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Prendergast, J. G. D.

Publications and source records attributed to Prendergast, J. G. D..

7 recordsLinked to original sources

Linking geography and mutation profiles across goat species

Recent studies have characterised the mutational profile across multiple mammalian species, highlighting substantial differences across lineages. However, none of these studies investigated whether mutation profiles and geography are significantly correlated. In this study, we present a multi-genome alignment spanning several Capra taxa, reconstruct the ancestral genome of Capra hircus and use it to characterize the mutational profiles across multiple Capra species by using the 1000 genomes VarGoats dataset. Results confirmed that the scale of differences among Capra species largely reflects their phylogenetic relationships, in particular with the Bezoar being genetically closer to domestic goats than to other wild species. Subsequently, we correlated the mutational profile and the geographical origin of the different individuals. In particular, ACG>ATG changes have the strongest correlation with longitude (r = -0.79, P-value = 3.02*10-204), while TCA>TGA are strongly correlated with latitude (r = -0.51, P-value = 4.30*10-63). We highlight how sequential dinucleotide mutations (SDMs) place cosmopolitan breeds closer to the sampling location, rather than the country of origin, showing how the recent relocation of cosmopolitan breeds to new continents is reshaping the genome of these animals. Finally, we used the mutational profile to predict the coordinate of origin of each animal in the dataset. In conclusion, we show the important role that geography had in shaping the genomes of domestic goats.

genomics↗

Accurate and robust classification of Mycobacterium bovis-infected cattle using peripheral blood RNA-seq data

Bovine tuberculosis (bTB) remains recalcitrant to eradication in many endemic countries where current diagnostics are suboptimal. Mycobacterium bovis causes bTB and is closely related to Mycobacterium tuberculosis, which causes human tuberculosis (hTB). Although blood-based mRNA biomarkers identified through machine learning can discriminate hTB-positive from hTB-negative individuals, similar approaches have not been explored for bTB. Here, we use RNA-seq and machine learning to investigate the utility of blood mRNA as a host-response biomarker for bTB. We identify a 30-gene signature and a 273-gene elastic net classifier that differentiate bTB-positive from bTB-negative cattle, achieving area under the curve (AUC) values of 0.986/0.900 for the former and 0.968/0.938 for the latter in training and testing, respectively. Additionally, we show that these classifiers distinguish bTB-positive cattle from cattle infected with other microbial pathogens (AUC [≥] 0.819). These mRNA-based classifiers represent a promising tool for augmenting current diagnostics to advance global bTB eradication efforts.

genomics↗

High quality genome assemblies of African cattle breeds using PacBio HiFi sequencing

Africa has a uniquely rich cattle diversity of [~]150 breeds comprising the Bos taurus indicus sub-species, Bos taurus taurus, and their crosses. These represent [~]23% of the global cattle population. However, high quality, representative assemblies are limited for African cattle and especially for indicine breeds. Here we built high quality de novo assemblies for five important African indigenous cattle breeds using PacBio HiFi sequencing: Lagune (Bos taurus taurus), Gudali, Iringa Red and Singida White (Bos taurus indicus), and Mpwapwa (Bos taurus taurus x Bos taurus indicus). These new assemblies are the most contiguous and complete African cattle assemblies produced so far, with genome sizes of 3.25 - 3.36Gb, contiguity N50s ranging from 83.59Mb to 97.87Mb and scaffold N50s from 100.30Mb to 113.37Mb. BUSCO genome completeness scores were also higher than 99.68%, indicative of highly contiguous assemblies. These improved and highly contiguous genome assemblies are consequently a valuable resource for future African and global livestock genomic studies.

genomics↗

Integrative genomics sheds light on the immunobiology of tuberculosis in cattle

Mycobacterium bovis causes bovine tuberculosis (bTB), an infectious disease of cattle that poses a zoonotic threat to humans. Research has shown that bTB susceptibility is a heritable trait, and that the peripheral blood (PB) transcriptome is perturbed during bTB disease. Hitherto, no study has integrated PB transcriptomic, genomic and GWAS data to study bTB disease, and little is known about the genomic architecture underpinning the PB transcriptional response to M. bovis infection. Here, we perform transcriptome profiling of PB from 63 control and 60 confirmed M. bovis infected animals and detect 2,592 differently expressed genes that perturb multiple immune response pathways. Leveraging imputed genome-wide SNP data, we characterise thousands of cis- and trans-expression quantitative trait loci (eQTLs) and show that the PB transcriptome is substantially impacted by intrapopulation genomic variation. We integrate our gene expression data with summary statistics from multiple GWAS data sets for bTB susceptibility and perform the first transcriptome-wide association study (TWAS) in the context of tuberculosis disease. From this TWAS, we identify 136 functionally relevant genes (including RGS10, GBP4, TREML2, and RELT) and provide important new omics data for understanding the host response to mycobacterial infections that cause tuberculosis in mammals.

genomics↗

Continent-wide genomic analysis of the African buffalo (Syncerus caffer).

The African buffalo (Syncerus caffer) is a wild bovid with a historical distribution across much of sub-Saharan Africa. Genomic analysis can provide insights into the evolutionary history of the species, and the key selective pressures shaping populations, including assessment of population level differentiation, population fragmentation, and population genetic structure. In this study we generated the highest quality de novo genome assembly (2.65 Gb, scaffold N50 69.17 Mb) of African buffalo to date, and sequenced a further 195 genomes from across the species distribution. Principal component and admixture analyses provided surprisingly little support for the currently described four subspecies, but indicated three main lineages, in Western/Central, Eastern and Southern Africa, respectively. Estimating Effective Migration Surfaces analysis suggested that geographical barriers have played a significant role in shaping gene flow and the population structure. Estimated effective population sizes indicated a substantial drop occurring in all populations 5-10,000 years ago, coinciding with the increase in human populations. Finally, signatures of selection were enriched for key genes associated with the immune response, suggesting infectious disease exert a substantial selective pressure upon the African buffalo. These findings have important implications for understanding bovid evolution, buffalo conservation and population management.

genomics↗

Rare Genetic Variants Underlie Outlying levels of DNA Methylation and Gene-Expression

Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on low-level genomic traits, such as gene expression or DNA methylation (DNAm), as effect sizes are expected to be larger for low-level compared to higher-order complex traits. Here, we investigate DNAm in healthy ageing populations - the Lothian Birth cohorts of 1921 and 1936 and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic variants within 1kb of DNAm sites in individuals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related individuals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels towards the tails of the population distribution. Overall, this study demonstrates the role of rare variants in the phenotypic variation of low-level genomic traits, and the effect of extreme levels of DNAm on gene expression.

genetics↗

Linked mutations at adjacent nucleotides have shaped human population differentiation and protein evolution

Despite the fundamental importance of single nucleotide polymorphisms (SNPs) to human evolution there are still large gaps in our understanding of the forces that shape their distribution across the genome. SNPs have been shown to not be distributed evenly, with directly adjacent SNPs found unusually frequently. Why this is the case is unclear. We illustrate how neighbouring SNPs that cant be explained by a single mutation event (that we term here sequential dinucleotide mutations, SDMs) are driven by distinct mutational processes and selective pressures to SNPs and multinucleotide polymorphisms (MNPs). By studying variation across multiple populations, including a novel cohort of 1,358 Scottish genomes, we show that, SDMs are over twice as common as MNPs and like SNPs, display distinct mutational spectra across populations. These biases are though not only different to those observed among SNPs and MNPs, but also more divergent between human population groups. We show that the changes that make up SDMs are not independent, and identify a distinct mutational profile, CA [->] CG [->] TG, that is observed an order of magnitude more often than other SDMs, including others that involve the gain and subsequent deamination of CpG sites. This suggests these specific changes are driven by a distinct process. In coding regions particular SDMs are favoured, and especially those that lead to the creation of single codon amino acids. Intriguingly selection has favoured particular pathways through the amino acid code, with epistatic selection appearing to have disfavoured sequential non-synonymous changes.

genomics↗