ORCID Profile
0000-0002-3067-3359
Current Organisation
Colorado State University
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Publisher: Wiley
Date: 21-07-2014
DOI: 10.1111/MEC.12845
Publisher: Wiley
Date: 10-01-2016
DOI: 10.1111/GCBB.12309
Publisher: Springer Science and Business Media LLC
Date: 2011
Publisher: Proceedings of the National Academy of Sciences
Date: 17-07-2007
Abstract: We used hybridization to the ATH1 gene expression array to interrogate genomic DNA ersity in 23 wild strains (accessions) of Arabidopsis thaliana (arabidopsis), in comparison with the reference strain Columbia (Col). At % false discovery rate, we detected 77,420 single-feature polymorphisms (SFPs) with distinct patterns of variation across the genome. Total and pair-wise ersity was higher near the centromeres and the heterochromatic knob region, but overall ersity was positively correlated with recombination rate ( R 2 = 3.1%). The difference between total and pair-wise SFP ersity is a relative measure contrasting ersifying or frequency-dependent selection, similar to Tajima's D, and can be calibrated by the empirical genome-wide distribution. Each unique locus, centered on a gene, has a ersity and selection score that suggest a relative role in past evolutionary processes. Homologs of disease resistance ( R ) genes include members with especially high levels of ersity often showing frequency-dependent selection and occasionally evidence of a past selective sweep. Receptor-like and S-locus proteins also contained members with elevated levels of ersity and signatures of selection, whereas other gene families, bHLH, F-box, and RING finger proteins, showed more typical levels of ersity. SFPs identified with the gene expression array also provide an empirical hybridization polymorphism background for studies of gene expression polymorphism and are available through the genome browser gi-bin/AtSFP .
Publisher: Wiley
Date: 08-11-2011
Publisher: Wiley
Date: 22-09-2023
DOI: 10.1111/NPH.19273
Publisher: Cold Spring Harbor Laboratory
Date: 03-10-2019
DOI: 10.1101/775221
Abstract: Successful management and utilization of increasingly large genomic datasets is essential for breeding programs to increase genetic gain and accelerate cultivar development. To help with data management and storage, we developed a sorghum Practical Haplotype Graph (PHG) pangenome database that stores all identified haplotypes and variant information for a given set of in iduals. We developed two PHGs in sorghum, one with 24 in iduals and another with 398 in iduals, that reflect the ersity across genic regions of the sorghum genome. 24 founders of the Chibas sorghum breeding program were sequenced at low coverage (0.01x) and processed through the PHG to identify genome-wide variants. The PHG called SNPs with only 5.9% error at 0.01x coverage - only 3% lower than its accuracy when calling SNPs from 8x coverage sequence. Additionally, 207 progeny from the Chibas genomic selection (GS) training population were sequenced and processed through the PHG. Missing genotypes in the progeny were imputed from the parental haplotypes available in the PHG and used for genomic prediction. Mean prediction accuracies with PHG SNP calls range from 0.57-0.73 for different traits, and are similar to prediction accuracies obtained with genotyping-by-sequencing (GBS) or markers from sequencing targeted licons (rhAmpSeq). This study provides a proof of concept for using a sorghum PHG to call and impute SNPs from low-coverage sequence data and also shows that the PHG can unify genotype calls from different sequencing platforms. By reducing the amount of input sequence needed, the PHG has the potential to decrease the cost of genotyping for genomic selection, making GS more feasible and facilitating larger breeding populations that can capture maximum recombination. Our results demonstrate that the PHG is a useful research and breeding tool that can maintain variant information from a erse group of taxa, store sequence data in a condensed but readily accessible format, unify genotypes from different genotyping methods, and provide a cost-effective option for genomic selection for any species.
Publisher: Wiley
Date: 03-2020
DOI: 10.1002/TPG2.20009
No related grants have been discovered for Geoffrey Preston Morris.