scholarly journals Epigenetic regulation of intestinal stem cell differentiation

2020 ◽  
Vol 319 (2) ◽  
pp. G189-G196
Author(s):  
Michael P. Verzi ◽  
Ramesh A. Shivdasani

To fulfill the lifelong need to supply diverse epithelial cells, intestinal stem cells (ISCs) rely on executing accurate transcriptional programs. This review addresses the mechanisms that control those programs. Genes that define cell behaviors and identities are regulated principally through thousands of dispersed enhancers, each individually <1 kb long and positioned from a few to hundreds of kilobases away from transcription start sites, upstream or downstream from coding genes or within introns. Wnt, Notch, and other epithelial control signals feed into these cis-regulatory DNA elements, which are also common loci of polymorphisms and mutations that confer disease risk. Cell-specific gene activity requires promoters to interact with the correct combination of signal-responsive enhancers. We review the current state of knowledge in ISCs regarding active enhancers, the nucleosome modifications that may enable appropriate and hinder inappropriate enhancer-promoter contacts, and the roles of lineage-restricted transcription factors.

2021 ◽  
Author(s):  
Jose M. G. Vilar ◽  
Leonor Saiz

The prevalent one-dimensional alignment of genomic signals to a reference landmark is a cornerstone of current methods to study transcription and its DNA-dependent processes but it is prone to mask potential relations among multiple DNA elements. We developed a systematic approach to align genomic signals to multiple locations simultaneously by expanding the dimensionality of the genomic-coordinate space. We analyzed transcription in human and uncovered a complex dependence on the relative position of neighboring transcription start sites (TSSs) that is consistently conserved among cell types. The dependence ranges from enhancement to suppression of transcription depending on the relative distances to the TSSs, their intragenic position, and the transcriptional activity of the gene. Our results reveal a conserved hierarchy of alternative TSS usage within a previously unrecognized level of genomic organization and provide a general methodology to analyze complex functional relationships among multiple types of DNA elements.


2017 ◽  
Author(s):  
Lingfei Wang ◽  
Tom Michoel

AbstractMapping gene expression as a quantitative trait using whole genome-sequencing and transcriptome analysis allows to discover the functional consequences of genetic variation. We developed a novel method and ultra-fast software Findr for higly accurate causal inference between gene expression traits using cis-regulatory DNA variations as causal anchors, which improves current methods by taking into account hidden confounders and weak regulations. Findr outperformed existing methods on the DREAM5 Systems Genetics challenge and on the prediction of microRNA and transcription factor targets in human lymphoblastoid cells, while being nearly a million times faster. Findr is publicly available at https://github.com/lingfeiwang/findr.Author summaryUnderstanding how genetic variation between individuals determines variation in observable traits or disease risk is one of the core aims of genetics. It is known that genetic variation often affects gene regulatory DNA elements and directly causes variation in expression of nearby genes. This effect in turn cascades down to other genes via the complex pathways and gene interaction networks that ultimately govern how cells operate in an ever changing environment. In theory, when genetic variation and gene expression levels are measured simultaneously in a large number of individuals, the causal effects of genes on each other can be inferred using statistical models similar to those used in randomized controlled trials. We developed a novel method and ultra-fast software Findr which, unlike existing methods, takes into account the complex but unknown network context when predicting causality between specific gene pairs. Findr’s predictions have a significantly higher overlap with known gene networks compared to existing methods, using both simulated and real data. Findr is also nearly a million times faster, and hence the only software in its class that can handle modern datasets where the expression levels of ten-thousands of genes are simultaneously measured in hundreds to thousands of individuals.


2020 ◽  
Author(s):  
Mitra Ansariola ◽  
Valerie N. Fraser ◽  
Sergei A. Filichkin ◽  
Maria G. Ivanchenko ◽  
Zachary A. Bright ◽  
...  

AbstractAcross tissues, gene expression is regulated by a combination of determinants, including the binding of transcription factors (TFs), along with other aspects of cellular state. Recent studies emphasize the importance of both genetic and epigenetic states – TF binding sites and binding site chromatin accessibility have emerged as potentially causal determinants of tissue specificity. To investigate the relative contributions of these determinants, we constructed three genome-scale datasets for both root and shoot tissues of the same Arabidopsis thaliana plants: TSS-seq data to identify Transcription Start Sites, OC-seq data to identify regions of Open Chromatin, and RNA-seq data to assess gene expression levels. For genes that are differentially expressed between root and shoot, we constructed a machine learning model predicting tissue of expression from chromatin accessibility and TF binding information upstream of TSS locations. The resulting model was highly accurate (over 90% auROC and auPRC), and our analysis of model contributions (feature weights) strongly suggests that patterns of TF binding sites within ∼500 nt TSS-proximal regions are predominant explainers of tissue of expression in most cases. Thus, in plants, cis-regulatory control of tissue-specific gene expression appears to be primarily determined by TSS-proximal sequences, and rarely by distal enhancer-like accessible chromatin regions. This study highlights the exciting future possibility of a native TF site-based design process for the tissue-specific targeting of plant gene promoters.


2019 ◽  
Vol 97 (Supplement_2) ◽  
pp. 16-16 ◽  
Author(s):  
Brenda M Murdoch

Abstract Reference genomes for some agricultural animals have been available for almost a decade; however, the annotation of these genomes remain an ongoing process. As a result, a detailed understanding of gene and gene product regulation that impart biological traits and physiological systems remains elusive. Through the Functional Annotation of ANimal Genomes (FAANG) consortium, coordinated efforts of the international scientific community are addressing this deficiency. The overarching goal of the Ovine FAANG project is to generate comprehensive transcriptome and chromatin state data sets from a large variety of adult tissues to accurately map functional elements of the ovine genome. In total, 100 tissues were collected (snap & slow frozen) from Benz 2616, the new reference genome, Oar_rambouillet_v1.0. Three methods of RNA sequencing have been utilized to fully understand tissue specific gene expression profiles. Transcript sequencing using poly-A+ messenger RNA has been completed for 60 tissues, whereas small microRNA as well as long read Iso-Sequencing data have been generated in a subset of these tissues. To further complement the gene expression data and to identify active promoters and confirm transcription start sites, Cap Analysis of Gene Expression (CAGE) has been completed. Histone modifications are being examined through Chromatin Immuno-precipitation (ChIP) sequencing to define different regulatory features. We are capitalizing on the knowledge that H3K4me3 and H3K27ac are enriched at transcription start sites and H3K4me1 at enhancer sites of actively transcribed genes, whereas H3K27me3 represses gene transcription. To determine chromatin accessibility, ATAC-seq is being performed for the 60 highest priority tissues. DNA methylation assays, specifically whole genome bisulfite and reduced representation bisulfite sequencing, are being performed on these tissues. This project will provide the first detailed understanding of tissue-specific gene regulatory signals and gene products, imparting a greater understanding of the mechanisms for genome to functional phenotype variation within sheep.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mathys Grapotte ◽  
Manu Saraswat ◽  
Chloé Bessière ◽  
Christophe Menichelli ◽  
Jordan A. Ramilowski ◽  
...  

AbstractUsing the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.


PLoS ONE ◽  
2009 ◽  
Vol 4 (10) ◽  
pp. e7526 ◽  
Author(s):  
Alfredo Mendoza-Vargas ◽  
Leticia Olvera ◽  
Maricela Olvera ◽  
Ricardo Grande ◽  
Leticia Vega-Alvarado ◽  
...  

2022 ◽  
Author(s):  
Edward J Banigan ◽  
Wen Tang ◽  
Aafke A van den Berg ◽  
Roman R Stocsits ◽  
Gordana Wutz ◽  
...  

Cohesin organizes mammalian interphase chromosomes by reeling chromatin fibers into dynamic loops (Banigan and Mirny, 2020; Davidson et al., 2019; Kim et al., 2019; Yatskevich et al., 2019). "Loop extrusion" is obstructed when cohesin encounters a properly oriented CTCF protein (Busslinger et al., 2017; de Wit et al., 2015; Fudenberg et al., 2016; Nora et al., 2017; Sanborn et al., 2015; Wutz et al., 2017), and recent work indicates that other factors, such as the replicative helicase MCM (Dequeker et al., 2020), can also act as barriers to loop extrusion. It has been proposed that transcription relocalizes (Busslinger et al., 2017; Glynn et al., 2004; Lengronne et al., 2004) or interferes with cohesin (Heinz et al., 2018; Jeppsson et al., 2020; Valton et al., 2021; S. Zhang et al., 2021), and that active transcription start sites function as cohesin loading sites (Busslinger et al., 2017; Kagey et al., 2010; Zhu et al., 2021; Zuin et al., 2014), but how these effects, and transcription in general, shape chromatin is unknown. To determine whether transcription can modulate loop extrusion, we studied cells in which the primary extrusion barriers could be removed by CTCF depletion and cohesin's residence time and abundance on chromatin could be increased by Wapl knockout. We found evidence that transcription directly interacts with loop extrusion through a novel "moving barrier" mechanism, but not by loading cohesin at active promoters. Hi-C experiments showed intricate, cohesin-dependent genomic contact patterns near actively transcribed genes, and in CTCF-Wapl double knockout (DKO) cells (Busslinger et al., 2017), genomic contacts were enriched between sites of transcription-driven cohesin localization ("cohesin islands"). Similar patterns also emerged in polymer simulations in which transcribing RNA polymerases (RNAPs) acted as "moving barriers" by impeding, slowing, or pushing loop-extruding cohesins. The model predicts that cohesin does not load preferentially at promoters and instead accumulates at TSSs due to the barrier function of RNAPs. We tested this prediction by new ChIP-seq experiments, which revealed that the "cohesin loader" Nipbl (Ciosk et al., 2000) co-localizes with cohesin, but, unlike in previous reports (Busslinger et al., 2017; Kagey et al., 2010; Zhu et al., 2021; Zuin et al., 2014), Nipbl did not accumulate at active promoters. We propose that RNAP acts as a new type of barrier to loop extrusion that, unlike CTCF, is not stationary in its precise genomic position, but is itself dynamically translocating and relocalizes cohesin along DNA. In this way, loop extrusion could enable translocating RNAPs to maintain contacts with distal regulatory elements, allowing transcriptional activity to shape genomic functional organization.


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