Recurrent DNMT3A Mutations In Patients with Myelodysplastic Syndrome

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 608-608
Author(s):  
Matthew J. Walter ◽  
Dong Shen ◽  
Jin Shao ◽  
Li Ding ◽  
Marcus Grillot ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bone Marrow ◽  
Myelodysplastic Syndrome ◽  
Sample Size ◽  
De Novo ◽  
Small Sample Size ◽  
Dna Methyltransferases ◽  
Small Sample ◽  
Mutation Status ◽  
Cd34 Cells

Abstract Abstract 608 Myelodysplastic syndrome (MDS) genomes are characterized by global DNA hypomethylation with concomitant hypermethylation of gene promoter regions compared to CD34+ cells from normal bone marrow samples. Currently, the underlying mechanism of altered DNA methylation in MDS genomes and the critical target genes affected by methylation remain largely unknown. The methylation of CpG dinucleotides in humans is mediated by DNA methyltransferases, including DNMT1, DNMT3A, and DNMT3B. DNMT3A and DNMT3B are the dominant DNA methyltransferases involved in de novo DNA methylation and act independent of replication, whereas DNMT1 acts predominantly during replication to maintain hemimethylated DNA. The function of these proteins in cancer cells is less well defined. Our group recently found that DNMT3A mutations are common in de novo acute myeloid leukemia (62/281 cases, 22%) and are associated with poor survival (Ley, et al, unpublished), providing a rationale for examining the mutation status of DNMT3A in MDS patients. MDS cases (n=150) were classified according to the French-American-British (FAB) system. The patients included refractory anemia (RA; n=67), RA with ringed sideroblasts (RARS; n=5), RA with excess blasts (RAEB; n=72), and RA with excess blasts in transformation (RAEB-T; n=6). The median International Prognostic Scoring System (IPSS) score was 1 (range 0–3), and the median myeloblast count was 4 (range 0–28%). We designed and validated 28 primer pairs covering the coding sequences and splice sites of all 23 exons for DNMT3A. Paired DNA samples were obtained from the bone marrow (tumor) and skin (normal) of each patient so that somatic mutations could be distinguished from inherited variants/polymorphisms. 17,120 reads were produced by capillary sequencing, providing at least 1X coverage for 82.6% of the target sequence (low/no coverage was obtained for 2 out of 28 amplicons). A semiautomated analysis pipeline was used to identify sequence variants and we restricted our analysis to nonsynonymous and splice site nucleotide changes. All mutations were confirmed by independent PCR and sequencing. We identified nonsynonymous DNMT3A mutations in 12/150 bone marrow samples (8% of cases). All the mutations were heterozygous (10 missense, 1 nonsense, 1 frameshift) and were computationally predicted (by SIFT and/or PolyPhen2) to have deleterious functional consequences. DNMT3A mRNA is expressed in normal CD34+ bone marrow cells and was expressed in all MDS patient samples tested (n=28), independent of mutation status. There was no difference in the expression level of total DNMT3A mRNA in CD34+ cells harvested from mutant (n=3) vs. non-mutant MDS samples (n=25). Amino acid R882, located in the methyltransferase domain of DNMT3A, was the most common mutation site, accounting for 4/12 mutations. The clinical characteristics of the 12 patients with DNMT3A mutations were similar to those of the 138 patients without mutations. Specifically, DNMT3A mutations were present in all MDS FAB subtypes (excluding CMML which was not tested) and in patients with IPSS scores ranging from 0–3. Mutations were not associated with a specific karyotype. In addition, there was no correlation between mutation detection and the myeloblast count of the banked bone marrow specimen, suggesting that mutations were not missed due to the cellular heterogeneity in the samples. We compared the overall (OS) and event-free survival (EFS) of the 12 patients with DNMT3A mutations vs. 138 patients without a mutation and observed a significantly worse OS in patients with mutations (p=0.02), with a median survival of 433 and 945 days, respectively. There was a trend towards worse EFS for patients with mutations (p=0.05). A multivariate analysis for outcomes could not be performed due to the small sample size of patients with mutations, indicating that a larger cohort from a clinical trial will be needed to properly address the affect of DNMT3A mutations on outcomes. The small sample size also precluded us from addressing whether the response to the hypomethylating agents 5-azacytidine or decitabine correlated with the mutation status of DNMT3A. If validated in larger cohort studies, we propose that DNMT3A mutation status could help risk stratify de novo MDS patients for more aggressive treatment early in their disease course. Disclosures: Westervelt: Novartis: Honoraria; Celgene: Honoraria, Speakers Bureau. DiPersio:Genzyme: Honoraria.

scholarly journals Filtering high-dimensional methylation marks with extremely small sample size: an application to gastric cancer data

2021 ◽  
Author(s):  
Xin Chen ◽  
Qingrun Zhang ◽  
Thierry Chekouo
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Sample Size ◽  
Small Sample Size ◽  
Small Sample ◽  
Differential Methylation ◽  
High Dimensional ◽  
Cancer Data ◽  
Cancer Pathogenesis ◽  
A Genome

Abstract Background: DNA methylations in critical regions are highly involved in cancer pathogenesis and drug response. However, to identify causal methylations out of a large number of potential polymorphic DNA methylation sites is challenging. This high-dimensional data brings two obstacles: first, many established statistical models are not scalable to so many features; second, multiple-test and overfitting become serious. To this end, a method to quickly filter candidate sites to narrow down targets for downstream analyses is urgently needed. Methods: BACkPAy is a pre-screening Bayesian approach to detect biological meaningful clusters of potential differential methylation levels with small sample size. BACkPAy prioritizes potentially important biomarkers by the Bayesian false discovery rate (FDR) approach. It filters non-informative sites (i.e. non-differential) with flat methylation pattern levels accross experimental conditions. In this work, we applied BACkPAy to a genome-wide methylation dataset with 3 tissue types and each type contains 3 gastric cancer samples. We also applied LIMMA (Linear Models for Microarray and RNA-Seq Data) to compare its results with what we achieved by BACkPAy. Then, Cox proportional hazards regression models were utilized to visualize prognostics significant markers with The Cancer Genome Atlas (TCGA) data for survival analysis. Results: Using BACkPAy, we identified 8 biological meaningful clusters/groups of differential probes from the DNA methylation dataset. Using TCGA data, we also identified five prognostic genes (i.e. predictive to the progression of gastric cancer) that contain some differential methylation probes, whereas no significant results was identified using the Benjamin-Hochberg FDR in LIMMA. Conclusions: We showed the importance of using BACkPAy for the analysis of DNA methylation data with extremely small sample size in gastric cancer. We revealed that RDH13, CLDN11, TMTC1, UCHL1 and FOXP2 can serve as predictive biomarkers for gastric cancer treatment and the promoter methylation level of these five genes in serum could have prognostic and diagnostic functions in gastric cancer patients.

Detection of Differential Mitotic Cell Ages in Bone Marrow CD34+ Cells Selected from Patients with Myelodysplastic Syndrome and Acute Leukemia by Pyrosequencing Analysis of An Epigenetic Molecular Clock DNA Signature

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2693-2693
Author(s):  
Maximilian Mossner ◽  
Olaf Hopfer ◽  
Claudia D Baldus ◽  
Uwe Neumann ◽  
Anke Kmetsch ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bone Marrow ◽  
High Risk ◽  
Myelodysplastic Syndrome ◽  
Molecular Clock ◽  
Mitotic Cell ◽  
Healthy Individuals ◽  
Healthy Donors ◽  
Cd34 Cells ◽  
B Lineage

Abstract Introduction: Disturbed proliferation and differentiation are the most crucial oncogeneic factors leading to malignant turnover of hematopoiesis in myeloid malignancies. Therefore, estimating the lifetime proliferation status of malignant hematopoietic cells is critical. Recently the hypothesis of an epigenetic molecular clock has been corroborated. Depending on the accumulation of CpG methylation errors throughout life after each cell division it is possible to measure an increased DNA methylation of formerly unmethylated CpG islands and subsequently relate it to the mitotic cell age. In order to elucidate the importance of disturbed proliferation in hematologic diseases we initiated a novel approach for profiling mitotic ages of hematopoietic cells in myelodysplastic syndrome and acute leukemia. Patients & Methods: Bone marrow (BM) cells of patients with myelodysplastic syndrome (MDS, IPSS-low/int-1-risk n=23, IPSS-int-2/high-risk n=27), acute myeloid leukemia (AML, n=55), acute lymphoblastic leukemia (ALL, T-lineage n=40, B-lineage n=8), and of age matched healthy individuals (n=24) were analyzed. In addition, selection of CD34+ cells was performed in MDS (n=43), in AML (n=10) as well as in healthy BM samples (n=31). CD19+ peripheral blood cells from healthy donors (n=13) served as an additional control. Genomic DNA was isolated and bisulfite converted using standard TRIZOL technique (Invitrogen, Carlsbad/CA, USA) followed by EpiTect-Bisulfite-Kit conversion (Qiagen, Hilden, Germany). PCR amplification of a CpG rich 3′ site of the Cardiac Specific Homeobox gene (CSX), considered as an epigenetic molecular clock locus, was performed as previously reported. DNA methylation was quantitative measured using the PyroMark ID Pyrosequencing system (Biotage, Uppsala, Sweden). Quantitative DNA methylation data are presented with mean ± S.E.M. Results: In MDS int-2/high-risk specific DNA methylation of BM (26.6 ± 1.8 %) and CD34+ (28.6 ± 2.7 %) was significant higher compared to low/int-1-risk MDS (BM: 19.2 ± 1.6 %, p=0.0047, CD34+: 18.7 ± 2.4 %, p=0.0093) and healthy donors (BM: 17.8 ± 0.5 %, CD34+: 17.0 ± 0.4 %, p<0.0001). Furthermore, AML BM samples showed significant higher methylation of 34.2 ± 1.7 % compared to MDS BM int-2/high-risk samples (p=0.0081). Interestingly we could detect significant higher differences in CSX methylation between paired BM/CD34+ samples in MDS low/int-1-risk, but not in MDS int-2/high-risk or AML compared to age matched healthy individuals (p=0.0063). Notably, T-lineage ALL samples did show a remarkable high mean methylation of 61.7 ± 3.1 %. However, B-lineage ALL analysis revealed a similar methylation pattern in comparison to healthy CD19+ cells (26.1 ± 1.4 % and 25.1 ± 1.4% respectively). Discussion: The significant higher CSX methylation in AML compared to int-2/high-risk and in int-2/high-risk compared to low/int-1-risk MDS or healthy individuals could possibly be considered as a disease stage related molecular marker. The intra-individual similarity of CSX methylation levels between BM and CD34+ cells in int-2/high-risk MDS patients supports the theory of a stem cell origin of this disease subgroup, whereas low/int-1-risk MDS samples reveal higher differences possibly pointing to an origin in a more differentiated progenitor cell. However, the observation of higher mitotic ages in T-lineage but not B-lineage ALL raises questions about the role of cell proliferation in distinct lymphoblastic leukemias. In summary, the determination of mitotic cell ages by quantitative DNA methylation analysis could contribute to the molecular classification of hematological malignancies and may further be used for riskassessment in patients with MDS.

Dnmt3b Is Dispensable for Hematopoietic Stem Cell Differentiation, but Acts Synergistically with Dnmt3a to Control the Balance Between Self-Renewal and Differentiation

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 848-848
Author(s):  
Allison Mayle ◽  
Grant Anthony Challen ◽  
Deqiang Sun ◽  
Mira Jeong ◽  
Min Luo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Bone Marrow ◽  
Peripheral Blood ◽  
De Novo ◽  
Annexin V ◽  
Dna Methyltransferases ◽  
Self Renewal ◽  
Minimal Impact ◽  
Hsc Transplantation

Abstract Abstract 848 DNA methylation is an epigenetic modification in vertebrate genomes critical for regulation of gene expression. DNA methylation is catalyzed by a family of DNA methyltransferase enzymes, Dnmt1, Dnmt3a, and Dnmt3b. Dnmt1 is primarily a maintenance methyltransferase, targeting hemimethylated DNA to reestablish methylation marks after DNA replication. Dnmt3a and Dnmt3b are de novo methyltransferases that are essential for normal embryonic development. In humans, somatic mutations in DNTM3A have been identified in ∼20% of human acute myeloid leukemia (AML) and ∼10% of myelodysplastic syndrome (MDS) patients, but the mechanisms through which these mutations contribute to pathogenesis is not well understood. Congenital mutations in DNMT3B can cause ICF (immunodeficiency, centromeric instability, and facial anomalies) syndrome. These patients exhibit chromosomal instability due to heterochromatin decondensation and demethylation of satellite DNA. Our group has recently reported that Dnmt3a is essential for HSC differentiation (Challen Nature Genetics, 2011). Conditional knockout of Dnmt3a (Dnmt3a-KO) resulted in HSCs that could not sustain peripheral blood generation after serial transplantation, but phenotypically defined HSCs accumulated in the bone marrow. Dnmt3b is also highly expressed in HSCs, but its contribution to gene regulation in hematopoiesis is unclear. Here, we examine the role of Dnmt3b, alone and in combination with Dnmt3a KO, in the regulation of hematopoiesis. We performed conditional ablation of Dnmt3b, as well as Dnmt3a and Dnmt3b simultaneously using the Mx1-cre system. Unlike the Dnmt3a-KO HSCs, loss of Dnmt3b had a minimal impact on blood production. Even after several rounds of transplantation, 3b-KO HSCs performed similarly to WT controls. However, the Dnmt3ab-dKO (double knock-out) peripheral blood contribution was quickly and severely diminished, accompanied by a dramatic accumulation of Dnmt3ab-dKO HSCs in the bone marrow (Figure 1). The dKO phenotype paralleled that of the 3a-KO HSC, but was more extreme. To examine the impact of loss of Dnmt3a and -3b on DNA methylation in HSCs, we performed Whole Genome Bisulfite Sequencing (WGBS) on Dnmt3a-KO, Dnmt3ab- dKO and control HSCs. As we previously found with more limited DNA methylation analysis, loss of Dnmt3a led to both increases and decreases of DNA methylation at distinct genomic regions (Challen, Nature Genetics, 2011). However, loss of both Dnmt3a and -3b primarily resulted in loss of DNA methylation that was much more extensive than that seen in the 3a-KO. In addition, RNAseq of the mutant HSCs revealed increased expression of repetitive elements, inappropriate splicing, and truncation of 3ÕUTRs. To gain insight into the accumulation of Dnmt3ab-dKO HSCs in the bone marrow, we performed a time course analysis of the proliferation and apoptosis status of the HSCs. Every four weeks after transplantation of HSCs, we sacrificed a cohort of 3 control and 3 dKO mice, counted donor derived HSCs in the bone marrow, and analyzed their Ki67 and Annexin V expression. Up to 12 weeks post-transplant, no significant differences are seen in the expression of Ki67 or Annexin V. These data show that while Dnmt3b alone has minimal impact on DNA methylation in HSCs, Dnmt3a and -3b act synergistically to effect gene expression changes that permit HSC differentiation. In the absence of both of these de novo DNA methyltransferases, there is an immediate and extreme shift toward self-renewal of dKO HSCs. The Ki67 and Annexin V expression patterns suggest that a lack of de novo DNA methylation does not affect the proliferation or apoptosis of HSCs, but instead that the accumulation of HSCs and lack of peripheral blood contribution is primarily due to an imbalance between self-renewal and differentiation. By understanding the mechanisms through which Dnmt3a and -3b exert these effects, we should identify genes that are critical for normal hematopoietic differentiation. These genes may serve as targets for therapeutic intervention in malignancies caused by defective DNA methyltransferases. Figure 1: HSC composition of the bone marrow after secondary transplantation of control (left) and double Dnmt3a/3b KO (right) HSCs. After control HSC transplantation, HSCs comprise ∼0.01% of whole bone marrow. After transplantation of dKO HSCs, phenotypically-defined HSCs (KLS CD34–Flk2–) comprise ∼0.48% of bone marrow. Figure 1:. HSC composition of the bone marrow after secondary transplantation of control (left) and double Dnmt3a/3b KO (right) HSCs. After control HSC transplantation, HSCs comprise ∼0.01% of whole bone marrow. After transplantation of dKO HSCs, phenotypically-defined HSCs (KLS CD34–Flk2–) comprise ∼0.48% of bone marrow. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Filtering High-Dimensional Methylation Marks With Extremely Small Sample Size: An Application to Gastric Cancer Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Chen ◽  
Qingrun Zhang ◽  
Thierry Chekouo
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Sample Size ◽  
Small Sample Size ◽  
Small Sample ◽  
Differential Methylation ◽  
High Dimensional ◽  
Cancer Data ◽  
Cancer Pathogenesis ◽  
A Genome

DNA methylations in critical regions are highly involved in cancer pathogenesis and drug response. However, to identify causal methylations out of a large number of potential polymorphic DNA methylation sites is challenging. This high-dimensional data brings two obstacles: first, many established statistical models are not scalable to so many features; second, multiple-test and overfitting become serious. To this end, a method to quickly filter candidate sites to narrow down targets for downstream analyses is urgently needed. BACkPAy is a pre-screening Bayesian approach to detect biological meaningful patterns of potential differential methylation levels with small sample size. BACkPAy prioritizes potentially important biomarkers by the Bayesian false discovery rate (FDR) approach. It filters non-informative sites (i.e., non-differential) with flat methylation pattern levels across experimental conditions. In this work, we applied BACkPAy to a genome-wide methylation dataset with three tissue types and each type contains three gastric cancer samples. We also applied LIMMA (Linear Models for Microarray and RNA-Seq Data) to compare its results with what we achieved by BACkPAy. Then, Cox proportional hazards regression models were utilized to visualize prognostics significant markers with The Cancer Genome Atlas (TCGA) data for survival analysis. Using BACkPAy, we identified eight biological meaningful patterns/groups of differential probes from the DNA methylation dataset. Using TCGA data, we also identified five prognostic genes (i.e., predictive to the progression of gastric cancer) that contain some differential methylation probes, whereas no significant results was identified using the Benjamin-Hochberg FDR in LIMMA. We showed the importance of using BACkPAy for the analysis of DNA methylation data with extremely small sample size in gastric cancer. We revealed that RDH13, CLDN11, TMTC1, UCHL1, and FOXP2 can serve as predictive biomarkers for gastric cancer treatment and the promoter methylation level of these five genes in serum could have prognostic and diagnostic functions in gastric cancer patients.

Cytogenetics in Adult De Novo Acute Myeloid Leukemia: An Institutional Experience of a Predominantly Minority Population.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 4484-4484
Author(s):  
Ebenezer Berko ◽  
David Osafo ◽  
Deimante Tamkus ◽  
Decebal S. Griza ◽  
Steven Sloan ◽  
...  
Keyword(s):  
Sample Size ◽  
De Novo ◽  
Small Sample Size ◽  
Small Sample ◽  
Minority Population ◽  
Intermediate Group ◽  
Cytogenetic Aberrations ◽  
Predominantly Minority ◽  
Institutional Experience ◽  
De Novo Aml

Abstract Cytogenetic findings at diagnosis correlate with prognosis in adult AML. Data have been largely derived from Caucasian populations. The purpose of this study was to define the frequency of cytogenetic abnormalities in de novo AML in a predominantly minority population and compare the data with that reported in the literature. We performed a retrospective review of cytogenetic findings at diagnosis in 40 adult AML patients diagnosed between 1999 and 2005. 17 African Americans, 11 Hispanics, 7 Caucasians, 1 Asian and 4 unknown ethnicity made up this population (72.5% minority). The age range was between 15 and 82 years. 28 patients (70%) were less than 55 years and 15 (37.5%) were less than 35 years of age. 75% of patients had abnormal karyotypes and 25% had normal karyotypes. Prognostic group categorization showed that 45% of patients were in the adverse group, 35% in the intermediate group and 20% in the favorable group. The most common cytogenetic finding was complex abnormalities occurring in 37.5% of patients. The frequency of complex abnormalities with adverse prognosis found in this predominantly minority population is higher than that reported in the literature (12% in SWOG/ECOG study; 6% in MRC AML 10 trial). Our study is limited by its small sample size. Further studies with a larger sample size would be needed to clarify the role of race/ethnicity in cytogenetic aberrations in AML.

Myelodysplastic Syndrome (MDS) Displays Profound and Functionally Significant Epigenetic Deregulation Compared to Acute Myeloid Leukemia (AML) and Normal Bone Marrow Cells.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 345-345
Author(s):  
Maria E. Figueroa ◽  
Tamer Fandy ◽  
Melanie J. McConnell ◽  
Windy Berkofsky-Fessler ◽  
Chris Nasrallah ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bone Marrow ◽  
Dna Methyltransferase ◽  
De Novo ◽  
Bone Marrow Cells ◽  
Single Locus ◽  
Aberrant Methylation ◽  
Cd34 Cells ◽  
De Novo Aml ◽  
Marrow Cells

Abstract MDS are a clinically heterogeneous group of clonal disorders, which share a high frequency of progression to secondary AML (MDS-AML). In contrast to de novo AML, MDS and MDS-AML are uniformly resistant to conventional chemotherapy. Among the few active drugs in MDS are the nucleoside analog DNA methyltransferase inhibitors (MTIs) 5-azacytidine and decitabine. Since tumor suppressor genes such as CDKN2B can be silenced by DNA methylation in MDS, it is believed that reversal of DNA methylation by MTIs might contribute to their anti-tumor effects. However, it is not clear whether methylation-dependent silencing of specific genes are predictive of response or even correlate with response to MTIs. Like MDS, AML also presents epigenetic silencing of CDKN2B and other genes; yet appear to not be as sensitive to MTIs. Given the particular sensitivity of MDS to MTIs and its resistance to standard AML chemotherapy, we hypothesized that MDS is a biologically distinct disease from AML due largely to extensive epigenetic deregulation, which is missed by single locus studies. In order to test this we studied DNA methylation levels at 24,000 gene promoters in 13 MDS pts. and 16 de novo normal karyotype AML cases, and compared and contrasted these to CD34+ bone marrow cells from 8 healthy donors. For this we used the HELP (HpaII tiny fragment Enrichment by Ligation-mediated PCR) assay, a robust method for detection of whole-genome DNA methylation, and using MassArray quantitative methylation for single locus validation. Remarkably, MDS was found to have a far greater number of hypermethylated genes than AML or normal CD34+ cells, while AML and CD34+ cells had similar number of methylated genes (MDS vs. AML: 6303 vs. 4177 promoters, p=0.026; MDS vs. normal CD34+ cells: 6303 vs. 4296 promoters, p=0.056). Using a moderated T test, an aberrant methylation signature of 736 genes (p<0.0000001) was identified in MDS vs. normal CD34+ cells, reflecting extensive epigenetic deregulation in this disease, including p16, CEBPZ, MSH2, CHES1, AKT1, Caspase2, BMP3, DAP and MYOD1. A comparison between MDS and de novo AML identified 498 genes (p<0.00005) differentially methylated, with a clear predominance of hypermethylated promoters in MDS vs. de novo AML. These genes included RUNX2 and 3, GFI1, DAPK2, MDM2, TGFA, CEBPZ and SHARP. Finally, a comparison between normal CD34+ cells and de novo AML demonstrated an aberrant pattern of methylation in 341 genes (p<0.00001), including CXCL1 and 5, PPARD, Caspase 2 HOXA4 and HOXA10, GFI1 and the MLL translocation partner Septin11. 7 of the 13 MDS cases were also examined for gene expression using the Affymetrix Hgu133plus2 array. A significant proportion of the genes that had been found to be methylated were also found to be underexpressed, including p16, DAP, BMP3, HOXA2 and HOXB8. Taken together, our data show that MDS is a unique and distinct biological entity than de novo AML featuring profound and functionally significant genome wide epigenetic deregulation. While the de novo AML methylation profile was clearly different from normal CD34+ cells, it was not as severely altered as MDS. These data also suggest that MTIs are most likely uniquely active in MDS due to their DNA methyltransferase activity.

scholarly journals Analysis of Genome DNA Methylation at Inherited Coat Color Dilutions of Rex Rabbits

2021 ◽  
Vol 11 ◽  
Author(s):  
Yang Chen ◽  
Shuaishuai Hu ◽  
Ming Liu ◽  
Bohao Zhao ◽  
Naisu Yang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Sample Size ◽  
Bisulfite Sequencing ◽  
Coat Color ◽  
Small Sample Size ◽  
Hair Follicles ◽  
Small Sample ◽  
Genome Wide ◽  
Different Color ◽  
Rex Rabbit

Background: The dilution of color in rabbits is associated with many different genetic mechanisms that form different color groups. A number of previous studies have revealed potential regulatory mechanisms by which epigenetics regulate pigmentation. However, the genome-wide DNA methylation involved in animal coat color dilution remains unknown.Results: We compared genome-wide DNA methylation profiles in Rex rabbit hair follicles in a Chinchilla group (Ch) and a diluted Chinchilla group (DCh) through whole-genome bisulfite sequencing (WGBS). Approximately 3.5% of the cytosine sites were methylated in both groups, of which the CG methylation type was in greatest abundance. In total, we identified 126,405 differentially methylated regions (DMRs) between the two groups, corresponding to 11,459 DMR-associated genes (DMGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that these DMGs were principally involved in developmental pigmentation and Wnt signaling pathways. In addition, two DMRs were randomly selected to verify that the WGBS data were reliable using bisulfite sequencing PCR, and seven DMGs were analyzed to establish the relationship between the level of DNA methylation and mRNA expression using qRT-PCR. Due to the limitation of small sample size, replication of the results with a larger sample size would be important in future studies.Conclusion: These findings provide evidence that there is an association between inherited color dilution and DNA methylation alterations in hair follicles, greatly contributing to our understanding of the epigenetic regulation of rabbit pigmentation.

scholarly journals A Cartography of Differential Gene Methylation in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Different Network Roles in the Protein-Protein Interactions Network Play Different, Biologically Relevant, Roles

2021 ◽  
Author(s):  
Aurelia Wilberforce ◽  
Giulio Valentino Dalla Riva
Keyword(s):  
Dna Methylation ◽  
Chronic Fatigue Syndrome ◽  
Sample Size ◽  
Protein Interactions ◽  
Small Sample Size ◽  
Chronic Fatigue ◽  
Small Sample ◽  
Myalgic Encephalomyelitis ◽  
Fatigue Syndrome ◽  
Differentially Methylated Genes

Myalgic Encephalomyelitis, also known as Chronic Fatigue Syndrome (ME/CFS), is a debilitating illness characterised by severe fatigue and associated with immune dysfunction. Previous studies of DNA methylation (epigenetic changes that can affect the gene transcription) have found evidence of changes in immune cells for ME/CFS. However these studies have been limited by their small sample size, precluding the ability to detect changes to methylation of smaller magnitude. Therefore, to achieve a larger sample size and detect small changes to DNA methylation, we aggregate three comparable datasets and analyse them in unison. We find 10,824 differentially methylated genes, with a very small average change. We then turn our attention to the network structure of the Protein-Protein interaction, which we built from the currently known interactions of relevant proteins, and localising the network cartography framework, we identify 184 hub genes. A distinct structuring emerges, with different hub types playing differing, meaningful, biological roles. Supporting previous theories about ME/CFS, Gene ontology enrichment analysis of these hubs reveal that they are involved in immune system processes, including response to TGF-β and LPS, as well as mitochondrial functioning. We also show that dopaminergic signalling may potentially contribute to immune pathology in ME/CFS. Our results demonstrate the potentiality of network cartographic approaches in shedding light on the epigenetic contribution to the immune dysregulation of ME/CFS.

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