Biology subjects

Pryce, J. E.

Publications and source records attributed to Pryce, J. E..

4 recordsLinked to original sources

bioRxiv2024

An integrative approach to prioritize candidate causal genes for complex traits in cattle

Genome-wide association studies (GWAS) have identified many quantitative trait loci (QTL) associated with complex traits, predominantly in non-coding regions, posing challenges in pinpointing the causal variants and their target genes. Three types of evidence can help identify the gene through which QTL act: (1) proximity to the most significant GWAS variant, (2) correlation of gene expression with the trait, and (3) the genes physiological role in the trait. However, there is still uncertainty in the success of these methods in identifying the correct genes. Here we test the ability of these methods in a comparatively simple series of traits associated with the concentration of polar lipids in milk. We conducted single-trait GWAS for [~]14 million imputed variants and 56 individual milk polar lipid (PL) phenotypes in 336 cows. A meta-analysis of multi-trait GWAS identified 10,063 significant SNPs at FDR [≤] 10% (P [≤] 7.15E-5). Transcriptome data from blood ([~]12.5K genes, 143 cows) and mammary tissue ([~]12.2K genes, 169 cows) were analysed using the genetic score omics regression (GSOR) method. This method links observed gene expression to genetically predicted phenotypes and was used to find associations between gene expression and 56 PL phenotypes. GSOR identified 2,186 genes in blood and 1,404 in mammary tissue associated with at least one PL phenotype (FDR [≤] 1%). We partitioned the genome into non-overlapping windows of 100 Kb to test for overlap between GSOR-identified genes and GWAS signals. We found a significant overlap between these two datasets, indicating GSOR significant genes were more likely to be located within 100 Kb windows that have GWAS signals compared to those without (P = 0.01; odds ratio = 1.47). These windows included 70 significant genes expressed in mammary tissue and 95 in blood. Compared to all expressed genes in each tissue, these genes were enriched for lipid metabolism gene ontology (GO). That is, 7 of the 70 significant mammary transcriptome genes (P < 0.01; odds ratio = 3.98) and 5 of the 95 significant blood genes (P < 0.10; odds ratio = 2.24) were involved in lipid metabolism GO. The candidate causal genes include DGAT1, ACSM5, SERINC5, ABHD3, CYP2U1, PIGL, ARV1, SMPD5, and NPC2, with some overlap between the two tissues. The overlap between GWAS, GSOR, and GO analyses suggests that together these methods can identify genes mediating QTL, though their power remains limited, as reflected by modest odds ratios. Larger sample sizes would enhance the power of these analyses, but issues like linkage disequilibrium would remain.

genomics↗

bioRxiv2021

New loci and neuronal pathways for resilience to heat stress in animals

Climate change and resilience to warming climates have implications for humans, livestock, and wildlife. The genetic mechanisms that confer thermotolerance to mammals are still not well characterized. We used dairy cows as a model to study heat tolerance because they are lactating, and therefore often prone to thermal stress. The data comprised almost 0.5 million milk records (milk, fat, and proteins) of 29,107 Australian Holsteins, each having around 15 million imputed sequence variants. Dairy animals often reduce their milk production when temperature and humidity rise; thus, the phenotypes used to measure an individuals heat tolerance were defined as the rate of milk production decline (slope traits) with a rising temperature-humidity index. With these slope traits, we performed a genome-wide association study (GWAS) using different approaches, including conditional analyses, to correct for the relationship between heat tolerance and level of milk production. The results revealed multiple novel loci for heat tolerance, including 61 potential functional variants at sites highly conserved across vertebrate species. Moreover, it was interesting that specific candidate variants and genes are related to the neuronal system (ITPR1, ITPR2, and GRIA4) and neuroactive ligand-receptor interaction functions for heat tolerance (NPFFR2, CALCR, and GHR), providing a novel insight that can help to develop genetic and management approaches to combat heat stress. Author summaryWhile understanding the genetic basis of heat tolerance is crucial in the context of global warmings effect on humans, livestock, and wildlife, the specific genetic variants and biological features that confer thermotolerance in animals are still not well characterized. The ability to tolerate heat varies across individuals, with substantial genetic control of this complex trait. Dairy cattle are excellent model in which to find genes associated with individual variations in heat tolerance since they significantly suffer from heat stress due to the metabolic heat of lactation. By genome-wide association studies of more than 29,000 cows with 15 million sequence variants and controlled phenotype measurements, we identify many new loci associated with heat tolerance. The biological functions of these loci are linked to the neuronal system and neuroactive ligand-receptor interaction functions. Also, several putative causal mutations for heat tolerance are at genomic sites that are otherwise evolutionarily conserved across 100 vertebrate species. Overall, our findings provide new insight into the molecular and biological basis of heat tolerance that can help to develop genetic and management approaches to combat heat stress.

genomics↗

bioRxiv2019

Genome-wide profiling of microRNAs and prediction of mRNA targets in 17 bovine tissues

MicroRNAs regulate many eukaryotic biological processes in a temporal- and spatial-specific manner. Yet in cattle it is not fully known which microRNAs are expressed in each tissue, which genes they regulate, or which sites a given microRNA bind to within messenger RNAs. An improved annotation of tissue-specific microRNA network may in the future assist with the identification of causal variants affecting complex traits. Here, we report findings from analysing short RNA sequence from 17 tissues from a single lactating dairy cow. Using miRDeep2, we identified 699 expressed mature microRNA sequences. Using TargetScan, known (60%) and novel (40%) microRNAs were predicted to interact with 780,481 sites in bovine messenger RNAs homologous with human. Putative interactions between microRNA families and targets were significantly enriched for interactions from previous experimental and computational identification. Characterizing features of microRNAs and targets, we showed that (1) mature microRNAs derived from different arms of the same precursor targeted different genes in different tissues; (2) miRNA target sites preferentially occurred within gene regions marked with active histone modification; (3) variants within microRNAs and targets had lower allele frequencies than variants across the genome, as identified from 65 million whole genome sequence variants; (4) no significant correlation was found between the abundance of microRNAs and messenger RNAs differentially expressed in the same tissue; (5) microRNAs and target sites werent significantly associated with allelic imbalance of gene targets. This study contributes to the goals of Functional Annotation of Animal Genomes consortium to improve the annotation of genomes of domestic animals.

bioinformatics↗

bioRxiv2018

Putative bovine topological association domains and CTCF binding motifs can reduce the search space for causative regulatory variants of complex traits

BackgroundTopological association domains (TADs) are chromosomal domains characterised by frequent internal DNA-DNA interactions. The transcription factor CTCF binds to conserved DNA sequence patterns called CTCF binding motifs to either prohibit or facilitate chromosomal interactions. TADs and CTCF binding motifs control gene expression, but they are not yet well defined in the bovine genome. In this paper, we sought to improve the annotation of bovine TADs and CTCF binding motifs, and assess whether the new annotation can reduce the search space for cis-regulatory variants.\n\nResultsWe used genomic synteny to map TADs and CTCF binding motifs from humans, mice, dogs and macaques to the bovine genome. We found that our mapped TADs exhibited the same hallmark properties of those sourced from experimental data, such as housekeeping gene, tRNA genes, CTCF binding motifs, SINEs, H3K4me3 and H3K27ac. Then we showed that runs of genes with the same pattern of allele-specific expression (ASE) (either favouring paternal or maternal allele) were often located in the same TAD or between the same conserved CTCF binding motifs. Analyses of variance showed that when averaged across all bovine tissues tested, TADs explained 14% of ASE variation (standard deviation, SD: 0.056), while CTCF explained 27% (SD: 0.078). Furthermore, we showed that the quantitative trait loci (QTLs) associated with gene expression variation (eQTLs) or ASE variation (aseQTLs), which were identified from mRNA transcripts from 141 lactating cows white blood and milk cells, were highly enriched at putative bovine CTCF binding motifs. The most significant aseQTL and eQTL for each genic target were located within the same TAD as the gene more often than expected (Chi-Squared test P-value [≤] 0.001).\n\nConclusionsOur results suggest that genomic synteny can be used to functionally annotate conserved transcriptional components, and provides a tool to reduce the search space for causative regulatory variants in the bovine genome.

genomics↗