1
|
Sharov AA, Nakatake Y, Wang W. Atlas of regulated target genes of transcription factors (ART-TF) in human ES cells. BMC Bioinformatics 2022; 23:377. [PMID: 36114445 PMCID: PMC9479252 DOI: 10.1186/s12859-022-04924-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 09/12/2022] [Indexed: 12/26/2022] Open
Abstract
Background Transcription factors (TFs) play central roles in maintaining “stemness” of embryonic stem (ES) cells and their differentiation into several hundreds of adult cell types. The regulatory competence of TFs is routinely assessed by detecting target genes to which they bind. However, these data do not indicate which target genes are activated, repressed, or not affected by the change of TF abundance. There is a lack of large-scale studies that compare the genome binding of TFs with the expression change of target genes after manipulation of each TF. Results In this paper we associated human TFs with their target genes by two criteria: binding to genes, evaluated from published ChIP-seq data (n = 1868); and change of target gene expression shortly after induction of each TF in human ES cells. Lists of direction- and strength-specific regulated target genes are generated for 311 TFs (out of 351 TFs tested) with expected proportion of false positives less than or equal to 0.30, including 63 new TFs not present in four existing databases of target genes. Our lists of direction-specific targets for 152 TFs (80.0%) are larger that in the TRRUST database. In average, 30.9% of genes that respond greater than or equal to twofold to the induction of TFs are regulated targets. Regulated target genes indicate that the majority of TFs are either strong activators or strong repressors, whereas sets of genes that responded greater than or equal to twofold to the induction of TFs did not show strong asymmetry in the direction of expression change. The majority of human TFs (82.1%) regulated their target genes primarily via binding to enhancers. Repression of target genes is more often mediated by promoter-binding than activation of target genes. Enhancer-promoter loops are more abundant among strong activator and repressor TFs. Conclusions We developed an atlas of regulated targets of TFs (ART-TF) in human ES cells by combining data on TF binding with data on gene expression change after manipulation of individual TFs. Sets of regulated gene targets were identified with a controlled rate of false positives. This approach contributes to the understanding of biological functions of TFs and organization of gene regulatory networks. This atlas should be a valuable resource for ES cell-based regenerative medicine studies. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04924-3.
Collapse
|
2
|
Cascini F, Beccia F, Causio FA, Gentili A, Melnyk A, Boccia S, Ricciardi W. Is blockchain the breakthrough we are looking for to facilitate genomic data sharing? The European Union perspective. Digit Health 2022; 8:20552076221114225. [PMID: 35860615 PMCID: PMC9290163 DOI: 10.1177/20552076221114225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 06/30/2022] [Indexed: 11/17/2022] Open
Abstract
The recent progress of genomics research is providing unprecedented insight into human genetic variance, susceptibility to disease and risk stratification. Current trends predict that a massive amount of genomic data will be produced in the upcoming years which, when coupled with the fast-paced development of the field, will create new social, ethical, and legal challenges. In the complex legislative environment of the European Union, genomic data sharing policies will have to weigh the benefits of scientific discovery against the ethical risks posed by the act of sharing sensitive data. In this complex, interconnected environment, blockchain provides a unique and novel solution to accountability, traceability, and transparency issues regarding genomic data sharing. Implementing a distributed ledger technology-based database could empower both patients and citizens to responsibly use genomic data pertaining to them because it allows for a higher degree of control over the recipients of their data and their uses. The blockchain technology will engage both data owners and policymakers to address the multiple issues of genomic data sharing and allow us to redefine the way we look at genomics.
Collapse
Affiliation(s)
- Fidelia Cascini
- Section of Hygiene and Public Health, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
| | - Flavia Beccia
- Section of Hygiene and Public Health, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
| | - Francesco A Causio
- Section of Hygiene and Public Health, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
| | - Andrea Gentili
- Section of Hygiene and Public Health, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
| | - Andriy Melnyk
- Section of Hygiene and Public Health, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
| | - Stefania Boccia
- Section of Hygiene and Public Health, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
- Department of Woman and Child Health and Public Health-Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Walter Ricciardi
- Section of Hygiene and Public Health, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
- Istituti Clinici Scientifici Maugeri, Pavia, Italy
| |
Collapse
|
3
|
Smith M, Flodman PL. Expanded Insights Into Mechanisms of Gene Expression and Disease Related Disruptions. Front Mol Biosci 2018; 5:101. [PMID: 30542652 PMCID: PMC6277798 DOI: 10.3389/fmolb.2018.00101] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Accepted: 11/02/2018] [Indexed: 12/31/2022] Open
Abstract
Definitive molecular diagnoses in disorders apparently due to genetic or genomic defects are still lacking in a significant number of investigated cases, despite use of studies designed to discover defects in the protein coding regions of the genome. Increasingly studies are being designed to search for defects in the non-protein coding genome, and for alterations in gene expression. Here we review new insights into genomic elements involved in control of gene expression, including methods to analyze chromatin that is accessible for transcription factor binding, enhancers, chromatin looping, transcription, RNA binding proteins, and alternative splicing. We review new studies on levels of genome organization, including the occurrence of transcriptional domains and their boundary elements. Information is presented on specific malformation syndromes that arise due to structural genomic changes that impact the non-protein coding genome and sometimes impact specific transcriptional domains. We also review convergence of genome-wide association with studies of gene expression, discoveries related to expression quantitative trait loci and splicing quantitative trait loci and the relevance of these to specific complex common diseases. Aspects of epigenetic mechanisms and clinical applications of analyses of methylation signatures are also discussed.
Collapse
Affiliation(s)
- Moyra Smith
- Department of Pediatrics, University of California, Irvine, Irvine, CA, United States
| | | |
Collapse
|
4
|
Lee PH, Lee C, Li X, Wee B, Dwivedi T, Daly M. Principles and methods of in-silico prioritization of non-coding regulatory variants. Hum Genet 2018; 137:15-30. [PMID: 29288389 PMCID: PMC5892192 DOI: 10.1007/s00439-017-1861-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Accepted: 12/14/2017] [Indexed: 12/13/2022]
Abstract
Over a decade of genome-wide association, studies have made great strides toward the detection of genes and genetic mechanisms underlying complex traits. However, the majority of associated loci reside in non-coding regions that are functionally uncharacterized in general. Now, the availability of large-scale tissue and cell type-specific transcriptome and epigenome data enables us to elucidate how non-coding genetic variants can affect gene expressions and are associated with phenotypic changes. Here, we provide an overview of this emerging field in human genomics, summarizing available data resources and state-of-the-art analytic methods to facilitate in-silico prioritization of non-coding regulatory mutations. We also highlight the limitations of current approaches and discuss the direction of much-needed future research.
Collapse
Affiliation(s)
- Phil H Lee
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA.
- Quantitative Genomics Program, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Christian Lee
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA
- Department of Life Sciences, Harvard University, Cambridge, MA, USA
| | - Xihao Li
- Quantitative Genomics Program, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brian Wee
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA
| | - Tushar Dwivedi
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Mark Daly
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Simches Research Building, 185 Cambridge St, Boston, MA, 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| |
Collapse
|
5
|
Muhammad D, Schmittling S, Williams C, Long TA. More than meets the eye: Emergent properties of transcription factors networks in Arabidopsis. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2016; 1860:64-74. [PMID: 27485161 DOI: 10.1016/j.bbagrm.2016.07.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Revised: 07/10/2016] [Accepted: 07/27/2016] [Indexed: 11/30/2022]
Abstract
Uncovering and mathematically modeling Transcription Factor Networks (TFNs) are the first steps in engineering plants with traits that are better equipped to respond to changing environments. Although several plant TFNs are well known, the framework for systematically modeling complex characteristics such as switch-like behavior, oscillations, and homeostasis that emerge from them remain elusive. This review highlights literature that provides, in part, experimental and computational techniques for characterizing TFNs. This review also outlines methodologies that have been used to mathematically model the dynamic characteristics of TFNs. We present several examples of TFNs in plants that are involved in developmental and stress response. In several cases, advanced algorithms capture or quantify emergent properties that serve as the basis for robustness and adaptability in plant responses. Increasing the use of mathematical approaches will shed new light on these regulatory properties that control plant growth and development, leading to mathematical models that predict plant behavior. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.
Collapse
Affiliation(s)
| | - Selene Schmittling
- Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA
| | - Cranos Williams
- Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA
| | - Terri A Long
- Plant and Microbial Biology, North Carolina State University, Raleigh, NC, USA.
| |
Collapse
|
6
|
Gurdziel K, Lorberbaum DS, Udager AM, Song JY, Richards N, Parker DS, Johnson LA, Allen BL, Barolo S, Gumucio DL. Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density. PLoS One 2015; 10:e0145225. [PMID: 26710299 PMCID: PMC4692483 DOI: 10.1371/journal.pone.0145225] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2015] [Accepted: 12/01/2015] [Indexed: 01/20/2023] Open
Abstract
The Hedgehog (Hh) signaling pathway directs a multitude of cellular responses during embryogenesis and adult tissue homeostasis. Stimulation of the pathway results in activation of Hh target genes by the transcription factor Ci/Gli, which binds to specific motifs in genomic enhancers. In Drosophila, only a few enhancers (patched, decapentaplegic, wingless, stripe, knot, hairy, orthodenticle) have been shown by in vivo functional assays to depend on direct Ci/Gli regulation. All but one (orthodenticle) contain more than one Ci/Gli site, prompting us to directly test whether homotypic clustering of Ci/Gli binding sites is sufficient to define a Hh-regulated enhancer. We therefore developed a computational algorithm to identify Ci/Gli clusters that are enriched over random expectation, within a given region of the genome. Candidate genomic regions containing Ci/Gli clusters were functionally tested in chicken neural tube electroporation assays and in transgenic flies. Of the 22 Ci/Gli clusters tested, seven novel enhancers (and the previously known patched enhancer) were identified as Hh-responsive and Ci/Gli-dependent in one or both of these assays, including: Cuticular protein 100A (Cpr100A); invected (inv), which encodes an engrailed-related transcription factor expressed at the anterior/posterior wing disc boundary; roadkill (rdx), the fly homolog of vertebrate Spop; the segment polarity gene gooseberry (gsb); and two previously untested regions of the Hh receptor-encoding patched (ptc) gene. We conclude that homotypic Ci/Gli clustering is not sufficient information to ensure Hh-responsiveness; however, it can provide a clue for enhancer recognition within putative Hedgehog target gene loci.
Collapse
Affiliation(s)
- Katherine Gurdziel
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Computational Medicine and Bioinformatics, The University of Michigan, Ann Arbor, MI 48109, United States of America
| | - David S. Lorberbaum
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
- Cellular and Molecular Biology Program, The University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Aaron M. Udager
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Jane Y. Song
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
- Cellular and Molecular Biology Program, The University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Neil Richards
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
| | - David S. Parker
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Lisa A. Johnson
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Benjamin L. Allen
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
- * E-mail: (DLG); (SB); (BLA)
| | - Scott Barolo
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
- * E-mail: (DLG); (SB); (BLA)
| | - Deborah L. Gumucio
- Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
- * E-mail: (DLG); (SB); (BLA)
| |
Collapse
|