scholarly journals Spatiotemporal dynamics of SETD5-containing NCoR–HDAC3 complex determines enhancer activation for adipogenesis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yoshihiro Matsumura ◽  
Ryo Ito ◽  
Ayumu Yajima ◽  
Rei Yamaguchi ◽  
Toshiya Tanaka ◽  
...  
Keyword(s):  
Gene Expression ◽  
Histone Acetylation ◽  
Ubiquitin Ligase ◽  
Cellular Differentiation ◽  
Specific Gene ◽  
Cell Type ◽  
Set Domain ◽  
Protein Levels ◽  
Primed State ◽  
Cell Type Specific

AbstractEnhancer activation is essential for cell-type specific gene expression during cellular differentiation, however, how enhancers transition from a hypoacetylated “primed” state to a hyperacetylated-active state is incompletely understood. Here, we show SET domain-containing 5 (SETD5) forms a complex with NCoR-HDAC3 co-repressor that prevents histone acetylation of enhancers for two master adipogenic regulatory genes Cebpa and Pparg early during adipogenesis. The loss of SETD5 from the complex is followed by enhancer hyperacetylation. SETD5 protein levels were transiently increased and rapidly degraded prior to enhancer activation providing a mechanism for the loss of SETD5 during the transition. We show that induction of the CDC20 co-activator of the ubiquitin ligase leads to APC/C mediated degradation of SETD5 during the transition and this operates as a molecular switch that facilitates adipogenesis.

Spatiotemporal dynamics of SETD5-containing NCoR-HDAC3 complex determines enhancer activation for adipogenesis

2021 ◽  
Author(s):  
Yoshihiro Matsumura ◽  
Ryo Ito ◽  
Ayumu Yajima ◽  
Rei Yamaguchi ◽  
Kenta Magoori ◽  
...  
Keyword(s):  
Gene Expression ◽  
Histone Acetylation ◽  
Ubiquitin Ligase ◽  
Cellular Differentiation ◽  
Specific Gene ◽  
Cell Type ◽  
Set Domain ◽  
Protein Levels ◽  
Primed State ◽  
Cell Type Specific

Abstract Enhancer activation is essential for cell-type specific gene expression during cellular differentiation, however, how enhancers transition from a hypoacetylated “primed” state to a hyperacetylated-active state is incompletely understood. Here, we show SET domain-containing 5 (SETD5) forms a complex with NCoR-HDAC3 co-repressor that prevents histone acetylation of enhancers for two master adipogenic regulatory genes Cebpa and Pparg early during adipogenesis. The loss of SETD5 from the complex is followed by enhancer hyperacetylation. SETD5 protein levels were transiently increased and rapidly degraded prior to enhancer activation providing a mechanism for the loss of SETD5 during the transition. We show that induction of the CDC20 co-activator of the ubiquitin ligase leads to APC/C mediated degradation of SETD5 during the transition and this operates as a molecular switch that facilitates adipogenesis.

scholarly journals Correlation of mRNA and protein levels: Cell type-specific gene expression of cluster designation antigens in the prostate

BMC Genomics ◽  
2008 ◽  
Vol 9 (1) ◽  
pp. 246 ◽  
Author(s):  
Laura E Pascal ◽  
Lawrence D True ◽  
David S Campbell ◽  
Eric W Deutsch ◽  
Michael Risk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Gene Expression ◽  
Protein Levels ◽  
Cluster Designation ◽  
Cell Type Specific

scholarly journals Genetic influences on cell type specific gene expression and splicing during neurogenesis elucidate regulatory mechanisms of brain traits

2020 ◽  
Author(s):  
Nil Aygün ◽  
Angela L. Elwell ◽  
Dan Liang ◽  
Michael J. Lafferty ◽  
Kerry E. Cheek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Elements ◽  
Regulatory Mechanisms ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Expression ◽  
Risk Variants ◽  
Allele Specific ◽  
Cell Type Specific ◽  
Regulatory Effects

SummaryInterpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing is mainly performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements of cells present during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs and allele specific expression in primary human neural progenitors (n=85) and their sorted neuronal progeny (n=74). Using colocalization and TWAS, we uncover cell-type specific regulatory mechanisms underlying risk for these traits.

scholarly journals Srf destabilizes cellular identity by suppressing cell-type-specific gene expression programs

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Takashi Ikeda ◽  
Takafusa Hikichi ◽  
Hisashi Miura ◽  
Hirofumi Shibata ◽  
Kanae Mitsunaga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Gene Expression ◽  
Cell Type Specific ◽  
Cellular Identity

New insights into promoter–enhancer communication mechanisms revealed by dynamic single-molecule imaging

2021 ◽  
Author(s):  
Jieru Li ◽  
Alexandros Pertsinidis
Keyword(s):  
Gene Expression ◽  
Single Molecule ◽  
Target Genes ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Single Molecule Imaging ◽  
Cell Type ◽  
Regulatory Information ◽  
Cell Type Specific ◽  
Target Promoters

Establishing cell-type-specific gene expression programs relies on the action of distal enhancers, cis-regulatory elements that can activate target genes over large genomic distances — up to Mega-bases away. How distal enhancers physically relay regulatory information to target promoters has remained a mystery. Here, we review the latest developments and insights into promoter–enhancer communication mechanisms revealed by live-cell, real-time single-molecule imaging approaches.

scholarly journals Using multiple measurements of tissue to estimate subject- and cell-type-specific gene expression

2019 ◽  
Vol 36 (3) ◽  
pp. 782-788 ◽  
Author(s):  
Jiebiao Wang ◽  
Bernie Devlin ◽  
Kathryn Roeder
Keyword(s):  
Gene Expression ◽  
Empirical Bayes ◽  
Brain Regions ◽  
Tissue Level ◽  
Supplementary Information ◽  
Specific Gene ◽  
Expression Data ◽  
Cell Type ◽  
Multiple Measurements ◽  
Cell Type Specific

Abstract Motivation Patterns of gene expression, quantified at the level of tissue or cells, can inform on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression data, which have been collected from thousands of subjects, and resources involving single-cell RNA-sequencing (scRNA-seq) data are expanding rapidly. The latter yields cell type information, although the data can be noisy and typically are derived from a small number of subjects. Results Complementing these approaches, we develop a method to estimate subject- and cell-type-specific (CTS) gene expression from tissue using an empirical Bayes method that borrows information across multiple measurements of the same tissue per subject (e.g. multiple regions of the brain). Analyzing expression data from multiple brain regions from the Genotype-Tissue Expression project (GTEx) reveals CTS expression, which then permits downstream analyses, such as identification of CTS expression Quantitative Trait Loci (eQTL). Availability and implementation We implement this method as an R package MIND, hosted on https://github.com/randel/MIND. Supplementary information Supplementary data are available at Bioinformatics online.

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