Quantitative trait loci mapping for lameness associated phenotypes in Holstein Friesian dairy cattle

Lameness represents a significant challenge for the dairy cattle industry, resulting in economic losses and reduced animal health and welfare. The existence of underlying genomic variation for lameness associated traits has the potential to improve selection strategies by using genomic markers. Therefore, the aim of this study was to identify genomic regions and potential candidate genes associated with lameness traits. Lameness related lesions and digital cushion thickness were studied using records collected by our research team, farm records, and a combination of both. Genome-wide analyses were performed to identify significant genomic effects, and a combination of single SNP association analysis and regional heritability mapping was used to identify associated genomic regions. Significant genomic effects were identified for several lameness related traits: Two genomic regions were identified on chromosome 3 associated with digital dermatitis and interdigital hyperplasia, one genomic region on chromosome 23 associated with interdigital hyperplasia, and one genomic region on chromosome 2 associated with sole haemorrhage. Candidate genes in those regions are mainly related to immune response and fibroblast proliferation. Quantitative trait loci (QTL) identified in this study could enlighten the understanding of lameness pathogenesis, providing an opportunity to improve health and welfare in dairy cattle with the addition of these regions into selection programs

The bovine foot skin microbiota is associated with host genotype and the development of infectious digital dermatitis lesions

Abstract Background Bovine Digital Dermatitis (BDD) is a prevalent infectious disease, causing painful foot skin lesions and lameness in cattle. We describe herein the bovine foot skin microbiota and its associations with BDD using 16S rRNA gene amplicon and shotgun metagenomic sequencing on samples from 259 dairy cows from three UK dairy farms. Results We show evidence of dysbiosis, and differences in taxonomy and functional profiles in the bovine foot skin microbiome of clinically healthy animals that subsequently develop BDD lesions, compared to those that do not. Our results suggest that taxonomical and functional differences together with alterations in ecological interactions between bacteria in the normal foot skin microbiome may predispose an animal to develop BDD lesions. Using genome-wide association and regional heritability mapping approaches, we provide first evidence for interactions between host genotype and certain members of the foot skin microbiota. We show the existence of significant genetic variation in the relative abundance of Treponema spp. and Peptoclostridium spp. and identify regions in the bovine genome that explain a significant proportion of this variation. Conclusions Collectively this work shows early changes in taxonomic and functional profiles of the bovine foot-skin microbiota in clinically healthy animals which are associated with subsequent development of BDD and could be relevant to prevention of disease. The description of host genetic control of members of the foot skin microbiota, combined with the association of the latter with BDD development offer new insights into a complex relationship that can be exploited in selective breeding programmes. </jats:sec

The heritability and patterns of DNA methylation in normal human colorectum

DNA methylation (DNAm) has been linked to changes in chromatin structure, gene expression and disease. The DNAm level can be affected by genetic variation; although, how this differs by CpG dinucleotide density and genic location of the DNAm site is not well understood. Moreover, the effect of disease causing variants on the DNAm level in a tissue relevant to disease has yet to be fully elucidated. To this end, we investigated the phenotypic profiles, genetic effects and regional genomic heritability for 196080 DNAm sites in healthy colorectum tissue from 132 unrelated Colombian individuals. DNAm sites in regions of low-CpG density were more variable, on average more methylated and were more likely to be significantly heritable when compared with DNAm sites in regions of high-CpG density. DNAm sites located in intergenic regions had a higher mean DNAm level and were more likely to be heritable when compared with DNAm sites in the transcription start site (TSS) of a gene expressed in colon tissue. Within CpG-dense regions, the propensity of the DNAm level to be heritable was lower in the TSS of genes expressed in colon tissue than in the TSS of genes not expressed in colon tissue. In addition, regional genetic variation was associated with variation in local DNAm level no more frequently for DNAm sites within colorectal cancer risk regions than it was for DNAm sites outside such regions. Overall, DNAm sites located in different genomic contexts exhibited distinguishable profiles and may have a different biological function

A comprehensive genome-wide scan detects genomic regions related to local adaptation and climate resilience in Mediterranean domestic sheep

BACKGROUND: The management of farm animal genetic resources and the adaptation of animals to climate change will probably have major effects on the long-term sustainability of the livestock sector. Genomic data harbour useful relevant information that needs to be harnessed for effectively managing genetic resources. In this paper, we report the genome characterization of the highly productive Mediterranean Chios dairy sheep and focus on genetic diversity measures related with local adaptation and selection and the genetic architecture of animal resilience to weather fluctuations as a novel adaptative trait linked to climate change. RESULTS: We detected runs of homozygosity (ROH) and heterozygosity (ROHet) that revealed multiple highly homozygous and heterozygous hotspots across the Chios sheep genome. A particularly highly homozygous region was identified on chromosome 13 as a candidate of directional genetic selection associated with milk traits, which includes annotated genes that were previously shown to be linked to local adaptation to harsh environmental conditions. Favourable heterozygosity related with a potentially protective role against livestock diseases and enhanced overall fitness was revealed in heterozygous-rich regions on sheep chromosomes 3, 10, 13 and 19. Furthermore, genomic analyses were conducted on sheep resilience phenotypes that display changes in milk production in response to weather variation. Sheep resilience to heat stress was a significantly heritable trait (h(2) = 0.26) and genetically antagonistic to milk production. Genome-wide association and regional heritability mapping analyses revealed novel genomic markers and regions on chromosome 5 that were significantly associated with sheep resilience to climate change. Subsequently, an annotation analysis detected a set of genes on chromosome 5 that were associated with olfactory receptor complexes that could participate in heat stress mitigation through changes in respiration rate and respiratory evaporation. Other genes were grouped in previously reported biological processes relevant to livestock heat dissipation, including stress and immune response. CONCLUSIONS: Our results may contribute to the optimal management of sheep genetic resources and inform modern selective breeding programmes that aim at mitigating future environmental challenges towards sustainable farming, while better balancing animal adaptation and productivity. Our results are directly relevant to the studied breed and the respective environmental conditions; however, the methodology may be extended to other livestock species of interest. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12711-021-00682-7

Genetic Architecture of Complex Traits and Accuracy of Genomic Selection in Dairy Cattle

Genomic selection has emerged as an effective approach in dairy cattle breeding, in which the key is prediction of genetic merit using dense SNP genotypes, i.e., genomic prediction. To improve the accuracy of genomic prediction, we need better understanding of the genetic architecture of complex traits and more sophisticated statistical modeling. In this dissertation, I developed several computing tools and performed a series of studies to investigate the genetic architecture of complex traits in dairy cattle and to improve genomic prediction models. First, we dissected additive, dominance, and imprinting effects for production, reproduction and health traits in dairy cattle. We found that non-additive effects contributed a non-negligible amount (more for reproduction traits) to the total genetic variance of complex traits in cattle. We also identified a dominant quantitative trait locus (QTL) for milk yield, revealing that detection of QTLs with non-additive effect is possible in genome-wide association studies (GWAS) using a large dataset. Second, we developed a powerful Bayesian method and a fast software tool (BFMAP) for SNP-set association and fine-mapping. We demonstrated that BFMAP achieves a power similar to or higher than existing software tools but is at least a few times faster for association tests. We also showed that BFMAP performs well for fine-mapping and can efficiently integrate fine-mapping with functional enrichment analysis. Third, we performed large-scale GWAS and fine-mapped 35 production, reproduction, and body conformation traits to single-gene resolution. We identified many novel association signals and many promising candidate genes. We also characterized causal effect enrichment patterns for a few functional annotations in dairy cattle genome and showed that our fine-mapping result can be readily used for future functional studies. Fourth, we developed an efficient Bayesian method and a fast computing tool (SSGP) for using functional annotations in genomic prediction. We demonstrated that the method and software have great potential to increase accuracy in genomic prediction and the capability to handle very large data. Collectively, these studies advance our understanding of the genetic architecture of complex traits in dairy cattle and provide fast computing tools for analyzing complex traits and improving genomic prediction

Inheritance of DNA methylation level in healthy human tissues

DNA methylation (DNAm) is the covalent modification of DNA by addition of a methyl group primarily at the cytosine directly upstream of a guanine. DNAm level plays a central role in transcriptional regulation and is linked to disease. Therefore, understanding genetic and environmental influences on DNAm level in healthy tissue is an important step in the elucidation of trait and disease etiology. However, at present only a minority of easy to access human tissues and ethnicities have been investigated. Therefore, we studied DNAm level measured in five human tissues: cerebellum, frontal cortex, pons, temporal cortex and colon in either North American or South American samples. We applied a novel statistical approach to estimate the heritability attributable to genomic regions (regional heritability, ĥ²/r,g ) for DNAm level at thousands of individual DNAm sites genome-wide. In all five tissues, DNAm level was significantly associated with the local genomic region for more DNAm sites than expected by chance. Moreover, DNAm level could be predicted from the local sequence variants with an accuracy that scaled with the estimated ĥ²/r,g . Our results inform on molecular mechanisms regulating DNAm level and trait etiology in several ways. Firstly, DNAm level at DNAm sites located in genomic risk regions and measured in a tissue relevant to the disease can be influenced by the local genetic variants. Specifically, we found that genetic variation within a region associated with Fluid Intelligence was also associated with local DNAm level at the proline-rich coiled-coil 1 (PRRC1) gene in healthy temporal cortex tissue. Additionally, we replicated the finding of a Colorectal Cancer risk variant (rs4925386) associated with two DNAm sites in healthy colon tissue. More generally, we showed that DNAm sites located within a susceptibility region and measured in a relevant tissue exhibit a similar overall pattern of estimated ĥ²/r,g to DNAm sites outwith a susceptibility region. Secondly, the propensity for DNAm level to be associated with the local sequence variation differs with respect to CpG dinucleotide density and genic location. Most notably, DNAm sites located in CpG dense regions of the genome are less likely to be heritable than DNAm sites located in CpG sparse regions of the genome. Additionally, within both CpG dense and CpG sparse regions of the genome intergenic DNAm sites are more likely to be heritable than intragenic DNAm sites. Overall, our study suggests that variation in DNAm level at some DNAm sites is at least partially controlled by nuclear genetic variation. Moreover, DNAm level in healthy tissue has the potential to act as an intermediary in trait variation and etiology