Genotype imputation for soybean nested association mapping population to improve precision of QTL detection.

ABSTRACT:

Key message

Software for high imputation accuracy in soybean was identified. Imputed dataset could significantly reduce the interval of genomic regions controlling traits, thus greatly improve the efficiency of candidate gene identification. Genotype imputation is a strategy to increase marker density of existing datasets without additional genotyping. We compared imputation performance of software BEAGLE 5.0, IMPUTE 5 and AlphaPlantImpute and tested software parameters that may help to improve imputation accuracy in soybean populations. Several factors including marker density, extent of linkage disequilibrium (LD), minor allele frequency (MAF), etc., were examined for their effects on imputation accuracy across different software. Our results showed that AlphaPlantImpute had a hi

SUBMITTER: Chen L 

PROVIDER: S-EPMC9110473 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature