30 research outputs found
Identifying clinically relevant imprinted gDMRs sensitive to a transient loss of DNA methylation in human differentiated cells
CandiMeth: Powerful yet simple visualization and quantification of DNA methylation at candidate genes
Assessing the efficacy of active learning to support student performance across undergraduate programmes in Biomedical Science
Introduction: Active learning is a useful tool to enhance student engagement and support learning in diverse educational situations. We aimed to assess the efficacy of an active learning approach within a large interprofessional first year Medical Cell Biology module taken by six healthcare programmes across the School of Biomedical Sciences at Ulster University, United Kingdom. Materials and methods: An active learning approach was developed for weekly formative assessment using Smartwork to design a weekly interactive multiple-choice quiz to reinforce key concepts specifically for each lecture. We tracked and assessed student performance in the module overall and in each element of course work and exam for 2 years prior to and following the introduction of an active learning strategy to engage and support learning for students from all academic backgrounds and abilities. Results: Full engagement with active learning was significantly associated with an increased overall module performance as well as a significantly increased performance in each element of class test (No engagement vs. Full engagement, p < 0.001), exam (No Engagement vs. Full engagement, p < 0.05) and coursework (No engagement vs. Full engagement, p < 0.001) within this overall total (No Engagement vs. Full engagement, p < 0.01). Partial engagement with active learning was associated significantly improved class test (No engagement vs. partially engaged, p < 0.001) and coursework (No engagement vs. partially engaged, p < 0.05) performance. While a trend toward increased performance in exam and overall module mark was observed, these were not significant. Discussion: Active learning is a useful tool to support student learning across a range of healthcare programmes taken by students with differing backgrounds and academic abilities in an interprofessional and widening participation setting. Student engagement in active learning was highlighted as a key contributory factor to enhanced student performance in all aspects of assessment.</p
Methylome profiling of young adults with depression supports a link with immune response and psoriasis
Gene-specific DNA methylation in newborns in response to folic acid supplementation during the second and third trimesters of pregnancy:epigenetic analysis from a randomized controlled trial
Depletion of DNMT1 in differentiated human cells highlights key classes of sensitive genes and an interplay with polycomb repression
Additional file 3: Figure S2. Changes in methylation levels by genomic element. (A) Protein levels in knockdown lines by western blotting. As a control HCT116 colon cancer cells which are WT or have a homozygous mutation in DNMT1 (KO) are shown: the DNMT1-specific top band is indicated by the arrowhead at right. (B) Median levels of methylation are shown for each genomic element (listed at top). The positions of medians are also indicated at right (arrowheads). The differences between WT and KD medians were used to plot Fig. 1d. (C) Density distribution of methylation at the three main elements involved in gene regulation, shown by cell line. Demethylation seems most marked at gene bodies (Genes), indicated by increased density of probes at low methylation (β) values
Intragenic sequences in the trophectoderm harbour the greatest proportion of methylation errors in day 17 bovine conceptuses generated using assisted reproductive technologies
Abstract Background Assisted reproductive technologies (ART) are widely used to treat fertility issues in humans and for the production of embryos in mammalian livestock. The use of these techniques, however, is not without consequence as they are often associated with inauspicious pre- and postnatal outcomes including premature birth, intrauterine growth restriction and increased incidence of epigenetic disorders in human and large offspring syndrome in cattle. Here, global DNA methylation profiles in the trophectoderm and embryonic discs of in vitro produced (IVP), superovulation-derived (SOV) and unstimulated, synchronised control day 17 bovine conceptuses (herein referred to as AI) were interrogated using the EmbryoGENE DNA Methylation Array (EDMA). Pyrosequencing was used to validate four loci identified as differentially methylated on the array and to assess the differentially methylated regions (DMRs) of six imprinted genes in these conceptuses. The impact of embryo-production induced DNA methylation aberrations was determined using Ingenuity Pathway Analysis, shedding light on the potential functional consequences of these differences. Results Of the total number of differentially methylated loci identified (3140) 77.3 and 22.7% were attributable to SOV and IVP, respectively. Differential methylation was most prominent at intragenic sequences within the trophectoderm of IVP and SOV-derived conceptuses, almost a third (30.8%) of the differentially methylated loci mapped to intragenic regions. Very few differentially methylated loci were detected in embryonic discs (ED); 0.16 and 4.9% of the differentially methylated loci were located in the ED of SOV-derived and IVP conceptuses, respectively. The overall effects of SOV and IVP on the direction of methylation changes were associated with increased methylation; 70.6% of the differentially methylated loci in SOV-derived conceptuses and 57.9% of the loci in IVP-derived conceptuses were more methylated compared to AI-conceptuses. Ontology analysis of probes associated with intragenic sequences suggests enrichment for terms associated with cancer, cell morphology and growth. Conclusion By examining (1) the effects of superovulation and (2) the effects of an in vitro system (oocyte maturation, fertilisation and embryo culture) we have identified that the assisted reproduction process of superovulation alone has the largest impact on the DNA methylome of subsequent embryos
The UHRF1 protein is a key regulator of retrotransposable elements and innate immune response to viral RNA in human cells
While epigenetic mechanisms such as DNA methylation and histone modification are known to be important for gene suppression, relatively little is still understood about the interplay between these systems. The UHRF1 protein can interact with both DNA methylation and repressive chromatin marks, but its primary function in humans has been unclear. To determine what that was, we first established stable UHRF1 knockdowns (KD) in normal, immortalized human fibroblasts using targeting shRNA, since CRISPR knockouts (KO) were lethal. Although these showed a loss of DNA methylation across the whole genome, transcriptional changes were dominated by the activation of genes involved in innate immune signalling, consistent with the presence of viral RNA from retrotransposable elements (REs). We confirmed using mechanistic approaches that 1) REs were demethylated and transcriptionally activated; 2) this was accompanied by activation of interferons and interferon-stimulated genes and 3) the pathway was conserved across other adult cell types. Restoring UHRF1 in either transient or stable KD systems could abrogate RE reactivation and the interferon response. Notably, UHRF1 itself could also re-impose RE suppression independent of DNA methylation, but not if the protein contained point mutations affecting histone 3 with trimethylated lysine 9 (H3K9me3) binding. Our results therefore show for the first time that UHRF1 can act as a key regulator of retrotransposon silencing independent of DNA methylation
A randomized controlled trial of folic acid intervention in pregnancy highlights a putative methylation-regulated control element at ZFP57
Table S1. Pyrosequencing and transcriptional primer sets used in this study. Pyroassay primers are given as bisulfite converted sequence. The same primers were used for both RT-PCR and RT-qPCR. (DOCX 15 kb