James G. D. Prendergast

This study links geography and mutation profiles in goat species, finding strong correlations between specific mutations and geographic coordinates.

The paper presents a reusable TWAS workflow for cattle to identify gene-trait associations using GWAS and transcriptomic data, improving variant calling and detecting novel associations.

The paper creates a high-resolution cattle regulatory variant atlas and identifies cross-species activity in human cells, highlighting both conservation and species-specific effects.

The paper identifies cis-regulatory elements and transcription factors involved in optic fissure closure using chicken embryos, linking them to human coloboma genes.

The paper develops mRNA-based classifiers using RNA-seq and machine learning to accurately distinguish bTB-positive from bTB-negative cattle and other pathogens.

This study develops a workflow to analyze mutation spectra across mammals, finding convergent evolution in mutation rates among species.

The paper identifies genetic variants associated with antibody responses to infectious diseases in Tanzanian dairy cattle using genome-wide association studies.

The paper imputes SNVs and SVs from low-coverage WGS data in Atlantic salmon, showing improved accuracy with SV genotype likelihoods.

This study integrates transcriptomic, genomic, and GWAS data to identify genes and eQTLs associated with the PB transcriptome response to M. bovis infection in cattle.

This study constructs a water buffalo pangenome using graph genomics, revealing extensive structural variation and population-specific selection signatures in 711 global samples.

This paper develops a framework to predict regulatory variants in cattle using machine learning, achieving high performance and demonstrating enrichment for functional variants linked to important traits.

This study presents a continent-wide genomic analysis of African buffalo, revealing three main lineages and signatures of selection related to immune response.

This study identifies rare genetic variants associated with extreme DNA methylation levels and shows their impact on gene expression in healthy ageing populations.

This study uses optical mapping to identify structural variants in cattle breeds, providing a database for further genetic and evolutionary studies.

This study identifies human functional variants with conserved effects in livestock species, showing their utility for understanding disease mechanisms.

The paper identifies a genetic locus associated with tolerance to Theileria parva infection in cattle, showing a strong heritability and replication across cohorts.

The paper creates a graph genome incorporating global cattle diversity, showing it includes more sequence and improves mapping and variant calling.

This study examines sexual differences in genetic architecture across 530 traits in 450,000 UK Biobank individuals, finding sex-specific heritability and genetic correlations.

nf-LO provides a scalable, containerised workflow for performing genome-to-genome lift over between any species with available assemblies.

Graphia is an open-source platform for graph-based analysis of complex biomedical data, offering visualization, transformation, and analysis tools for high-dimensional datasets.

The paper identifies rare CRE variants associated with X-linked intellectual disability by combining sequencing, functional assays in zebrafish and mice, and phenotypic analysis.

The paper analyzes whole genome sequencing data from an isolated Shetland population, finding increased ultra-rare variants in exonic and regulatory regions compared to mainland Scottish populations.

The paper analyzes chick optic fissure closure, identifying Netrin-1 as a conserved mediator of epithelial fusion essential for vertebrate development and linked to human coloboma.

The paper identifies a missense variant in OLFML3 as a candidate for severe goniodysgenesis and glaucoma in Border Collies.

The paper investigates how linked mutations at adjacent nucleotides, termed sequential dinucleotide mutations, influence human population differentiation and protein evolution.