DOI: 10.1101/452276Oct 24, 2018Paper

Genomic prediction offers the most effective marker assisted breeding approach for ability to prevent arsenic accumulation in rice grains

BioRxiv : the Preprint Server for Biology
J FrouinNourollah Ahmadi


The high concentration of arsenic (As) in rice grains, in the paddy fields and the irrigation water in a large proportion of the rice growing areas is a critical issue. We explored the feasibility of conventional (QTL-based) marker-assisted selection and genomic selection to improve the ability of rice to prevent As uptake and accumulation in the grains. A japonica diversity panel (RP) of 228 accessions phenotyped for As concentration in the flag leaf (FL-As) and in the cargo grain (CG-As), and genotyped at 22,370 SNP loci, was used to map QTLs by association analysis (GWAS) and to train genomic prediction models. Similar phenotypic and genotypic data from 95 advanced breeding lines (VP) with genetic backgrounds similar to RP, was used to validate the QTLs mapped in the RP through GWAS and to evaluate the predictive ability of across populations (RP-VP) genomic estimate of breeding value (GEBV). Several QTLs for FL-As and CG-As with a low-medium individual effect were detected in the RP, some colocalizing with known QTLs and candidate genes. However, few of those QTLs could be validated in the VP without loosening colocalization parameters. Conversely, the average predictive ability of across populations GEBV was rather high, 0...Continue Reading

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