The Role of Deleterious Substitutions in Crop Genomes

• Published in: Molecular biology and evolution 2016-09, Vol.33 (9), p.2307-2317
• Main Authors: Kono, Thomas J Y, Fu, Fengli, Mohammadi, Mohsen, Hoffman, Paul J, Liu, Chaochih, Stupar, Robert M, Smith, Kevin P, Tiffin, Peter, Fay, Justin C, Morrell, Peter L
• Format: Article
• Language: English
• Subjects: Amino Acid Substitution; Chromosome Mapping - methods; Computational Biology - methods; Crops, Agricultural - genetics; Discoveries; Evolution, Molecular; Gene Frequency; Genetic Fitness; Genetic Variation; Genome, Plant; Glycine max - genetics; Hordeum - genetics; Mutation; Mutation Rate; Plant Breeding; Polymorphism, Single Nucleotide; Sequence Analysis, DNA - methods
• ISSN: 0737-4038; 1537-1719
• DOI: 10.1093/molbev/msw102

Populations continually incur new mutations with fitness effects ranging from lethal to adaptive. While the distribution of fitness effects of new mutations is not directly observable, many mutations likely either have no effect on organismal fitness or are deleterious. Historically, it has been hypothesized that a population may carry many mildly deleterious variants as segregating variation, which reduces the mean absolute fitness of the population. Recent advances in sequencing technology and sequence conservation-based metrics for inferring the functional effect of a variant permit examination of the persistence of deleterious variants in populations. The issue of segregating deleterious variation is particularly important for crop improvement, because the demographic history of domestication and breeding allows deleterious variants to persist and reach moderate frequency, potentially reducing crop productivity. In this study, we use exome resequencing of 15 barley accessions and genome resequencing of 8 soybean accessions to investigate the prevalence of deleterious single nucleotide polymorphisms (SNPs) in the protein-coding regions of the genomes of two crops. We conclude that individual cultivars carry hundreds of deleterious SNPs on average, and that nonsense variants make up a minority of deleterious SNPs. Our approach identifies known phenotype-altering variants as deleterious more frequently than the genome-wide average, suggesting that putatively deleterious variants are likely to affect phenotypic variation. We also report the implementation of a SNP annotation tool BAD_Mutations that makes use of a likelihood ratio test based on alignment of all currently publicly available Angiosperm genomes.