Dataset Information

Phosphorylation of methyltransferase Set2p and demethylase Jhd1p and its association with histone H3K36 methylation and stress response pathways in Saccharomyces cerevisiae

ABSTRACT: Histone lysine methylation is a key epigenetic modification that regulates eukaryotic transcription. In Saccharomyces cerevisiae, it is controlled by a reduced but evolutionarily conserved suite of methyltransferase (Set1p, Set2p, Dot1p, and Set5p) and demethylase (Jhd1p, Jhd2p, Rph1p, and Gis1p) enzymes. Many of these enzymes are extensively phosphorylated in vivo; however, the functions of specific phosphosites are poorly understood. Here, we comprehensively investigate the phosphoregulation of the yeast histone methylation network by analysing 40 phosphosites on six enzymes through mutagenesis. A total of 82 genomically-edited S. cerevisiae strains were generated and screened for changes in native H3K4, H3K36, and H3K79 methylation levels, and for sensitivity to environmental stress conditions. This demonstrated the functional relevance of phosphosites on methyltransferase Set2p (S6, S8, S10, and T127) and demethylase Jhd1p (S44) in the regulation of H3K36 methylation in vivo, and in the coordination of specific stress response pathways in budding yeast. Proteomic analysis of SET2 mutants revealed that phosphorylation site mutations lead to significant downregulation of membrane-associated proteins and processes, consistent with changes brought about by SET2 deletion. This study represents the first systematic investigation into the phosphoregulation of an entire epigenetic network in any eukaryote, and our findings establish phosphorylation as an important regulator of histone lysine methylation in S. cerevisiae.

INSTRUMENT(S): Orbitrap Fusion Lumos, Q Exactive

ORGANISM(S): Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Ryan Separovich

LAB HEAD: Marc Ronald Wilkins

PROVIDER: PXD029088 | Pride | 2022-03-07

REPOSITORIES: Pride

ACCESS DATA

Similar Datasets

Project description:DNA methylation is a defining feature of mammalian cellular identity and is essential for normal development. Most cell types, except germ cells and pre-implantation embryos, display relatively stable DNA methylation patterns, with 70-80% of all CpGs being methylated. Despite recent advances we still have a too limited understanding of when, where and how many CpGs participate in genomic regulation. Here we report the in depth analysis of 42 whole genome bisulfite sequencing (WGBS) data sets across 30 diverse human cell and tissue types. We observe dynamic regulation for only 21.8% of autosomal CpGs within a normal developmental context, a majority of which are distal to transcription start sites. These dynamic CpGs co-localize with gene regulatory elements, particularly enhancers and transcription factor binding sites (TFBS), which allow identification of key lineage specific regulators. In addition, differentially methylated regions (DMRs) often harbor SNPs associated with cell type related diseases as determined by GWAS. The results also highlight the general inefficiency of WGBS as 70-80% of the sequencing reads across these data sets provided little or no relevant information regarding CpG methylation. To further demonstrate the utility of our DMR set, we use it to classify unknown samples and identify representative signature regions that recapitulate major DNA methylation dynamics. In summary, although in theory every CpG can change its methylation state, our results confirm that only a fraction does so as part of coordinated regulatory programs. Therefore our selected DMRs can serve as a starting point to help guide novel, more effective reduced representation approaches to capture the most informative fraction of CpGs as well as further pinpoint putative regulatory elements. Analysis of 42 human WGBS libraries comprising 30 distinct primary cell lines, tissues, in vitro derived cell types and cell lines. BiSeq raw sequencing reads were aligned using maq in bisulfite mode (Li et al. 2008) or bsmap 2.7 (Xi et al. 2009) against human genome version hg19/GRCh37, discarding duplicate reads. DNA methylation calling was performed based on an extended custom software pipeline published previously for RRBS (Gu et al., 2010). The bed files contain all seen CpGs within the given library. The number of methylated reads/number of total reads is listed in the score column. This study includes a re-analysis of Samples from the NIH Roadmap Epigenomics Mapping Consortium (REMC; GSE16256, GSE17312), Hodges et al. 2011 (GSE31971), Molaro et al. 2011 (GSE30340), and Xi et al. 2013. WARNING: This submission is incomplete pending further deposits of raw data files from Meissner via EDACC.

Dataset Information

Phosphorylation of methyltransferase Set2p and demethylase Jhd1p and its association with histone H3K36 methylation and stress response pathways in Saccharomyces cerevisiae

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure