scholarly journals Use of Two Complementary Bioinformatic Approaches to Identify Differentially Methylated Regions in Neonatal Sepsis

2021 ◽  
Vol 14 (1) ◽  
pp. 144-152
Author(s):  
Paula Navarrete ◽  
María José Garzón ◽  
Sheila Lorente-Pozo ◽  
Salvador Mena-Mollá ◽  
Máximo Vento ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Neonatal Sepsis ◽  
Late Onset ◽  
Underlying Disease ◽  
Methylation Pattern ◽  
Differentially Methylated Regions ◽  
Genome Wide ◽  
Bioinformatic Approaches ◽  
Using Data ◽  
Underlying Mechanisms

Background: Neonatal sepsis is a heterogeneous condition affecting preterm infants whose underlying mechanisms remain unknown. The analysis of changes in the DNA methylation pattern can contribute to improving the understanding of molecular pathways underlying disease pathophysiology. Methylation EPIC 850K BeadChip technology is an excellent tool for genome-wide methylation analyses and the detection of differentially methylated regions (DMRs). Objective: The aim is to identify DNA methylation traits in complex diseases, such as neonatal sepsis, using data from Methylation EPIC 850K BeadChip arrays. Methods: Two different bioinformatic methods, DMRcate (a supervised approach) and mCSEA (an unsupervised approach), were used to identify DMRs using EPIC data from leukocytes of neonatal septic patients. Here, we describe with detail the implementation of both methods as well as their applicability, briefly discussing the results obtained for neonatal sepsis. Results: Differences in methylation levels were observed in neonatal sepsis patients. Moreover, differences were identified between the two subsets of the disease: Early-Onset neonatal Sepsis (EOS) and Late-Onset Neonatal Sepsis (LOS). Conclusion: This approach by using DMRcate and mCSA helped us to gain insight into the intricate mechanisms that may drive EOS and LOS development and progression in newborns.

scholarly journals Distinct epigenetic signatures between adult-onset and late-onset depression

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hirotaka Yamagata ◽  
Hiroyuki Ogihara ◽  
Koji Matsuo ◽  
Shusaku Uchida ◽  
Ayumi Kobayashi ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Clinical Symptoms ◽  
Late Onset ◽  
Adult Onset ◽  
Blood Biomarkers ◽  
Major Depressive ◽  
Genome Wide ◽  
Healthy Control ◽  
Epigenetic Signatures

AbstractThe heterogeneity of major depressive disorder (MDD) is attributed to the fact that diagnostic criteria (e.g., DSM-5) are only based on clinical symptoms. The discovery of blood biomarkers has the potential to change the diagnosis of MDD. The purpose of this study was to identify blood biomarkers of DNA methylation by strategically subtyping patients with MDD by onset age. We analyzed genome-wide DNA methylation of patients with adult-onset depression (AOD; age ≥ 50 years, age at depression onset < 50 years; N = 10) and late-onset depression (LOD; age ≥ 50 years, age at depression onset ≥ 50 years; N = 25) in comparison to that of 30 healthy subjects. The methylation profile of the AOD group was not only different from that of the LOD group but also more homogenous. Six identified methylation CpG sites were validated by pyrosequencing and amplicon bisulfite sequencing as potential markers for AOD in a second set of independent patients with AOD and healthy control subjects (N = 11). The combination of three specific methylation markers achieved the highest accuracy (sensitivity, 64%; specificity, 91%; accuracy, 77%). Taken together, our findings suggest that DNA methylation markers are more suitable for AOD than for LOD patients.

scholarly journals Genome-wide DNA methylation profile of early-onset endometrial cancer: its correlation with genetic aberrations and comparison with late-onset endometrial cancer

2019 ◽  
Vol 40 (5) ◽  
pp. 611-623 ◽  
Author(s):  
Takeshi Makabe ◽  
Eri Arai ◽  
Takuro Hirano ◽  
Nanako Ito ◽  
Yukihiro Fukamachi ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Endometrial Cancer ◽  
Early Onset ◽  
Late Onset ◽  
Methylation Profile ◽  
Cancer Tissue ◽  
Cpg Sites ◽  
Genome Wide ◽  
Dna Methylation Profile ◽  
Endometrioid Endometrial Cancer

Abstract The present study was performed to clarify the significance of DNA methylation alterations during endometrial carcinogenesis. Genome-wide DNA methylation analysis and targeted sequencing of tumor-related genes were performed using the Infinium MethylationEPIC BeadChip and the Ion AmpliSeq Cancer Hotspot Panel v2, respectively, for 31 samples of normal control endometrial tissue from patients without endometrial cancer and 81 samples of endometrial cancer tissue. Principal component analysis revealed that tumor samples had a DNA methylation profile distinct from that of control samples. Gene Ontology enrichment analysis revealed significant differences of DNA methylation at 1034 CpG sites between early-onset endometrioid endometrial cancer (EE) tissue (patients aged ≤40 years) and late-onset endometrioid endometrial cancer (LE) tissue, which were accumulated among ‘transcriptional factors’. Mutations of the CTNNB1 gene or DNA methylation alterations of genes participating in Wnt signaling were frequent in EEs, whereas genetic and epigenetic alterations of fibroblast growth factor signaling genes were observed in LEs. Unsupervised hierarchical clustering grouped EE samples in Cluster EA (n = 22) and samples in Cluster EB (n = 12). Clinicopathologically less aggressive tumors tended to be accumulated in Cluster EB, and DNA methylation levels of 18 genes including HOXA9, HOXD10 and SOX11 were associated with differences in such aggressiveness between the two clusters. We identified 11 marker CpG sites that discriminated EB samples from EA samples with 100% sensitivity and specificity. These data indicate that genetically and epigenetically different pathways may participate in the development of EEs and LEs, and that DNA methylation profiling may help predict tumors that are less aggressive and amenable to fertility preservation treatment.

scholarly journals Phenotypic and genetic characterization of lower LDL-C and increased type-2 diabetes risk in the UK Biobank

2020 ◽  
Author(s):  
Ada Admin ◽  
Yann C. Klimentidis ◽  
Amit Arora ◽  
Michelle Newell ◽  
Jin Zhou ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Uk Biobank ◽  
Alcoholic Fatty Liver ◽  
Genome Wide ◽  
Using Data ◽  
Underlying Mechanisms ◽  
Phenotypic And Genetic Characterization ◽  
The Uk

Although hyperlipidemia is traditionally considered a risk factor for type-2 diabetes (T2D), evidence has emerged from statin trials and candidate gene investigations suggesting that lower LDL-C increases T2D risk. We thus sought to more comprehensively examine the phenotypic and genotypic relationships of LDL-C with T2D. Using data from the UK Biobank, we found that levels of circulating LDL-C were negatively associated with T2D prevalence (OR=0.41[0.39, 0.43] per mmol/L unit of LDL-C), despite positive associations of circulating LDL-C with HbA1c and BMI. We then performed the first genome-wide exploration of variants simultaneously associated with lower circulating LDL-C and increased T2D risk, using data on LDL-C from the UK Biobank (n=431,167) and the GLGC consortium (n=188,577), and T2D from the DIAGRAM consortium (n=898,130). We identified 31 loci associated with lower circulating LDL-C and increased T2D, capturing several potential mechanisms. Seven of these loci have previously been identified for this dual phenotype, and 9 have previously been implicated in non-alcoholic fatty liver disease. These findings extend our current understanding of the higher T2D risk among individuals with low circulating LDL-C, and of the underlying mechanisms, including those responsible for the diabetogenic effect of LDL-C-lowering medications.

scholarly journals The value of DNA methylation profiling in characterizing preeclampsia and intrauterine growth restriction

2017 ◽  
Author(s):  
Samantha L Wilson ◽  
Katherine Leavey ◽  
Brian Cox ◽  
Wendy P Robinson
Keyword(s):  
Dna Methylation ◽  
Intrauterine Growth Restriction ◽  
Late Onset ◽  
Growth Restriction ◽  
Hypertensive Disorder ◽  
Intrauterine Growth ◽  
Healthy Pregnancy ◽  
Genome Wide ◽  
Illumina Humanmethylation450 ◽  
Clinical Diagnoses

AbstractPlacental health is a key component to healthy pregnancy. Placental insufficiency (PI), inadequate nutrient delivery to the fetus, is associated with preeclampsia (PE), a maternal hypertensive disorder, and intrauterine growth restriction (IUGR), pathologically poor fetal growth. PI is more common in early-onset PE (EOPE) than late-onset PE (LOPE). However, the relationship between these disorders remains unclear. While DNA methylation (DNAm) alterations have been identified in PE and IUGR, these entities can overlap and few studies have analyzed these separately. This study aims to identify altered DNAm in EOPE, LOPE, and normotensive IUGR, validate these alterations, and use them to better understand the relationships between these related disorders.Placental samples from a discovery cohort (43 controls, 22 EOPE, 18 LOPE, 11 IUGR) and validation cohort (15 controls, 22 EOPE, 11 LOPE) were evaluated using the Illumina HumanMethylation450 array. To minimize gestational age (GA) effects, EOPE samples were compared to pre-term controls (GA <37 weeks), while LOPE and IUGR were compared to term controls (GA >37 weeks). There were 1703 differentially methylated (DM) sites (FDR<0.05, Δβ>0.1) in EOPE, 5 in LOPE, and 0 in IUGR. Of the 1703 EOPE sites, 599 were validated in the second cohort. These sites cluster samples from both cohorts into 3 distinct methylation clusters. Interestingly, LOPE samples diagnosed between 34-36 weeks with co-occurring IUGR clustered with the EOPE methylation cluster. DNAm profiling may provide an independent tool to refine clinical diagnoses into subgroups with more uniform pathology. The challenges in reproducing genome-wide DNAm studies are also discussed.

scholarly journals High Resolution Genome Wide DNA Methylation Analysis in a Large Trial Group Reveals a Novel Epigenetically Defined Subgroup of Myeloma Patients Characterized By Developmental Gene Hypermethylation

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2189-2189
Author(s):  
Martin F Kaiser ◽  
Alexander Murison ◽  
Charlotte Pawlyn ◽  
Eileen M Boyle ◽  
David C Johnson ◽  
...  
Keyword(s):  
Dna Methylation ◽  
High Resolution ◽  
Methylation Pattern ◽  
Gene Set Enrichment Analysis ◽  
Epigenetic Changes ◽  
Dna Hypomethylation ◽  
Dna Hypermethylation ◽  
Epigenetic Programming ◽  
Genome Wide ◽  
Dna Methylation Pattern

Abstract Introduction Multiple myeloma is a clinically highly heterogeneous disease, which is reflected by both a complex genome and epigenome. Dynamic epigenetic changes are involved at several stages of myeloma biology, such as transformation and disease progression. Our previous genome wide epigenetic analyses identified prognostically relevant DNA hypermethylation at specific tumor suppressor genes (Kaiser MF et al., Blood 2013), indicating that specific epigenetic programming influences clinical behavior. This clinically relevant finding prompted further investigation of the epigenomic structure of myeloma and its interaction with genetic aberrations. Material and Methods Genome wide DNA methylation of CD138-purified myeloma cells from 464 patients enrolled in the NCRI Myeloma XI trial at presentation were analyzed using the high resolution 450k DNA methylation array platform (Illumina). In addition, 4 plasma cell leukemia (PCL) cases (two t(11;14) and two (4;14)) and 7 myeloma cell lines (HMCL) carrying different translocations were analysed. Analyses were performed in R Bioconductor packages after filtering and removal of low quality and non-uniquely mapping probes. Results Variation in genome wide DNA methylation was analyzed using unsupervised hierarchical clustering of the 10,000 most variable probes, which revealed epigenetically defined subgroups of disease. Presence of recurrent IGH translocations was strongly associated with specific epigenetic profiles. All 60 cases with t(4;14) clustered into two highly similar sub-clusters, confirming that overexpression of the H3K36 methyltransferase MMSET in t(4;14) has a defined and specific effect on the myeloma epigenome. Interestingly, HMCLs KMS-11 and LP-1, which carry t(4;14), MM1.S, a t(14;16) cell line with an E1099K MMSET activating mutation as well as two PCLs with t(4;14) all clustered in one sub-clade. The majority (59/85) of t(11;14) cases showed global DNA hypomethylation compared to t(4;14) cases and clustered in one subclade, indicating a epigenetic programming effect associated with CCND1, with a subgroup of t(11;14) cases showing a variable DNA methylation pattern. In addition to translocation-defined subgroups, a small cluster of samples with a distinct epigenetic profile was identified. In total 7 cases with a shared specific DNA methylation pattern (median inter-sample correlation 0.4) were identified. The group was characterized by DNA hypermethylation (4,341 hypermethylated regions vs. 750 hypomethylated regions) in comparison to all other cases. Intersection of regions hypermethylated in this subgroups with ENCODE datasets revealed mapping to poised enhancers and promoters in H1-hESC, indicating functionally relevant epigenetic changes. Gene set enrichment analysis (KEGG) demonstrated enrichment of developmental pathway genes, e.g. Hedgehog signaling (adj p=5x10exp-13), amongst others and all four HOX clusters were differentially methylated in this group. Of note, three of seven cases in this subgroup carried a t(11;14) and all t(11;14) or t(11;14)-like HMCLs clustered closely together with these patient cases, but not with the cluster carrying the majority of t(11;14) myeloma or t(11;14) PCLs. This potentially indicates that t(11;14) HMCL could be derived from a subgroup of patients with specific epigenetic characteristics. Conclusion Our results indicate that the recurrent IGH translocations are fundamentally involved in shaping the myeloma epigenome through either direct upregulation of epigenetic modifiers (e.g. MMSET) or through insufficiently understood mechanisms. However, developmental epigenetic processes seem to independently contribute to the complexity of the epigenome in some cases. This work provides important insights into the spectrum of epigenetic subgroups of myeloma and helps identify subgroups of disease that may benefit from specific epigenetic therapies currently being developed. Disclosures Walker: Onyx Pharmaceuticals: Consultancy, Honoraria.

1 Whole-genome bisulfite sequencing of bovine gametes and invivo-produced pre-implantation embryos

2019 ◽  
Vol 31 (1) ◽  
pp. 126
Author(s):  
J. E. Duan ◽  
Z. Jiang ◽  
F. Alqahtani ◽  
I. Mandoiu ◽  
H. Dong ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Epigenetic Regulation ◽  
Bisulfite Sequencing ◽  
Whole Genome ◽  
Differentially Methylated Regions ◽  
Whole Genome Bisulfite Sequencing ◽  
Cpg Sites ◽  
Genome Wide ◽  
Genome Bisulfite Sequencing

Dynamic changes in DNA methylation are crucial in the epigenetic regulation of mammalian embryogenesis. Global DNA methylation studies in the bovine, however, remain mostly at the immunostaining level. We adopted the single-cell whole-genome bisulfite sequencing method to characterise stage-specific genome-wide DNA methylation in bovine sperm, individual oocytes derived invivo and invitro, and invivo-developed embryos at the 2-, 4-, 8-, and 16-cell stages. This method allowed us to theoretically cover all CpG sites in the genome using a limited number of cells from single embryos. Pools of 20 sperm were selected from a bull with proven fertility. Single oocytes (n=6) and embryos (n=4 per stage) were collected from Holstein cows (n=10). Single-cell whole-genome bisulfite sequencing libraries were prepared and sequenced using the Illumina HiSEqn 4000 platform (Illumina, San Diego, CA, USA). Sequencing reads were filtered and aligned to the bovine reference genome (UMD 3.1.1) using Bismark (Krueger and Andrews 2011Bioinformatics27, 1571-1572, DOI: 10.1093/bioinformatics/btr167).A 300-bp tile-based method was applied to bin the genome into consecutive windows to facilitate comparison across samples. The DNA methylation level was calculated as the fraction of read counts of the total number of cytosines (methylated) in the total read counts of reported cytosines and thymines (methylated and unmethylated), only if more than 3 CpG sites were covered in this tile. Gamete-specific differentially methylated regions were identified when DNA methylation levels were greater than 75% in one type of gamete and less than 25% in the other with false discovery rate-corrected Fisher’s exact test P-values of less than 0.05. The major wave of genome-wide DNA demethylation was complete at the 8-cell stage when de novo methylation became prominent. Sperm and oocytes had numerous differentially methylated regions that were enriched in intergenic regions. Differentially methylated regions were also identified between invivo- and invitro-matured oocytes. Moreover, X chromosome methylation followed the global dynamic patterns. Virtually no (less than 1.5%) DNA methylation was found in mitochondrial DNA. Finally, using our RNA sequencing data generated from the same developmental stages (Jiang et al. 2014 BMC Genomics 15, 756; DOI: 10.1186/1471-2164-15-756), we revealed an inverse correlation between gene expression and promoter methylation. Our study provides the first fully comprehensive analysis of the global dynamics of DNA methylation in bovine gametes and single early embryos using single-cell whole-genome bisulfite sequencing. These data provide insights into the critical features of the methylome of bovine embryos and serve as an important reference for embryos produced by assisted reproduction, such as IVF and cloning, and a model for human early embryo epigenetic regulation.

scholarly journals Methylome and transcriptome profiles in three yak tissues revealed that DNA methylation and transcription factor ZGPAT co-regulate milk production

2020 ◽  
Author(s):  
Jinwei Xin ◽  
Zhixin Chai ◽  
Chengfu Zhang ◽  
Qiang Zhang ◽  
Yong Zhu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Network Analysis ◽  
Milk Production ◽  
Breast Tissue ◽  
Age Groups ◽  
High Expression ◽  
Differentially Methylated Regions ◽  
Genome Wide ◽  
Younger Age ◽  
Gene Correlation

Abstract Background Domestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat, and have evolved numerous physiological adaptabilities to high-altitude landscape, such as strong capacity of blood oxygen transportation and high metabolism. The role of DNA methylation and network of gene expression underlying milk production and adaptation to high altitudes of yak need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lungs, and gluteal muscle from yaks of different ages. We identified differentially methylated regions (DMRs) across age groups within the each tissue, and breast tissue had considerably more differentially methylated regions than that from the three younger age groups. Hypomethylated genes with high expression level might regulate milk production by influencing protein processing in the endoplasmic reticulum. Weighted gene correlation network analysis revealed that the “hub” gene ZGPAT was highly expressed in post-mature breast tissue and that it potentially regulated the transcription of 280 genes, which play roles in regulating protein synthesis, processing, and secretion. Besides, Tissue network analysis indicates that high expression of HIF1A regulates energy metabolism in the lung. Conclusions The results of this comprehensive study provide a solid basis for understanding the epigenetic mechanisms underlying milk production in yaks, which could be helpful to breeding programs aimed at improving milk production.

scholarly journals Methylome and transcriptome profiles in three yak tissues revealed that DNA methylation and transcription factor ZGPAT co-regulate milk production

2020 ◽  
Author(s):  
Jinwei Xin ◽  
Zhixin Chai ◽  
Chengfu Zhang ◽  
Qiang Zhang ◽  
Yong Zhu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Network Analysis ◽  
Milk Production ◽  
Breast Tissue ◽  
Biceps Brachii ◽  
Age Groups ◽  
High Expression ◽  
Differentially Methylated Regions ◽  
Genome Wide ◽  
Gene Correlation

Abstract Background Domestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat. They have evolved numerous physiological adaptabilities to high-altitude environment, such as the strong capacity of blood oxygen transportation and high metabolism. The role of DNA methylation and network of gene expression underlying milk production and adaptation to high altitudes of yak need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lung, and biceps brachii muscle from yaks of different ages. We identified differentially methylated regions (DMRs) across age groups within the each tissue. The breast tissue had considerably more differentially methylated regions than that from the three younger age groups. Hypomethylated genes with high expression level might regulate milk production by influencing protein processing in the endoplasmic reticulum. Weighted gene correlation network analysis revealed that the “hub” gene ZGPAT was highly expressed in the post-mature breast tissue. It potentially regulated the transcription of 280 genes, which play roles in regulating protein synthesis, processing, and secretion. Besides, Tissue network analysis indicates that high expression of HIF1A regulates energy metabolism in the lung. Conclusions The results of this comprehensive study provide a solid basis for understanding the epigenetic mechanisms underlying milk production in yaks, which could be helpful to breeding programs aimed at improving milk production.

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