 2013 and 2014. Our result showed abundant phenotypic and genetic diversities found in the studied population. In total, 2953 alleles were detected with an average of 11.3 alleles per locus. The population was divided into seven subpopulations and the levels of linkage disequilibrium (LD) ranged from 34 to 84 cM. Genome-wide association mapping detected 10 marker trait association (MTAs) loci for GL, 1MTAs locus for GW, 7 MTAs loci for GT, 3 MTAs loci for GL/GW, and 1 MTAs locus for TGW. Twenty-nine, 2, 10, 5, and 3 elite alleles were found for the GL, GW, GT, GL/GW, and TGW, respectively. Optimal cross designs were predicted for improving the target traits. The accessions containing elite alleles for grain traits mined in this study could be used for breeding rice cultivars and cloning the candidate genes.

SUBMITTER: Edzesi WM

PROVIDER: S-EPMC4896222 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Genetic Diversity and Elite Allele Mining for Grain Traits in Rice (Oryza sativa L.) by Association Mapping.

Edzesi Wisdom M WM Dang Xiaojing X Liang Lijun L Liu Erbao E Zaid Imdad U IU Hong Delin D

Frontiers in plant science 20160607

Mining elite alleles for grain size and weight is of importance for the improvement of cultivated rice and selection for market demand. In this study, association mapping for grain traits was performed on a selected sample of 628 rice cultivars using 262 SSRs. Grain traits were evaluated by grain length (GL), grain width (GW), grain thickness (GT), grain length to width ratio (GL/GW), and 1000-grain weight (TGW) in 2013 and 2014. Our result showed abundant phenotypic and genetic diversities foun ...[more]

PMID: 27375646

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Project description:Microarray-based markers such as Diversity Arrays Technology (DArT) have become the genetic markers of choice for construction of high-density maps, quantitative trait loci (QTL) mapping and genetic diversity analysis based on their efficiency and low cost. More recently, the DArT technology was further developed in combination with high-throughput next-generation sequencing (NGS) technologies to generate the DArTseq platform representing a new sequencing tool of complexity-reduced representations. In this study, we used DArTseq markers to investigate genetic diversity and genome-wide association studies (GWAS) of grain quality traits in rice (Oryza sativa L.). The study was performed using 59 rice genotypes with 525 SNPs derived from DArTseq platform. Population structure analysis revealed only two distinct genetic clusters where genotypes were grouped based on environmental adaptation and pedigree information. Analysis of molecular variance indicated a low degree of differentiation among populations suggesting the need for broadening the genetic base of the current germplasm collection. GWAS revealed 22 significant associations between DArTseq-derived SNP markers and rice grain quality traits in the test genotypes. In general, 2 of the 22 significant associations were in chromosomal regions where the QTLs associated with the given traits had previously been reported, the other 20 significant SNP marker loci were indicative of the likelihood discovery of novel alleles associated with rice grain quality traits. DArTseq-derived SNP markers that include SNP12_100006178, SNP13_3052560 and SNP14_3057360 individually co-localised with two functional gene groups that were associated with QTLs for grain width and grain length to width ratio on chromosome 3, indicating trait dependency or pleiotropic-effect loci. This study demonstrated that DArTseq markers were useful genomic resources for genome-wide association studies of rice grain quality traits to accelerate varietal development and release.

Project description:Background:Grain weight is a grain yield component, which is an integrated index of grain length, width and thickness. They are controlled by a large number of quantitative trait loci (QTLs). Besides major QTLs, minor QTLs play an essential role. In our previous studies, QTL analysis for grain length and width was performed using a recombinant inbred line population derived from rice cross TQ/IRBB lines. Two major QTLs were detected, which were located in proximity to GS3 and GW5 that have been cloned. In the present study, QTLs for grain weight and shape were identified using rice populations that were homozygous at GS3 and GW5. Method:Nine populations derived from the indica rice cross TQ/IRBB52 were used. An F10:11population named W1, consisting of 250 families and covering 16 segregating regions, was developed from one residual heterozygote (RH) in the F7generation of Teqing/IRBB52. Three near isogenic line (NIL)-F2 populations, ZH1, ZH2 and ZH3 that comprised 205, 239 and 234 plants, respectively, were derived from three RHs in F10:11. They segregated the target QTL region in an isogenic background. Two NIL populations, HY2 and HY3, were respectively produced from homozygous progeny of the ZH2 and ZH3 populations. Three other NIL-F2 populations, Z1, Z2 and Z3, were established using three RHs having smaller heterozygous segments. QTL analysis for 1000-grain weight (TGW), grain length (GL), grain width (GW), and length/width ratio (LWR) was conducted using QTL IciMapping and SAS procedure with GLM model. Result:A total of 27 QTLs distributed on 12 chromosomes were identified. One QTL cluster, qTGW2/qGL2/qGW2 located in the terminal region of chromosome 2, were selected for further analysis. Two linked QTLs were separated in region Tw31911-RM266. qGL2 was located in Tw31911-Tw32437 and mainly controlled GL and GW. The effects were larger on GL than on GW and the allelic directions were opposite. qTGW2 was located in Tw35293-RM266 and affected TGW, GL and GW with the same allelic direction. Finally, qTGW2 was delimited within a 103-kb region flanked by Tw35293 and Tw35395. Conclusion:qTGW2 with significant effects on TGW, GL and GW was validated and fine-mapped using NIL and NIL-F2 populations. These results provide a basis for map-based cloning of qTGW2 and utilization of qTGW2 in the breeding of high-yielding rice varieties.

Dataset Information

Genetic Diversity and Elite Allele Mining for Grain Traits in Rice (Oryza sativa L.) by Association Mapping.

Publications

Genetic Diversity and Elite Allele Mining for Grain Traits in Rice (Oryza sativa L.) by Association Mapping.

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