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Li L, Miao W, Huang M, Williams P, Wang Y. Integrated Genomic and Proteomic Analyses Reveal Novel Mechanisms of the Methyltransferase SETD2 in Renal Cell Carcinoma Development. Mol Cell Proteomics 2019; 18:437-447. [PMID: 30487242 PMCID: PMC6398210 DOI: 10.1074/mcp.ra118.000957] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 11/14/2018] [Indexed: 01/20/2023] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common type of RCC in humans. SET domain-containing 2 (SETD2), a lysine methyltransferase for histone and other proteins, has been found to be frequently lost in ccRCC. However, the mechanisms through which deficiency in SETD2 contributes to ccRCC development remain largely unknown. Here, we used a human embryonic kidney epithelial cell line with the SETD2 gene being knocked out using CRISPR/Cas9 technology. Using ChIP-seq analysis, we showed that SETD2 loss leads to diminished occupancy of histone H3K36me3 and H4K16ac on actively transcribed genes. Transcriptome sequencing of the knockout cells revealed diminished expression of genes involved in metabolic pathways and elevated expression of genes involved in regulation of RNA polymerase II-mediated transcription. Quantitative proteomic analysis of chromatin-associated proteins showed that genetic ablation of SETD2 leads to elevated chromatin occupancy of proteins involved in chromatin remodeling and RNA polymerase II transcription regulation, and diminished chromatin binding of proteins involved in translation elongation and RNA splicing. Interestingly, we found that SETD2 depletion attenuates cell proliferation, and this can be rescued by knockdown of CDK1. Taken together, we illustrate multiple SETD2-regulated cellular pathways that suppress cancer development and uncover mechanisms underlying aberrant cell cycle regulation in SETD2-depleted cells.
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Affiliation(s)
- Lin Li
- From the ‡Department of Chemistry, University of California, Riverside, California 92521
| | - Weili Miao
- From the ‡Department of Chemistry, University of California, Riverside, California 92521
| | - Ming Huang
- §Environmental Toxicology Graduate Program, University of California, Riverside, California 92521
| | - Preston Williams
- From the ‡Department of Chemistry, University of California, Riverside, California 92521
| | - Yinsheng Wang
- From the ‡Department of Chemistry, University of California, Riverside, California 92521;
- §Environmental Toxicology Graduate Program, University of California, Riverside, California 92521
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2
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Kalender Atak Z, Imrichova H, Svetlichnyy D, Hulselmans G, Christiaens V, Reumers J, Ceulemans H, Aerts S. Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks. Genome Med 2017; 9:80. [PMID: 28854983 PMCID: PMC5575942 DOI: 10.1186/s13073-017-0464-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Accepted: 08/02/2017] [Indexed: 01/05/2023] Open
Abstract
The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying "personal" gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genomes of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers. μ-cisTarget is available from http://mucistarget.aertslab.org .
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Affiliation(s)
- Zeynep Kalender Atak
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Hana Imrichova
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Dmitry Svetlichnyy
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Gert Hulselmans
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Valerie Christiaens
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Joke Reumers
- Discovery Sciences, Janssen Research & Development, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - Hugo Ceulemans
- Discovery Sciences, Janssen Research & Development, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - Stein Aerts
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium.
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
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3
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Neto M, Naval-Sánchez M, Potier D, Pereira PS, Geerts D, Aerts S, Casares F. Nuclear receptors connect progenitor transcription factors to cell cycle control. Sci Rep 2017; 7:4845. [PMID: 28687780 PMCID: PMC5501803 DOI: 10.1038/s41598-017-04936-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 05/23/2017] [Indexed: 01/31/2023] Open
Abstract
The specification and growth of organs is controlled simultaneously by networks of transcription factors. While the connection between these transcription factors with fate determinants is increasingly clear, how they establish the link with the cell cycle is far less understood. Here we investigate this link in the developing Drosophila eye, where two transcription factors, the MEIS1 homologue hth and the Zn-finger tsh, synergize to stimulate the proliferation of naïve eye progenitors. Experiments combining transcriptomics, open-chromatin profiling, motif analysis and functional assays indicate that these progenitor transcription factors exert a global regulation of the proliferation program. Rather than directly regulating cell cycle genes, they control proliferation through an intermediary layer of nuclear receptors of the ecdysone/estrogen-signaling pathway. This regulatory subnetwork between hth, tsh and nuclear receptors might be conserved from Drosophila to mammals, as we find a significant co-overexpression of their human homologues in specific cancer types.
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Affiliation(s)
- Marta Neto
- CABD, Andalusian Centre for Developmental Biology, CSIC-UPO-JA, 41013, Seville, Spain.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Rua Alfredo Allen, 208, 4200-135, Porto, Portugal.,IBMC - Instituto de Biologia Molecular e Celular, Universidade do Porto, Rua Alfredo Allen, 208, 4200-135, Porto, Portugal
| | | | - Delphine Potier
- School of Medicine, University of Leuven, box 602 3000, Leuven, Belgium
| | - Paulo S Pereira
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Rua Alfredo Allen, 208, 4200-135, Porto, Portugal.,IBMC - Instituto de Biologia Molecular e Celular, Universidade do Porto, Rua Alfredo Allen, 208, 4200-135, Porto, Portugal
| | - Dirk Geerts
- Department of Medical Biology L2-109, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Stein Aerts
- School of Medicine, University of Leuven, box 602 3000, Leuven, Belgium.
| | - Fernando Casares
- CABD, Andalusian Centre for Developmental Biology, CSIC-UPO-JA, 41013, Seville, Spain.
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Morabito F, Voso MT, Hohaus S, Gentile M, Vigna E, Recchia AG, Iovino L, Benedetti E, Lo-Coco F, Galimberti S. Panobinostat for the treatment of acute myelogenous leukemia. Expert Opin Investig Drugs 2016; 25:1117-31. [PMID: 27485472 DOI: 10.1080/13543784.2016.1216971] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Therapeutic strategies in patients with acute myeloid leukemia (AML) have not changed significantly over the last decades. Appropriate strategies are ultimately driven by the assessment of patients' fitness to define suitability for intensive induction chemotherapy, which produces high initial remission rates but, increased likelihood of relapse. Old/unfit AML patients still represent an urgent and unmet therapeutic need. Epigenetic deregulation represents a strategic characteristic of AML pathophysiology whereby aberrant gene transcription provides an advantage to leukemic cell survival. Efforts to re-establish impaired epigenetic regulation include hypomethylating agents and histone deacetylase inhibitors (HDACi). AREAS COVERED The review discusses the underlying mechanisms leading to disruption of lysine acetyltransferases (KAT or HAT)/deacetylase (KDAC or HDAC) balance and the rationale for using the HDACi panobinostat (LBH-589) in AML. EXPERT OPINION Although panobinostat has produced significant results in myeloma, its efficacy remains limited in AML. Panobinostat exerts pleiotropic activity and lack of specificity, which likely contributes to its inadequate safety in elderly AML patients. Phase I-II trials, utilizing panobinostat associated with well-known chemotherapeutic agents are ongoing and combinations with other druggable targets may likely be evaluated in future trials. The clinical use of this HDACi in AML the near future does not appearing promising.
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Affiliation(s)
- Fortunato Morabito
- a Hematology Unit, Department of Onco-Hematology , A.O. of Cosenza , Cosenza , Italy.,b Biotechnology Research Unit , ASP of Cosenza , Aprigliano (CS) , Italy
| | - Maria Teresa Voso
- c Department of Biomedicine and Prevention , Universita' Tor Vergata , Rome , Italy
| | - Stefan Hohaus
- d Department of Hematology , Universita' Cattolica S. Cuore , Rome , Italy
| | - Massimo Gentile
- a Hematology Unit, Department of Onco-Hematology , A.O. of Cosenza , Cosenza , Italy
| | - Ernesto Vigna
- a Hematology Unit, Department of Onco-Hematology , A.O. of Cosenza , Cosenza , Italy
| | | | - Lorenzo Iovino
- e Department of Clinical and Experimental Medicine, Hematology Division , University of Pisa , Pisa , Italy
| | - Edoardo Benedetti
- e Department of Clinical and Experimental Medicine, Hematology Division , University of Pisa , Pisa , Italy
| | - Francesco Lo-Coco
- c Department of Biomedicine and Prevention , Universita' Tor Vergata , Rome , Italy
| | - Sara Galimberti
- e Department of Clinical and Experimental Medicine, Hematology Division , University of Pisa , Pisa , Italy
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Svetlichnyy D, Imrichova H, Fiers M, Kalender Atak Z, Aerts S. Identification of High-Impact cis-Regulatory Mutations Using Transcription Factor Specific Random Forest Models. PLoS Comput Biol 2015; 11:e1004590. [PMID: 26562774 PMCID: PMC4642938 DOI: 10.1371/journal.pcbi.1004590] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2015] [Accepted: 10/10/2015] [Indexed: 02/02/2023] Open
Abstract
Cancer genomes contain vast amounts of somatic mutations, many of which are passenger mutations not involved in oncogenesis. Whereas driver mutations in protein-coding genes can be distinguished from passenger mutations based on their recurrence, non-coding mutations are usually not recurrent at the same position. Therefore, it is still unclear how to identify cis-regulatory driver mutations, particularly when chromatin data from the same patient is not available, thus relying only on sequence and expression information. Here we use machine-learning methods to predict functional regulatory regions using sequence information alone, and compare the predicted activity of the mutated region with the reference sequence. This way we define the Predicted Regulatory Impact of a Mutation in an Enhancer (PRIME). We find that the recently identified driver mutation in the TAL1 enhancer has a high PRIME score, representing a “gain-of-target” for MYB, whereas the highly recurrent TERT promoter mutation has a surprisingly low PRIME score. We trained Random Forest models for 45 cancer-related transcription factors, and used these to score variations in the HeLa genome and somatic mutations across more than five hundred cancer genomes. Each model predicts only a small fraction of non-coding mutations with a potential impact on the function of the encompassing regulatory region. Nevertheless, as these few candidate driver mutations are often linked to gains in chromatin activity and gene expression, they may contribute to the oncogenic program by altering the expression levels of specific oncogenes and tumor suppressor genes. Precise regulation of gene expression is controlled by cis-regulatory modules (CRM) containing binding sites for transcription factors (TF). The genome-wide location of all TF binding sites can often be obtained by ChIP-seq (chromatin immunoprecipitation followed by deep sequencing), yet in most cases only a minority of the binding peaks actually represent functional CRMs that control the transcription initiation of a bona fide TF target gene. Here, we investigated for 45 cancer-related TFs how machine-learning approaches can be used to predict functional TF target CRMs. After careful evaluation of their performance, we used these TF-target classifiers to predict which cis-regulatory mutations may have a significant impact on gene regulation by evaluating whether the mutation causes a significant gain or loss in the probability that the CRM is a functional TF target. We found that Random Forest classifiers can achieve more than 100-fold higher specificity for mutation prediction compared to the simple approaches based on scanning with position weight matrices. By scanning somatic mutations in breast cancer genomes and in the HeLa genome, we finally show that our TF-target classifiers can identify high impact non-coding mutations that are associated with concordant TF binding, gene expression changes and chromatin activity. In conclusion, TF-specific Random Forest classifiers can be used to prioritize cis-regulatory mutations in cancer genomes with high accuracy.
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Affiliation(s)
- Dmitry Svetlichnyy
- Laboratory of Computational Biology, KU Leuven Center for Human Genetics, Leuven, Belgium
| | - Hana Imrichova
- Laboratory of Computational Biology, KU Leuven Center for Human Genetics, Leuven, Belgium
| | - Mark Fiers
- VIB Center for the Biology of Disease, Leuven, Belgium
| | - Zeynep Kalender Atak
- Laboratory of Computational Biology, KU Leuven Center for Human Genetics, Leuven, Belgium
| | - Stein Aerts
- Laboratory of Computational Biology, KU Leuven Center for Human Genetics, Leuven, Belgium
- * E-mail:
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Smith KS, Yadav VK, Pedersen BS, Shaknovich R, Geraci MW, Pollard KS, De S. Signatures of accelerated somatic evolution in gene promoters in multiple cancer types. Nucleic Acids Res 2015; 43:5307-17. [PMID: 25934800 PMCID: PMC4477653 DOI: 10.1093/nar/gkv419] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2015] [Accepted: 04/17/2015] [Indexed: 11/13/2022] Open
Abstract
Cancer-associated somatic mutations outside protein-coding regions remain largely unexplored. Analyses of the TERT locus have indicated that non-coding regulatory mutations can be more frequent than previously suspected and play important roles in oncogenesis. Using a computational method called SASE-hunter, developed here, we identified a novel signature of accelerated somatic evolution (SASE) marked by a significant excess of somatic mutations localized in a genomic locus, and prioritized those loci that carried the signature in multiple cancer patients. Interestingly, even when an affected locus carried the signature in multiple individuals, the mutations contributing to SASE themselves were rarely recurrent at the base-pair resolution. In a pan-cancer analysis of 906 samples from 12 tumor types, we detected SASE in the promoters of several genes, including known cancer genes such as MYC, BCL2, RBM5 and WWOX. Nucleotide substitution patterns consistent with oxidative DNA damage and local somatic hypermutation appeared to contribute to this signature in selected gene promoters (e.g. MYC). SASEs in selected cancer gene promoters were associated with over-expression, and also correlated with the age of onset of cancer, aggressiveness of the disease and survival. Taken together, our work detects a hitherto under-appreciated and clinically important class of regulatory changes in cancer genomes.
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Affiliation(s)
- Kyle S Smith
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA Computational Biosciences Program, University of Colorado-Denver, Aurora, CO, USA
| | - Vinod K Yadav
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Brent S Pedersen
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Rita Shaknovich
- Division of Hematology/Oncology, Department of Medicine, and Division of Immunopathology, Department of Pathology, Weill Cornell Medical College, New York, NY, USA
| | - Mark W Geraci
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA University of Colorado Cancer Center, Aurora, CO, USA
| | - Katherine S Pollard
- Gladstone Institutes and Department of Epidemiology and Biostatistics, University of California San Francisco, CA, USA
| | - Subhajyoti De
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA Computational Biosciences Program, University of Colorado-Denver, Aurora, CO, USA University of Colorado Cancer Center, Aurora, CO, USA Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA
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7
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Malhotra S, Sowdhamini R. Sequence search and analysis of gene products containing RNA recognition motifs in the human genome. BMC Genomics 2014; 15:1159. [PMID: 25534245 PMCID: PMC4367854 DOI: 10.1186/1471-2164-15-1159] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2014] [Accepted: 12/12/2014] [Indexed: 11/25/2022] Open
Abstract
Background Gene expression is tightly regulated at both transcriptional and post-transcriptional levels. RNA-binding proteins are involved in post-transcriptional gene regulation events. They are involved in a variety of functions such as splicing, alternative splicing, nuclear import and export of mRNA, RNA stability and translation. There are several well-characterized RNA-binding motifs present in a whole genome, such as RNA recognition motif (RRM), KH domain, zinc-fingers etc. In the present study, we have investigated human genome for the presence of RRM-containing gene products starting from RRM domains in the Pfam (Protein family database) repository. Results In Pfam, seven families are recorded to contain RRM-containing proteins. We studied these families for their taxonomic representation, sequence features (identity, length, phylogeny) and structural properties (mapping conservation on the structures). We then examined the presence of RRM-containing gene products in Homo sapiens genome and identified 928 RRM-containing gene products. These were studied for their predicted domain architectures, biological processes, involvement in pathways, disease relevance and disorder content. RRM domains were observed to occur multiple times in a single polypeptide. However, there are 56 other co-existing domains involved in different regulatory functions. Further, functional enrichment analysis revealed that RRM-containing gene products are mainly involved in biological functions such as mRNA splicing and its regulation. Conclusions Our sequence analysis identified RRM-containing gene products in the human genome and provides insights into their domain architectures and biological functions. Since mRNA splicing and gene regulation are important in the cellular machinery, this analysis provides an early overview of genes that carry out these functions. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-1159) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Ramanathan Sowdhamini
- National Centre for Biological Sciences (TIFR), GKVK Campus, Bellary Road, Bangalore 560 065, India.
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Ongen H, Andersen CL, Bramsen JB, Oster B, Rasmussen MH, Ferreira PG, Sandoval J, Vidal E, Whiffin N, Planchon A, Padioleau I, Bielser D, Romano L, Tomlinson I, Houlston RS, Esteller M, Orntoft TF, Dermitzakis ET. Putative cis-regulatory drivers in colorectal cancer. Nature 2014; 512:87-90. [PMID: 25079323 DOI: 10.1038/nature13602] [Citation(s) in RCA: 113] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2013] [Accepted: 06/19/2014] [Indexed: 01/20/2023]
Abstract
The cis-regulatory effects responsible for cancer development have not been as extensively studied as the perturbations of the protein coding genome in tumorigenesis. To better characterize colorectal cancer (CRC) development we conducted an RNA-sequencing experiment of 103 matched tumour and normal colon mucosa samples from Danish CRC patients, 90 of which were germline-genotyped. By investigating allele-specific expression (ASE) we show that the germline genotypes remain important determinants of allelic gene expression in tumours. Using the changes in ASE in matched pairs of samples we discover 71 genes with excess of somatic cis-regulatory effects in CRC, suggesting a cancer driver role. We correlate genotypes and gene expression to identify expression quantitative trait loci (eQTLs) and find 1,693 and 948 eQTLs in normal samples and tumours, respectively. We estimate that 36% of the tumour eQTLs are exclusive to CRC and show that this specificity is partially driven by increased expression of specific transcription factors and changes in methylation patterns. We show that tumour-specific eQTLs are more enriched for low CRC genome-wide association study (GWAS) P values than shared eQTLs, which suggests that some of the GWAS variants are tumour specific regulatory variants. Importantly, tumour-specific eQTL genes also accumulate more somatic mutations when compared to the shared eQTL genes, raising the possibility that they constitute germline-derived cancer regulatory drivers. Collectively the integration of genome and the transcriptome reveals a substantial number of putative somatic and germline cis-regulatory cancer changes that may have a role in tumorigenesis.
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Affiliation(s)
- Halit Ongen
- 1] Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland [2] Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland [3] Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Claus L Andersen
- Department of Molecular Medicine, Aarhus University Hospital, 8000 Aarhus, Denmark
| | - Jesper B Bramsen
- Department of Molecular Medicine, Aarhus University Hospital, 8000 Aarhus, Denmark
| | - Bodil Oster
- Department of Molecular Medicine, Aarhus University Hospital, 8000 Aarhus, Denmark
| | - Mads H Rasmussen
- Department of Molecular Medicine, Aarhus University Hospital, 8000 Aarhus, Denmark
| | - Pedro G Ferreira
- 1] Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland [2] Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland [3] Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Juan Sandoval
- Cancer Epigenetics and Biology Program (PEBC), Bellvitge Biomedical Research Institute (IDIBELL), 08908 Barcelona, Catalonia, Spain
| | - Enrique Vidal
- Cancer Epigenetics and Biology Program (PEBC), Bellvitge Biomedical Research Institute (IDIBELL), 08908 Barcelona, Catalonia, Spain
| | - Nicola Whiffin
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey SM2 5NG, UK
| | - Alexandra Planchon
- 1] Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland [2] Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland [3] Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Ismael Padioleau
- 1] Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland [2] Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland [3] Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Deborah Bielser
- 1] Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland [2] Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland [3] Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Luciana Romano
- 1] Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland [2] Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland [3] Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Ian Tomlinson
- Nuffield Department of Clinical Medicine and Oxford NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Richard S Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey SM2 5NG, UK
| | - Manel Esteller
- 1] Cancer Epigenetics and Biology Program (PEBC), Bellvitge Biomedical Research Institute (IDIBELL), 08908 Barcelona, Catalonia, Spain [2] Department of Physiological Sciences II, School of Medicine, University of Barcelona, 08007 Barcelona, Barcelona, Spain [3] Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain
| | - Torben F Orntoft
- Department of Molecular Medicine, Aarhus University Hospital, 8000 Aarhus, Denmark
| | - Emmanouil T Dermitzakis
- 1] Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland [2] Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland [3] Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
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Dowen JM, Young RA. SMC complexes link gene expression and genome architecture. Curr Opin Genet Dev 2014; 25:131-7. [PMID: 24794701 PMCID: PMC4045092 DOI: 10.1016/j.gde.2013.11.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2013] [Revised: 11/14/2013] [Accepted: 11/15/2013] [Indexed: 12/15/2022]
Abstract
The structural maintenance of chromosomes (SMC) complexes are associated with transcriptional enhancers, promoters and insulators, where they contribute to the control of gene expression and genome structure. We review here recent insights into the interlinked roles of SMC complexes in gene expression and genome architecture. Among these, we note evidence that SMC complexes play important roles in the regulation of genes that control cell identity. We conclude by reviewing diseases associated with SMC mutations.
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Affiliation(s)
- Jill M Dowen
- Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, United States
| | - Richard A Young
- Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, United States; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
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