Browsing by Author "Kono, Thomas John Y"

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    Comparative genomics approaches accurately predict deleterious variants in plants
    (2018-07-03) Kono, Thomas John Y; Lei, Li; Shih, Ching-Hua; Hoffman, Paul J; Morrell, Peter L; Fay, Justin C; pmorrell@umn.edu; Morrell, Peter L; University of Minnesota Department of Agronomy and Plant Genetics; University of Rochester Department of Biology
    Recent advances in genome resequencing have led to increased interest in prediction of the functional consequences of genetic variants. Variants at phylogenetically conserved sites are of particular interest, because they are more likely than variants at phylogenetically variable sites to have deleterious effects on fitness and contribute to phenotypic variation. Numerous comparative genomic approaches have been developed to predict deleterious variants, but they are nearly always judged based on their ability to identify known disease-causing mutations in humans. Determining the accuracy of deleterious variant predictions in nonhuman species is important to understanding evolution, domestication, and potentially to improving crop quality and yield. To examine our ability to predict deleterious variants in plants we generated a curated database of 2,910 Arabidopsis thaliana mutants with known phenotypes. We evaluated seven approaches and found that while all performed well, the single best-performing approach was a likelihood ratio test applied to homologs identified in 42 plant genomes. Although the approaches did not always agree, we found only slight differences in performance when comparing mutations with gross versus biochemical phenotypes, duplicated versus single copy genes, and when using a single approach versus ensemble predictions. We conclude that deleterious mutations can be reliably predicted in A. thaliana and likely other plant species, but that the relative performance of various approaches can depend on the organism to which they are applied.
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    Supporting data for The Fate of Deleterious Variants in a Barley Genomic Prediction Population
    (2019-10-21) Morrell, Peter L; Smith, Kevin P; Vonderharr, Emily E; Kono, Thomas John Y; Fay, Justin C; Koenig, Daniel; pmorrell@umn.edu; Morrell, Peter L; Department of Agronomy and Plant Genetics, University of Minnesota; Department of Botany & Plant Sciences, University of California, Riverside; Department of Biology, University of Rochester
    Targeted identification and purging of segregating deleterious genetic variants has been proposed as a novel approach to plant breeding. This approach is motivated in part by the observation that demographic events and strong selection associated with cultivated species pose a “cost of domestication.” This includes an increase in the proportion of genetic variants at phylogenetically-constrained sites where a mutation is likely to reduce fitness. Recent advances in DNA resequencing technology and sequence constraint-based approaches to predict the functional impact of a mutation now permit the identification of putatively deleterious SNPs (dSNPs) on a genome-wide scale. Using exome capture resequencing of 21 barley 6-row spring breeding lines, we identify 3,855 dSNPs among 497,754 total SNPs. The dSNPs are more frequent in portions of the genome with a higher recombination rate, as measured by cM/Mb, than in pericentromeric regions with lower recombination rate and gene density. Using 5,215 progeny from a genomic prediction experiment, we examine the fate of dSNPs over three breeding cycles. Average derived allele frequency is lower for dSNPs than any other class of variants. Adjusting for frequency, derived alleles at dSNPs reduce in frequency or are lost more frequently than other classes of SNPs. Using a linear mixed model applied to 677 lines phenotyped at 5 year-locations, we find that a genomic region with the strongest association with a fungal disease resistance trait that was selected for in the population also negatively impacts yield. Finally, the highest yielding lines in the experiment, as chosen by standard genomic prediction approaches, carry fewer homozygous dSNPs than randomly selected lines.