Browsing by Author "Lei, Li"

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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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    Environmental association identifies candidates for tolerance to low temperature and drought
    (2019-02-11) Lei, Li; Poets, Ana M; Liu, Chaochih; Wyant, Skylar R; Hoffman, Paul J; Carter, Corey K; Trantow, Richard M; Shaw, Brian G; Li, Xin; Muehlbauer, Gary J; Katagiri, Fumiaki; Morrell, Peter L; pmorrell@umn.edu; Morrell, Peter L; University of Minnesota Department of Plant and Microbial Biology; University of Minnesota Department of Agronomy and Plant Genetics
    Barley is cultivated from the equator to the Arctic Circle. The wild progenitor species, Hordeum vulgare ssp. spontaneum, occupies a relatively narrow latitudinal range (~30 - 40˚ N) primarily at low elevation, < 1500 m. Adaptation to the range of cultivation has occurred over ~8,000 years. The genetic basis of this adaptation is amenable to study through environmental association. Using genotyping from 7,864 SNPs in 784 barley landraces, we perform mixed model association analysis relative to bioclimatic variables and analysis of allele frequency differentiation across multiple partitions of the data. Using resequencing data from a subset of the landraces, we test for linkage disequilibrium (LD) between SNPs queried in genotyping and SNPs in neighboring loci. We identify seven loci previously reported to contribute to adaptive differences to flowering time and abiotic stress in barley and four loci previously identified in other plant species. In many cases, patterns of LD are consistent with the causative variant occurring in the immediate vicinity of the queried SNP. The identification of barley orthologs to well characterized genes may provide new understanding of the nature of adaptive variation and could permit a more targeted use of potentially adaptive variants in barley breeding and germplasm improvement.
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    Supporting data for Development of a multi-parent population for genetic mapping and allele discovery in six-row barley
    (2019-08-12) Hemshrot, Alex; Poets, Ana M; Tyagi, Priyanka; Lei, Li; Carter, Corey; Hirsch, Candice N; Li, Lin; Brown-Guedira, Gina; Morrell, Peter L; Muehlbauer, Gary J; Smith, Kevin P; llei@umn.edu; Lei, Li; University of Minnesota Department of Plant and Microbial Biology; HuaZhong Agricultural University Department of Genetics, College of Plant Science and Technology; USDA Eastern Regional Small Grains Genotyping Laboratory; University of Minnesota Department of Agronomy & Plant Genetics
    Germplasm collections hold valuable allelic diversity for crop improvement and genetic mapping of complex traits. To gain access to the genetic diversity within the USDA National Small Grain Collection (NSGC), we developed the Barley Recombinant Inbred Diverse Germplasm Population (BRIDG6), a six-row spring barley multi-parent population (MPP) with 88 cultivated accessions ranging from landrace to cultivars crossed to a common parent (Rasmusson). The parents were randomly selected from a core subset of the NSGC that represents the genetic diversity of landrace and breeding accessions. In total, we generated 6,160 F5 recombinant inbred lines (RILs) with an average of 69 and a range of 37-168 RILs per family genotyped with 7,773 SNPs. The number of segregating SNPs per family range from 956 to 6,775, with an average of 3,889 SNPs per family. Using BRIDG6, we detected 23 QTL contributing to flowering time. Five QTL were within five megabase pairs of previously described flowering time genes. For the major QTL detected near HvPpd-H1, a flowering time gene that affects photoperiod, we observed both positive and negative allele effects ranging from +4 to –3 days relative to Rasmusson among the 79 families segregating for the SNP. Haplotype-based analysis of HvPpd-H1 identified private alleles to families of Asian origin conferring both positive and negative effects, providing the first observation of flowering time-related alleles private to Asian accessions. We evaluate several subsampling strategies to determine their effect on the power of QTL detection and found that for flowering time in barley, a sample size larger than 50 families or 3,000 individuals results in the highest QTL detection. This MPP will be useful for uncovering large and small effect QTL for traits of interest and identifying and utilizing valuable alleles from the NSGC for barley improvement.