Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human

Abstract

Background: Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle. Results: We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cellspecific gene, was significantly associated with both allergic diseases in human and metritis in cattle.

Large-scale genomic analysis reveals the genetic cost of chicken domestication

“…Further validation using higher coverage genomes is warranted. Lastly, our analysis focused on variants in the coding regions; however, non-coding regions are increasingly known to play important regulatory roles, and some variants within these regions likely have significant biological functions [ 73 ]; future studies should be designed to explore the evolutionary and functional roles of variants within regulatory regions in domestication and genetic improvement of chickens.…”

Cerebrum, liver, and muscle regulatory networks uncover maternal nutrition effects in developmental programming of beef cattle during early pregnancy

“…Furthermore, fetal adaptive response by affecting insulin metabolism may adversely affect animal feed efficiency. It's worth mentioning that due to the similarities underlying embryonic development in humans www.nature.com/scientificreports/ and cattle and the conserved genetic architecture of complex traits in both species 69 , our findings can help understanding the effects of maternal nutrition on human fetal development. Obesity, molecular disorders, and cardiovascular diseases later in life have been associated with pre-natal maternal stressors 8,70 .…”

Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

“…For instance, it has been demonstrated that the immune system mounts a specific autoimmune response against hair follicle antigens [ 53 ], and that the breakdown of the hair follicle immune privilege leads to T-cell inflammation [ 54 ]. These results reveal the importance of integrating omics data for the detection of relevant tissues and candidate genes for complex traits [ 21 , 62 – 64 ] and suggest the potential of cross-species mapping to benefit the livestock industry and human biomedicine [ 65 , 66 ]. However, it should be noted that the PheWAS results based on human data, similar to the results from comparative genomic mapping, are not easily transposable to findings in livestock, and that their interpretation is often biased by many factors that differ between humans and livestock.…”