1
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Raditsa V, Tsukanov A, Bogomolov A, Levitsky V. Genomic background sequences systematically outperform synthetic ones in de novo motif discovery for ChIP-seq data. NAR Genom Bioinform 2024; 6:lqae090. [PMID: 39071850 PMCID: PMC11282361 DOI: 10.1093/nargab/lqae090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 06/03/2024] [Accepted: 07/19/2024] [Indexed: 07/30/2024] Open
Abstract
Efficient de novo motif discovery from the results of wide-genome mapping of transcription factor binding sites (ChIP-seq) is dependent on the choice of background nucleotide sequences. The foreground sequences (ChIP-seq peaks) represent not only specific motifs of target transcription factors, but also the motifs overrepresented throughout the genome, such as simple sequence repeats. We performed a massive comparison of the 'synthetic' and 'genomic' approaches to generate background sequences for de novo motif discovery. The 'synthetic' approach shuffled nucleotides in peaks, while in the 'genomic' approach selected sequences from the reference genome randomly or only from gene promoters according to the fraction of A/T nucleotides in each sequence. We compiled the benchmark collections of ChIP-seq datasets for mouse, human and Arabidopsis, and performed de novo motif discovery. We showed that the genomic approach has both more robust detection of the known motifs of target transcription factors and more stringent exclusion of the simple sequence repeats as possible non-specific motifs. The advantage of the genomic approach over the synthetic approach was greater in plants compared to mammals. We developed the AntiNoise web service (https://denovosea.icgbio.ru/antinoise/) that implements a genomic approach to extract genomic background sequences for twelve eukaryotic genomes.
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Affiliation(s)
- Vladimir V Raditsa
- Department of System Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
| | - Anton V Tsukanov
- Department of System Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
| | - Anton G Bogomolov
- Department of Cell Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
| | - Victor G Levitsky
- Department of System Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
- Department of Natural Science, Novosibirsk State University, Novosibirsk 630090, Russia
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2
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Hemphill WO, Steiner HR, Kominsky JR, Wuttke DS, Cech TR. Transcription factors ERα and Sox2 have differing multiphasic DNA- and RNA-binding mechanisms. RNA (NEW YORK, N.Y.) 2024; 30:1089-1105. [PMID: 38760076 PMCID: PMC11251522 DOI: 10.1261/rna.080027.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/01/2024] [Indexed: 05/19/2024]
Abstract
Many transcription factors (TFs) have been shown to bind RNA, leading to open questions regarding the mechanism(s) of this RNA binding and its role in regulating TF activities. Here, we use biophysical assays to interrogate the k on, k off, and K d for DNA and RNA binding of two model human TFs, ERα and Sox2. Unexpectedly, we found that both proteins exhibit multiphasic nucleic acid-binding kinetics. We propose that Sox2 RNA and DNA multiphasic binding kinetics can be explained by a conventional model for sequential Sox2 monomer association and dissociation. In contrast, ERα nucleic acid binding exhibited biphasic dissociation paired with novel triphasic association behavior, in which two apparent binding transitions are separated by a 10-20 min "lag" phase depending on protein concentration. We considered several conventional models for the observed kinetic behavior, none of which adequately explained all the ERα nucleic acid-binding data. Instead, simulations with a model incorporating sequential ERα monomer association, ERα nucleic acid complex isomerization, and product "feedback" on isomerization rate recapitulated the general kinetic trends for both ERα DNA and RNA binding. Collectively, our findings reveal that Sox2 and ERα bind RNA and DNA with previously unappreciated multiphasic binding kinetics, and that their reaction mechanisms differ with ERα binding nucleic acids via a novel reaction mechanism.
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Affiliation(s)
- Wayne O Hemphill
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303, USA
- Howard Hughes Medical Institute and BioFrontiers Institute, University of Colorado Boulder, Boulder, Colorado 80303, USA
| | - Halley R Steiner
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303, USA
| | - Jackson R Kominsky
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303, USA
- Howard Hughes Medical Institute and BioFrontiers Institute, University of Colorado Boulder, Boulder, Colorado 80303, USA
| | - Deborah S Wuttke
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303, USA
| | - Thomas R Cech
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303, USA
- Howard Hughes Medical Institute and BioFrontiers Institute, University of Colorado Boulder, Boulder, Colorado 80303, USA
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3
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Rao M, McDuffie E, Srivastava S, Plaisted W, Sachs C. Safety Implications of Modulating Nuclear Receptors: A Comprehensive Analysis from Non-Clinical and Clinical Perspectives. Pharmaceuticals (Basel) 2024; 17:875. [PMID: 39065726 PMCID: PMC11279859 DOI: 10.3390/ph17070875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 06/13/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024] Open
Abstract
The unintended modulation of nuclear receptor (NR) activity by drugs can lead to toxicities amongst the endocrine, gastrointestinal, hepatic cardiovascular, and central nervous systems. While secondary pharmacology screening assays include NRs, safety risks due to unintended interactions of small molecule drugs with NRs remain poorly understood. To identify potential nonclinical and clinical safety effects resulting from functional interactions with 44 of the 48 human-expressed NRs, we conducted a systematic narrative review of the scientific literature, tissue expression data, and used curated databases (OFF-X™) (Off-X, Clarivate) to organize reported toxicities linked to the functional modulation of NRs in a tabular and machine-readable format. The top five NRs associated with the highest number of safety alerts from peer-reviewed journals, regulatory agency communications, congresses/conferences, clinical trial registries, and company communications were the Glucocorticoid Receptor (GR, 18,328), Androgen Receptor (AR, 18,219), Estrogen Receptor (ER, 12,028), Retinoic acid receptors (RAR, 10,450), and Pregnane X receptor (PXR, 8044). Toxicities associated with NR modulation include hepatotoxicity, cardiotoxicity, endocrine disruption, carcinogenicity, metabolic disorders, and neurotoxicity. These toxicities often arise from the dysregulation of receptors like Peroxisome proliferator-activated receptors (PPARα, PPARγ), the ER, PXR, AR, and GR. This dysregulation leads to various health issues, including liver enlargement, hepatocellular carcinoma, heart-related problems, hormonal imbalances, tumor growth, metabolic syndromes, and brain function impairment. Gene expression analysis using heatmaps for human and rat tissues complemented the functional modulation of NRs associated with the reported toxicities. Interestingly, certain NRs showed ubiquitous expression in tissues not previously linked to toxicities, suggesting the potential utilization of organ-specific NR interactions for therapeutic purposes.
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Affiliation(s)
- Mohan Rao
- Toxicology Department, Neurocrine Biosciences, Inc., San Diego, CA 92130, USA (C.S.)
| | - Eric McDuffie
- Toxicology Department, Neurocrine Biosciences, Inc., San Diego, CA 92130, USA (C.S.)
| | - Sanjay Srivastava
- Chemistry Department, Neurocrine Biosciences, Inc., San Diego, CA 92130, USA
| | - Warren Plaisted
- Biology Department, Neurocrine Biosciences, Inc., San Diego, CA 92130, USA
| | - Clifford Sachs
- Toxicology Department, Neurocrine Biosciences, Inc., San Diego, CA 92130, USA (C.S.)
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4
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Coetzee SG, Hazelett DJ. MotifbreakR v2: extended capability and database integration. ARXIV 2024:arXiv:2407.03441v1. [PMID: 39010878 PMCID: PMC11247919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
MotifbreakR is a software tool that scans genetic variants against position weight matrices of transcription factors (TF) to determine the potential for the disruption of TF binding at the site of the variant. It leverages the Bioconductor suite of software packages and annotations to operate across a diverse array of genomes and motif databases. Initially developed to interrogate the effect of single nucleotide variants (common and rare SNVs) on potential TF binding sites, in motifbreakR v2, we have updated the functionality. New features include the ability to query other types of more complex genetic variants, such as short insertions and deletions (indels). This function allows modeling a more extensive array of variants that may have more significant effects on TF binding. Additionally, while TF binding is based partly on sequence preference, predictions of TF binding based on sequence preference alone can indicate many more potential binding events than observed. Adding information from DNA-binding sequencing datasets lends confidence to motif disruption prediction by demonstrating TF binding in cell lines and tissue types. Therefore, motifbreakR implements querying the ReMap2022 database for evidence that a TF matching the disrupted motif binds over the disrupting variant. Finally, in motifbreakR, in addition to the existing interface, we have implemented an R/Shiny graphical user interface to simplify and enhance access to researchers with different skill sets.
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Affiliation(s)
- Simon G Coetzee
- Department of Computational Biomedicine at Cedars-Sinai Medical Center
| | - Dennis J Hazelett
- Department of Computational Biomedicine at Cedars-Sinai Medical Center
- Cancer Prevention and Control - Samuel Oschin Cancer Center, Cedars-Sinai
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5
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Charrier A, Ockunzzi J, Main L, Ghanta SV, Buchner DA. Molecular regulation of PPARγ/RXRα signaling by the novel cofactor ZFP407. PLoS One 2024; 19:e0294003. [PMID: 38781157 PMCID: PMC11115250 DOI: 10.1371/journal.pone.0294003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 02/20/2024] [Indexed: 05/25/2024] Open
Abstract
Cofactors interacting with PPARγ can regulate adipogenesis and adipocyte metabolism by modulating the transcriptional activity and selectivity of PPARγ signaling. ZFP407 was previously demonstrated to regulate PPARγ target genes such as GLUT4, and its overexpression improved glucose homeostasis in mice. Here, using a series of molecular assays, including protein-interaction studies, mutagenesis, and ChIP-seq, ZFP407 was found to interact with the PPARγ/RXRα protein complex in the nucleus of adipocytes. Consistent with this observation, ZFP407 ChIP-seq peaks significantly overlapped with PPARγ ChIP-seq peaks, with more than half of ZFP407 peaks overlapping with PPARγ peaks. Transcription factor binding motifs enriched in these overlapping sites included CTCF, RARα/RXRγ, TP73, and ELK1, which regulate cellular development and function within adipocytes. Site-directed mutagenesis of frequent PPARγ phosphorylation or SUMOylation sites did not prevent its regulation by ZFP407, while mutagenesis of ZFP407 domains potentially necessary for RXR and PPARγ binding abrogated any impact of ZFP407 on PPARγ activity. These data suggest that ZFP407 controls the activity of PPARγ, but does so independently of post-translational modifications, likely by direct binding, establishing ZFP407 as a newly identified PPARγ cofactor. In addition, ZFP407 ChIP-seq analyses identified regions that did not overlap with PPARγ peaks. These non-overlapping peaks were significantly enriched for the transcription factor binding motifs of TBX19, PAX8, HSF4, and ZKSCAN3, which may contribute to the PPARγ-independent functions of ZFP407 in adipocytes and other cell types.
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Affiliation(s)
- Alyssa Charrier
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Jeremiah Ockunzzi
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Leighanne Main
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Siddharth V. Ghanta
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - David A. Buchner
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
- Department of Biochemistry, Case Western Reserve University, Cleveland, Ohio, United States of America
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6
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Hemphill WO, Steiner HR, Kominsky JR, Wuttke DS, Cech TR. Transcription factors ERα and Sox2 have differing multiphasic DNA and RNA binding mechanisms. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.18.585577. [PMID: 38562825 PMCID: PMC10983890 DOI: 10.1101/2024.03.18.585577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Many transcription factors (TFs) have been shown to bind RNA, leading to open questions regarding the mechanism(s) of this RNA binding and its role in regulating TF activities. Here we use biophysical assays to interrogate the k o n , k o f f , and K d for DNA and RNA binding of two model human transcription factors, ERα and Sox2. Unexpectedly, we found that both proteins exhibited multiphasic nucleic acid binding kinetics. We propose that Sox2 RNA and DNA multiphasic binding kinetics could be explained by a conventional model for sequential Sox2 monomer association and dissociation. In contrast, ERα nucleic acid binding exhibited biphasic dissociation paired with novel triphasic association behavior, where two apparent binding transitions are separated by a 10-20 min "lag" phase depending on protein concentration. We considered several conventional models for the observed kinetic behavior, none of which adequately explained all the ERα nucleic acid binding data. Instead, simulations with a model incorporating sequential ERα monomer association, ERα nucleic acid complex isomerization, and product "feedback" on isomerization rate recapitulated the general kinetic trends for both ERα DNA and RNA binding. Collectively, our findings reveal that Sox2 and ERα bind RNA and DNA with previously unappreciated multiphasic binding kinetics, and that their reaction mechanisms differ with ERα binding nucleic acids via a novel reaction mechanism.
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Affiliation(s)
- Wayne O. Hemphill
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303 USA
- Howard Hughes Medical Institute and BioFrontiers Institute, University of Colorado Boulder, Boulder, Colorado 80303 USA
| | - Halley R. Steiner
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303 USA
| | - Jackson R. Kominsky
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303 USA
- Howard Hughes Medical Institute and BioFrontiers Institute, University of Colorado Boulder, Boulder, Colorado 80303 USA
| | - Deborah S. Wuttke
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303 USA
| | - Thomas R. Cech
- Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado 80303 USA
- Howard Hughes Medical Institute and BioFrontiers Institute, University of Colorado Boulder, Boulder, Colorado 80303 USA
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7
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Rieu P, Beretta VM, Caselli F, Thévénon E, Lucas J, Rizk M, Franchini E, Caporali E, Paleni C, Nanao MH, Kater MM, Dumas R, Zubieta C, Parcy F, Gregis V. The ALOG domain defines a family of plant-specific transcription factors acting during Arabidopsis flower development. Proc Natl Acad Sci U S A 2024; 121:e2310464121. [PMID: 38412122 PMCID: PMC10927535 DOI: 10.1073/pnas.2310464121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 12/05/2023] [Indexed: 02/29/2024] Open
Abstract
The ALOG (Arabidopsis LIGHT-DEPENDENT SHORT HYPOCOTYLS 1 (LSH1) and Oryza G1) proteins are conserved plant-specific Transcription Factors (TFs). They play critical roles in the development of various plant organs (meristems, inflorescences, floral organs, and nodules) from bryophytes to higher flowering plants. Despite the fact that the first members of this family were originally discovered in Arabidopsis, their role in this model plant has remained poorly characterized. Moreover, how these transcriptional regulators work at the molecular level is unknown. Here, we study the redundant function of the ALOG proteins LSH1,3,4 from Arabidopsis. We uncover their role in the repression of bract development and position them within a gene regulatory network controlling this process and involving the floral regulators LEAFY, BLADE-ON-PETIOLE, and PUCHI. Next, using in vitro genome-wide studies, we identified the conserved DNA motif bound by ALOG proteins from evolutionarily distant species (the liverwort Marchantia polymorpha and the flowering plants Arabidopsis, tomato, and rice). Resolution of the crystallographic structure of the ALOG DNA-binding domain in complex with DNA revealed the domain is a four-helix bundle with a disordered NLS and a zinc ribbon insertion between helices 2 and 3. The majority of DNA interactions are mediated by specific contacts made by the third alpha helix and the NLS. Taken together, this work provides the biochemical and structural basis for DNA-binding specificity of an evolutionarily conserved TF family and reveals its role as a key player in Arabidopsis flower development.
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Affiliation(s)
- Philippe Rieu
- Laboratoire Physiologie Cellulaire et Végétale, Université Grenoble Alpes, Centre national de la recherche scientifique, Commissariat à l’énergie atomique et aux énergies alternatives, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Département de Biologie Structurale et Cellulaire intégrée, GrenobleF-38054, France
| | | | - Francesca Caselli
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milano20133, Italy
| | - Emmanuel Thévénon
- Laboratoire Physiologie Cellulaire et Végétale, Université Grenoble Alpes, Centre national de la recherche scientifique, Commissariat à l’énergie atomique et aux énergies alternatives, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Département de Biologie Structurale et Cellulaire intégrée, GrenobleF-38054, France
| | - Jérémy Lucas
- Laboratoire Physiologie Cellulaire et Végétale, Université Grenoble Alpes, Centre national de la recherche scientifique, Commissariat à l’énergie atomique et aux énergies alternatives, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Département de Biologie Structurale et Cellulaire intégrée, GrenobleF-38054, France
| | - Mahmoud Rizk
- Structural Biology Group, European Synchrotron Radiation Facility, Grenoble38000, France
| | - Emanuela Franchini
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milano20133, Italy
| | - Elisabetta Caporali
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milano20133, Italy
| | - Chiara Paleni
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milano20133, Italy
| | - Max H. Nanao
- Structural Biology Group, European Synchrotron Radiation Facility, Grenoble38000, France
| | - Martin M. Kater
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milano20133, Italy
| | - Renaud Dumas
- Laboratoire Physiologie Cellulaire et Végétale, Université Grenoble Alpes, Centre national de la recherche scientifique, Commissariat à l’énergie atomique et aux énergies alternatives, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Département de Biologie Structurale et Cellulaire intégrée, GrenobleF-38054, France
| | - Chloe Zubieta
- Laboratoire Physiologie Cellulaire et Végétale, Université Grenoble Alpes, Centre national de la recherche scientifique, Commissariat à l’énergie atomique et aux énergies alternatives, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Département de Biologie Structurale et Cellulaire intégrée, GrenobleF-38054, France
| | - François Parcy
- Laboratoire Physiologie Cellulaire et Végétale, Université Grenoble Alpes, Centre national de la recherche scientifique, Commissariat à l’énergie atomique et aux énergies alternatives, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Département de Biologie Structurale et Cellulaire intégrée, GrenobleF-38054, France
| | - Veronica Gregis
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milano20133, Italy
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8
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Vorontsov IE, Eliseeva IA, Zinkevich A, Nikonov M, Abramov S, Boytsov A, Kamenets V, Kasianova A, Kolmykov S, Yevshin I, Favorov A, Medvedeva YA, Jolma A, Kolpakov F, Makeev V, Kulakovskiy I. HOCOMOCO in 2024: a rebuild of the curated collection of binding models for human and mouse transcription factors. Nucleic Acids Res 2024; 52:D154-D163. [PMID: 37971293 PMCID: PMC10767914 DOI: 10.1093/nar/gkad1077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 10/17/2023] [Accepted: 10/26/2023] [Indexed: 11/19/2023] Open
Abstract
We present a major update of the HOCOMOCO collection that provides DNA binding specificity patterns of 949 human transcription factors and 720 mouse orthologs. To make this release, we performed motif discovery in peak sets that originated from 14 183 ChIP-Seq experiments and reads from 2554 HT-SELEX experiments yielding more than 400 thousand candidate motifs. The candidate motifs were annotated according to their similarity to known motifs and the hierarchy of DNA-binding domains of the respective transcription factors. Next, the motifs underwent human expert curation to stratify distinct motif subtypes and remove non-informative patterns and common artifacts. Finally, the curated subset of 100 thousand motifs was supplied to the automated benchmarking to select the best-performing motifs for each transcription factor. The resulting HOCOMOCO v12 core collection contains 1443 verified position weight matrices, including distinct subtypes of DNA binding motifs for particular transcription factors. In addition to the core collection, HOCOMOCO v12 provides motif sets optimized for the recognition of binding sites in vivo and in vitro, and for annotation of regulatory sequence variants. HOCOMOCO is available at https://hocomoco12.autosome.org and https://hocomoco.autosome.org.
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Affiliation(s)
- Ilya E Vorontsov
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Irina A Eliseeva
- Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Russia
| | - Arsenii Zinkevich
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Mikhail Nikonov
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Sergey Abramov
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- Altius Institute for Biomedical Sciences, 98121 Seattle, WA, USA
| | - Alexandr Boytsov
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- Altius Institute for Biomedical Sciences, 98121 Seattle, WA, USA
| | - Vasily Kamenets
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Russia
- Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
| | - Alexandra Kasianova
- Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
- Institute for Information Transmission Problems of the Russian Academy of Sciences, 127051 Moscow, Russia
| | - Semyon Kolmykov
- Department of Computational Biology, Sirius University of Science and Technology, 354340 Sirius, Krasnodar region, Russia
| | | | - Alexander Favorov
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Yulia A Medvedeva
- Research Center of Biotechnology RAS, Russian Academy of Sciences, 119071 Moscow, Russia
| | - Arttu Jolma
- Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | - Fedor Kolpakov
- Department of Computational Biology, Sirius University of Science and Technology, 354340 Sirius, Krasnodar region, Russia
- Bioinformatics Laboratory, Federal Research Center for Information and Computational Technologies, 630090 Novosibirsk, Russia
| | - Vsevolod J Makeev
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Russia
- Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
| | - Ivan V Kulakovskiy
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Russia
- Laboratory of Regulatory Genomics, Institute of Fundamental Medicine and Biology, Kazan Federal University, 420008 Kazan, Russia
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9
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Rauluseviciute I, Riudavets-Puig R, Blanc-Mathieu R, Castro-Mondragon J, Ferenc K, Kumar V, Lemma RB, Lucas J, Chèneby J, Baranasic D, Khan A, Fornes O, Gundersen S, Johansen M, Hovig E, Lenhard B, Sandelin A, Wasserman W, Parcy F, Mathelier A. JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles. Nucleic Acids Res 2024; 52:D174-D182. [PMID: 37962376 PMCID: PMC10767809 DOI: 10.1093/nar/gkad1059] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/20/2023] [Accepted: 10/31/2023] [Indexed: 11/15/2023] Open
Abstract
JASPAR (https://jaspar.elixir.no/) is a widely-used open-access database presenting manually curated high-quality and non-redundant DNA-binding profiles for transcription factors (TFs) across taxa. In this 10th release and 20th-anniversary update, the CORE collection has expanded with 329 new profiles. We updated three existing profiles and provided orthogonal support for 72 profiles from the previous release's UNVALIDATED collection. Altogether, the JASPAR 2024 update provides a 20% increase in CORE profiles from the previous release. A trimming algorithm enhanced profiles by removing low information content flanking base pairs, which were likely uninformative (within the capacity of the PFM models) for TFBS predictions and modelling TF-DNA interactions. This release includes enhanced metadata, featuring a refined classification for plant TFs' structural DNA-binding domains. The new JASPAR collections prompt updates to the genomic tracks of predicted TF binding sites (TFBSs) in 8 organisms, with human and mouse tracks available as native tracks in the UCSC Genome browser. All data are available through the JASPAR web interface and programmatically through its API and the updated Bioconductor and pyJASPAR packages. Finally, a new TFBS extraction tool enables users to retrieve predicted JASPAR TFBSs intersecting their genomic regions of interest.
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Affiliation(s)
- Ieva Rauluseviciute
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Rafael Riudavets-Puig
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Romain Blanc-Mathieu
- Laboratoire Physiologie Cellulaire et Végétale, Univ. Grenoble Alpes, CNRS, CEA, INRAE, IRIG-DBSCI-LPCV, 17 avenue des martyrs, F-38054, Grenoble, France
| | - Jaime A Castro-Mondragon
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Katalin Ferenc
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Vipin Kumar
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Roza Berhanu Lemma
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Jérémy Lucas
- Laboratoire Physiologie Cellulaire et Végétale, Univ. Grenoble Alpes, CNRS, CEA, INRAE, IRIG-DBSCI-LPCV, 17 avenue des martyrs, F-38054, Grenoble, France
| | - Jeanne Chèneby
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Damir Baranasic
- MRC London Institute of Medical Sciences, Du Cane Road, London W12 0NN, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK
- Division of Electronics, Ruđer Bošković Institute, Bijenička cesta, 10000 Zagreb, Croatia
| | - Aziz Khan
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Oriol Fornes
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children's Hospital Research Institute, University of British Columbia, 950 W 28th Ave, Vancouver, BC V5Z 4H4, Canada
| | - Sveinung Gundersen
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Morten Johansen
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Eivind Hovig
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, 0424 Oslo, Norway
| | - Boris Lenhard
- MRC London Institute of Medical Sciences, Du Cane Road, London W12 0NN, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK
| | - Albin Sandelin
- Department of Biology and Biotech Research and Innovation Centre, University of Copenhagen, Ole Maaløes Vej 5, DK2200 Copenhagen N, Denmark
| | - Wyeth W Wasserman
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children's Hospital Research Institute, University of British Columbia, 950 W 28th Ave, Vancouver, BC V5Z 4H4, Canada
| | - François Parcy
- Laboratoire Physiologie Cellulaire et Végétale, Univ. Grenoble Alpes, CNRS, CEA, INRAE, IRIG-DBSCI-LPCV, 17 avenue des martyrs, F-38054, Grenoble, France
| | - Anthony Mathelier
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
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10
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Gordon T. Brief Electrical Stimulation Promotes Recovery after Surgical Repair of Injured Peripheral Nerves. Int J Mol Sci 2024; 25:665. [PMID: 38203836 PMCID: PMC10779324 DOI: 10.3390/ijms25010665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/07/2023] [Accepted: 12/08/2023] [Indexed: 01/12/2024] Open
Abstract
Injured peripheral nerves regenerate their axons in contrast to those in the central nervous system. Yet, functional recovery after surgical repair is often disappointing. The basis for poor recovery is progressive deterioration with time and distance of the growth capacity of the neurons that lose their contact with targets (chronic axotomy) and the growth support of the chronically denervated Schwann cells (SC) in the distal nerve stumps. Nonetheless, chronically denervated atrophic muscle retains the capacity for reinnervation. Declining electrical activity of motoneurons accompanies the progressive fall in axotomized neuronal and denervated SC expression of regeneration-associated-genes and declining regenerative success. Reduced motoneuronal activity is due to the withdrawal of synaptic contacts from the soma. Exogenous neurotrophic factors that promote nerve regeneration can replace the endogenous factors whose expression declines with time. But the profuse axonal outgrowth they provoke and the difficulties in their delivery hinder their efficacy. Brief (1 h) low-frequency (20 Hz) electrical stimulation (ES) proximal to the injury site promotes the expression of endogenous growth factors and, in turn, dramatically accelerates axon outgrowth and target reinnervation. The latter ES effect has been demonstrated in both rats and humans. A conditioning ES of intact nerve days prior to nerve injury increases axonal outgrowth and regeneration rate. Thereby, this form of ES is amenable for nerve transfer surgeries and end-to-side neurorrhaphies. However, additional surgery for applying the required electrodes may be a hurdle. ES is applicable in all surgeries with excellent outcomes.
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Affiliation(s)
- Tessa Gordon
- Division of Reconstructive Surgery, Department of Surgery, University of Toronto, Toronto, ON M4G 1X8, Canada
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11
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Chuang KT, Chiou SS, Hsu SH. Recent Advances in Transcription Factors Biomarkers and Targeted Therapies Focusing on Epithelial-Mesenchymal Transition. Cancers (Basel) 2023; 15:3338. [PMID: 37444447 DOI: 10.3390/cancers15133338] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 06/07/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023] Open
Abstract
Transcription factors involve many proteins in the process of transactivating or transcribing (none-) encoded DNA to initiate and regulate downstream signals, such as RNA polymerase. Their unique characteristic is that they possess specific domains that bind to specific DNA element sequences called enhancer or promoter sequences. Epithelial-mesenchymal transition (EMT) is involved in cancer progression. Many dysregulated transcription factors-such as Myc, SNAIs, Twists, and ZEBs-are key drivers of tumor metastasis through EMT regulation. This review summarizes currently available evidence related to the oncogenic role of classified transcription factors in EMT editing and epigenetic regulation, clarifying the roles of the classified conserved transcription factor family involved in the EMT and how these factors could be used as therapeutic targets in future investigations.
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Affiliation(s)
- Kai-Ting Chuang
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Shyh-Shin Chiou
- Division of Pediatric Hematology and Oncology, Department of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan
- Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
- Center of Applied Genomics, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Shih-Hsien Hsu
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Center of Applied Genomics, Kaohsiung Medical University, Kaohsiung 807, Taiwan
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan
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12
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Ji X, Cai J, Liang L, Shi T, Liu J. Gene expression variability across cells and species shapes the relationship between renal resident macrophages and infiltrated macrophages. BMC Bioinformatics 2023; 24:72. [PMID: 36858955 PMCID: PMC9976410 DOI: 10.1186/s12859-023-05198-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 02/21/2023] [Indexed: 03/03/2023] Open
Abstract
BACKGROUND Two main subclasses of macrophages are found in almost all solid tissues: embryo-derived resident tissue macrophages and bone marrow-derived infiltrated macrophages. These macrophage subtypes show transcriptional and functional divergence, and the programs that have shaped the evolution of renal macrophages and related signaling pathways remain poorly understood. To clarify these processes, we performed data analysis based on single-cell transcriptional profiling of renal tissue-resident and infiltrated macrophages in human, mouse and rat. RESULTS In this study, we (i) characterized the transcriptional divergence among species and (ii) illustrated variability in expression among cells of each subtype and (iii) compared the gene regulation network and (iv) ligand-receptor pairs in human and mouse. Using single-cell transcriptomics, we mapped the promoter architecture during homeostasis. CONCLUSIONS Transcriptionally divergent genes, such as the differentially TF-encoding genes expressed in resident and infiltrated macrophages across the three species, vary among cells and include distinct promoter structures. The gene regulatory network in infiltrated macrophages shows comparatively better species-wide consistency than resident macrophages. The conserved transcriptional gene regulatory network in infiltrated macrophages among species is uniquely enriched in pathways related to kinases, and TFs associated with largely conserved regulons among species are uniquely enriched in kinase-related pathways.
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Affiliation(s)
- Xiangjun Ji
- grid.284723.80000 0000 8877 7471Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515 China
| | - Junwei Cai
- grid.284723.80000 0000 8877 7471Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515 China
| | - Lixin Liang
- grid.284723.80000 0000 8877 7471Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515 China
| | - Tieliu Shi
- Center for Bioinformatics and Computational Biology, The Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China. .,Beijing Advanced Innovation Center, for Big Data-Based Precision Medicine, Beihang University and Capital Medical University, Beijing, 100083, China.
| | - Jinghua Liu
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.
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13
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Valakh V, Wise D, Zhu XA, Sha M, Fok J, Van Hooser SD, Schectman R, Cepeda I, Kirk R, O'Toole SM, Nelson SB. A transcriptional constraint mechanism limits the homeostatic response to activity deprivation in mammalian neocortex. eLife 2023; 12:e74899. [PMID: 36749029 PMCID: PMC10010687 DOI: 10.7554/elife.74899] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 02/03/2023] [Indexed: 02/08/2023] Open
Abstract
Healthy neuronal networks rely on homeostatic plasticity to maintain stable firing rates despite changing synaptic drive. These mechanisms, however, can themselves be destabilizing if activated inappropriately or excessively. For example, prolonged activity deprivation can lead to rebound hyperactivity and seizures. While many forms of homeostasis have been described, whether and how the magnitude of homeostatic plasticity is constrained remains unknown. Here, we uncover negative regulation of cortical network homeostasis by the PARbZIP family of transcription factors. In cortical slice cultures made from knockout mice lacking all three of these factors, the network response to prolonged activity withdrawal measured with calcium imaging is much stronger, while baseline activity is unchanged. Whole-cell recordings reveal an exaggerated increase in the frequency of miniature excitatory synaptic currents reflecting enhanced upregulation of recurrent excitatory synaptic transmission. Genetic analyses reveal that two of the factors, Hlf and Tef, are critical for constraining plasticity and for preventing life-threatening seizures. These data indicate that transcriptional activation is not only required for many forms of homeostatic plasticity but is also involved in restraint of the response to activity deprivation.
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Affiliation(s)
- Vera Valakh
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Derek Wise
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Xiaoyue Aelita Zhu
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Mingqi Sha
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Jaidyn Fok
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Stephen D Van Hooser
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Robin Schectman
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Isabel Cepeda
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Ryan Kirk
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Sean M O'Toole
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
| | - Sacha B Nelson
- Department of Biology and Program in Neuroscience, Brandeis UniversityWalthamUnited States
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14
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Mola S, Beauchamp C, Boucher G, Lesage S, Karaky M, Goyette P, Foisy S, Rioux JD. Identifying transcript-level differential expression in primary human immune cells. Mol Immunol 2023; 153:181-193. [PMID: 36527757 DOI: 10.1016/j.molimm.2022.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 11/17/2022] [Accepted: 12/09/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Multipotential hematopoietic stem cells differentiate into a wide variety of immune cells with a diversity of functions, including the ability to respond to a variety of stimuli. Importantly, numerous studies have demonstrated the importance of gene transcription in defining cell identity and functions. While these studies have primarily been performed at the level of the gene, it is known that key immune genes such as CD44 and CD45 generate multiple different transcripts that are differentially expressed across different immune cells, and that encode proteins with different sequences and functions. Prior genomic surveys have shown that the mechanisms for generating diversity in expressed transcripts (alternate splicing, alternate transcription start sites, etc.) are very active in immune cells, but have been lacking in terms of identifying genes with multiple transcripts, that are differentially expressed, and likely to affect cell functions. METHODS We first identified the set of genes that had at least two transcripts expressed in our RNA sequencing dataset generated from purified populations of neutrophils, monocytes and five lymphocyte populations (B, NK, γδ T, CD4 + T and CD8 + T) from twelve healthy donors. Next, we developed a heuristic approach to identify genes where two or more transcripts have distinct expression patterns across lymphoid and/or myeloid populations. We then focused our annotation and interpretation on differentially expressed transcripts that affect the coding sequence. This process was repeated to identify transcripts that were differentially expressed between monocytes and populations of macrophages and LPS-stimulated macrophages derived from these monocytes in vitro. RESULTS We found that over 55 % of genes had two or more expressed transcripts, with an average ∼3 transcripts per gene, and that 70 % of these had at least two of the transcripts that encoded proteins with different sequences. As expected, we identified a complex pattern of differential expression for multiple transcripts encoding the CD45 transmembrane protein, but we also found similar evidence for ten other genes (CD300A, FYB1, GPI, LITAF, PSMA1, PTMA, RPL32, SEPTIN9, SH3BP2, SH3KBP1) when comparing the expression patterns of transcripts within myeloid and lymphoid cells. We also identified five genes with differentially expressed transcripts associated with the transition from monocytes to macrophages (FNBP1, KLF6, and SEPTIN9) or between macrophages and LPS-stimulated macrophages (CD44, OAZ2, and SEPTIN9). For the most part, we found that the different transcripts of these genes are expected to impact specific biological functions, for example the different transcripts of SEPTIN9 likely regulate the cytoskeleton in immune cells via their interactions with actins filaments and microtubules. CONCLUSIONS This analytic approach successfully identified multi-transcript genes that are differentially expressed across immune cells and could be applied to other transcriptomic data. DATA AVAILABILITY STATEMENT Researchers can request access to the individual-level data from the current study by contacting the Montreal Heart Institute ethics committee at the following institutional email address: cer.icm@icm-mhi.org.
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Affiliation(s)
- Saraï Mola
- Centre de recherche, Institut de cardiologie de Montréal, 5000 Rue Bélanger, Montréal, Québec H1T 1C8, Canada; Département de biochimie et médecine moléculaire, Université de Montréal, Pavillon Roger-Gaudry, C.P. 6128, Succ. Centre-ville, Montréal, Québec H3C 3J7, Canada.
| | - Claudine Beauchamp
- Centre de recherche, Institut de cardiologie de Montréal, 5000 Rue Bélanger, Montréal, Québec H1T 1C8, Canada.
| | - Gabrielle Boucher
- Centre de recherche, Institut de cardiologie de Montréal, 5000 Rue Bélanger, Montréal, Québec H1T 1C8, Canada.
| | - Sylvie Lesage
- Maisonneuve-Rosemont Hospital Research Center, 5415 boul. De l'Assomption, Montréal, Québec H1T 2M4, Canada; Département de Microbiologie, Infectiologie et Immunologie, Université de Montréal, C.P. 6128, Succ. Centre-ville, Montréal, Québec H3C 3J7, Canada.
| | - Mohamad Karaky
- Centre de recherche, Institut de cardiologie de Montréal, 5000 Rue Bélanger, Montréal, Québec H1T 1C8, Canada.
| | - Philippe Goyette
- Centre de recherche, Institut de cardiologie de Montréal, 5000 Rue Bélanger, Montréal, Québec H1T 1C8, Canada.
| | - Sylvain Foisy
- Centre de recherche, Institut de cardiologie de Montréal, 5000 Rue Bélanger, Montréal, Québec H1T 1C8, Canada.
| | - John D Rioux
- Centre de recherche, Institut de cardiologie de Montréal, 5000 Rue Bélanger, Montréal, Québec H1T 1C8, Canada; Département de biochimie et médecine moléculaire, Université de Montréal, Pavillon Roger-Gaudry, C.P. 6128, Succ. Centre-ville, Montréal, Québec H3C 3J7, Canada; Département de médecine, Université de Montréal, Pavillon Roger-Gaudry, C.P. 6128, Succ. Centre-ville, Montréal, Québec H3C 3J7, Canada.
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15
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Lesha E, George H, Zaki MM, Smith CJ, Khoshakhlagh P, Ng AHM. A Survey of Transcription Factors in Cell Fate Control. Methods Mol Biol 2023; 2594:133-141. [PMID: 36264493 DOI: 10.1007/978-1-0716-2815-7_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Transcription factors (TFs) play a cardinal role in the development and maintenance of human physiology by acting as mediators of gene expression and cell state control. Recent advancements have broadened our knowledge on the potency of TFs in governing cell physiology and have deepened our understanding of the mechanisms through which they exert this control. The ability of TFs to program cell fates has gathered significant interest in recent decades, and high-throughput technologies now allow for the systematic discovery of forward programming factors to convert pluripotent stem cells into numerous differentiated cell types. The next generation of these technologies has the potential to improve our understanding and control of cell fates and states and provide advanced therapeutic modalities to address many medical conditions.
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Affiliation(s)
- Emal Lesha
- GC Therapeutics Inc., Cambridge, MA, USA
- Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Haydy George
- GC Therapeutics Inc., Cambridge, MA, USA
- School of Medicine, St. George's University, West Indies, Grenada
| | - Mark M Zaki
- GC Therapeutics Inc., Cambridge, MA, USA
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, USA
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16
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Lim J, Lim CW, Lee SC. Role of pepper MYB transcription factor CaDIM1 in regulation of the drought response. FRONTIERS IN PLANT SCIENCE 2022; 13:1028392. [PMID: 36304389 PMCID: PMC9592997 DOI: 10.3389/fpls.2022.1028392] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 09/14/2022] [Indexed: 06/16/2023]
Abstract
Abscisic acid (ABA) is a major phytohormone that plays important roles in stress responses, including regulation of gene expression and stomatal closure. Regulation of gene expression by transcription factors is a key cellular process for initiating defense responses to biotic and abiotic stresses. Here, using pepper (Capsicum annuum) leaves, we identified the MYB transcription factor CaDIM1 (Capsicum annuum Drought Induced MYB 1), which was highly induced by ABA and drought stress. CaDIM1 has an MYB domain in the N-terminal region and an acidic domain in the C-terminal region, which are responsible for recognition and transactivation of the target gene, respectively. Compared to control plants, CaDIM1-silenced pepper plants displayed ABA-insensitive and drought-sensitive phenotypes with reduced expression of stress-responsive genes. On the other hand, overexpression of CaDIM1 in Arabidopsis exhibited the opposite phenotypes of CaDIM1-silenced pepper plants, accompanied by enhanced ABA sensitivity and drought tolerance. Taken together, we demonstrate that CaDIM1 functions as a positive regulator of the drought-stress response via modulating ABA-mediated gene expression.
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17
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Spreitzer E, Alderson TR, Bourgeois B, Eggenreich L, Habacher H, Brahmersdorfer G, Pritišanac I, Sánchez-Murcia PA, Madl T. FOXO transcription factors differ in their dynamics and intra/intermolecular interactions. Curr Res Struct Biol 2022; 4:118-133. [PMID: 35573459 PMCID: PMC9097636 DOI: 10.1016/j.crstbi.2022.04.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 03/19/2022] [Accepted: 04/07/2022] [Indexed: 11/19/2022] Open
Affiliation(s)
- Emil Spreitzer
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - T. Reid Alderson
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Benjamin Bourgeois
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Loretta Eggenreich
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Hermann Habacher
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Greta Brahmersdorfer
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Iva Pritišanac
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Pedro A. Sánchez-Murcia
- Division of Physiological Chemistry, Otto-Loewi Research Center, Medical University of Graz, Graz, Austria
| | - Tobias Madl
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- Corresponding author. Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria.
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18
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Fischer F, Grigolon G, Benner C, Ristow M. Evolutionarily conserved transcription factors as regulators of longevity and targets for geroprotection. Physiol Rev 2022; 102:1449-1494. [PMID: 35343830 DOI: 10.1152/physrev.00017.2021] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Aging is the single largest risk factor for many debilitating conditions, including heart diseases, stroke, cancer, diabetes, and neurodegenerative disorders. While far from understood in its full complexity, it is scientifically well-established that aging is influenced by genetic and environmental factors, and can be modulated by various interventions. One of aging's early hallmarks are aberrations in transcriptional networks, controlling for example metabolic homeostasis or the response to stress. Evidence in different model organisms abounds that a number of evolutionarily conserved transcription factors, which control such networks, can affect lifespan and healthspan across species. These transcription factors thus potentially represent conserved regulators of longevity and are emerging as important targets in the challenging quest to develop treatments to mitigate age-related diseases, and possibly even to slow aging itself. This review provides an overview of evolutionarily conserved transcription factors that impact longevity or age-related diseases in at least one multicellular model organism (nematodes, flies, or mice), and/or are tentatively linked to human aging. Discussed is the general evidence for transcriptional regulation of aging and disease, followed by a more detailed look at selected transcription factor families, the common metabolic pathways involved, and the targeting of transcription factors as a strategy for geroprotective interventions.
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Affiliation(s)
- Fabian Fischer
- Energy Metabolism Laboratory, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETH) Zurich, Schwerzenbach, Switzerland
| | - Giovanna Grigolon
- Energy Metabolism Laboratory, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETH) Zurich, Schwerzenbach, Switzerland
| | - Christoph Benner
- Energy Metabolism Laboratory, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETH) Zurich, Schwerzenbach, Switzerland
| | - Michael Ristow
- Energy Metabolism Laboratory, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETH) Zurich, Schwerzenbach, Switzerland
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19
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Vazquez M, Krallinger M, Leitner F, Kuiper M, Valencia A, Laegreid A. ExTRI: Extraction of transcription regulation interactions from literature. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2022; 1865:194778. [PMID: 34875418 DOI: 10.1016/j.bbagrm.2021.194778] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 11/22/2021] [Accepted: 11/29/2021] [Indexed: 11/18/2022]
Abstract
The regulation of gene transcription by transcription factors is a fundamental biological process, yet the relations between transcription factors (TF) and their target genes (TG) are still only sparsely covered in databases. Text-mining tools can offer broad and complementary solutions to help locate and extract mentions of these biological relationships in articles. We have generated ExTRI, a knowledge graph of TF-TG relationships, by applying a high recall text-mining pipeline to MedLine abstracts identifying over 100,000 candidate sentences with TF-TG relations. Validation procedures indicated that about half of the candidate sentences contain true TF-TG relationships. Post-processing identified 53,000 high confidence sentences containing TF-TG relationships, with a cross-validation F1-score close to 75%. The resulting collection of TF-TG relationships covers 80% of the relations annotated in existing databases. It adds 11,000 other potential interactions, including relationships for ~100 TFs currently not in public TF-TG relation databases. The high confidence abstract sentences contribute 25,000 literature references not available from other resources and offer a wealth of direct pointers to functional aspects of the TF-TG interactions. Our compiled resource encompassing ExTRI together with publicly available resources delivers literature-derived TF-TG interactions for more than 900 of the 1500-1600 proteins considered to function as specific DNA binding TFs. The obtained result can be used by curators, for network analysis and modelling, for causal reasoning or knowledge graph mining approaches, or serve to benchmark text mining strategies.
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Affiliation(s)
| | | | | | - Martin Kuiper
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Alfonso Valencia
- Barcelona Supercomputing Center, Barcelona, Spain; ICREA, Barcelona, Spain
| | - Astrid Laegreid
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim 7491, Norway
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20
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Santos-Terra J, Deckmann I, Fontes-Dutra M, Schwingel GB, Bambini-Junior V, Gottfried C. Transcription factors in neurodevelopmental and associated psychiatric disorders: A potential convergence for genetic and environmental risk factors. Int J Dev Neurosci 2021; 81:545-578. [PMID: 34240460 DOI: 10.1002/jdn.10141] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 06/23/2021] [Accepted: 07/02/2021] [Indexed: 12/16/2022] Open
Abstract
Neurodevelopmental disorders (NDDs) are a heterogeneous and highly prevalent group of psychiatric conditions marked by impairments in the nervous system. Their onset occurs during gestation, and the alterations are observed throughout the postnatal life. Although many genetic and environmental risk factors have been described in this context, the interactions between them challenge the understanding of the pathways associated with NDDs. Transcription factors (TFs)-a group of over 1,600 proteins that can interact with DNA, regulating gene expression through modulation of RNA synthesis-represent a point of convergence for different risk factors. In addition, TFs organize critical processes like angiogenesis, blood-brain barrier formation, myelination, neuronal migration, immune activation, and many others in a time and location-dependent way. In this review, we summarize important TF alterations in NDD and associated disorders, along with specific impairments observed in animal models, and, finally, establish hypotheses to explain how these proteins may be critical mediators in the context of genome-environment interactions.
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Affiliation(s)
- Júlio Santos-Terra
- Translational Research Group in Autism Spectrum Disorders (GETTEA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.,School of Pharmacology and Biomedical Sciences, University of Central Lancashire, Autism Wellbeing And Research Development (AWARD) Institute, BR-UK-CA, Preston, UK
| | - Iohanna Deckmann
- Translational Research Group in Autism Spectrum Disorders (GETTEA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.,School of Pharmacology and Biomedical Sciences, University of Central Lancashire, Autism Wellbeing And Research Development (AWARD) Institute, BR-UK-CA, Preston, UK
| | - Mellanie Fontes-Dutra
- Translational Research Group in Autism Spectrum Disorders (GETTEA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.,School of Pharmacology and Biomedical Sciences, University of Central Lancashire, Autism Wellbeing And Research Development (AWARD) Institute, BR-UK-CA, Preston, UK
| | - Gustavo Brum Schwingel
- Translational Research Group in Autism Spectrum Disorders (GETTEA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.,School of Pharmacology and Biomedical Sciences, University of Central Lancashire, Autism Wellbeing And Research Development (AWARD) Institute, BR-UK-CA, Preston, UK
| | - Victorio Bambini-Junior
- Translational Research Group in Autism Spectrum Disorders (GETTEA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.,School of Pharmacology and Biomedical Sciences, University of Central Lancashire, Autism Wellbeing And Research Development (AWARD) Institute, BR-UK-CA, Preston, UK.,School of Pharmacology and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Carmem Gottfried
- Translational Research Group in Autism Spectrum Disorders (GETTEA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.,School of Pharmacology and Biomedical Sciences, University of Central Lancashire, Autism Wellbeing And Research Development (AWARD) Institute, BR-UK-CA, Preston, UK
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21
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Kagawa W, Kurumizaka H. Structural basis for DNA sequence recognition by pioneer factors in nucleosomes. Curr Opin Struct Biol 2021; 71:59-64. [PMID: 34218163 DOI: 10.1016/j.sbi.2021.05.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 05/12/2021] [Indexed: 12/20/2022]
Abstract
Most of the genomic DNA in eukaryotes is bound to histone complexes, which hinders transcription factors from accessing their target DNA sequences. Here, we discuss recent structural insights into the mechanisms by which pioneer factors, an emerging class of transcription factors, can recognize DNA motifs located on the nucleosome surface.
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Affiliation(s)
- Wataru Kagawa
- Department of Chemistry, Graduate School of Science and Engineering, Meisei University, 2-1-1 Hodokubo, Hino-shi, Tokyo, 191-8506, Japan
| | - Hitoshi Kurumizaka
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan.
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22
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Chiou J, Geusz RJ, Okino ML, Han JY, Miller M, Melton R, Beebe E, Benaglio P, Huang S, Korgaonkar K, Heller S, Kleger A, Preissl S, Gorkin DU, Sander M, Gaulton KJ. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature 2021; 594:398-402. [PMID: 34012112 PMCID: PMC10560508 DOI: 10.1038/s41586-021-03552-w] [Citation(s) in RCA: 152] [Impact Index Per Article: 50.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Accepted: 04/14/2021] [Indexed: 02/04/2023]
Abstract
Genetic risk variants that have been identified in genome-wide association studies of complex diseases are primarily non-coding1. Translating these risk variants into mechanistic insights requires detailed maps of gene regulation in disease-relevant cell types2. Here we combined two approaches: a genome-wide association study of type 1 diabetes (T1D) using 520,580 samples, and the identification of candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cells using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) of 131,554 nuclei. Risk variants for T1D were enriched in cCREs that were active in T cells and other cell types, including acinar and ductal cells of the exocrine pancreas. Risk variants at multiple T1D signals overlapped with exocrine-specific cCREs that were linked to genes with exocrine-specific expression. At the CFTR locus, the T1D risk variant rs7795896 mapped to a ductal-specific cCRE that regulated CFTR; the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in the pathogenesis of T1D and highlight the power of large-scale genome-wide association studies and single-cell epigenomics for understanding the cellular origins of complex disease.
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Affiliation(s)
- Joshua Chiou
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA.
- Internal Medicine Research Unit, Pfizer Worldwide Research, Cambridge, MA, USA.
| | - Ryan J Geusz
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Mei-Lin Okino
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Jee Yun Han
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Michael Miller
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Rebecca Melton
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Elisha Beebe
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Paola Benaglio
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Serina Huang
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Katha Korgaonkar
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Sandra Heller
- Department of Internal Medicine I, Ulm University, Ulm, Germany
| | | | - Sebastian Preissl
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - David U Gorkin
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Biology, Emory University, Atlanta, GA, USA
| | - Maike Sander
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kyle J Gaulton
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
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23
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Ge W, Meier M, Roth C, Söding J. Bayesian Markov models improve the prediction of binding motifs beyond first order. NAR Genom Bioinform 2021; 3:lqab026. [PMID: 33928244 PMCID: PMC8057495 DOI: 10.1093/nargab/lqab026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 03/11/2021] [Accepted: 03/30/2021] [Indexed: 12/13/2022] Open
Abstract
Transcription factors (TFs) regulate gene expression by binding to specific DNA motifs. Accurate models for predicting binding affinities are crucial for quantitatively understanding of transcriptional regulation. Motifs are commonly described by position weight matrices, which assume that each position contributes independently to the binding energy. Models that can learn dependencies between positions, for instance, induced by DNA structure preferences, have yielded markedly improved predictions for most TFs on in vivo data. However, they are more prone to overfit the data and to learn patterns merely correlated with rather than directly involved in TF binding. We present an improved, faster version of our Bayesian Markov model software, BaMMmotif2. We tested it with state-of-the-art motif discovery tools on a large collection of ChIP-seq and HT-SELEX datasets. BaMMmotif2 models of fifth-order achieved a median false-discovery-rate-averaged recall 13.6% and 12.2% higher than the next best tool on 427 ChIP-seq datasets and 164 HT-SELEX datasets, respectively, while being 8 to 1000 times faster. BaMMmotif2 models showed no signs of overtraining in cross-cell line and cross-platform tests, with similar improvements on the next-best tool. These results demonstrate that dependencies beyond first order clearly improve binding models for most TFs.
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Affiliation(s)
- Wanwan Ge
- Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany
| | - Markus Meier
- Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany
| | - Christian Roth
- Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany
| | - Johannes Söding
- Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany
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24
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Jovanovic VM, Sarfert M, Reyna-Blanco CS, Indrischek H, Valdivia DI, Shelest E, Nowick K. Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution. Front Genet 2021; 12:662239. [PMID: 34079582 PMCID: PMC8166252 DOI: 10.3389/fgene.2021.662239] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 04/19/2021] [Indexed: 01/09/2023] Open
Abstract
Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.
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Affiliation(s)
- Vladimir M Jovanovic
- Human Biology and Primate Evolution, Freie Universität Berlin, Berlin, Germany.,Bioinformatics Solution Center, Freie Universität Berlin, Berlin, Germany
| | - Melanie Sarfert
- Human Biology and Primate Evolution, Freie Universität Berlin, Berlin, Germany
| | - Carlos S Reyna-Blanco
- Department of Biology, University of Fribourg, Fribourg, Switzerland.,Swiss Institute of Bioinformatics, Fribourg, Switzerland
| | - Henrike Indrischek
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.,Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.,Center for Systems Biology Dresden, Dresden, Germany
| | - Dulce I Valdivia
- Evolutionary Genomics Laboratory and Genome Topology and Regulation Laboratory, Genetic Engineering Department, Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-Irapuato), Irapuato, Mexico
| | - Ekaterina Shelest
- Centre for Enzyme Innovation, University of Portsmouth, Portsmouth, United Kingdom
| | - Katja Nowick
- Human Biology and Primate Evolution, Freie Universität Berlin, Berlin, Germany
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25
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Single-cell chromatin accessibility identifies pancreatic islet cell type- and state-specific regulatory programs of diabetes risk. Nat Genet 2021; 53:455-466. [PMID: 33795864 PMCID: PMC9037575 DOI: 10.1038/s41588-021-00823-0] [Citation(s) in RCA: 80] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 02/18/2021] [Indexed: 02/06/2023]
Abstract
Single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq) creates new opportunities to dissect cell type-specific mechanisms of complex diseases. Since pancreatic islets are central to type 2 diabetes (T2D), we profiled 15,298 islet cells by using combinatorial barcoding snATAC-seq and identified 12 clusters, including multiple alpha, beta and delta cell states. We cataloged 228,873 accessible chromatin sites and identified transcription factors underlying lineage- and state-specific regulation. We observed state-specific enrichment of fasting glucose and T2D genome-wide association studies for beta cells and enrichment for other endocrine cell types. At T2D signals localized to islet-accessible chromatin, we prioritized variants with predicted regulatory function and co-accessibility with target genes. A causal T2D variant rs231361 at the KCNQ1 locus had predicted effects on a beta cell enhancer co-accessible with INS and genome editing in embryonic stem cell-derived beta cells affected INS levels. Together our findings demonstrate the power of single-cell epigenomics for interpreting complex disease genetics.
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26
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Cevallos RR, Edwards YJK, Parant JM, Yoder BK, Hu K. Human transcription factors responsive to initial reprogramming predominantly undergo legitimate reprogramming during fibroblast conversion to iPSCs. Sci Rep 2020; 10:19710. [PMID: 33184372 PMCID: PMC7661723 DOI: 10.1038/s41598-020-76705-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 10/19/2020] [Indexed: 12/14/2022] Open
Abstract
The four transcription factors OCT4, SOX2, KLF4, and MYC (OSKM) together can convert human fibroblasts to induced pluripotent stem cells (iPSCs). It is, however, perplexing that they can do so only for a rare population of the starting cells with a long latency. Transcription factors (TFs) define identities of both the starting fibroblasts and the end product, iPSCs, and are also of paramount importance for the reprogramming process. It is critical to upregulate or activate the iPSC-enriched TFs while downregulate or silence the fibroblast-enriched TFs. This report explores the initial TF responses to OSKM as the molecular underpinnings for both the potency aspects and the limitation sides of the OSKM reprogramming. The authors first defined the TF reprogramome, i.e., the full complement of TFs to be reprogrammed. Most TFs were resistant to OSKM reprogramming at the initial stages, an observation consistent with the inefficiency and long latency of iPSC reprogramming. Surprisingly, the current analyses also revealed that most of the TFs (at least 83 genes) that did respond to OSKM induction underwent legitimate reprogramming. The initial legitimate transcriptional responses of TFs to OSKM reprogramming were also observed in the reprogramming fibroblasts from a different individual. Such early biased legitimate reprogramming of the responsive TFs aligns well with the robustness aspect of the otherwise inefficient and stochastic OSKM reprogramming.
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Affiliation(s)
- Ricardo R Cevallos
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Yvonne J K Edwards
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
- Department of Cell Developmental and Integrative Biology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - John M Parant
- Department of Pharmacology and Toxicology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Bradley K Yoder
- Department of Cell Developmental and Integrative Biology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Kejin Hu
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
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27
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Oo JA, Irmer B, Günther S, Warwick T, Pálfi K, Izquierdo Ponce J, Teichmann T, Pflüger-Müller B, Gilsbach R, Brandes RP, Leisegang MS. ZNF354C is a transcriptional repressor that inhibits endothelial angiogenic sprouting. Sci Rep 2020; 10:19079. [PMID: 33154469 PMCID: PMC7645770 DOI: 10.1038/s41598-020-76193-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 10/26/2020] [Indexed: 11/19/2022] Open
Abstract
Zinc finger proteins (ZNF) are a large group of transcription factors with diverse functions. We recently discovered that endothelial cells harbour a specific mechanism to limit the action of ZNF354C, whose function in endothelial cells is unknown. Given that ZNF354C has so far only been studied in bone and tumour, its function was determined in endothelial cells. ZNF354C is expressed in vascular cells and localises to the nucleus and cytoplasm. Overexpression of ZNF354C in human endothelial cells results in a marked inhibition of endothelial sprouting. RNA-sequencing of human microvascular endothelial cells with and without overexpression of ZNF354C revealed that the protein is a potent transcriptional repressor. ZNF354C contains an active KRAB domain which mediates this suppression as shown by mutagenesis analysis. ZNF354C interacts with dsDNA, TRIM28 and histones, as observed by proximity ligation and immunoprecipitation. Moreover, chromatin immunoprecipitation revealed that the ZNF binds to specific endothelial-relevant target-gene promoters. ZNF354C suppresses these genes as shown by CRISPR/Cas knockout and RNAi. Inhibition of endothelial sprouting by ZNF354C is dependent on the amino acids DV and MLE of the KRAB domain. These results demonstrate that ZNF354C is a repressive transcription factor which acts through a KRAB domain to inhibit endothelial angiogenic sprouting.
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Affiliation(s)
- James A Oo
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.,German Center of Cardiovascular Research (DZHK), Partner site RheinMain, Frankfurt, Germany
| | - Barnabas Irmer
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Stefan Günther
- Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Timothy Warwick
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Katalin Pálfi
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Judit Izquierdo Ponce
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Tom Teichmann
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Beatrice Pflüger-Müller
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.,German Center of Cardiovascular Research (DZHK), Partner site RheinMain, Frankfurt, Germany
| | - Ralf Gilsbach
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.,German Center of Cardiovascular Research (DZHK), Partner site RheinMain, Frankfurt, Germany
| | - Ralf P Brandes
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.,German Center of Cardiovascular Research (DZHK), Partner site RheinMain, Frankfurt, Germany
| | - Matthias S Leisegang
- Institute for Cardiovascular Physiology, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany. .,German Center of Cardiovascular Research (DZHK), Partner site RheinMain, Frankfurt, Germany.
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28
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Price RM, Budzyński MA, Kundra S, Teves SS. Advances in visualizing transcription factor - DNA interactions. Genome 2020; 64:449-466. [PMID: 33113335 DOI: 10.1139/gen-2020-0086] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
At the heart of the transcription process is the specific interaction between transcription factors (TFs) and their target DNA sequences. Decades of molecular biology research have led to unprecedented insights into how TFs access the genome to regulate transcription. In the last 20 years, advances in microscopy have enabled scientists to add imaging as a powerful tool in probing two specific aspects of TF-DNA interactions: structure and dynamics. In this review, we examine how applications of diverse imaging technologies can provide structural and dynamic information that complements insights gained from molecular biology assays. As a case study, we discuss how applications of advanced imaging techniques have reshaped our understanding of TF behavior across the cell cycle, leading to a rethinking in the field of mitotic bookmarking.
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Affiliation(s)
- Rachel M Price
- Department of Biochemistry and Molecular Biology, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada.,Department of Biochemistry and Molecular Biology, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
| | - Marek A Budzyński
- Department of Biochemistry and Molecular Biology, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada.,Department of Biochemistry and Molecular Biology, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
| | - Shivani Kundra
- Department of Biochemistry and Molecular Biology, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada.,Department of Biochemistry and Molecular Biology, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
| | - Sheila S Teves
- Department of Biochemistry and Molecular Biology, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada.,Department of Biochemistry and Molecular Biology, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
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29
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Funk CC, Casella AM, Jung S, Richards MA, Rodriguez A, Shannon P, Donovan-Maiye R, Heavner B, Chard K, Xiao Y, Glusman G, Ertekin-Taner N, Golde TE, Toga A, Hood L, Van Horn JD, Kesselman C, Foster I, Madduri R, Price ND, Ament SA. Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types. Cell Rep 2020; 32:108029. [PMID: 32814038 PMCID: PMC7462736 DOI: 10.1016/j.celrep.2020.108029] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 05/07/2020] [Accepted: 07/22/2020] [Indexed: 12/27/2022] Open
Abstract
Characterizing the tissue-specific binding sites of transcription factors (TFs) is essential to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting enables the prediction of genome-wide binding sites for hundreds of TFs simultaneously. Despite the public availability of high-quality DNase-seq data from hundreds of samples, a comprehensive, up-to-date resource for the locations of genomic footprints is lacking. Here, we develop a scalable footprinting workflow using two state-of-the-art algorithms: Wellington and HINT. We apply our workflow to detect footprints in 192 ENCODE DNase-seq experiments and predict the genomic occupancy of 1,515 human TFs in 27 human tissues. We validate that these footprints overlap true-positive TF binding sites from ChIP-seq. We demonstrate that the locations, depth, and tissue specificity of footprints predict effects of genetic variants on gene expression and capture a substantial proportion of genetic risk for complex traits.
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Affiliation(s)
- Cory C Funk
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Alex M Casella
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Medical Scientist Training Program, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Segun Jung
- Globus, University of Chicago, Chicago, IL 60637, USA
| | | | | | - Paul Shannon
- Institute for Systems Biology, Seattle, WA 98109, USA
| | | | - Ben Heavner
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Kyle Chard
- Globus, University of Chicago, Chicago, IL 60637, USA
| | - Yukai Xiao
- Globus, University of Chicago, Chicago, IL 60637, USA
| | | | | | - Todd E Golde
- Mayo Clinic, Department of Neuroscience, Jacksonville, FL 32224, USA
| | - Arthur Toga
- Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Leroy Hood
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - John D Van Horn
- Department of Psychology, University of Southern California, Los Angeles, CA 90007, USA
| | - Carl Kesselman
- Information Sciences Institute, University of Southern California, Los Angeles, CA 90292, USA
| | - Ian Foster
- Globus, University of Chicago, Chicago, IL 60637, USA; Data Science and Learning Division, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Ravi Madduri
- Globus, University of Chicago, Chicago, IL 60637, USA; Data Science and Learning Division, Argonne National Laboratory, Argonne, IL 60439, USA.
| | | | - Seth A Ament
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
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30
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Mola S, Foisy S, Boucher G, Major F, Beauchamp C, Karaky M, Goyette P, Lesage S, Rioux JD. A transcriptome-based approach to identify functional modules within and across primary human immune cells. PLoS One 2020; 15:e0233543. [PMID: 32469933 PMCID: PMC7259617 DOI: 10.1371/journal.pone.0233543] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 05/07/2020] [Indexed: 11/20/2022] Open
Abstract
Genome-wide transcriptomic analyses have provided valuable insight into fundamental biology and disease pathophysiology. Many studies have taken advantage of the correlation in the expression patterns of the transcriptome to infer a potential biologic function of uncharacterized genes, and multiple groups have examined the relationship between co-expression, co-regulation, and gene function on a broader scale. Given the unique characteristics of immune cells circulating in the blood, we were interested in determining whether it was possible to identify functional co-expression modules in human immune cells. Specifically, we sequenced the transcriptome of nine immune cell types from peripheral blood cells of healthy donors and, using a combination of global and targeted analyses of genes within co-expression modules, we were able to determine functions for these modules that were cell lineage-specific or shared among multiple cell lineages. In addition, our analyses identified transcription factors likely important for immune cell lineage commitment and/or maintenance.
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Affiliation(s)
- Saraï Mola
- Centre de recherche, Institut de cardiologie de Montréal, Montréal, Québec, Canada
| | - Sylvain Foisy
- Centre de recherche, Institut de cardiologie de Montréal, Montréal, Québec, Canada
| | - Gabrielle Boucher
- Centre de recherche, Institut de cardiologie de Montréal, Montréal, Québec, Canada
| | - François Major
- Unité de recherche en ingénierie des ARN, Institut de recherche en immunologie et en cancérologie, Montréal, Québec, Canada
- Département d’informatique et de recherche opérationnelle, Université de Montréal, Montréal, Québec, Canada
- Département de biochimie et médecine moléculaire, Université de Montréal, Montréal, Québec, Canada
| | - Claudine Beauchamp
- Centre de recherche, Institut de cardiologie de Montréal, Montréal, Québec, Canada
| | - Mohamad Karaky
- Centre de recherche, Institut de cardiologie de Montréal, Montréal, Québec, Canada
| | - Philippe Goyette
- Centre de recherche, Institut de cardiologie de Montréal, Montréal, Québec, Canada
| | - Sylvie Lesage
- Centre de recherche, Hôpital Maisonneuve-Rosemont, Montréal, Québec, Canada
- Département de microbiologie, infectiologie et immunologie, Université de Montréal, Montréal, Québec, Canada
| | - John D. Rioux
- Centre de recherche, Institut de cardiologie de Montréal, Montréal, Québec, Canada
- Département de biochimie et médecine moléculaire, Université de Montréal, Montréal, Québec, Canada
- * E-mail:
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31
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Qian FC, Li XC, Guo JC, Zhao JM, Li YY, Tang ZD, Zhou LW, Zhang J, Bai XF, Jiang Y, Pan Q, Wang QY, Li EM, Li CQ, Xu LY, Lin DC. SEanalysis: a web tool for super-enhancer associated regulatory analysis. Nucleic Acids Res 2020; 47:W248-W255. [PMID: 31028388 PMCID: PMC6602466 DOI: 10.1093/nar/gkz302] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 04/04/2019] [Accepted: 04/18/2019] [Indexed: 01/07/2023] Open
Abstract
Super-enhancers (SEs) have prominent roles in biological and pathological processes through their unique transcriptional regulatory capability. To date, several SE databases have been developed by us and others. However, these existing databases do not provide downstream or upstream regulatory analyses of SEs. Pathways, transcription factors (TFs), SEs, and SE-associated genes form complex regulatory networks. Therefore, we designed a novel web server, SEanalysis, which provides comprehensive SE-associated regulatory network analyses. SEanalysis characterizes SE-associated genes, TFs binding to target SEs, and their upstream pathways. The current version of SEanalysis contains more than 330 000 SEs from more than 540 types of cells/tissues, 5042 TF ChIP-seq data generated from these cells/tissues, DNA-binding sequence motifs for ∼700 human TFs and 2880 pathways from 10 databases. SEanalysis supports searching by either SEs, samples, TFs, pathways or genes. The complex regulatory networks formed by these factors can be interactively visualized. In addition, we developed a customizable genome browser containing >6000 customizable tracks for visualization. The server is freely available at http://licpathway.net/SEanalysis.
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Affiliation(s)
- Feng-Cui Qian
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Xue-Cang Li
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Jin-Cheng Guo
- Institute of Oncologic Pathology, Medical College of Shantou University, Shantou 515041, China
| | - Jian-Mei Zhao
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Yan-Yu Li
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Zhi-Dong Tang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Li-Wei Zhou
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Jian Zhang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Xue-Feng Bai
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Yong Jiang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Qi Pan
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Qiu-Yu Wang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China.,Institute of Oncologic Pathology, Medical College of Shantou University, Shantou 515041, China
| | - En-Min Li
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Chun-Quan Li
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Li-Yan Xu
- Institute of Oncologic Pathology, Medical College of Shantou University, Shantou 515041, China
| | - De-Chen Lin
- Guangdong Province Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
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32
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Gambini A, Stein P, Savy V, Grow EJ, Papas BN, Zhang Y, Kenan AC, Padilla-Banks E, Cairns BR, Williams CJ. Developmentally Programmed Tankyrase Activity Upregulates β-Catenin and Licenses Progression of Embryonic Genome Activation. Dev Cell 2020; 53:545-560.e7. [PMID: 32442396 DOI: 10.1016/j.devcel.2020.04.018] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Revised: 03/16/2020] [Accepted: 04/27/2020] [Indexed: 12/14/2022]
Abstract
Embryonic genome activation (EGA) is orchestrated by an intrinsic developmental program initiated during oocyte maturation with translation of stored maternal mRNAs. Here, we show that tankyrase, a poly(ADP-ribosyl) polymerase that regulates β-catenin levels, undergoes programmed translation during oocyte maturation and serves an essential role in mouse EGA. Newly translated TNKS triggers proteasomal degradation of axin, reducing targeted destruction of β-catenin and promoting β-catenin-mediated transcription of target genes, including Myc. MYC mediates ribosomal RNA transcription in 2-cell embryos, supporting global protein synthesis. Suppression of tankyrase activity using knockdown or chemical inhibition causes loss of nuclear β-catenin and global reductions in transcription and histone H3 acetylation. Chromatin and transcriptional profiling indicate that development arrests prior to the mid-2-cell stage, mediated in part by reductions in β-catenin and MYC. These findings indicate that post-transcriptional regulation of tankyrase serves as a ligand-independent developmental mechanism for post-translational β-catenin activation and is required to complete EGA.
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Affiliation(s)
- Andrés Gambini
- Reproductive and Developmental Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Paula Stein
- Reproductive and Developmental Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Virginia Savy
- Reproductive and Developmental Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Edward J Grow
- Department of Oncological Sciences, Huntsman Cancer Institute and Howard Hughes Medical Institute, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Brian N Papas
- Integrative Bioinformatics, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Yingpei Zhang
- Reproductive and Developmental Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Anna C Kenan
- Reproductive and Developmental Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Elizabeth Padilla-Banks
- Reproductive and Developmental Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Bradley R Cairns
- Department of Oncological Sciences, Huntsman Cancer Institute and Howard Hughes Medical Institute, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Carmen J Williams
- Reproductive and Developmental Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA.
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33
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Daou R, Beißbarth T, Wingender E, Gültas M, Haubrock M. Constructing temporal regulatory cascades in the context of development and cell differentiation. PLoS One 2020; 15:e0231326. [PMID: 32275727 PMCID: PMC7147753 DOI: 10.1371/journal.pone.0231326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 03/20/2020] [Indexed: 12/02/2022] Open
Abstract
Cell differentiation is a complex process orchestrated by sets of regulators precisely appearing at certain time points, resulting in regulatory cascades that affect the expression of broader sets of genes, ending up in the formation of different tissues and organ parts. The identification of stage-specific master regulators and the mechanism by which they activate each other is a key to understanding and controlling differentiation, particularly in the fields of tissue regeneration and organoid engineering. Here we present a workflow that combines a comprehensive general regulatory network based on binding site predictions with user-provided temporal gene expression data, to generate a a temporally connected series of stage-specific regulatory networks, which we call a temporal regulatory cascade (TRC). A TRC identifies those regulators that are unique for each time point, resulting in a cascade that shows the emergence of these regulators and regulatory interactions across time. The model was implemented in the form of a user-friendly, visual web-tool, that requires no expert knowledge in programming or statistics, making it directly usable for life scientists. In addition to generating TRCs the tool links multiple interactive visual workflows, in which a user can track and investigate further different regulators, target genes, and interactions, directing the tool along the way into biologically sensible results based on the given dataset. We applied the TRC model on two different expression datasets, one based on experiments conducted on human induced pluripotent stem cells (hiPSCs) undergoing differentiation into mature cardiomyocytes and the other based on the differentiation of H1-derived human neuronal precursor cells. The model was successful in identifying previously known and new potential key regulators, in addition to the particular time points with which these regulators are associated, in cardiac and neural development.
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Affiliation(s)
- Rayan Daou
- Department of Medical Bioinformatics, University Medical Center Göttingen, Goettingen, Niedersachsen, Germany
| | - Tim Beißbarth
- Department of Medical Bioinformatics, University Medical Center Göttingen, Goettingen, Niedersachsen, Germany
| | - Edgar Wingender
- Department of Medical Bioinformatics, University Medical Center Göttingen, Goettingen, Niedersachsen, Germany
| | - Mehmet Gültas
- Breeding Informatics Group, Department of Animal Science, Georg-August University, Goettingen, Niedersachsen, Germany
- Center for Integrated Breeding Research (CiBreed), Georg-August University, Goettingen, Niedersachsen, Germany
| | - Martin Haubrock
- Department of Medical Bioinformatics, University Medical Center Göttingen, Goettingen, Niedersachsen, Germany
- * E-mail:
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34
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Li Y, Li X, Yang Y, Li M, Qian F, Tang Z, Zhao J, Zhang J, Bai X, Jiang Y, Zhou J, Zhang Y, Zhou L, Xie J, Li E, Wang Q, Li C. TRlnc: a comprehensive database for human transcriptional regulatory information of lncRNAs. Brief Bioinform 2020; 22:1929-1939. [PMID: 32047897 DOI: 10.1093/bib/bbaa011] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 01/09/2020] [Indexed: 12/20/2022] Open
Abstract
Long noncoding RNAs (lncRNAs) have been proven to play important roles in transcriptional processes and biological functions. With the increasing study of human diseases and biological processes, information in human H3K27ac ChIP-seq, ATAC-seq and DNase-seq datasets is accumulating rapidly, resulting in an urgent need to collect and process data to identify transcriptional regulatory regions of lncRNAs. We therefore developed a comprehensive database for human regulatory information of lncRNAs (TRlnc, http://bio.licpathway.net/TRlnc), which aimed to collect available resources of transcriptional regulatory regions of lncRNAs and to annotate and illustrate their potential roles in the regulation of lncRNAs in a cell type-specific manner. The current version of TRlnc contains 8 683 028 typical enhancers/super-enhancers and 32 348 244 chromatin accessibility regions associated with 91 906 human lncRNAs. These regions are identified from over 900 human H3K27ac ChIP-seq, ATAC-seq and DNase-seq samples. Furthermore, TRlnc provides the detailed genetic and epigenetic annotation information within transcriptional regulatory regions (promoter, enhancer/super-enhancer and chromatin accessibility regions) of lncRNAs, including common SNPs, risk SNPs, eQTLs, linkage disequilibrium SNPs, transcription factors, methylation sites, histone modifications and 3D chromatin interactions. It is anticipated that the use of TRlnc will help users to gain in-depth and useful insights into the transcriptional regulatory mechanisms of lncRNAs.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Chunquan Li
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
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35
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Wei J, Man Q, Ding C, Hu Y, Liu M, Li H, Guo F, Zhang Y, Li D, Song L, Yang H, Tang S. Proteomic Investigations of Transcription Factors Critical in Geniposide-Mediated Suppression of Alcoholic Steatosis and in Overdose-Induced Hepatotoxicity on Liver in Rats. J Proteome Res 2019; 18:3821-3830. [DOI: 10.1021/acs.jproteome.9b00140] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Junying Wei
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Qiong Man
- Gansu University of Chinese Medicine, Lanzhou 730000, China
| | - Chen Ding
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institute of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Yanzhen Hu
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Mingwei Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China
| | - Hui Li
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Feifei Guo
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Yi Zhang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Defeng Li
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Lei Song
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China
| | - Hongjun Yang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Shihuan Tang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
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36
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Khan A, Fornes O, Stigliani A, Gheorghe M, Castro-Mondragon JA, van der Lee R, Bessy A, Chèneby J, Kulkarni SR, Tan G, Baranasic D, Arenillas DJ, Sandelin A, Vandepoele K, Lenhard B, Ballester B, Wasserman WW, Parcy F, Mathelier A. JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework. Nucleic Acids Res 2019; 46:D260-D266. [PMID: 29140473 PMCID: PMC5753243 DOI: 10.1093/nar/gkx1126] [Citation(s) in RCA: 859] [Impact Index Per Article: 171.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Accepted: 10/27/2017] [Indexed: 12/31/2022] Open
Abstract
JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six taxonomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition, we have introduced 316 TFFMs (95 for vertebrates, 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally, this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the underlying data can be retrieved programmatically using a RESTful API and through the JASPAR 2018 R/Bioconductor package.
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Affiliation(s)
- Aziz Khan
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Oriol Fornes
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children's Hospital Research Institute, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z 4H4, Canada
| | - Arnaud Stigliani
- University of Grenoble Alpes, CNRS, CEA, INRA, BIG-LPCV, 38000 Grenoble, France
| | - Marius Gheorghe
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Jaime A Castro-Mondragon
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Robin van der Lee
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children's Hospital Research Institute, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z 4H4, Canada
| | - Adrien Bessy
- University of Grenoble Alpes, CNRS, CEA, INRA, BIG-LPCV, 38000 Grenoble, France
| | - Jeanne Chèneby
- INSERM, UMR1090 TAGC, Marseille, F-13288, France.,Aix-Marseille Université, UMR1090 TAGC, Marseille, F-13288, France
| | - Shubhada R Kulkarni
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Technologiepark 927, 9052 Ghent, Belgium.,VIB Center for Plant Systems Biology, Technologiepark 927, 9052 Ghent, Belgium.,Bioinformatics Institute Ghent, Ghent University, Technologiepark 927, 9052 Ghent, Belgium
| | - Ge Tan
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK.,Computational Regulatory Genomics, MRC London Institute of Medical Sciences, London W12 0NN, UK
| | - Damir Baranasic
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK.,Computational Regulatory Genomics, MRC London Institute of Medical Sciences, London W12 0NN, UK
| | - David J Arenillas
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children's Hospital Research Institute, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z 4H4, Canada
| | - Albin Sandelin
- The Bioinformatics Centre, Department of Biology and Biotech Research & Innovation Centre, University of Copenhagen, DK2200 Copenhagen N, Denmark
| | - Klaas Vandepoele
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Technologiepark 927, 9052 Ghent, Belgium.,VIB Center for Plant Systems Biology, Technologiepark 927, 9052 Ghent, Belgium.,Bioinformatics Institute Ghent, Ghent University, Technologiepark 927, 9052 Ghent, Belgium
| | - Boris Lenhard
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK.,Computational Regulatory Genomics, MRC London Institute of Medical Sciences, London W12 0NN, UK.,Sars International Centre for Marine Molecular Biology, University of Bergen, N-5008 Bergen, Norway
| | - Benoît Ballester
- INSERM, UMR1090 TAGC, Marseille, F-13288, France.,Aix-Marseille Université, UMR1090 TAGC, Marseille, F-13288, France
| | - Wyeth W Wasserman
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children's Hospital Research Institute, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z 4H4, Canada
| | - François Parcy
- University of Grenoble Alpes, CNRS, CEA, INRA, BIG-LPCV, 38000 Grenoble, France
| | - Anthony Mathelier
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway.,Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
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37
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Kulakovskiy IV, Vorontsov IE, Yevshin IS, Sharipov RN, Fedorova AD, Rumynskiy EI, Medvedeva YA, Magana-Mora A, Bajic VB, Papatsenko DA, Kolpakov FA, Makeev VJ. HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis. Nucleic Acids Res 2019; 46:D252-D259. [PMID: 29140464 PMCID: PMC5753240 DOI: 10.1093/nar/gkx1106] [Citation(s) in RCA: 489] [Impact Index Per Article: 97.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Accepted: 10/31/2017] [Indexed: 12/15/2022] Open
Abstract
We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.
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Affiliation(s)
- Ivan V Kulakovskiy
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991, GSP-1, Vavilova 32, Moscow, Russia.,Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991, GSP-1, Gubkina 3, Moscow, Russia.,Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, 143026 Moscow, Russia
| | - Ilya E Vorontsov
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991, GSP-1, Gubkina 3, Moscow, Russia
| | - Ivan S Yevshin
- BIOSOFT.RU Ltd, 630058, Russkaya 41/1, Novosibirsk, Russia
| | - Ruslan N Sharipov
- BIOSOFT.RU Ltd, 630058, Russkaya 41/1, Novosibirsk, Russia.,Institute of Computational Technologies, Siberian Branch of the Russian Academy of Sciences, 630090, Akad. Rzhanova 6, Novosibirsk, Russia.,Novosibirsk State University, 630090, Pirogova 2, Novosibirsk, Russia
| | - Alla D Fedorova
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 119234, Leninskiye Gory 1-73, Moscow, Russia
| | - Eugene I Rumynskiy
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991, GSP-1, Gubkina 3, Moscow, Russia.,Moscow Institute of Physics and Technology (State University), 141700, 9 Institutskiy per, Dolgoprudny, Russia
| | - Yulia A Medvedeva
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991, GSP-1, Gubkina 3, Moscow, Russia.,Moscow Institute of Physics and Technology (State University), 141700, 9 Institutskiy per, Dolgoprudny, Russia.,Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, 119071, 2 Leninsky Ave. 33, Moscow, Russia
| | - Arturo Magana-Mora
- National Institute of Advanced Industrial Science and Technology (AIST), Com. Bio Big-Data Open Innovation Lab. (CBBD-OIL), AIST Tokyo Waterfront Main Bldg. #323, 2-3-26 Aomi, Tokyo 135-0064, Japan.,King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal 23955-6900, Saudi Arabia
| | - Vladimir B Bajic
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal 23955-6900, Saudi Arabia
| | - Dmitry A Papatsenko
- Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, 143026 Moscow, Russia
| | - Fedor A Kolpakov
- BIOSOFT.RU Ltd, 630058, Russkaya 41/1, Novosibirsk, Russia.,Institute of Computational Technologies, Siberian Branch of the Russian Academy of Sciences, 630090, Akad. Rzhanova 6, Novosibirsk, Russia
| | - Vsevolod J Makeev
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991, GSP-1, Vavilova 32, Moscow, Russia.,Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991, GSP-1, Gubkina 3, Moscow, Russia.,Moscow Institute of Physics and Technology (State University), 141700, 9 Institutskiy per, Dolgoprudny, Russia
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38
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Wingender E, Schoeps T, Haubrock M, Krull M, Dönitz J. TFClass: expanding the classification of human transcription factors to their mammalian orthologs. Nucleic Acids Res 2019; 46:D343-D347. [PMID: 29087517 PMCID: PMC5753292 DOI: 10.1093/nar/gkx987] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 10/12/2017] [Indexed: 02/03/2023] Open
Abstract
TFClass is a resource that classifies eukaryotic transcription factors (TFs) according to their DNA-binding domains (DBDs), available online at http://tfclass.bioinf.med.uni-goettingen.de. The classification scheme of TFClass was originally derived for human TFs and is expanded here to the whole taxonomic class of mammalia. Combining information from different resources, checking manually the retrieved mammalian TFs sequences and applying extensive phylogenetic analyses, >39 000 TFs from up to 41 mammalian species were assigned to the Superclasses, Classes, Families and Subfamilies of TFClass. As a result, TFClass now provides the corresponding sequence collection in FASTA format, sequence logos and phylogenetic trees at different classification levels, predicted TF binding sites for human, mouse, dog and cow genomes as well as links to several external databases. In particular, all those TFs that are also documented in the TRANSFAC® database (FACTOR table) have been linked and can be freely accessed. TRANSFAC® FACTOR can also be queried through an own search interface.
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Affiliation(s)
- Edgar Wingender
- Institute of Bioinformatics, University Medical Center Göttingen, Georg August University, D-37077 Göttingen, Germany.,geneXplain GmbH, D-38302 Wolfenbüttel, Germany
| | - Torsten Schoeps
- Institute of Bioinformatics, University Medical Center Göttingen, Georg August University, D-37077 Göttingen, Germany
| | - Martin Haubrock
- Institute of Bioinformatics, University Medical Center Göttingen, Georg August University, D-37077 Göttingen, Germany
| | | | - Jürgen Dönitz
- Institute of Bioinformatics, University Medical Center Göttingen, Georg August University, D-37077 Göttingen, Germany.,Dpt. of Evolutionary Developmental Genetics, Johann-Friedrich-Blumenbach Institute of Zoology and Anthropology, Georg August University, D-37077 Göttingen, Germany
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Perdomo-Sabogal Á, Nowick K. Genetic Variation in Human Gene Regulatory Factors Uncovers Regulatory Roles in Local Adaptation and Disease. Genome Biol Evol 2019; 11:2178-2193. [PMID: 31228201 PMCID: PMC6685493 DOI: 10.1093/gbe/evz131] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/18/2019] [Indexed: 01/13/2023] Open
Abstract
Differences in gene regulation have been suggested to play essential roles in the evolution of phenotypic changes. Although DNA changes in cis-regulatory elements affect only the regulation of its corresponding gene, variations in gene regulatory factors (trans) can have a broader effect, because the expression of many target genes might be affected. Aiming to better understand how natural selection may have shaped the diversity of gene regulatory factors in human, we assembled a catalog of all proteins involved in controlling gene expression. We found that at least five DNA-binding transcription factor classes are enriched among genes located in candidate regions for selection, suggesting that they might be relevant for understanding regulatory mechanisms involved in human local adaptation. The class of KRAB-ZNFs, zinc-finger (ZNF) genes with a Krüppel-associated box, stands out by first, having the most genes located on candidate regions for positive selection. Second, displaying most nonsynonymous single nucleotide polymorphisms (SNPs) with high genetic differentiation between populations within these regions. Third, having 27 KRAB-ZNF gene clusters with high extended haplotype homozygosity. Our further characterization of nonsynonymous SNPs in ZNF genes located within candidate regions for selection, suggests regulatory modifications that might influence the expression of target genes at population level. Our detailed investigation of three candidate regions revealed possible explanations for how SNPs may influence the prevalence of schizophrenia, eye development, and fertility in humans, among other phenotypes. The genetic variation we characterized here may be responsible for subtle to rough regulatory changes that could be important for understanding human adaptation.
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Affiliation(s)
- Álvaro Perdomo-Sabogal
- Human Biology Group, Department of Biology, Chemistry and Pharmacy, Institute for Zoology, Freie Universität Berlin, Germany
| | - Katja Nowick
- Human Biology Group, Department of Biology, Chemistry and Pharmacy, Institute for Zoology, Freie Universität Berlin, Germany
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40
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Fernandez Garcia M, Moore CD, Schulz KN, Alberto O, Donague G, Harrison MM, Zhu H, Zaret KS. Structural Features of Transcription Factors Associating with Nucleosome Binding. Mol Cell 2019; 75:921-932.e6. [PMID: 31303471 DOI: 10.1016/j.molcel.2019.06.009] [Citation(s) in RCA: 126] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 05/01/2019] [Accepted: 06/07/2019] [Indexed: 10/26/2022]
Abstract
Fate-changing transcription factors (TFs) scan chromatin to initiate new genetic programs during cell differentiation and reprogramming. Yet the protein structure domains that allow TFs to target nucleosomal DNA remain unexplored. We screened diverse TFs for binding to nucleosomes containing motif-enriched sequences targeted by pioneer factors in vivo. FOXA1, OCT4, ASCL1/E12α, PU1, CEBPα, and ZELDA display a range of nucleosome binding affinities that correlate with their cell reprogramming potential. We further screened 593 full-length human TFs on protein microarrays against different nucleosome sequences, followed by confirmation in solution, to distinguish among factors that bound nucleosomes, such as the neuronal AP-2α/β/γ, versus factors that only bound free DNA. Structural comparisons of DNA binding domains revealed that efficient nucleosome binders use short anchoring α helices to bind DNA, whereas weak nucleosome binders use unstructured regions and/or β sheets. Thus, specific modes of DNA interaction allow nucleosome scanning that confers pioneer activity to transcription factors.
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Affiliation(s)
- Meilin Fernandez Garcia
- Biochemistry and Molecular Biophysics Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104-5157, USA
| | - Cedric D Moore
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Katharine N Schulz
- Department of Biomolecular Chemistry, School of Medicine and Public Health, University of Wisconsin Madison, Madison, WI 53706, USA
| | - Oscar Alberto
- Institute for Regenerative Medicine, Department of Cell and Developmental Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104-5157, USA
| | - Greg Donague
- Institute for Regenerative Medicine, Department of Cell and Developmental Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104-5157, USA
| | - Melissa M Harrison
- Department of Biomolecular Chemistry, School of Medicine and Public Health, University of Wisconsin Madison, Madison, WI 53706, USA
| | - Heng Zhu
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Kenneth S Zaret
- Institute for Regenerative Medicine, Department of Cell and Developmental Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104-5157, USA.
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41
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Eggeling R. Disentangling transcription factor binding site complexity. Nucleic Acids Res 2019; 46:e121. [PMID: 30085218 PMCID: PMC6237759 DOI: 10.1093/nar/gky683] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 07/17/2018] [Indexed: 12/15/2022] Open
Abstract
The binding motifs of many transcription factors (TFs) comprise a higher degree of complexity than a single position weight matrix model permits. Additional complexity is typically taken into account either as intra-motif dependencies via more sophisticated probabilistic models or as heterogeneities via multiple weight matrices. However, both orthogonal approaches have limitations when learning from in vivo data where binding sites of other factors in close proximity can interfere with motif discovery for the protein of interest. In this work, we demonstrate how intra-motif complexity can, purely by analyzing the statistical properties of a given set of TF-binding sites, be distinguished from complexity arising from an intermix with motifs of co-binding TFs or other artifacts. In addition, we study the related question whether intra-motif complexity is represented more effectively by dependencies, heterogeneities or variants in between. Benchmarks demonstrate the effectiveness of both methods for their respective tasks and applications on motif discovery output from recent tools detect and correct many undesirable artifacts. These results further suggest that the prevalence of intra-motif dependencies may have been overestimated in previous studies on in vivo data and should thus be reassessed.
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Affiliation(s)
- Ralf Eggeling
- Department of Computer Science, University of Helsinki, Gustaf-Hällströmin katu 2b, FIN-00140 Helsinki, Finland
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42
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Huang J, Fang L, Wang S, Liu X, Chen Y, Chen Y, Tian H, Lin S, Tian S, Wei H, Gu X. Molecular cloning, expression profiling, and functional analysis of a broad-complex isoform 2/3 (Br-Z2/Z3) transcription factor in the diamondback moth, Plutella xylostella (L.). ARCHIVES OF INSECT BIOCHEMISTRY AND PHYSIOLOGY 2019; 101:e21549. [PMID: 30941822 DOI: 10.1002/arch.21549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 02/23/2019] [Accepted: 03/06/2019] [Indexed: 06/09/2023]
Abstract
The diamondback moth, Plutella xylostella (L.) (Lepidoptera: Plutellidae), is a widespread and destructive pest of cruciferous crops. New strategies for controlling it are needed because it is rapidly developing resistance to conventional pesticides. In insects, transcription factors (TFs) including broad-complex (Br-C) are thought to be useful for insecticide development because they are able to regulate the transcription of functional genes involved in responses to external stimuli including insecticides. In the present study, we cloned and sequenced the open reading frames (ORFs) of three BTB-ZF encoding genes from the diamondback moth deposited in the National Center for Biotechnology Information (NCBI) database under accessions MG753773, MG288674, and MG753772. The lengths of these ORFs were 1,680, 1,428, and 1,647 bp, respectively. The phylogenetic analysis based on the predicted amino acid sequences of ZF domains showed that MG753773 and MG288674 belonged to Z2/Z3 and Z7 of Br-C while MG753772 belonged to Ttk types. In the agreement, the highest expression level of MG753773 occurred during the prepupal stage, MG288674 and MG753772 were expressed during all stages and peaked in the adult and egg stages, respectively. RNA interference silencing of MG753773 in the late third instar larvae significantly decreased survival and pupation of the insects. With precocene II, transcription of MG753773 increased (4×) in the fourth instar larva 24 hr later; 48 hr later the rate of prepupation and pupation was significantly higher. These findings will contribute to the development of new regulators of the growth and development for diamondback moth control.
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Affiliation(s)
- Jingfei Huang
- College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China
| | - Ling Fang
- College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China
| | - Shuai Wang
- College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China
| | - Xiang Liu
- College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China
| | - Yong Chen
- Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
- Fujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
| | - Yixin Chen
- Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
- Fujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
| | - Houjun Tian
- Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
- Fujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
| | - Shuo Lin
- Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
- Fujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
| | - Sufen Tian
- College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China
| | - Hui Wei
- Institute of Plant Protection, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
- Fujian Key Laboratory for Monitoring and Integrated Management of Crop Pests, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian Province, China
| | - Xiaojun Gu
- College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China
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43
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Gutiérrez-González M, Latorre Y, Zúñiga R, Aguillón JC, Molina MC, Altamirano C. Transcription factor engineering in CHO cells for recombinant protein production. Crit Rev Biotechnol 2019; 39:665-679. [PMID: 31030575 DOI: 10.1080/07388551.2019.1605496] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The continuous increase of approved biopharmaceutical products drives the development of more efficient recombinant protein expression systems. Chinese hamster ovary (CHO) cells are the mainstay for this purpose but have some drawbacks, such as low levels of expression. Several strategies have been applied to increase the productivity of CHO cells with different outcomes. Transcription factor (TF) engineering has emerged as an interesting and successful approach, as these proteins can act as master regulators; the expression and function of a TF can be controlled by small molecules, and it is possible to design tailored TFs and promoters with desired features. To date, the majority of studies have focused on the use of TFs with growth, metabolic, cell cycle or endoplasmic reticulum functions, although there is a trend to develop new, synthetic TFs. Moreover, new synthetic biological approaches are showing promising advances for the development of specific TFs, even with tailored ligand sensitivity. In this article, we summarize the strategies to increase recombinant protein expression by modulating and designing TFs and with advancements in synthetic biology. We also illustrate how this class of proteins can be used to develop more robust expression systems.
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Affiliation(s)
| | - Yesenia Latorre
- b Escuela de Ingeniería Bioquímica, Pontificia Universidad Católica de Valparaíso , Valparaíso , Chile
| | - Roberto Zúñiga
- a Centro de InmunoBiotecnología, Universidad de Chile , Santiago , Chile
| | | | | | - Claudia Altamirano
- b Escuela de Ingeniería Bioquímica, Pontificia Universidad Católica de Valparaíso , Valparaíso , Chile
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44
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Kołat D, Kałuzińska Ż, Bednarek AK, Płuciennik E. The biological characteristics of transcription factors AP-2α and AP-2γ and their importance in various types of cancers. Biosci Rep 2019; 39:BSR20181928. [PMID: 30824562 PMCID: PMC6418405 DOI: 10.1042/bsr20181928] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 02/11/2019] [Accepted: 02/27/2019] [Indexed: 02/07/2023] Open
Abstract
The Activator Protein 2 (AP-2) transcription factor (TF) family is vital for the regulation of gene expression during early development as well as carcinogenesis process. The review focusses on the AP-2α and AP-2γ proteins and their dualistic regulation of gene expression in the process of carcinogenesis. Both AP-2α and AP-2γ influence a wide range of physiological or pathological processes by regulating different pathways and interacting with diverse molecules, i.e. other proteins, long non-coding RNAs (lncRNA) or miRNAs. This review summarizes the newest information about the biology of two, AP-2α and AP-2γ, TFs in the carcinogenesis process. We emphasize that these two proteins could have either oncogenic or suppressive characteristics depending on the type of cancer tissue or their interaction with specific molecules. They have also been found to contribute to resistance and sensitivity to chemotherapy in oncological patients. A better understanding of molecular network of AP-2 factors and other molecules may clarify the atypical molecular mechanisms occurring during carcinogenesis, and may assist in the recognition of new diagnostic biomarkers.
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Affiliation(s)
- Damian Kołat
- Faculty of Biomedical Sciences and Postgraduate Education, Medical University of Lodz, Lodz, Poland
| | - Żaneta Kałuzińska
- Faculty of Biomedical Sciences and Postgraduate Education, Medical University of Lodz, Lodz, Poland
| | - Andrzej K Bednarek
- Department of Molecular Carcinogenesis, Medical University of Lodz, Lodz, Poland
| | - Elżbieta Płuciennik
- Department of Molecular Carcinogenesis, Medical University of Lodz, Lodz, Poland
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45
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Smith AD, Panickar KS, Urban JF, Dawson HD. Impact of Micronutrients on the Immune Response of Animals. Annu Rev Anim Biosci 2019; 6:227-254. [PMID: 29447473 DOI: 10.1146/annurev-animal-022516-022914] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Vitamins and minerals (micronutrients) play an important role in regulating and shaping an immune response. Deficiencies generally result in inadequate or dysregulated cellular activity and cytokine expression, thereby affecting the immune response. Decreased levels of natural killer, granulocyte, and phagocytic cell activity and T and B cell proliferation and trafficking are associated with inadequate levels of micronutrients, as well as increased susceptibility to various adverse health conditions, including inflammatory disorders, infection, and altered vaccine efficacy. In addition, most studies of micronutrient modulation of immune responses have been done in rodents and humans, thus limiting application to the health and well-being of livestock and companion animals. This exploratory review elucidates the role of vitamins and minerals on immune function and inflammatory responses in animals (pigs, dogs, cats, horses, goats, sheep, and cattle), with reference to rodents and humans.
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Affiliation(s)
- Allen D Smith
- United States Department of Agriculture, Agricultural Research Service, Beltsville Human Nutrition Research Center, Diet, Genomics & Immunology Laboratory, Beltsville, Maryland 20705-2350, USA;
| | - Kiran S Panickar
- Science & Technology Center, Hills Pet Nutrition Center, Topeka, Kansas 66617, USA
| | - Joseph F Urban
- United States Department of Agriculture, Agricultural Research Service, Beltsville Human Nutrition Research Center, Diet, Genomics & Immunology Laboratory, Beltsville, Maryland 20705-2350, USA;
| | - Harry D Dawson
- United States Department of Agriculture, Agricultural Research Service, Beltsville Human Nutrition Research Center, Diet, Genomics & Immunology Laboratory, Beltsville, Maryland 20705-2350, USA;
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46
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Miraldi ER, Pokrovskii M, Watters A, Castro DM, De Veaux N, Hall JA, Lee JY, Ciofani M, Madar A, Carriero N, Littman DR, Bonneau R. Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells. Genome Res 2019; 29:449-463. [PMID: 30696696 PMCID: PMC6396413 DOI: 10.1101/gr.238253.118] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Accepted: 01/15/2019] [Indexed: 12/13/2022]
Abstract
Transcriptional regulatory networks (TRNs) provide insight into cellular behavior by describing interactions between transcription factors (TFs) and their gene targets. The assay for transposase-accessible chromatin (ATAC)–seq, coupled with TF motif analysis, provides indirect evidence of chromatin binding for hundreds of TFs genome-wide. Here, we propose methods for TRN inference in a mammalian setting, using ATAC-seq data to improve gene expression modeling. We test our methods in the context of T Helper Cell Type 17 (Th17) differentiation, generating new ATAC-seq data to complement existing Th17 genomic resources. In this resource-rich mammalian setting, our extensive benchmarking provides quantitative, genome-scale evaluation of TRN inference, combining ATAC-seq and RNA-seq data. We refine and extend our previous Th17 TRN, using our new TRN inference methods to integrate all Th17 data (gene expression, ATAC-seq, TF knockouts, and ChIP-seq). We highlight newly discovered roles for individual TFs and groups of TFs (“TF–TF modules”) in Th17 gene regulation. Given the popularity of ATAC-seq, which provides high-resolution with low sample input requirements, we anticipate that our methods will improve TRN inference in new mammalian systems, especially in vivo, for cells directly from humans and animal models.
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Affiliation(s)
- Emily R Miraldi
- Divisions of Immunobiology and Biomedical Informatics, Cincinnati Children's Hospital, Cincinnati, Ohio 45229, USA.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio 45257, USA
| | - Maria Pokrovskii
- Molecular Pathogenesis Program, The Kimmel Center for Biology and Medicine of the Skirball Institute, New York, New York 10016, USA
| | - Aaron Watters
- Center for Computational Biology, Flatiron Institute, New York, New York 10010, USA
| | - Dayanne M Castro
- Department of Biology, New York University, New York, New York 10012, USA
| | - Nicholas De Veaux
- Center for Computational Biology, Flatiron Institute, New York, New York 10010, USA
| | - Jason A Hall
- Molecular Pathogenesis Program, The Kimmel Center for Biology and Medicine of the Skirball Institute, New York, New York 10016, USA
| | - June-Yong Lee
- Molecular Pathogenesis Program, The Kimmel Center for Biology and Medicine of the Skirball Institute, New York, New York 10016, USA
| | - Maria Ciofani
- Department of Immunology, Duke University School of Medicine, Durham, North Carolina 27710, USA
| | - Aviv Madar
- Department of Biology, New York University, New York, New York 10012, USA
| | - Nick Carriero
- Center for Computational Biology, Flatiron Institute, New York, New York 10010, USA
| | - Dan R Littman
- Molecular Pathogenesis Program, The Kimmel Center for Biology and Medicine of the Skirball Institute, New York, New York 10016, USA.,The Howard Hughes Medical Institute
| | - Richard Bonneau
- Center for Computational Biology, Flatiron Institute, New York, New York 10010, USA.,Department of Biology, New York University, New York, New York 10012, USA.,Center for Data Science, New York University, New York, New York 10010, USA
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47
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Lambert SA, Jolma A, Campitelli LF, Das PK, Yin Y, Albu M, Chen X, Taipale J, Hughes TR, Weirauch MT. The Human Transcription Factors. Cell 2019; 172:650-665. [PMID: 29425488 DOI: 10.1016/j.cell.2018.01.029] [Citation(s) in RCA: 1547] [Impact Index Per Article: 309.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 01/15/2018] [Accepted: 01/22/2018] [Indexed: 12/13/2022]
Abstract
Transcription factors (TFs) recognize specific DNA sequences to control chromatin and transcription, forming a complex system that guides expression of the genome. Despite keen interest in understanding how TFs control gene expression, it remains challenging to determine how the precise genomic binding sites of TFs are specified and how TF binding ultimately relates to regulation of transcription. This review considers how TFs are identified and functionally characterized, principally through the lens of a catalog of over 1,600 likely human TFs and binding motifs for two-thirds of them. Major classes of human TFs differ markedly in their evolutionary trajectories and expression patterns, underscoring distinct functions. TFs likewise underlie many different aspects of human physiology, disease, and variation, highlighting the importance of continued effort to understand TF-mediated gene regulation.
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Affiliation(s)
- Samuel A Lambert
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Arttu Jolma
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
| | - Laura F Campitelli
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Pratyush K Das
- Genome-Scale Biology Program, University of Helsinki, Helsinki, Finland
| | - Yimeng Yin
- Division of Functional Genomics and Systems Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden
| | - Mihai Albu
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
| | - Xiaoting Chen
- Center for Autoimmune Genomics and Etiology (CAGE), Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Jussi Taipale
- Genome-Scale Biology Program, University of Helsinki, Helsinki, Finland; Division of Functional Genomics and Systems Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden; Department of Biochemistry, Cambridge University, Cambridge CB2 1GA, United Kingdom.
| | - Timothy R Hughes
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada; Donnelly Centre, University of Toronto, Toronto, ON, Canada.
| | - Matthew T Weirauch
- Center for Autoimmune Genomics and Etiology (CAGE), Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA; Divisions of Biomedical Informatics and Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.
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48
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Gergics P. Pituitary Transcription Factor Mutations Leading to Hypopituitarism. EXPERIENTIA SUPPLEMENTUM (2012) 2019; 111:263-298. [PMID: 31588536 DOI: 10.1007/978-3-030-25905-1_13] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Congenital pituitary hormone deficiency is a disabling condition. It is part of a spectrum of disorders including craniofacial midline developmental defects ranging from holoprosencephaly through septo-optic dysplasia to combined and isolated pituitary hormone deficiency. The first genes discovered in the human disease were based on mouse models of dwarfism due to mutations in transcription factor genes. High-throughput DNA sequencing technologies enabled clinicians and researchers to find novel genetic causes of hypopituitarism for the more than three quarters of patients without a known genetic diagnosis to date. Transcription factor (TF) genes are at the forefront of the functional analysis of novel variants of unknown significance due to the relative ease in in vitro testing in a research lab. Genetic testing in hypopituitarism is of high importance to the individual and their family to predict phenotype composition, disease progression and to avoid life-threatening complications such as secondary adrenal insufficiency.This chapter aims to highlight our current understanding about (1) the contribution of TF genes to pituitary development (2) the diversity of inheritance and phenotype features in combined and select isolated pituitary hormone deficiency and (3) provide an initial assessment on how to approach variants of unknown significance in human hypopituitarism. Our better understanding on how transcription factor gene variants lead to hypopituitarism is a meaningful step to plan advanced therapies to specific genetic changes in the future.
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Affiliation(s)
- Peter Gergics
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
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49
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Ouyang JF, Kamaraj US, Polo JM, Gough J, Rackham OJL. Molecular Interaction Networks to Select Factors for Cell Conversion. Methods Mol Biol 2019; 1975:333-361. [PMID: 31062318 DOI: 10.1007/978-1-4939-9224-9_16] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The process of identifying sets of transcription factors that can induce a cell conversion can be time-consuming and expensive. To help alleviate this, a number of computational tools have been developed which integrate gene expression data with molecular interaction networks in order to predict these factors. One such approach is Mogrify, an algorithm which ranks transcriptions factors based on their regulatory influence in different cell types and tissues. These ranks are then used to identify a nonredundant set of transcription factors to promote cell conversion between any two cell types/tissues. Here we summarize the important concepts and data sources that were used in the implementation of this approach. Furthermore, we describe how the associated web resource ( www.mogrify.net ) can be used to tailor predictions to specific experimental scenarios, for instance, limiting the set of possible transcription factors and including domain knowledge. Finally, we describe important considerations for the effective selection of reprogramming factors. We envision that such data-driven approaches will become commonplace in the field, rapidly accelerating the progress in stem cell biology.
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Affiliation(s)
- John F Ouyang
- Program in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore
| | - Uma S Kamaraj
- Program in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore
| | - Jose M Polo
- Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, Australia.,Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Clayton, VIC, Australia.,Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia
| | - Julian Gough
- Medical Research Council (MRC) Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge, UK
| | - Owen J L Rackham
- Program in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore.
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Vierbuchen T, Ling E, Cowley CJ, Couch CH, Wang X, Harmin DA, Roberts CWM, Greenberg ME. AP-1 Transcription Factors and the BAF Complex Mediate Signal-Dependent Enhancer Selection. Mol Cell 2018; 68:1067-1082.e12. [PMID: 29272704 DOI: 10.1016/j.molcel.2017.11.026] [Citation(s) in RCA: 250] [Impact Index Per Article: 41.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Revised: 09/16/2017] [Accepted: 11/17/2017] [Indexed: 02/08/2023]
Abstract
Enhancer elements are genomic regulatory sequences that direct the selective expression of genes so that genetically identical cells can differentiate and acquire the highly specialized forms and functions required to build a functioning animal. To differentiate, cells must select from among the ∼106 enhancers encoded in the genome the thousands of enhancers that drive the gene programs that impart their distinct features. We used a genetic approach to identify transcription factors (TFs) required for enhancer selection in fibroblasts. This revealed that the broadly expressed, growth-factor-inducible TFs FOS/JUN (AP-1) play a central role in enhancer selection. FOS/JUN selects enhancers together with cell-type-specific TFs by collaboratively binding to nucleosomal enhancers and recruiting the SWI/SNF (BAF) chromatin remodeling complex to establish accessible chromatin. These experiments demonstrate how environmental signals acting via FOS/JUN and BAF coordinate with cell-type-specific TFs to select enhancer repertoires that enable differentiation during development.
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Affiliation(s)
- Thomas Vierbuchen
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
| | - Emi Ling
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Christopher J Cowley
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Cameron H Couch
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Xiaofeng Wang
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - David A Harmin
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Charles W M Roberts
- Comprehensive Cancer Center and Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Michael E Greenberg
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
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