Comparative analyses of sperm DNA methylomes among human, mouse and cattle provide insights into epigenomic evolution and complex traits

Abstract

Sperm DNA methylation is crucial for fertility and viability of offspring but epigenome evolution in mammals is largely understudied. By comparing sperm DNA methylomes and large-scale genome-wide association study (GWAS) signals between human and cattle, we aimed to examine the DNA methylome evolution and its associations with complex phenotypes in mammals. Our analysis revealed that genes with conserved non-methylated promoters (e.g., ANKS1A and WNT7A) among human and cattle were involved in common system and embryo development, and enriched for GWAS signals of body conformation traits in both species, while genes with conserved hypermethylated promoters (e.g., TCAP and CD80) were engaged in immune responses and highlighted by immune-related traits. On the other hand, genes with human-specific hypomethylated promoters (e.g., FOXP2 and HYDIN) were engaged in neuron system development and enriched for GWAS signals of brain-related traits, while genes with cattle-specific hypomethylated promoters (e.g., LDHB and DGAT2) mainly participated in lipid storage and metabolism. We validated our findings using sperm-retained nucleosome, preimplantation transcriptome, and adult tissue transcriptome data, as well as sequence evolutionary features, including motif binding sites, mutation rates, recombination rates and evolution signatures. In conclusion, our results demonstrate important roles of epigenome evolution in shaping the genetic architecture underlying complex phenotypes, hence enhance signal prioritization in GWAS and provide valuable information for human neurological disorders and livestock genetic improvement.

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

“…For human GWAS data, we obtained the summary statistics for 58 complex traits with an average sample size of 128,848 and an average SNP number of 5,905,874. Details of human GWAS studies are summarized in [26]. We grouped these diseases and traits into 5 categories similarly as in cattle: reproduction (n = 4), metabolic (n = 13), mental (n = 22), immune (n = 8), and growth (n = 13).…”

“…When integrating tissue-specific histone marks with human GWAS, we first transferred tissue-specific histone marks from GRCh38 to GRCh37 using UCSC LiftOver tool (-min-Match = 0.8), as coordinates of variants in GWAS were based on GRCh37. Detailed procedures were presented in [26]. We applied a sum-based marker-set test approach, implemented in the QGG package [78], to determine whether GWAS signals were enriched in tissue-specific histone marks.…”

“…Selection signature is available in [43]. Details of human GWAS summary statistics are summarized in [26]. Among 40 WGBS data being analyzed, 4 WGBS of macrophages were downloaded from GSE110412 [88]; 2 breast WGBS samples from SRP190079; 6 WGBS of brain, mammary, and whole blood cells (WBC) from GSE106538 [89]; and 2 WGBS of sperm from GSE131851.…”

“…These may make Holstein cattle a potential animal model for studying certain human complex traits and diseases. Recently, by comparing sperm methylomes between human and Holstein cattle, we demonstrated that genomic variants of morphology-relevant traits were consistently and significantly enriched in the evolutionarily conserved hypomethylated regions in human and cattle [26]. Furthermore, the rapidly reduced immune and reproductive capacity of dairy cattle has been observed during the strong selection for milk production over the past decades [27].…”

GeneDMRs: An R Package for Gene-Based Differentially Methylated Regions Analysis

“…One was download from GEO with the accession number GSE129385 (https://www.ncbi.nlm.nih.gov/geo/query/ acc.cgi?acc=GSE129385) that is also RRBS sequencing data from nine porcine testis samples Kadarmideen, 2019a, 2020). Another one was downloaded from GEO with the accession number GSE106538 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106538) that is WGBS sequencing data from four bovine sperm samples (Zhou et al, 2018;Fang et al, 2019). For all reference genes (n = 4475) and all gene bodies (n = 77,022) of porcine RRBS data with around 1 million analyzed CpG sites, GeneDMRs package completed the whole DMR detections in around 1 minute and 1 hour, respectively.…”