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Congenital heart defects are the most common birth defect and have a clear genetic component, yet genomic structural variations or gene mutations account for only a third of the cases. Epigenomic dynamics during human heart organogenesis thus may play a critical role in regulating heart development. However, it is unclear how histone mark H3K36me3 acts on heart development. Here we report that histone-lysine N-methyltransferase SETD2, an H3K36me3 methyltransferase, is a crucial regulator of the mouse heart epigenome. Setd2 is highly expressed in embryonic stages and accounts for a predominate role of H3K36me3 in the heart. Loss of Setd2 in cardiac progenitors results in obvious coronary vascular defects and ventricular non-compaction, leading to fetus lethality in mid-gestation, without affecting peripheral blood vessel, yolk sac, and placenta formation. Furthermore, deletion of Setd2 dramatically decreased H3K36me3 level and impacted the transcriptional landscape of key cardiac-related genes, including Rspo3 and Flrt2. Taken together, our results strongly suggest that SETD2 plays a primary role in H3K36me3 and is critical for coronary vascular formation and heart development in mice.
Pubmed ID: 33898448
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software Python package that provides infrastructure to process data from high-throughput sequencing assays. While the main purpose of HTSeq is to allow you to write your own analysis scripts, customized to your needs, there are also a couple of stand-alone scripts for common tasks that can be used without any Python knowledge.
View all literature mentionsWeb server to identify statistically enriched pathways, diseases, and GO terms for a set of genes or proteins, using pathway, disease, and GO knowledge from multiple famous databases. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). A standalone command line version is also available
View all literature mentionsSoftware repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.
View all literature mentionsCommercial vendor and service provider of laboratory reagents and antibodies. Supplier of scientific instrumentation, reagents and consumables, and software services.
View all literature mentionsSoftware tool that removes adapter sequences from DNA sequencing reads.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsA commercial antibody supplier which supplies primary and secondary antibodies, biochemicals, proteins, peptides, lysates, immunoassays and other kits.
View all literature mentionsCompany provides laboratories worldwide with analytical instruments and supplies, clinical and diagnostic testing services, consumables, applications and expertise in life sciences and applied chemical markets.
View all literature mentionsGraph-based alignment of next generation sequencing reads to a population of genomes.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
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