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Taylor, J. F.

Publications and source records attributed to Taylor, J. F..

3 recordsLinked to original sources

A Multi-Breed Reference Panel and Additional Rare Variation Maximizes Imputation Accuracy in Cattle

BackgroundThe use of array-based SNP genotyping in the beef and dairy industries has produced an astounding amount of medium-to-low density genomic data in the last decade. While low-density assays work exceptionally well in the context of genomic prediction, they are less useful in mapping and causal variant discovery. This project focuses on maximizing imputation accuracies to the marker set of two high-density research assays, the Illumina Bovine HD, and the GGP-F250 which contains a large proportion of rare and potentially functional variants (~850,000 total SNPs). This 850K SNP set is well-suited for both imputation to sequence-level genotypes and direct downstream analysis.\n\nResultsWe find that a large multi-breed composite imputation reference comprised of 36,131 samples with either HD and/or F250 genotypes significantly increases imputation accuracy compared to a standard within-breed reference panel, particularly at low minor allele frequencies. Imputation accuracies were maximized when an individuals ancestry was adequately represented in the composite reference, particularly with complete 850K genotypes. The addition of rare content from the F250 to our composite reference panel significantly increased the imputation accuracy of rare variants found exclusively on the HD. Additionally, we identify 50,000 variants as an ideal starting density for 850K imputation.\n\nConclusionUsing high-density genotypes on all available individuals in a multi-breed reference panel maximizes imputation accuracy for all cattle populations. Admixed breeds or those sparsely represented in the composite reference are still imputed at high accuracy which will increase further as the reference panel grows. We expect that the addition of rare variation from the F250 will increase the accuracy of imputation at the sequence level.

genomics↗

CRUMBLER: A tool for the Prediction of Ancestry in Cattle

BackgroundIn many beef and some dairy production systems, crossbreeding is used to take advantage of breed complementarity and heterosis. Admixed animals are frequently identified by their coat color and body conformation phenotypes, however, without pedigree information it is not possible to identify the expected breed composition of an admixed animal and in the presence of selection, the actual composition may differ from expectation.\n\nResultsWe tested an approach to estimate the global ancestry of individuals using ADMIXTURE and SNPweights. ADMIXTURE estimates ancestry using a model-based approach applied to large single nucleotide polymorphism (SNP) genotype datasets. Individuals are assumed to be unrelated and a supervised analysis can be performed using reference animals sampled to represent ancestral populations. SNPweights infers ancestry using weights estimated by principal component analysis for genome-wide SNP panels that have been genotyped in the reference panel animals. We constructed analysis pipelines to determine the ancestry of individuals with potentially complex ancestries using both methods and a specified reference population SNP dataset. The reference population was constructed using breed association pedigree information and an iterative analysis to identify sets of purebred individuals representative of each breed.\n\nConclusionThe finally adopted CRUMBLER pipeline extracts a subset of genotypes that are common to all current commercially available genotyping platforms and processes these into the file formats required for the analysis software and predicts admixture proportions using the reference population dataset.

genomics↗

A comprehensive manually-curated Compendium of Bovine Transcription Factors

Transcription factors (TFs) are pivotal regulatory proteins that control gene expression in a context-dependent and tissue-specific manner. In contrast to human, where comprehensive curated TF collections exist, bovine TFs are only rudimentary recorded and characterized. In this article, we present a manually-curated compendium of 865 sequence-specific DNA-binding bovines TFs, which we analyzed for domain family distribution, evolutionary conservation, and tissue-specific expression. In addition, we provide a list of putative transcription cofactors derived from known interactions with the identified TFs. Since there is a general lack of knowledge concerning the regulation of gene expression in cattle, the curated list of TF should provide a basis for an improved comprehension of regulatory mechanisms that are specific to the species.

genomics↗