Differentially Methylated Genes Research Articles

Differential DNA methylation across environments has no effect on gene expression in the eastern oyster.

It has been hypothesized that environmentally induced changes to gene body methylation could facilitate adaptive transgenerational responses to changing environments. We compared patterns of global gene expression (Tag-seq) and gene body methylation (reduced representation bisulfite sequencing) in 80 eastern oysters Crassostrea virginica from six full-sib families, common gardened for 14months at two sites in the northern Gulf of Mexico that differed in mean salinity. At the time of sampling, oysters from the two sites differed in mass by 60% and in parasite loads by nearly two orders of magnitude. They also differentially expressed 35% of measured transcripts. However, we observed differential methylation at only 1.4% of potentially methylated loci in comparisons between individuals from these different environments, and little correspondence between differential methylation and differential gene expression. Instead, methylation patterns were largely driven by genetic differences among families, with a PERMANOVA analysis indicating nearly a two orders of magnitude greater number of genes differentially methylated between families than between environments. An analysis of CpG observed/expected values (CpG O/E) across the C. virginica genome showed a distinct bimodal distribution, with genes from the first cluster showing the lower CpG O/E values, greater methylation and higher and more stable gene expression, while genes from the second cluster showed lower methylation, and lower and more variable gene expression. Taken together, the differential methylation results suggest that only a small portion of the C. virginica genome is affected by environmentally induced changes in methylation. At this point, there is little evidence to suggest that environmentally induced methylation states would play a leading role in regulating gene expression responses to new environments.

Integration of Transcriptome and Methylome Analyses Provides Insight Into the Pathway of Floral Scent Biosynthesis in Prunus mume.

DNA methylation is a common epigenetic modification involved in regulating many biological processes. However, the epigenetic mechanisms involved in the formation of floral scent have rarely been reported within a famous traditional ornamental plant Prunus mume emitting pleasant fragrance in China. By combining whole-genome bisulfite sequencing and RNA-seq, we determined the global change in DNA methylation and expression levels of genes involved in the biosynthesis of floral scent in four different flowering stages of P. mume. During flowering, the methylation status in the “CHH” sequence context (with H representing A, T, or C) in the promoter regions of genes showed the most significant change. Enrichment analysis showed that the differentially methylated genes (DMGs) were widely involved in eight pathways known to be related to floral scent biosynthesis. As the key biosynthesis pathway of the dominant volatile fragrance of P. mume, the phenylpropane biosynthesis pathway contained the most differentially expressed genes (DEGs) and DMGs. We detected 97 DMGs participated in the most biosynthetic steps of the phenylpropane biosynthesis pathway. Furthermore, among the previously identified genes encoding key enzymes in the biosynthesis of the floral scent of P. mume, 47 candidate genes showed an expression pattern matching the release of floral fragrances and 22 of them were differentially methylated during flowering. Some of these DMGs may or have already been proven to play an important role in biosynthesis of the key floral scent components of P. mume, such as PmCFAT1a/1c, PmBEAT36/37, PmPAL2, PmPAAS3, PmBAR8/9/10, and PmCNL1/3/5/6/14/17/20. In conclusion, our results for the first time revealed that DNA methylation is widely involved in the biosynthesis of floral scent and may play critical roles in regulating the floral scent biosynthesis of P. mume. This study provided insights into floral scent metabolism for molecular breeding.

Transcriptome-wide N 6-Methyladenosine Methylome Profiling Reveals m6A Regulation of Skeletal Myoblast Differentiation in Cattle (Bos taurus).

N 6 -methyladenosine (m6A) is the most prevalent methylation modification of eukaryotic mRNA, and it plays an important role in regulating gene expression. Previous studies have found that m6A methylation plays a role in mammalian skeletal muscle development. However, the effect of m6A on bovine skeletal myogenesis are still unclear. Here, we selected proliferating myoblasts (GM) and differentiated myotubes (on the 4th day of differentiation, DM) for m6A-seq and RNA-seq to explore the m6A methylation modification pattern during bovine skeletal myogenesis. m6A-seq analysis revealed that m6A methylation was an abundant modification of the mRNA in bovine myoblasts and myotubes. We scanned 5,691–8,094 m6A-modified transcripts, including 1,437 differentially methylated genes (DMGs). GO and KEGG analyses revealed that DMGs were primarily involved in transcriptional regulation and RNA metabolism, as well as insulin resistance and metabolic pathways related to muscle development. The combined analysis further identified 268 genes that had significant changes at both m6A and mRNA levels, suggesting that m6A modification may regulate myoblast differentiation by mediating the expression of these genes. Furthermore, we experimentally confirmed four genes related to myogenesis, including MYOZ2, TWIST1, KLF5 and MYOD1, with differential changes in both m6A and mRNA levels during bovine myoblast differentiation, indicating that they can be potential candidate targets for m6A regulation of skeletal myogenesis. Our results may provide new insight into molecular genetics and breeding of beef cattle, and provide a reference for investigating the mechanism of m6A regulating skeletal muscle development.

Integration of Transcriptome and Methylome Highlights the Roles of Cell Cycle and Hippo Signaling Pathway in Flatfish Sexual Size Dimorphism.

Sexual size dimorphism (SSD) is the difference in segments or body size between sexes prevalent in various species. Understanding the genetic architecture of SSD has remained a significant challenge owing to the complexity of growth mechanisms and the sexual influences among species. The Chinese tongue sole (Cynoglossus semilaevis), which exhibits a female-biased SSD and sex reversal from female to pseudomale, is an ideal model for exploring SSD mechanism at the molecular level. The present study aimed to integrate transcriptome and methylome analysis to unravel the genetic and epigenetic changes in female, male, and pseudomale C. semilaevis. The somatotropic and reproductive tissues (brain, liver, gonad, and muscle) transcriptomes were characterized by RNA-seq technology. Transcriptomic analysis unravelled numerous differentially expressed genes (DEGs) involved in cell growth and death-related pathways. The gonad and muscle methylomes were further employed for screening differentially methylated genes (DMGs). Relatively higher DNA methylation levels were observed in the male and pseudomale individuals. In detail, hypermethylation of the chromosome W was pronounced in the pseudomale group than in the female group. Furthermore, weighted gene co-expression network analysis showed that turquoise and brown modules positively and negatively correlated with the female-biased SSD, respectively. A combined analysis of the module genes and DMGs revealed the female-biased mRNA transcripts and hypomethylated levels in the upstream and downstream regions across the cell cycle-related genes. Moreover, the male and pseudomale-biased gene expression in the hippo signaling pathway were positively correlated with their hypermethylation levels in the gene body. These findings implied that the activation of the cell cycle and the inhibition of the hippo signaling pathway were implicated in C. semilaevis female-biased SSD. In addition, the dynamic expression pattern of the epigenetic regulatory factors, including dnmt1, dnmt3a, dnmt3b, and uhrf1, among the different sexes correspond with their distinct DNA methylation levels. Herein, we provide valuable clues for understanding female-biased SSD in C. semilaevis.

Integrative Analysis of DNA Methylation and Gene Expression Profiling Data Reveals Candidate Methylation-Regulated Genes in Hepatoblastoma

PurposeThis study aimed to identify novel methylation-regulated genes as diagnostic biomarkers and therapeutic targets for hepatoblastoma (HB).Materials and MethodsThe DNA methylation data of 19 HB tumor samples and 10 normal liver samples from the GSE78732 dataset and gene expression profiling data of 53 HB tumor samples and 14 normal liver samples from the GSE131329 dataset and 31 HB tumor samples and 32 normal liver samples from the GSE133039 dataset were downloaded form the Gene Expression Omnibus database. Next, differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified. Venn diagrams were used to identify methylation-regulated genes. The VarElect online tool was selected to identify key methylation-regulated genes, and a protein–protein interaction (PPI) network was constructed to show the interactions among key methylation-regulated genes and DEGs. Finally, Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to investigate the potential regulatory mechanisms of key methylation-regulated genes.ResultsA total of 457 DMGs and 1597 DEGs were identified between the HB and normal liver samples. After DMGs and DEGs overlapping, 22 hypomethylated and upregulated genes and 19 hypermethylated and downregulated genes in HB were screened. Survival analysis revealed that 13 methylation-regulated genes were associated with the prognosis of liver cancer. Moreover, SPP1, UHRF1, and HEY1 were selected as the key DNA methylation-regulated genes. The PPI network revealed that all of them could affect TP53, while both UHRF1 and HEY1 could influence BMP4. Enrichment analysis suggested that the DEGs were involved in TP53-related pathways, including the cell cycle and p53 signaling pathway. Finally, SPP1, UHRF1, and HEY1 were hypomethylated and upregulated in the HB samples compared with those in the normal liver samples.ConclusionSPP1, UHRE1, and HEY1 may play important roles in HB and be used as biomarkers for its diagnosis and treatment.

Methylome and transcriptome analyses of soybean response to bean pyralid larvae

BackgroundBean pyralid is one of the major leaf-feeding insects that affect soybean crops. DNA methylation can control the networks of gene expressions, and it plays an important role in responses to biotic stress. However, at present the genome-wide DNA methylation profile of the soybean resistance to bean pyralid has not been reported so far.ResultsUsing whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq), we analyzed the highly resistant material (Gantai-2-2, HRK) and highly susceptible material (Wan82–178, HSK), under bean pyralid larvae feeding 0 h and 48 h, to clarify the molecular mechanism of the soybean resistance and explore its insect-resistant genes. We identified 2194, 6872, 39,704 and 40,018 differentially methylated regions (DMRs), as well as 497, 1594, 9596 and 9554 differentially methylated genes (DMGs) in the HRK0/HRK48, HSK0/HSK48, HSK0/HRK0 and HSK48/HRK48 comparisons, respectively. Through the analysis of global methylation and transcription, 265 differentially expressed genes (DEGs) were negatively correlated with DMGs, there were 34, 49, 141 and 116 negatively correlated genes in the HRK0/HRK48, HSK0/HSK48, HSK0/HRK0 and HSK48/HRK48, respectively. The MapMan cluster analysis showed that 114 negatively correlated genes were clustered in 24 pathways, such as protein biosynthesis and modification; primary metabolism; secondary metabolism; cell cycle, cell structure and component; RNA biosynthesis and processing, and so on. Moreover, CRK40; CRK62; STK; MAPK9; L-type lectin-domain containing receptor kinase VIII.2; CesA; CSI1; fimbrin-1; KIN-14B; KIN-14 N; KIN-4A; cytochrome P450 81E8; BEE1; ERF; bHLH25; bHLH79; GATA26, were likely regulatory genes involved in the soybean responses to bean pyralid larvae. Finally, 5 DMRs were further validated that the genome-wide DNA data were reliable through PS-PCR and 5 DEGs were confirmed the relationship between DNA methylation and gene expression by qRT-PCR. The results showed an excellent agreement with deep sequencing.ConclusionsGenome-wide DNA methylation profile of soybean response to bean pyralid was obtained for the first time. Several specific DMGs which participated in protein kinase, cell and organelle, flavonoid biosynthesis and transcription factor were further identified to be likely associated with soybean response to bean pyralid. Our data will provide better understanding of DNA methylation alteration and their potential role in soybean insect resistance.

Comprehensive Analysis of N6-Methyladenosine (m6A) Methylation in Neuromyelitis Optica Spectrum Disorders.

Background: N6-Methyladenosine (m6A) methylation is the most prevalent internal posttranscriptional modification on mammalian mRNA. But its role in neuromyelitis optica spectrum disorders (NMOSD) is not known. Aims: To explore the mechanism of m6A in NMOSD patients. Methods: This study assessed the m6A methylation levels in blood from two groups: NMOSD patients and healthy controls. Methylated RNA immunoprecipitation Sequencing (MeRIP-seq) and RNA-seq were performed to assess differences in m6A methylation between NMOSD patients and healthy controls. Ultra-high performance liquid chromatography coupled with triple quadruple mass spectrometry (UPLC-QQQ-MS) method was performed to check m6A level. Differential m6A methylation genes were validated by MeRIP-qPCR. Results: Compared with that in the control group, the total m6A level was decreased in the NMOSD group. Genes with upregulated methylation were primarily enriched in processes associated with RNA splicing, mRNA processing, and innate immune response, while genes with downregulated methylation were enriched in processes associated with the regulation of transcription, DNA-templating, and the positive regulation of I-kappa B kinase/NF-kappa B signalling. Conclusion: These findings demonstrate that differential m6A methylation may act on functional genes to regulate immune homeostasis in NMOSD.

Transcriptome-wide N6-methyladenosine (m6A) methylation in watermelon under CGMMV infection

BackgroundCucumber green mottle mosaic virus (CGMMV) causes substantial global losses in cucurbit crops, especially watermelon. N6-methyladenosine (m6A) methylation in RNA is one of the most important post-transcriptional modification mechanisms in eukaryotes. It has been shown to have important regulatory functions in some model plants, but there has been no research regarding m6A modifications in watermelon.ResultsWe measured the global m6A level in resistant watermelon after CGMMV infection using a colorimetric method. And the results found that the global m6A level significantly decreased in resistant watermelon after CGMMV infection. Specifically, m6A libraries were constructed for the resistant watermelon leaves collected 48 h after CGMMV infection and the whole-genome m6A-seq were carried out. Numerous m6A modified peaks were identified from CGMMV-infected and control (uninfected) samples. The modification distributions and motifs of these m6A peaks were highly conserved in watermelon transcripts but the modification was more abundant than in other reported crop plants. In early response to CGMMV infection, 422 differentially methylated genes (DMGs) were identified, most of which were hypomethylated, and probably associated with the increased expression of watermelon m6A demethylase gene ClALKBH4B. Gene Ontology (GO) analysis indicated quite a few DMGs were involved in RNA biology and stress responsive pathways. Combined with RNA-seq analysis, there was generally a negative correlation between m6A RNA methylation and transcript level in the watermelon transcriptome. Both the m6A methylation and transcript levels of 59 modified genes significantly changed in response to CGMMV infection and some were involved in plant immunity.ConclusionsOur study represents the first comprehensive characterization of m6A patterns in the watermelon transcriptome and helps to clarify the roles and regulatory mechanisms of m6A modification in watermelon in early responses to CGMMV.

Dynamic changes of genomic methylation profiles at different growth stages in Chinese Tan sheep

BackgroundTan sheep, an important local sheep breed in China, is famous for their fur quality. One-month-old Tan sheep have white, curly hair with beautiful flower spikes, commonly known as “nine bends”, which has high economic value. However, the “nine bends” characteristic gradually disappears with age; consequently, the economic value of the Tan sheep decreases. Age-related changes in DNA methylation have been reported and may be responsible for age-induced changes in gene expression. Until now, no genome-wide surveys have been conducted to identify potential DNA methylation sites involved in different sheep growth stages. In this study we investigated the dynamic changes of genome-wide DNA methylation profiles in Tan sheep using DNA from skin and deep whole-genome bisulfite sequencing, and compared the DNA methylation levels at three different growth stages: 1, 24, and 48 months old (mon1, mon24, and mon48, respectively).ResultsIn this study, 11 skin samples from three growth stages (four for mon1, four for mon24, and three for mon48) were used for DNA methylation analysis and gene expression profiling. There were 52, 288 and 236 differentially methylated genes (DMGs) identified between mon1 and mon24, mon1 and mon48, and mon24 and mon48, respectively. Of the differentially methylated regions, 1.11%, 7.61%, and 7.65% were in the promoter in mon1 vs. mon24, mon24 vs. mon48, and mon1 vs. mon48, respectively. DMGs were enriched in the MAPK and WNT signaling pathways, which are related to age growth and hair follicle morphogenesis processes. There were 51 DMGs associated with age growth and curly fleece formation. Four DMGs between mon1 and mon48 (KRT71, CD44, ROR2 and ZDHHC13) were further validated by bisulfite sequencing.ConclusionsThis study revealed dynamic changes in the genomic methylation profiles of mon1, mon24, and mon48 sheep, and the percentages of methylated cytosines were 3.38%, 2.85% and 4.17%, respectively. Of the DMGs, KRT71 and CD44 were highly methylated in mon1, and ROR2 and ZDHHC13 were highly methylated in mon48. These findings provide foundational information that may be used to develop strategies for potentially retaining the lamb fur and thus improving the economic value of Tan sheep.

Contribution of Dysregulated DNA Methylation to Autoimmunity.

Epigenetic mechanisms, such as DNA methylation, histone modifications, and non-coding RNAs are known regulators of gene expression and genomic stability in cell growth, development, and differentiation. Because epigenetic mechanisms can regulate several immune system elements, epigenetic alterations have been found in several autoimmune diseases. The purpose of this review is to discuss the epigenetic modifications, mainly DNA methylation, involved in autoimmune diseases in which T cells play a significant role. For example, Rheumatoid Arthritis and Systemic Lupus Erythematosus display differential gene methylation, mostly hypomethylated 5′-C-phosphate-G-3′ (CpG) sites that may associate with disease activity. However, a clear association between DNA methylation, gene expression, and disease pathogenesis must be demonstrated. A better understanding of the impact of epigenetic modifications on the onset of autoimmunity will contribute to the design of novel therapeutic approaches for these diseases.

A five-gene methylation signature predicts overall survival of patients with clear cell renal cell carcinoma.

BackgroundIn this study, we aimed to screen methylation signatures associated with the prognosis of patients with clear cell renal cell carcinoma (ccRCC).MethodsGene expression and methylation profiles of ccRCC patients were downloaded from publicly available databases, and differentially expressed genes (DEGs)‐differentially methylated genes (DMGs) were obtained. Subsequently, gene set enrichment and transcription factor (TF) regulatory network analyses were performed. In addition, a prognostic model was constructed and the relationship between disease progression and immunity was analyzed.ResultsA total of 23 common DEGs‐DMGs were analyzed, among which 14 DEGs‐DMGs were obtained with a cutoff value of PCC < 0 and p < 0.05. The enrichment analysis showed that the 14 DEGs‐DMGs were enriched in three GO terms and three KEGG pathways. In addition, a total of six TFs were shown to be associated with the 14 DEGs‐DMGs, including RP58, SOX9, NF‐κB65, ATF6, OCT, and IK2. A prognostic model using five optimized DEGs‐DMGs which efficiently predicted survival was constructed and validated using the GSE105288 dataset. Additionally, four types of immune cells (NK cells, macrophages, neutrophils, and cancer‐associated fibroblasts), as well as ESTIMATE, immune, and stromal scores were found to be significantly correlated with ccRCC progression (normal, primary, and metastasis) in addition to the five optimized DEGs‐DMGs.ConclusionA five‐gene methylation signature with the predictive ability for ccRCC prognosis was investigated in this study, consisting of CCNB2, CDKN1C, CTSH, E2F2, and ERMP1. In addition, potential targets for methylation‐mediated immunotherapy were highlighted.

Genome-Wide DNA Methylation Profile in Jejunum Reveals the Potential Genes Associated With Paratuberculosis in Dairy Cattle.

Paratuberculosis in cattle causes substantial economic losses to the dairy industry. Exploring functional genes and corresponding regulatory pathways related to resistance or susceptibility to paratuberculosis is essential to the breeding of disease resistance in cattle. Co-analysis of genome-wide DNA methylation and transcriptome profiles is a critically important approach to understand potential regulatory mechanism underlying the development of diseases. In this study, we characterized the profiles of DNA methylation of jejunum from nine Holstein cows in clinical, subclinical, and healthy groups using whole-genome bisulfite sequencing (WGBS). The average methylation level in functional regions was 29.95% in the promoter, 29.65% in the 5’ untranslated region (UTR), 68.24% in exons, 71.55% in introns, and 72.81% in the 3’ UTR. A total of 3,911, 4,336, and 4,094 differentially methylated genes (DMGs) were detected in clinical vs. subclinical, clinical vs. healthy, and subclinical vs. healthy comparative group, respectively. Gene ontology (GO) and analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that these DMGs were significantly enriched in specific biological processes related to immune response, such as Th1 and Th2 cell differentiation, wnt, TNF, MAPK, ECM-receptor interaction, cellular senescence, calcium, and chemokine signaling pathways (q value <0.05). The integration of information about DMGs, differentially expressed genes (DEGs), and biological functions suggested nine genes CALCRL, TNC, GATA4, CD44, TGM3, CXCL9, CXCL10, PPARG, and NFATC1 as promising candidates related to resistance/susceptibility to Mycobacterium avium subspecies paratuberculosis (MAP). This study reports on the high-resolution DNA methylation landscapes of the jejunum methylome across three conditions (clinical, subclinical, and healthy) in dairy cows. Our investigations integrated different sources of information about DMGs, DEGs, and pathways, enabling us to find nine functional genes that might have potential application in resisting paratuberculosis in dairy cattle.

ABCA1, TCF7, NFATC1, PRKCZ and PDGFA DNA methylation as potential epigenetic-sensitive targets in acute coronary syndrome via network analysis

Abstract Background Acute coronary syndrome (ACS) is the most severe clinical manifestation of coronary heart disease and the leading cause of death worldwide. Purpose To perform an epigenome-wide analysis in circulating CD4+ and CD8+ T cells of ACS patients and healthy subjects (HS) enrolled in the DIANA clinical trial (NCT04371809) in order to identify differentially methylated genes (DMGs). Methods Genomic DNA was extracted from CD4+ and CD8+ T cells of all subjects and sequenced by the reduced representation bisulfite sequencing (RRBS) platform. Functional pathway analysis was performed and significant DMGs were selected for gene expression validation by qRT-PCR in ACS patients and HS. GeneMANIA was used to built a prediction gene network. Correlation analyses between molecular data and clinical variables were performed. Results In CD4+ T cells we identified 61 differentially methylated regions (DMRs) associated to 57 annotated genes of which 53% (n=32) were hyper- and 47% (n=29) were hypo-methylated in ACS patients vs HS. In CD8+ T cells we identified 613 DMRs associated to 569 annotated genes of which 28% (n=173) were hyper- and 72% (n=440) were hypo-methylated between two groups. In both cell type of ACS patients, 175 DMRs were associated to 157 annotated genes of which 41% (n=72) were hyper- and 59% (n=103) were hypo-methylated. From functional analysis, we selected the top 5 DMGs in the prevalent pathways with the highest differential of methylation values. Specifically, we considered 6 hub genes: NFATC1, TCF7, PDGFA, PRKCB, PRKCZ and ABCA1 and determined their respective expression levels by q-RT-PCR. We found a significant up-regulation of the selected genes in ACS patients vs HS (P&amp;lt;0.001 for all comparisons). Correlation analysis showed both common and cell specific correlation patterns. In CD4+ T cells, PDGFA promoter methylation was negatively correlated with CK-MB concentrations (r=−0.79, P=0.018). ABCA1, TCF7, PDGFA and PRKCZ gene expression was positively associated to CK-MB concentrations (r=0.75, P=0.03; r=0.760, P=0.029; r=0.72, P=0.044; r=0.74, P=0.035, respectively). Conlusions This study is the first single-base resolution map of DNA methylome by RRBS in CD4+ and CD8+ T cells, providing specific methylation signatures that could help to clarify the role of aberrant methylation in ACS pathogenesis, and provide the basis for the search of novel epigenetic-sensitive biomarkers in the prevention and early diagnosis of this pathology. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Italian Ministry of Health;Italian Ministry of Research and University

160 Studies of Sperm DNA Methylation Variations and Their Potential Regulations on Production and Reproduction Traits in Cattle and Pigs

Abstract Identification of inter-individual variations of sperm DNA methylation is very essential for elucidating phenotypic variation of reproduction and production traits. We had generated 28 sperm whole genome sequencing (WGBS) data from healthy individuals. We detected 46 variably methylated regions (VMRs) significantly (P &amp;lt; 5.77 × 10−5) associated with reproduction traits. These significant VMRs were also co-localized (±10 kb) with genes related to sperm motility and reproduction, including ZFP36L1, CRISP2 and HGF. To further identify epigenomic markers associated with reproduction and production traits, we generated WGBS dada for a specific pair of monozygotic twin artificial insemination Holstein bulls with moderately different sperm qualities (Bull1 &amp;gt; Bull2). We found 528 differentially methylated regions between the twin bulls, which spanned or overlapped with 309 differentially methylated genes (DMG). These DMG were particularly associated with reproduction, embryo development and the nervous system. To further obtain DNA methylation markers involved in the diversity of porcine reproduction and production traits due to long-term artificial selection, we profiled sperm DNA methylation of three commercial pig breeds--Duroc, Landrace and Large White. we found the hypomethylated regions (HMRs) were highly conserved among pig breeds, while 1040–1666 breed-specific HMRs were identified and associated with the QTLs of embryonic developmental and phenotypic changes. By integrating reduced representation bisulfite sequencing public data of pig testis, we further defined 1743 conservative HMRs between sperm and testis, which may play a role in spermatogenesis process. Overall, our studies demonstrated associations of sperm DNA methylation with bovine and porcine production and reproduction traits, highlighting the potential of epigenomic information in genomic improvement programs for livestock. (*: yuying@cau.edu.cn)

164 Genome-wide DNA Methylation Profiling in in Utero Heat-stressed Pigs as Measured by Whole-genome Bisulfite Sequencing

Abstract In utero heat stress (IUHS) has several postnatal consequences in pigs that compromise health, increase stress response, and reduce performance. These phenotypes may be caused by epigenetic modifications such as DNA methylation, which are heritable molecular modifications that impact gene expression and phenotypic outcomes without changing the DNA sequence. Therefore, we aimed to compare the DNA methylation profiles between in-utero thermoneutral (IUTN) and IUHS pigs to identify differentially methylated regions. Twenty-four pregnant gilts were evenly assigned to either a thermoneutral (17.5 ± 2.1°C) or heat stress (cycling 26 to 36°C) chamber from d 0 to 59 of gestation, followed by thermoneutral conditions (20.9 ± 2.3°C) for the rest of gestation and until the piglets were weaned. At 105 d of age, 10 IUTN and 10 IUHS piglets were euthanized and Longissimus dorsi muscle samples were collected and used to perform whole-genome bisulfite sequencing (WGBS). Purified genomic DNA was fragmented and bisulfite conversion was performed. Illumina platforms were used to sequence WGBS libraries. All pigs had similar proportions of methylation at CpG sites. Two-hundred-sixty-eight genomic regions were differentially methylated between IUTN and IUHS pigs. These identified regions are located across all pig chromosomes and ranged from 2 (SSC18) to 40 (SSC10). Eighty-five unique differentially-methylated genes were identified. These genes have been reported to be involved in key biological processes such as transcriptional repressor activity and tRNA processing (e.g., SKOR2,TRMT6, TSEN2), cellular response to heat stress (e.g.,CCAR2), placental vascularization (e.g.,FZD5), central nervous system (e.g.,VEPH1), cholesterol biosynthesis (e.g., CYB5R1), insulin receptor substrate (e.g.,IRS2), synaptic transmission (e.g.,RIMBP2), neurotrophic factor receptor activity (e.g.,LIFR), immune response (e.g., CD84), DNA repair (e.g., CHD1L), and cell proliferation and endocrine signaling (e.g., SSTR1, CYB5R1). These findings contribute to a better understanding of the epigenomic mechanisms underlying postnatal consequences of IUHS in pigs.

Methylome changes during Lr48-mediated APR for leaf rust in wheat (Triticum aestivum L.)

Differential DNA methylation due to APR gene Lr48 for leaf rust resistance in wheat cv. CSP44 was examined at pre-adult plant (P-AP) susceptible stage and adult plant (AP) resistant stage. As many as 52,872 differentially methylated regions (DMRs) carrying 897 differentially methylated genes (DMGs) and many intergenic regions were identified. A proportion of individual DMGs involved in methylation included exons/introns, promoters and UTRs. DMGs were also compared with transcriptome data based on RNA-seq. Susceptibility (at P-AP) was found to be governed by activation (due to hypomethylation) of relatively more genes, whereas resistance (at AP) involved silencing of relatively large number of genes. Using GO terms, DMGs were assigned to a variety of functions belonging to biological processes including transcription regulation, protein synthesis, signal transduction, defense, photosynthesis, lipid and carbohydrate metabolism. The results of the present study improved our understanding of the epigenetic control of APR to leaf rust in wheat.

Novel DNA methylation markers of PRRSV-specific antibodies and their intergenerational transmission from pregnant sows to piglets.

The main strategy for preventing porcine reproductive and respiratory syndrome (PRRS) is vaccination. However, current commercial porcine reproductive and respiratory syndrome virus (PRRSV) vaccines have limited effectiveness and may even cause infections in pigs. The identification of stable molecular markers associated with immune responses to PRRSV vaccination in pigs provides a new approach for PRRS prevention. DNA methylation, the most stable epigenetic molecular marker related to PRRSV vaccination, has not been investigated. In the current research, we used whole genome bisulfite sequencing (WGBS) to investigate DNA methylation in pregnant sows that received PRRSV vaccination and their piglets with high and low PRRSV-specific antibody levels. By performing methylation data analysis and basing on our previous transcriptomic studies, we identified several differentially methylated genes (DMGs) that are involved in the pathways of inflammatory and immune responses. Among the DMGs, ISG15, MX1, SERPINE1, GNG11 and IFIT3 were common hub genes in the two generations. MX1 and GNG11 were located in quantitative trait loci related with PRRSV antibody titer and PRRSV susceptibility, respectively. These results suggest that PRRSV vaccination in sows induces DNA methylation changes in genes and DNA methylation changes occur through intergenerational transmission. The novel DNA methylation markers and target genes observed in our study provide new insights into the molecular mechanisms of immune responses to PRRSV vaccination across two pig generations.

Differences in DNA methylation between slow and fast muscle in Takifugu rubripes.

Fish skeletal muscle is comprised of fast muscle (FM) and slow muscle (SM), which constitutes 60% of total the body mass. Fish skeletal muscle can affect fish swimming activity, which is important for aquaculture due to its growth-potentiating effects. DNA methylation can influence gene expression level. We previously identified multiple differentially expressed genes (DEGs) between FM and SM in Takifugu rubripes. However, it is unknown if the expression levels of these DEGs are influenced by DNA methylation. In the present study, we used DNA methylation sequencing to study the DNA methylation profiles of FM and SM in T. rubripes. SM had higher overall methylation levels than FM. A total of 8479 differentially methylated genes (DMGs) and 3407 DMGs containing differentially methylated regions (DMRs) in the promoter regions between FM and SM were identified. After enrichment analysis, we found functionally relevant DMGs between FM and SM, including Kapca, Plcd3a, Plcd1, Pi3k, Tsp4b and Pgfrb in the hedgehog signaling pathway and phosphatidylinositol (PI)-related pathways. Due to the different methylation levels of these genes between FM and SM, the expression levels of Kapca, Plcd3a, Plcd1, Pi3k, and Tsp4b were higher in FM and Pgfrb was higher in SM. There were differences in the hedgehog signaling pathway and PI-related pathways between FM and SM. In SM, the cytokine-cytokine receptor interaction promoted focal adhesion, while ECM-receptor interactions promoted focal adhesion in FM. These results provide information regarding the difference between FM and SM in T. rubripes.

Genome-wide analysis of DNA methylation in 106 schizophrenia family trios in Han Chinese

BackgroundSchizophrenia (SCZ) is a severe psychiatric disorder that affects approximately 0.75% of the global population. Both genetic and environmental factors contribute to development of SCZ. SCZ tends to run in family while both genetic and environmental factor contribute to its etiology. Much evidence suggested that alterations in DNA methylations occurred in SCZ patients.MethodsTo investigate potential inheritable pattern of DNA methylation in SCZ family, we performed a genome-wide analysis of DNA methylation of peripheral blood samples from 106 Chinese SCZ family trios. Genome-wide DNA methylations were quantified by Agilent 1 × 244 k Human Methylation Microarray.FindingsIn this study, we proposed a loci inheritance frequency model that allows characterization of differential methylated regions as SCZ biomarkers. Based on this model, 112 hypermethylated and 125 hypomethylated regions were identified. Additionally, 121 hypermethylated and 139 hypomethylated genes were annotated. The results of functional enrichment analysis indicated that multiple differentially methylated genes (DMGs) involved in Notch/HH/Wnt signaling, MAPK signaling, GPCR signaling, immune response signaling. Notably, a number of hypomethylated genes were significantly enriched in cerebral cortex and functionally enriched in nervous system development.InterpretationOur findings not only validated previously discovered risk genes of SCZ but also identified novel candidate DMGs in SCZ. These results may further the understanding of altered DNA methylations in SCZ.

Genome-wide DNA methylation profiles provide insight into epigenetic regulation of red and white muscle development in Chinese perch Siniperca chuatsi.

Fish skeletal muscles are composed of spatially well-separated fiber types, namely, red and white muscles with different physiological functions and metabolism. To compare the DNA methylation profiles of the two types of muscle tissues and identify potential candidate genes for the muscle growth and development under epigenetic regulation, genome-wide DNA methylation of the red and white muscle in Chinese perch Siniperca chuatsi were comparatively analyzed using bisulfate sequencing methods. An average of 0.9 billion 150-bp paired-end reads were obtained, of which 86% were uniquely mapped to the genome. Methylation mostly occurred at CG sites at a ratio of 94.43% in the red muscle and 93.16% in the white muscle. The mean methylation levels at C-sites were 5.95% in red muscle and 5.83% in white muscle, whereas the mean methylation levels of CG, CHG, and CHH were 73.23%, 0.62%, and 0.67% in red muscle, and 71.01%, 0.62%, and 0.67% in white muscle, respectively. A total of 4192 differentially methylated genes (DMGs) were identified significantly enriched in cell signaling pathways related to skeletal muscle differentiation and growth. Various muscle-related genes, including myosin gene isoforms and regulatory factors, are differentially methylated in the promoter region between the red and white muscles. Further analysis of the transcriptional expression of these genes showed that the muscle regulatory factors (myf5, myog, pax3, pax7, and twitst2) and myosin genes (myh10, myh16, myo18a, myo7a, myo9a, and myl3) were differentially expressed between the two kinds of muscles, consistent with the DNA methylation analysis results. ELISA assays confirmed that the level of 5mC in red muscle was significantly higher than in white muscle (P<0.05). The RT-qPCR assays revealed that the expression levels of the three DNA methylation transferase (dnmt) subtypes, dnmt1, dnmt3ab, and dnmt3bb1, were significantly higher in red muscle than in white muscle. The higher DNA methylation levels in the red muscle may result from higher DNA methylation transferase expression in the red muscles. Thus, this study might provide a theoretical foundation to better understand epigenetic regulation in the growth and development of red and white muscles in animals, at least in Chinese perch fish.