Genome-wide analysis of sperm DNA methylation from monozygotic twin bulls

2017 ◽  
Vol 29 (4) ◽  
pp. 838 ◽  
Author(s):  
Habib A. Shojaei Saadi ◽  
Éric Fournier ◽  
Christian Vigneault ◽  
Patrick Blondin ◽  
Janice Bailey ◽  
...  
Keyword(s):  
Complex Traits ◽  
Semen Quality ◽  
Enrichment Analysis ◽  
Monozygotic Twin ◽  
Progeny Testing ◽  
Dna Methylome ◽  
Genome Wide ◽  
Sperm Dna ◽  
Significant Enrichment ◽  
Mz Twins

Monozygotic (MZ) twins are of great interest to elucidate the contributions of pre- and postnatal environmental factors on epigenetics in the expression of complex traits and diseases. Progeny testing recently revealed that MZ twin bulls do not necessarily lead to identical genetic merit estimates (i.e. breeding values). Therefore, to explain differences in offspring productivity of MZ twin bulls despite their identical genetic backgrounds, we hypothesised that paternal sperm epigenomes vary between MZ twin bulls. In the present study, semen characteristics and global sperm DNA methylome were profiled for four pairs of MZ twin bulls. Some MZ twin pairs had divergent semen quality (sperm morphology, motility and viability). Comparative genome-wide DNA methylome surveys were performed using methyl-sensitive enrichment and microarray identification. Between 2% and 10% of all probes (400 000) were differentially methylated between MZ twin pairs. In addition, there were 580 loci differentially methylated across all pairs of MZ twins. Furthermore, enrichment analysis indicated a significant enrichment for fertility associated quantitative trait loci (P = 0.033). In conclusion, differences in the sperm epigenome may contribute to incongruous diverging performances of daughters sired by bulls that are MZ twins.

scholarly journals Epigenome-Wide DNA Methylation Analysis of Monozygotic Twins Discordant for Diurnal Preference

2015 ◽  
Vol 18 (6) ◽  
pp. 662-669 ◽  
Author(s):  
Chloe C. Y. Wong ◽  
Michael J. Parsons ◽  
Kathryn J. Lester ◽  
Joe Burrage ◽  
Thalia C. Eley ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Circadian Clock ◽  
Monozygotic Twins ◽  
Enrichment Analysis ◽  
Genome Wide ◽  
Analysis Strategy ◽  
Diurnal Preference ◽  
Significant Enrichment ◽  
Longitudinal Twin Study ◽  
Mz Twins

Diurnal preference is an individual's preference for daily activities and sleep timing and is strongly correlated with the underlying circadian clock and the sleep-wake cycle validating its use as an indirect circadian measure in humans. Recent research has implicated DNA methylation as a mechanism involved in the regulation of the circadian clock system in humans and other mammals. In order to evaluate the extent of epigenetic differences associated with diurnal preference, we examined genome-wide patterns of DNA methylation in DNA from monozygotic (MZ) twin-pairs discordant for diurnal preference. MZ twins were selected from a longitudinal twin study designed to investigate the interplay of genetic and environmental factors in the development of emotional and behavioral difficulties. Fifteen pairs of MZ twins were identified in which one member scored considerably higher on the Horne–Ostberg Morningness–Eveningness Questionnaire (MEQ) than the other. Genome-wide DNA methylation patterns were assessed in twins’ buccal cell DNA using the Illumina Infinium HumanMethylation450 BeadChips. Quality control and data pre-processing was undertaken using the wateRmelon package. Differentially methylated probes (DMPs) were identified using an analysis strategy taking into account both the significance and the magnitude of DNA methylation differences. Our data indicate that DNA methylation differences are detectable in MZ twins discordant for diurnal preference. Moreover, downstream gene ontology (GO) enrichment analysis on the top-ranked diurnal preference associated DMPs revealed significant enrichment of pathways that have been previously associated with circadian rhythm regulation, including cell adhesion processes and calcium ion binding.

scholarly journals Integrating Signals from Sperm Methylome Analysis and Genome-Wide Association Study for a Better Understanding of Male Fertility in Cattle

Epigenomes ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 10 ◽  
Author(s):  
Lingzhao Fang ◽  
Yang Zhou ◽  
Shuli Liu ◽  
Jicai Jiang ◽  
Derek M. Bickhart ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Complex Traits ◽  
Male Fertility ◽  
Genome Wide Association ◽  
Human Society ◽  
Potential Candidate ◽  
Genome Wide ◽  
Sperm Dna ◽  
Genomic Regions ◽  
Sperm Dna Methylation

Decreased male fertility is a big concern in both human society and the livestock industry. Sperm DNA methylation is commonly believed to be associated with male fertility. However, due to the lack of accurate male fertility records (i.e., limited mating times), few studies have investigated the comprehensive impacts of sperm DNA methylation on male fertility in mammals. In this study, we generated 10 sperm DNA methylomes and performed a preliminary correlation analysis between signals from sperm DNA methylation and signals from large-scale (n = 27,214) genome-wide association studies (GWAS) of 35 complex traits (including 12 male fertility-related traits). We detected genomic regions, which experienced DNA methylation alterations in sperm and were associated with aging and extreme fertility phenotypes (e.g., sire-conception rate or SCR). In dynamic hypomethylated regions (HMRs) and partially methylated domains (PMDs), we found genes (e.g., HOX gene clusters and microRNAs) that were involved in the embryonic development. We demonstrated that genomic regions, which gained rather than lost methylations during aging, and in animals with low SCR were significantly and selectively enriched for GWAS signals of male fertility traits. Our study discovered 16 genes as the potential candidate markers for male fertility, including SAMD5 and PDE5A. Collectively, this initial effort supported a hypothesis that sperm DNA methylation may contribute to male fertility in cattle and revealed the usefulness of functional annotations in enhancing biological interpretation and genomic prediction for complex traits and diseases.

scholarly journals The molecular genetics of hand preference revisited

2018 ◽  
Author(s):  
Carolien G.F. de Kovel ◽  
Clyde Francks
Keyword(s):  
Complex Traits ◽  
Large Population ◽  
Enrichment Analysis ◽  
Hand Preference ◽  
Population Based ◽  
Gene Set Enrichment Analysis ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

AbstractHand preference is a prominent behavioural trait linked to human brain asymmetry. A handful of genetic variants have been reported to associate with hand preference or quantitative measures related to it. Most of these reports were on the basis of limited sample sizes, by current standards for genetic analysis of complex traits. Here we performed a genome-wide association analysis of hand preference in the large, population-based UK Biobank cohort (N=331,037). We used gene-set enrichment analysis to investigate whether genes involved in visceral asymmetry are particularly relevant to hand preference, following one previous report. We found no evidence implicating any specific candidate variants previously reported. We also found no evidence that genes involved in visceral laterality play a role in hand preference. It remains possible that some of the previously reported genes or pathways are relevant to hand preference as assessed in other ways, or else are relevant within specific disorder populations. However, some or all of the earlier findings are likely to be false positives, and none of them appear relevant to hand preference as defined categorically in the general population. Within the UK Biobank itself, a significant association implicates the gene MAP2 in handedness.

scholarly journals A large-scale genome-wide enrichment analysis identifies new trait-associated genes, pathways and tissues across 31 human phenotypes*

2017 ◽  
Author(s):  
Xiang Zhu ◽  
Matthew Stephens
Keyword(s):  
Complex Traits ◽  
Large Scale ◽  
Late Onset ◽  
Association Studies ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Enrichment Analysis ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Artery Disease

Genome-wide association studies (GWAS) aim to identify genetic factors that are associated with complex traits. Standard analyses test individual genetic variants, one at a time, for association with a trait. However, variant-level associations are hard to identify (because of small effects) and can be difficult to interpret biologically. “Enrichment analyses” help address both these problems by focusing on sets of biologically-related variants. Here we introduce a new model-based enrichment analysis method that requires only GWAS summary statistics, and has several advantages over existing methods. Applying this method to interrogate 3,913 biological pathways and 113 tissue-based gene sets in 31 human phenotypes identifies many previously-unreported enrichments. These include enrichments of the endochondral ossification pathway for adult height, the NFAT-dependent transcription pathway for rheumatoid arthritis, brain-related genes for coronary artery disease, and liver-related genes for late-onset Alzheimer’s disease. A key feature of our method is that inferred enrichments automatically help identify new trait-associated genes. For example, accounting for enrichment in lipid transport genes yields strong evidence for association between MTTP and low-density lipoprotein levels, whereas conventional analyses of the same data found no significant variants near this gene.

scholarly journals Multi-omics data analysis implicating epigenetic inheritance in evolution and disease

2019 ◽  
Author(s):  
Abhay Sharma
Keyword(s):  
Epigenetic Inheritance ◽  
Enrichment Analysis ◽  
Human Sperm ◽  
Gene Set Enrichment Analysis ◽  
Environment Interaction ◽  
Omics Data ◽  
Loss Of Function ◽  
Dna Methylome ◽  
Sperm Dna ◽  
Unbiased Gene

AbstractRecent evidence surprisingly suggests existence of germline mediated epigenetic inheritance in diverse species including mammals. The evolutionary and health implications as well as the mechanistic plausibility of epigenetic inheritance are subjects of immense current interest and controversy, with integrative analysis expected to provide valuable insights. Here, an unbiased gene set enrichment analysis of existing multi-omics data is presented that readily supports a role of sperm DNA methylome in evolution and disease, as also in developmental mechanisms. In mice, differentially methylated sperm genes in cold induced inheritance specifically overrepresent genes associated with cold adaptation. Similarly, in humans, differentially methylated sperm genes associate with disease and adaptation in general, with specific disease association supported by prior evidence. Further, the sperm genes, like disease and adaptation genes, overrepresent genes known to exhibit higher mutability, loss-of-function intolerance, and haploinsufficiency. Finally, both mouse and human sperm genes show enrichment for genes that retain sperm methylation during development and are developmentally expressed. Together, the present analysis provides one-stop evidence to suggest that sperm DNA methylome acts as a melting pot of gene-environment interaction, inheritance, evolution, and health and disease.

scholarly journals Monozygotic Twins Discordant for Immunoglobulin A Nephropathy Display Differences in DNA Methylation and Gene Expression

2020 ◽  
pp. 1-10
Author(s):  
Min Wei ◽  
Sijun Meng ◽  
Sufang Shi ◽  
Lijun Liu ◽  
Xujie Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Expression Profiles ◽  
Immunoglobulin A ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Genome Wide ◽  
Mz Twins

<b><i>Introduction:</i></b> Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis. It involves both genetic and environmental factors, among which DNA methylation, the most studied epigenetic modification, was shown to play a role. Here, we assessed genome-wide DNA methylation and gene expression profiles in 2 pairs of IgAN-discordant monozygotic (MZ) twins, in order to characterize methylation changes and their potential influences on gene expression in IgAN. <b><i>Methods:</i></b> Genome-wide DNA methylation and gene expression profiles were evaluated in peripheral blood mononuclear cells obtained from 2 IgAN-discordant MZ twins. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were detected, and an integrated analysis was performed. Finally, functional enrichment analysis was done for DMR-associated genes and DEGs. <b><i>Results:</i></b> Totally 521 DMRs were detected for 2 IgAN-discordant MZ twins. Among them, 9 DMRs were found to be mapped to genes that differentially expressed in 2 MZ twins, indicating the potential regulatory mechanisms of expression for these 9 genes (<i>MNDA</i>, <i>DYSF</i>, <i>IL1R2</i>, <i>TLR6</i>, <i>TREML2</i>, <i>TREM1</i>, <i>IL32</i>, <i>S1PR5</i>, and <i>ADGRE3</i>) in IgAN. Biological process analysis of them showed that they were mostly involved in the immune system process. Functional enrichment analysis of DEGs and DMR-associated genes both identified multiple pathways relevant to inflammatory and immune responses. And DMR-associated genes were significantly enriched in terms related to T-cell function. <b><i>Conclusions:</i></b> Our findings indicate that changes in DNA methylation patterns were involved in the pathogenesis of IgAN. Nine target genes detected in our study may provide new ideas for the exploration of molecular mechanisms of IgAN.

scholarly journals Divergence Analyses of Sperm DNA Methylomes between Monozygotic Twin AI Bulls

Epigenomes ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 21 ◽  
Author(s):  
Shuli Liu ◽  
Siqian Chen ◽  
Wentao Cai ◽  
Hongwei Yin ◽  
Aoxing Liu ◽  
...  
Keyword(s):  
Artificial Insemination ◽  
Bisulfite Sequencing ◽  
Semen Quality ◽  
Monozygotic Twin ◽  
Differentially Methylated Regions ◽  
Sperm Dna ◽  
Differentially Methylated Genes ◽  
Genome Bisulfite Sequencing ◽  
Holstein Bulls ◽  
Specific Pair

Semen quality is critical for fertility. However, it is easily influenced by environmental factors and can induce subfertility in the next generations. Here, we aimed to assess the impacts of differentially methylated regions and genes on semen quality and offspring fertility. A specific pair of monozygotic (MZ) twin artificial insemination (AI) Holstein bulls with moderately different sperm qualities (Bull1 > Bull2) was used in the study, and each twin bull had produced ~6000 recorded daughters nationwide in China. Using whole genome bisulfite sequencing, we profiled the landscape of the twin bulls’ sperm methylomes, and we observed markedly higher sperm methylation levels in Bull1 than in Bull2. Furthermore, we found 528 differentially methylated regions (DMR) between the MZ twin bulls, which spanned or overlapped with 309 differentially methylated genes (DMG). These DMG were particularly associated with embryo development, organ development, reproduction, and the nervous system. Several DMG were also shown to be differentially expressed in the sperm cells. Moreover, the significant differences in DNA methylation on gene INSL3 between the MZ twin bulls were confirmed at three different age points. Our results provided new insights into the impacts of AI bull sperm methylomes on offspring fertility.

scholarly journals Phenotype-specific enrichment of Mendelian disorder genes near GWAS regions across 62 complex traits

2018 ◽  
Author(s):  
Malika Kumar Freund ◽  
Kathryn Burch ◽  
Huwenbo Shi ◽  
Nicholas Mancuso ◽  
Gleb Kichaev ◽  
...  
Keyword(s):  
Complex Traits ◽  
Large Scale ◽  
Genetic Basis ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Mendelian Disorder ◽  
Mendelian Disorders ◽  
Gene Sets ◽  
Genome Wide ◽  
Significant Enrichment

ABSTRACTAlthough recent studies provide evidence for a common genetic basis between complex traits and Mendelian disorders, a thorough quantification of their overlap in a phenotype-specific manner remains elusive. Here, we quantify the overlap of genes identified through large-scale genome-wide association studies (GWAS) for 62 complex traits and diseases with genes known to cause 20 broad categories of Mendelian disorders. We identify a significant enrichment of phenotypically-matched Mendelian disorder genes in GWAS gene sets. Further, we observe elevated GWAS effect sizes near phenotypically-matched Mendelian disorder genes. Finally, we report examples of GWAS variants localized at the transcription start site or physically interacting with the promoters of phenotypically-matched Mendelian disorder genes. Our results are consistent with the hypothesis that genes that are disrupted in Mendelian disorders are dysregulated by noncoding variants in complex traits, and demonstrate how leveraging findings from related Mendelian disorders and functional genomic datasets can prioritize genes that are putatively dysregulated by local and distal non-coding GWAS variants.

scholarly journals Integrating Molecular QTL Data into Genome-wide Genetic Association Analysis: Probabilistic Assessment of Enrichment and Colocalization

2016 ◽  
Author(s):  
Xiaoquan Wen ◽  
Roger Pique-Regi ◽  
Francesca Luca
Keyword(s):  
Genetic Association ◽  
Association Analysis ◽  
Complex Traits ◽  
Association Studies ◽  
Enrichment Analysis ◽  
Computational Procedure ◽  
Candidate Snps ◽  
Power Calculation ◽  
Genetic Association Analysis ◽  
Genome Wide

AbstractWe propose a novel statistical framework for integrating genetic data from molecular quantitative trait loci (QTL) mapping into genome-wide genetic association analysis of complex traits, with the primary objectives of quantitatively assessing the enrichment of the molecular QTLs in complex trait-associated genetic variants and the colocalizations of the two types of association signals. We introduce a natural Bayesian hierarchical model that treats the latent association status of molecular QTLs as SNP-level annotations for candidate SNPs for complex traits. We detail a computational procedure to seamlessly perform enrichment, fine-mapping and colocalization analyses, which is a distinct feature compared to the existing colocalization analysis procedures in the literature. The proposed approach is computationally efficient and requires only summary-level statistics. We evaluate and demonstrate the proposed computational approach through extensive simulation studies and the analysis of blood lipid data and the whole blood eQTL data from the GTEx project. In addition, a useful utility from our proposed method enables the computation of expected colocalization signals, which is analogous to the power calculation in genetic association studies. Using this utility, we further illustrate the importance of enrichment analysis on the ability of discovering colocalized signals and the potential limitations of currently available molecular QTL data.

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