For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
1
views
48
references
 Top references
cited by
0
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      293
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Epigenetic repression of Cend1 by lysine-specific demethylase 1 is essential for murine heart development

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Summary

          Epigenetic regulation of heart development remains incompletely understood. Here we show that LSD1, a histone demethylase, plays a crucial role in regulating cardiomyocyte proliferation during heart development. Cardiomyocyte-specific deletion of Lsd1 in mice inhibited cardiomyocyte proliferation, causing severe growth defect of embryonic and neonatal heart . In vivo RNA-seq and in vitro functional studies identified Cend1 as a target suppressed by LSD1. Lsd1 loss resulted in elevated Cend1 transcription associated with increased active histone mark H3K4me2 at Cend1 promoter. Cend1 knockdown relieved the cell-cycle arrest and proliferation defect caused by LSD1 inhibition in primary rat cardiomyocytes. Moreover, genetic deletion of Cend1 rescued cardiomyocyte proliferation defect and embryonic lethality in Lsd1 null embryos. Consistently, LSD1 promoted the cell cycle of cardiomyocytes derived from human-induced pluripotent stem cells by repressing CEND1. Together, these findings reveal an epigenetic regulatory mechanism involving the LSD1-CEND1 axis that controls cardiomyocyte proliferation essential for murine heart development.

          Graphical abstract

          Highlights

          • •

            LSD1 is essential for embryonic and neonatal heart development in mice

          • •

            LSD1-dependent suppression of CEND1 supports cardiomyocyte proliferation

          • •

            LSD1 represses Cend1 transcription by erasing H3K4me2 at its promoter

          • •

            LSD1-CEND1 axis regulates the proliferation of hiPSC-CMs

          Abstract

          Natural sciences; Biological sciences; Developmental biology

          Related collections

          Most cited references48

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          Michael Love, Wolfgang Huber, Simon Anders (2014)
          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
          Article 0 comments Cited 23723 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Guangchuang Yu, Li-Gen Wang, Yanyan Han … (2012)
            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
            Article 0 comments Cited 11265 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

              Y. Liao, G K Smyth, W Shi (2014)
              Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
              Article 0 comments Cited 6955 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Zuyi Yuan
                Yidong Wang
                Journal
                Journal ID (nlm-ta): iScience
                Journal ID (iso-abbrev): iScience
                Title: iScience
                Publisher: Elsevier
                ISSN (Electronic): 2589-0042
                Publication date PMC-release: 13 December 2023
                Publication date Collection: 19 January 2024
                Publication date (Electronic): 13 December 2023
                Volume: 27
                Issue: 1
                Electronic Location Identifier: 108722
                Affiliations
                [1 ]Department of Cardiology, First Affiliated Hospital, Cardiometabolic Innovation Center of Ministry of Education, Xi’an Jiaotong University, Xi’an, China
                [2 ]The Institute of Cardiovascular Sciences, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
                [3 ]Key Laboratory of Precision Medicine to Pediatric Diseases of Shaanxi Province, Shaanxi Institute for Pediatric Diseases, Xi’an Children’s Hospital, Affiliated Children’s Hospital, Xi’an Jiaotong University, Xi’an, China
                [4 ]Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
                [5 ]Department of Cardiology, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
                [6 ]Division of Cardiology, Department of Medicine, University of California, San Diego, CA, USA
                [7 ]Department of Genetics, Albert Einstein College of Medicine, New York, NY, USA
                [8 ]The Institute of Cardiovascular Sciences, School of Basic Medical Sciences, Department of Cardiology, First Affiliated Hospital, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education, Cardiometabolic Innovation Center of Ministry of Education, Xi’an Jiaotong University, Xi’an, China
                Author notes
                [∗ ]Corresponding author zuyiyuan@ 123456mail.xjtu.edu.cn
                [∗∗ ]Corresponding author yidwang119@ 123456xjtu.edu.cn
                [9]

                These authors contributed equally

                [10]

                Lead contact

                Article
                Publisher Item ID: S2589-0042(23)02799-2 Publisher ID: 108722
                DOI: 10.1016/j.isci.2023.108722
                PMC ID: 10788269
                PubMed ID: 38226173
                SO-VID: cb5d552b-cf61-460f-ab7a-eb5c9e476e16
                Copyright © © 2023 The Authors
                License:

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Date received : 30 June 2023
                Date revision received : 29 September 2023
                Date accepted : 11 December 2023
                Categories
                Subject: Article

                Keywords: natural sciences,biological sciences,developmental biology
                Data availability:
                Keywords: natural sciences, biological sciences, developmental biology

                Comments

                Comment on this article