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Okamoto AS, Capellini TD. Parallel Evolution at the Regulatory Base-Pair Level Contributes to Mammalian Interspecific Differences in Polygenic Traits. Mol Biol Evol 2024; 41:msae157. [PMID: 39073613 PMCID: PMC11321361 DOI: 10.1093/molbev/msae157] [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: 04/22/2024] [Revised: 07/02/2024] [Accepted: 07/23/2024] [Indexed: 07/30/2024] Open
Abstract
Parallel evolution occurs when distinct lineages with similar ancestral states converge on a new phenotype. Parallel evolution has been well documented at the organ, gene pathway, and amino acid sequence level but in theory, it can also occur at individual nucleotides within noncoding regions. To examine the role of parallel evolution in shaping the biology of mammalian complex traits, we used data on single-nucleotide polymorphisms (SNPs) influencing human intraspecific variation to predict trait values in other species for 11 complex traits. We found that the alleles at SNP positions associated with human intraspecific height and red blood cell (RBC) count variation are associated with interspecific variation in the corresponding traits across mammals. These associations hold for deeper branches of mammalian evolution as well as between strains of collaborative cross mice. While variation in RBC count between primates uses both ancient and more recently evolved genomic regions, we found that only primate-specific elements were correlated with primate body size. We show that the SNP positions driving these signals are flanked by conserved sequences, maintain synteny with target genes, and overlap transcription factor binding sites. This work highlights the potential of conserved but tunable regulatory elements to be reused in parallel to facilitate evolutionary adaptation in mammals.
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Affiliation(s)
- Alexander S Okamoto
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Terence D Capellini
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
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2
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Tan Y, Zhou Y, Zhang W, Wu Z, Xu Q, Wu Q, Yang J, Lv T, Yan L, Luo H, Shi Y, Yang J. Repaglinide restrains HCC development and progression by targeting FOXO3/lumican/p53 axis. Cell Oncol (Dordr) 2024; 47:1167-1181. [PMID: 38326640 DOI: 10.1007/s13402-024-00919-9] [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] [Accepted: 01/11/2024] [Indexed: 02/09/2024] Open
Abstract
PURPOSE The recent focus on the roles of N-linked glycoproteins in carcinogenesis across various malignancies has prompted our exploration of aberrantly expressed glycoproteins responsible for HCC progression and potential therapeutic strategy. METHODS Mass spectrometry was applied to initially identify abnormally expressed glycoproteins in HCC, which was further assessed by immunohistochemistry (IHC) staining. The role of selected glycoprotein on HCC development and underlying mechanism was systematically investigated by colony formation, mouse xenograft, RNA-sequencing and western blot assays, etc. Chromatin immunoprecipitation (ChIP) and luciferase assays were performed to explore potential transcription factors (TFs) of selected glycoprotein. The regulation of repaglinide (RPG) on expression of lumican and downstream effectors was assessed by western blot and IHC, while its impact on malignant phenotypes of HCC was explored through in vitro and in vivo analyses, including a murine NASH-HCC model established using western diet and carbon tetrachloride (CCl4). RESULTS Lumican exhibited upregulation in both serum and tumor tissue, with elevated expression associated with an inferior prognosis in HCC patients. Knockdown of lumican resulted in significantly reduced growth of HCC in vitro and in vivo. Mechanically, lumican promoted HCC malignant phenotypes by inhibiting the p53/p21 signaling pathway. Forkhead Box O3 (FOXO3) was identified as the TF of lumican that transcriptionally enhanced its expression. Without silencing FOXO3, RPG blocked the binding of FOXO3 to the promoter region of lumican, thereby inhibiting the activation of lumican/p53/p21 axis. Mice treated with RPG developed fewer and smaller HCCs than those in the control group at 24 weeks after establishment. CONCLUSION Our results indicate that RPG prevented the development and progression of HCC via alteration of FOXO3/lumican/p53 axis.
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Affiliation(s)
- Yifei Tan
- Department of Liver Transplantation Center and Laboratory of Liver Transplantation, West China Hospital of Sichuan University, Chengdu, China
- Department of Ultrasonography, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Yongjie Zhou
- Department of Liver Transplantation Center and Laboratory of Liver Transplantation, West China Hospital of Sichuan University, Chengdu, China
| | - Wei Zhang
- Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhenru Wu
- Laboratory of Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Qing Xu
- Laboratory of Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Qiong Wu
- Department of Liver Transplantation Center and Laboratory of Liver Transplantation, West China Hospital of Sichuan University, Chengdu, China
| | - Jian Yang
- Department of Liver Transplantation Center and Laboratory of Liver Transplantation, West China Hospital of Sichuan University, Chengdu, China
| | - Tao Lv
- Department of Liver Transplantation Center and Laboratory of Liver Transplantation, West China Hospital of Sichuan University, Chengdu, China
| | - Lvnan Yan
- Department of Liver Transplantation Center and Laboratory of Liver Transplantation, West China Hospital of Sichuan University, Chengdu, China
| | - Hong Luo
- Department of Ultrasonography, West China Second University Hospital, Sichuan University, Chengdu, China.
| | - Yujun Shi
- Department of Liver Transplantation Center and Laboratory of Liver Transplantation, West China Hospital of Sichuan University, Chengdu, China.
- Laboratory of Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital of Sichuan University, Chengdu, 610041, China.
| | - Jiayin Yang
- Department of Liver Transplantation Center and Laboratory of Liver Transplantation, West China Hospital of Sichuan University, Chengdu, China.
- Laboratory of Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital of Sichuan University, Chengdu, 610041, China.
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3
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Panten J, Heinen T, Ernst C, Eling N, Wagner RE, Satorius M, Marioni JC, Stegle O, Odom DT. The dynamic genetic determinants of increased transcriptional divergence in spermatids. Nat Commun 2024; 15:1272. [PMID: 38341412 PMCID: PMC10858866 DOI: 10.1038/s41467-024-45133-1] [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: 02/07/2023] [Accepted: 01/16/2024] [Indexed: 02/12/2024] Open
Abstract
Cis-genetic effects are key determinants of transcriptional divergence in discrete tissues and cell types. However, how cis- and trans-effects act across continuous trajectories of cellular differentiation in vivo is poorly understood. Here, we quantify allele-specific expression during spermatogenic differentiation at single-cell resolution in an F1 hybrid mouse system, allowing for the comprehensive characterisation of cis- and trans-genetic effects, including their dynamics across cellular differentiation. Collectively, almost half of the genes subject to genetic regulation show evidence for dynamic cis-effects that vary during differentiation. Our system also allows us to robustly identify dynamic trans-effects, which are less pervasive than cis-effects. In aggregate, genetic effects were strongest in round spermatids, which parallels their increased transcriptional divergence we identified between species. Our approach provides a comprehensive quantification of the variability of genetic effects in vivo, and demonstrates a widely applicable strategy to dissect the impact of regulatory variants on gene regulation in dynamic systems.
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Affiliation(s)
- Jasper Panten
- Division of Regulatory Genomics and Cancer Evolution, German Cancer Research Centre (DKFZ), 69120, Heidelberg, Germany
- Division of Computational Genomics and Systems Genetics, German Cancer Research Centre (DKFZ), 69120, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, 69117, Heidelberg, Germany
| | - Tobias Heinen
- Division of Computational Genomics and Systems Genetics, German Cancer Research Centre (DKFZ), 69120, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- European Molecular Biology Laboratory, Genome Biology Unit, 69117, Heidelberg, Germany
| | - Christina Ernst
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Nils Eling
- University of Zurich, Department of Quantitative Biomedicine, Zurich, 8057, Switzerland
- ETH Zurich, Institute for Molecular Health Sciences, Zurich, 8093, Switzerland
| | - Rebecca E Wagner
- Faculty of Biosciences, Heidelberg University, 69117, Heidelberg, Germany
- Division of Mechanisms Regulating Gene Expression, German Cancer Research Centre (DKFZ), 69120, Heidelberg, Germany
| | - Maja Satorius
- Division of Regulatory Genomics and Cancer Evolution, German Cancer Research Centre (DKFZ), 69120, Heidelberg, Germany
| | - John C Marioni
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Oliver Stegle
- Division of Computational Genomics and Systems Genetics, German Cancer Research Centre (DKFZ), 69120, Heidelberg, Germany.
- European Molecular Biology Laboratory, Genome Biology Unit, 69117, Heidelberg, Germany.
| | - Duncan T Odom
- Division of Regulatory Genomics and Cancer Evolution, German Cancer Research Centre (DKFZ), 69120, Heidelberg, Germany.
- Faculty of Biosciences, Heidelberg University, 69117, Heidelberg, Germany.
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
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4
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Smith GD, Ching WH, Cornejo-Páramo P, Wong ES. Decoding enhancer complexity with machine learning and high-throughput discovery. Genome Biol 2023; 24:116. [PMID: 37173718 PMCID: PMC10176946 DOI: 10.1186/s13059-023-02955-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 04/28/2023] [Indexed: 05/15/2023] Open
Abstract
Enhancers are genomic DNA elements controlling spatiotemporal gene expression. Their flexible organization and functional redundancies make deciphering their sequence-function relationships challenging. This article provides an overview of the current understanding of enhancer organization and evolution, with an emphasis on factors that influence these relationships. Technological advancements, particularly in machine learning and synthetic biology, are discussed in light of how they provide new ways to understand this complexity. Exciting opportunities lie ahead as we continue to unravel the intricacies of enhancer function.
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Affiliation(s)
- Gabrielle D Smith
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia
| | - Wan Hern Ching
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
| | - Paola Cornejo-Páramo
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia
| | - Emily S Wong
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia.
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia.
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5
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Limited conservation in cross-species comparison of GLK transcription factor binding suggested wide-spread cistrome divergence. Nat Commun 2022; 13:7632. [PMID: 36494366 PMCID: PMC9734178 DOI: 10.1038/s41467-022-35438-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 12/02/2022] [Indexed: 12/13/2022] Open
Abstract
Non-coding cis-regulatory variants in animal genomes are an important driving force in the evolution of transcription regulation and phenotype diversity. However, cistrome dynamics in plants remain largely underexplored. Here, we compare the binding of GOLDEN2-LIKE (GLK) transcription factors in tomato, tobacco, Arabidopsis, maize and rice. Although the function of GLKs is conserved, most of their binding sites are species-specific. Conserved binding sites are often found near photosynthetic genes dependent on GLK for expression, but sites near non-differentially expressed genes in the glk mutant are nevertheless under purifying selection. The binding sites' regulatory potential can be predicted by machine learning model using quantitative genome features and TF co-binding information. Our study show that genome cis-variation caused wide-spread TF binding divergence, and most of the TF binding sites are genetically redundant. This poses a major challenge for interpreting the effect of individual sites and highlights the importance of quantitatively measuring TF occupancy.
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6
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Min Soe K, Ogawa T, Moriyama K. Molecular mechanism of hyperactive tooth root formation in oculo-facio-cardio-dental syndrome. Front Physiol 2022; 13:946282. [PMID: 35957990 PMCID: PMC9359619 DOI: 10.3389/fphys.2022.946282] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
Mutations in the B-cell lymphoma 6 (BCL6) interacting corepressor (BCOR) cause oculo-facio-cardio-dental (OFCD) syndrome, a rare X-linked dominant condition that includes dental radiculomegaly among other characteristics. BCOR regulates downstream genes via BCL6 as a transcriptional corepressor. However, the molecular mechanism underlying the occurrence of radiculomegaly is still unknown. Thus, this study was aimed at identifying BCOR-regulated genetic pathways in radiculomegaly. The microarray profile of affected tissues revealed that the gene-specific transcriptional factors group, wherein nucleus factor 1B, distal-less homeobox 5, and zinc finger protein multitype 2 (ZFPM2) were the most upregulated, was significantly expressed in periodontal ligament (PDL) cells of the diseased patient with a frameshift mutation (c.3668delC) in BCOR. Wild-type BCOR overexpression in human periodontal ligament fibroblasts cells significantly hampered cellular proliferation and ZFPM2 mRNA downregulation. Promoter binding assays showed that wild-type BCOR was recruited in the BCL6 binding of the ZFPM2 promoter region after immunoprecipitation, while mutant BCOR, which was the same genotype as of our patient, failed to recruit these promoter regions. Knockdown of ZFPM2 expression in mutant PDL cells significantly reduced cellular proliferation as well as mRNA expression of alkaline phosphatase, an important marker of odontoblasts and cementoblasts. Collectively, our findings suggest that BCOR mutation-induced ZFPM2 regulation via BCL6 possibly contributes to hyperactive root formation in OFCD syndrome. Clinical data from patients with rare genetic diseases may aid in furthering the understanding of the mechanism controlling the final root length.
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7
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Genome-wide analysis of cis-regulatory changes underlying metabolic adaptation of cavefish. Nat Genet 2022; 54:684-693. [PMID: 35551306 DOI: 10.1038/s41588-022-01049-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 03/09/2022] [Indexed: 12/13/2022]
Abstract
Cis-regulatory changes are key drivers of adaptative evolution. However, their contribution to the metabolic adaptation of organisms is not well understood. Here, we used a unique vertebrate model, Astyanax mexicanus-different morphotypes of which survive in nutrient-rich surface and nutrient-deprived cave waters-to uncover gene regulatory networks underlying metabolic adaptation. We performed genome-wide epigenetic profiling in the liver tissues of Astyanax and found that many of the identified cis-regulatory elements (CREs) have genetically diverged and have differential chromatin features between surface and cave morphotypes, while retaining remarkably similar regulatory signatures between independently derived cave populations. One such CRE in the hpdb gene harbors a genomic deletion in cavefish that abolishes IRF2 repressor binding and derepresses enhancer activity in reporter assays. Selection of this mutation in multiple independent cave populations supports its importance in cave adaptation, and provides novel molecular insights into the evolutionary trade-off between loss of pigmentation and adaptation to food-deprived caves.
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8
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Three topological features of regulatory networks control life-essential and specialized subsystems. Sci Rep 2021; 11:24209. [PMID: 34930908 PMCID: PMC8688434 DOI: 10.1038/s41598-021-03625-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 12/07/2021] [Indexed: 11/08/2022] Open
Abstract
Gene regulatory networks (GRNs) play key roles in development, phenotype plasticity, and evolution. Although graph theory has been used to explore GRNs, associations amongst topological features, transcription factors (TFs), and systems essentiality are poorly understood. Here we sought the relationship amongst the main GRN topological features that influence the control of essential and specific subsystems. We found that the Knn, page rank, and degree are the most relevant GRN features: the ones are conserved along the evolution and are also relevant in pluripotent cells. Interestingly, life-essential subsystems are governed mainly by TFs with intermediary Knn and high page rank or degree, whereas specialized subsystems are mainly regulated by TFs with low Knn. Hence, we suggest that the high probability of TFs be toured by a random signal, and the high probability of the signal propagation to target genes ensures the life-essential subsystems' robustness. Gene/genome duplication is the main evolutionary process to rise Knn as the most relevant feature. Herein, we shed light on unexplored topological GRN features to assess how they are related to subsystems and how the duplications shaped the regulatory systems along the evolution. The classification model generated can be found here: https://github.com/ivanrwolf/NoC/ .
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9
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Laverre A, Tannier E, Necsulea A. Long-range promoter-enhancer contacts are conserved during evolution and contribute to gene expression robustness. Genome Res 2021; 32:280-296. [PMID: 34930799 PMCID: PMC8805723 DOI: 10.1101/gr.275901.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 12/16/2021] [Indexed: 11/25/2022]
Abstract
Gene expression is regulated through complex molecular interactions, involving cis-acting elements that can be situated far away from their target genes. Data on long-range contacts between promoters and regulatory elements are rapidly accumulating. However, it remains unclear how these regulatory relationships evolve and how they contribute to the establishment of robust gene expression profiles. Here, we address these questions by comparing genome-wide maps of promoter-centered chromatin contacts in mouse and human. We show that there is significant evolutionary conservation of cis-regulatory landscapes, indicating that selective pressures act to preserve not only regulatory element sequences but also their chromatin contacts with target genes. The extent of evolutionary conservation is remarkable for long-range promoter–enhancer contacts, illustrating how the structure of regulatory landscapes constrains large-scale genome evolution. We show that the evolution of cis-regulatory landscapes, measured in terms of distal element sequences, synteny, or contacts with target genes, is significantly associated with gene expression evolution.
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Affiliation(s)
- Alexandre Laverre
- Université de Lyon, Université Claude Bernard Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive
| | - Eric Tannier
- Université de Lyon, Université Claude Bernard Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive, Centre de recherche Inria de Lyon
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10
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Matthews BJ, Melia T, Waxman DJ. Harnessing natural variation to identify cis regulators of sex-biased gene expression in a multi-strain mouse liver model. PLoS Genet 2021; 17:e1009588. [PMID: 34752452 PMCID: PMC8664386 DOI: 10.1371/journal.pgen.1009588] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 12/10/2021] [Accepted: 10/27/2021] [Indexed: 12/13/2022] Open
Abstract
Sex differences in gene expression are widespread in the liver, where many autosomal factors act in tandem with growth hormone signaling to regulate individual variability of sex differences in liver metabolism and disease. Here, we compare hepatic transcriptomic and epigenetic profiles of mouse strains C57BL/6J and CAST/EiJ, representing two subspecies separated by 0.5-1 million years of evolution, to elucidate the actions of genetic factors regulating liver sex differences. We identify 144 protein coding genes and 78 lncRNAs showing strain-conserved sex bias; many have gene ontologies relevant to liver function, are more highly liver-specific and show greater sex bias, and are more proximally regulated than genes whose sex bias is strain-dependent. The strain-conserved genes include key growth hormone-dependent transcriptional regulators of liver sex bias; however, three other transcription factors, Trim24, Tox, and Zfp809, lose their sex-biased expression in CAST/EiJ mouse liver. To elucidate the observed strain specificities in expression, we characterized the strain-dependence of sex-biased chromatin opening and enhancer marks at cis regulatory elements (CREs) within expression quantitative trait loci (eQTL) regulating liver sex-biased genes. Strikingly, 208 of 286 eQTLs with strain-specific, sex-differential effects on expression were associated with a complete gain, loss, or reversal of the sex differences in expression between strains. Moreover, 166 of the 286 eQTLs were linked to the strain-dependent gain or loss of localized sex-biased CREs. Remarkably, a subset of these CREs apparently lacked strain-specific genetic variants yet showed coordinated, strain-dependent sex-biased epigenetic regulation. Thus, we directly link hundreds of strain-specific genetic variants to the high variability in CRE activity and expression of sex-biased genes and uncover underlying genetically-determined epigenetic states controlling liver sex bias in genetically diverse mouse populations.
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Affiliation(s)
- Bryan J. Matthews
- Department of Biology, Boston University, Boston, Massachusetts, United States of America
| | - Tisha Melia
- Department of Biology, Boston University, Boston, Massachusetts, United States of America
- Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America
| | - David J. Waxman
- Department of Biology, Boston University, Boston, Massachusetts, United States of America
- Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America
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11
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Wong ES, Zheng D, Tan SZ, Bower NL, Garside V, Vanwalleghem G, Gaiti F, Scott E, Hogan BM, Kikuchi K, McGlinn E, Francois M, Degnan BM. Deep conservation of the enhancer regulatory code in animals. Science 2020; 370:370/6517/eaax8137. [PMID: 33154111 DOI: 10.1126/science.aax8137] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 04/29/2020] [Accepted: 09/30/2020] [Indexed: 12/15/2022]
Abstract
Interactions of transcription factors (TFs) with DNA regulatory sequences, known as enhancers, specify cell identity during animal development. Unlike TFs, the origin and evolution of enhancers has been difficult to trace. We drove zebrafish and mouse developmental transcription using enhancers from an evolutionarily distant marine sponge. Some of these sponge enhancers are located in highly conserved microsyntenic regions, including an Islet enhancer in the Islet-Scaper region. We found that Islet enhancers in humans and mice share a suite of TF binding motifs with sponges, and that they drive gene expression patterns similar to those of sponge and endogenous Islet enhancers in zebrafish. Our results suggest the existence of an ancient and conserved, yet flexible, genomic regulatory syntax that has been repeatedly co-opted into cell type-specific gene regulatory networks across the animal kingdom.
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Affiliation(s)
- Emily S Wong
- School of Biological Sciences, University of Queensland, Brisbane, Australia. .,Victor Chang Cardiac Research Institute, Sydney, Australia.,School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, Australia
| | - Dawei Zheng
- Victor Chang Cardiac Research Institute, Sydney, Australia
| | - Siew Z Tan
- Institute for Molecular Biosciences, University of Queensland, Brisbane, Australia
| | - Neil L Bower
- Institute for Molecular Biosciences, University of Queensland, Brisbane, Australia
| | - Victoria Garside
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Australia
| | | | - Federico Gaiti
- School of Biological Sciences, University of Queensland, Brisbane, Australia
| | - Ethan Scott
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Benjamin M Hogan
- Institute for Molecular Biosciences, University of Queensland, Brisbane, Australia.,Department of Anatomy and Neuroscience and Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - Kazu Kikuchi
- Victor Chang Cardiac Research Institute, Sydney, Australia
| | - Edwina McGlinn
- Australian Regenerative Medicine Institute, Monash University, Melbourne, Australia
| | - Mathias Francois
- Institute for Molecular Biosciences, University of Queensland, Brisbane, Australia. .,Centenary Institute, David Richmond Program for Cardio-Vascular Research: Gene Regulation and Editing, School of Life and Environmental Sciences, University of Sydney, Sydney, Australia
| | - Bernard M Degnan
- School of Biological Sciences, University of Queensland, Brisbane, Australia.
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12
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Palazzo AF, Koonin EV. Functional Long Non-coding RNAs Evolve from Junk Transcripts. Cell 2020; 183:1151-1161. [PMID: 33068526 DOI: 10.1016/j.cell.2020.09.047] [Citation(s) in RCA: 129] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 08/20/2020] [Accepted: 09/17/2020] [Indexed: 12/30/2022]
Abstract
Transcriptome studies reveal pervasive transcription of complex genomes, such as those of mammals. Despite popular arguments for functionality of most, if not all, of these transcripts, genome-wide analysis of selective constraints indicates that most of the produced RNA are junk. However, junk is not garbage. On the contrary, junk transcripts provide the raw material for the evolution of diverse long non-coding (lnc) RNAs by non-adaptive mechanisms, such as constructive neutral evolution. The generation of many novel functional entities, such as lncRNAs, that fuels organismal complexity does not seem to be driven by strong positive selection. Rather, the weak selection regime that dominates the evolution of most multicellular eukaryotes provides ample material for functional innovation with relatively little adaptation involved.
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Affiliation(s)
- Alexander F Palazzo
- Department of Biochemistry, University of Toronto, Toronto, ON M5G 1M1, Canada.
| | - Eugene V Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.
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13
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Krieger G, Lupo O, Levy AA, Barkai N. Independent evolution of transcript abundance and gene regulatory dynamics. Genome Res 2020; 30:1000-1011. [PMID: 32699020 PMCID: PMC7397873 DOI: 10.1101/gr.261537.120] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 06/24/2020] [Indexed: 12/13/2022]
Abstract
Changes in gene expression drive novel phenotypes, raising interest in how gene expression evolves. In contrast to the static genome, cells modulate gene expression in response to changing environments. Previous comparative studies focused on specific conditions, describing interspecies variation in expression levels, but providing limited information about variation across different conditions. To close this gap, we profiled mRNA levels of two related yeast species in hundreds of conditions and used coexpression analysis to distinguish variation in the dynamic pattern of gene expression from variation in expression levels. The majority of genes whose expression varied between the species maintained a conserved dynamic pattern. Cases of diverged dynamic pattern correspond to genes that were induced under distinct subsets of conditions in the two species. Profiling the interspecific hybrid allowed us to distinguish between genes with predominantly cis- or trans-regulatory variation. We find that trans-varying alleles are dominantly inherited, and that cis-variations are often complemented by variations in trans Based on these results, we suggest that gene expression diverges primarily through changes in expression levels, but does not alter the pattern by which these levels are dynamically regulated.
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Affiliation(s)
- Gat Krieger
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Offir Lupo
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Avraham A Levy
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Naama Barkai
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
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14
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Dukler N, Huang YF, Siepel A. Phylogenetic Modeling of Regulatory Element Turnover Based on Epigenomic Data. Mol Biol Evol 2020; 37:2137-2152. [PMID: 32176292 PMCID: PMC7306682 DOI: 10.1093/molbev/msaa073] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Evolutionary changes in gene expression are often driven by gains and losses of cis-regulatory elements (CREs). The dynamics of CRE evolution can be examined using multispecies epigenomic data, but so far such analyses have generally been descriptive and model-free. Here, we introduce a probabilistic modeling framework for the evolution of CREs that operates directly on raw chromatin immunoprecipitation and sequencing (ChIP-seq) data and fully considers the phylogenetic relationships among species. Our framework includes a phylogenetic hidden Markov model, called epiPhyloHMM, for identifying the locations of multiply aligned CREs, and a combined phylogenetic and generalized linear model, called phyloGLM, for accounting for the influence of a rich set of genomic features in describing their evolutionary dynamics. We apply these methods to previously published ChIP-seq data for the H3K4me3 and H3K27ac histone modifications in liver tissue from nine mammals. We find that enhancers are gained and lost during mammalian evolution at about twice the rate of promoters, and that turnover rates are negatively correlated with DNA sequence conservation, expression level, and tissue breadth, and positively correlated with distance from the transcription start site, consistent with previous findings. In addition, we find that the predicted dosage sensitivity of target genes positively correlates with DNA sequence constraint in CREs but not with turnover rates, perhaps owing to differences in the effect sizes of the relevant mutations. Altogether, our probabilistic modeling framework enables a variety of powerful new analyses.
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Affiliation(s)
- Noah Dukler
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
- Physiology, Biophysics, and Systems Biology, Weill Cornell Medical College, New York, NY
| | - Yi-Fei Huang
- Department of Biology and Huck Institute of Life Sciences, Pennsylvania State University, University Park, PA
| | - Adam Siepel
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
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15
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Yap MW, Young GR, Varnaite R, Morand S, Stoye JP. Duplication and divergence of the retrovirus restriction gene Fv1 in Mus caroli allows protection from multiple retroviruses. PLoS Genet 2020; 16:e1008471. [PMID: 32525879 PMCID: PMC7313476 DOI: 10.1371/journal.pgen.1008471] [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: 10/08/2019] [Revised: 06/23/2020] [Accepted: 05/13/2020] [Indexed: 12/29/2022] Open
Abstract
Viruses and their hosts are locked in an evolutionary race where resistance to infection is acquired by the hosts while viruses develop strategies to circumvent these host defenses. Forming one arm of the host defense armory are cell autonomous restriction factors like Fv1. Originally described as protecting laboratory mice from infection by murine leukemia virus (MLV), Fv1s from some wild mice have also been found to restrict non-MLV retroviruses, suggesting an important role in the protection against viruses in nature. We surveyed the Fv1 genes of wild mice trapped in Thailand and characterized their restriction activities against a panel of retroviruses. An extra copy of the Fv1 gene, named Fv7, was found on chromosome 6 of three closely related Asian species of mice: Mus caroli, M. cervicolor, and M. cookii. The presence of flanking repeats suggested it arose by LINE-mediated retroduplication within their most recent common ancestor. A high degree of natural variation was observed in both Fv1 and Fv7 and, on top of positive selection at certain residues, insertions and deletions were present that changed the length of the reading frames. These genes exhibited a range of restriction phenotypes, with activities directed against gamma-, spuma-, and lentiviruses. It seems likely, at least in the case of M. caroli, that the observed gene duplication may expand the breadth of restriction beyond the capacity of Fv1 alone and that one or more such viruses have recently driven or continue to drive the evolution of the Fv1 and Fv7 genes.
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Affiliation(s)
| | | | | | - Serge Morand
- Centre National de la Recherche Scientifique-Centre de coopération
Internationale en Recherche Agronomique pour le Développement Animal et Gestion
Intégrée des Risques, Faculty of Veterinary Technology, Kasetsart University,
Bangkok, Thailand
| | - Jonathan P. Stoye
- The Francis Crick Institute, London, United Kingdom
- Faculty of Medicine, Imperial College London, London, United
Kingdom
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16
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LncRNA SNHG17 aggravated prostate cancer progression through regulating its homolog SNORA71B via a positive feedback loop. Cell Death Dis 2020; 11:393. [PMID: 32447342 PMCID: PMC7245601 DOI: 10.1038/s41419-020-2569-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 09/25/2019] [Accepted: 10/17/2019] [Indexed: 01/11/2023]
Abstract
Prostate cancer (PC) is a prevalent male malignancy with high occurrence rate. Recent studies have showed that small nucleolar host genes (SNHGs) and their homolog small nucleolar RNAs (snoRNAs) elicit regulatory functions in carcinogenesis. Present study aimed to investigate the role of SNHG17 and its homolog SNORA71B in PC. Function of SNHG17 and SNORA71B in PC is detected by CCK-8, colony formation, flow cytometry analysis of apoptosis, and transwell migration assay. The mechanism whereby SNHG17 regulated SNORA71B was detected by RIP, pulldown, ChIP, and luciferase reporter assays. Results depicted that transcript 6 of SNHG17 and SNORA71B were upregulated in PC. Knockdown of SNHG17 or SNORA71B weakened proliferation, invasion, migration, and epithelial-to-mesenchymal transition (EMT) and strengthened apoptosis. Mechanistically, SNHG17 and SNORA71B were transcriptionally activated by signal transducer and activator of transcription 5A (STAT5A). SNHG17 positively regulated SNORA71B in PC cell lines and other cell lines. SNHG17 sponged miR-339-5p to upregulate STAT5A and therefore to cause transactivation of SNORA71B. Rescue experiments delineated that SNORA71B was required for the regulation of SNHG17 on PC. Moreover, SNHG17 silence hindered tumorigenesis of PC in vivo. In conclusion, current study first revealed that lncRNA SNHG17 aggravated prostate cancer progression through regulating its homolog SNORA71B via a positive feedback loop, which might do help to the pursuit of better PC treatment.
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17
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Yang J, Ruan H, Zou Y, Su Z, Gu X. Ancestral transcriptome inference based on RNA-Seq and ChIP-seq data. Methods 2020; 176:99-105. [DOI: 10.1016/j.ymeth.2018.11.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 11/09/2018] [Accepted: 11/15/2018] [Indexed: 11/24/2022] Open
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18
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Peng PC, Khoueiry P, Girardot C, Reddington JP, Garfield DA, Furlong EEM, Sinha S. The Role of Chromatin Accessibility in cis-Regulatory Evolution. Genome Biol Evol 2020; 11:1813-1828. [PMID: 31114856 PMCID: PMC6601868 DOI: 10.1093/gbe/evz103] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/13/2019] [Indexed: 02/07/2023] Open
Abstract
Transcription factor (TF) binding is determined by sequence as well as chromatin accessibility. Although the role of accessibility in shaping TF-binding landscapes is well recorded, its role in evolutionary divergence of TF binding, which in turn can alter cis-regulatory activities, is not well understood. In this work, we studied the evolution of genome-wide binding landscapes of five major TFs in the core network of mesoderm specification, between Drosophila melanogaster and Drosophila virilis, and examined its relationship to accessibility and sequence-level changes. We generated chromatin accessibility data from three important stages of embryogenesis in both Drosophila melanogaster and Drosophila virilis and recorded conservation and divergence patterns. We then used multivariable models to correlate accessibility and sequence changes to TF-binding divergence. We found that accessibility changes can in some cases, for example, for the master regulator Twist and for earlier developmental stages, more accurately predict binding change than is possible using TF-binding motif changes between orthologous enhancers. Accessibility changes also explain a significant portion of the codivergence of TF pairs. We noted that accessibility and motif changes offer complementary views of the evolution of TF binding and developed a combined model that captures the evolutionary data much more accurately than either view alone. Finally, we trained machine learning models to predict enhancer activity from TF binding and used these functional models to argue that motif and accessibility-based predictors of TF-binding change can substitute for experimentally measured binding change, for the purpose of predicting evolutionary changes in enhancer activity.
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Affiliation(s)
- Pei-Chen Peng
- Department of Computer Science, University of Illinois at Urbana-Champaign.,Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Pierre Khoueiry
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.,American University of Beirut (AUB), Department of Biochemistry and Molecular Genetics, Beirut, Lebanon
| | - Charles Girardot
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - James P Reddington
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - David A Garfield
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.,IRI-Life Sciences, Humboldt Universität zu Berlin, Berlin, Germany
| | - Eileen E M Furlong
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Saurabh Sinha
- Department of Computer Science, University of Illinois at Urbana-Champaign.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign
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19
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Kentepozidou E, Aitken SJ, Feig C, Stefflova K, Ibarra-Soria X, Odom DT, Roller M, Flicek P. Clustered CTCF binding is an evolutionary mechanism to maintain topologically associating domains. Genome Biol 2020; 21:5. [PMID: 31910870 PMCID: PMC6945661 DOI: 10.1186/s13059-019-1894-x] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 11/21/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND CTCF binding contributes to the establishment of a higher-order genome structure by demarcating the boundaries of large-scale topologically associating domains (TADs). However, despite the importance and conservation of TADs, the role of CTCF binding in their evolution and stability remains elusive. RESULTS We carry out an experimental and computational study that exploits the natural genetic variation across five closely related species to assess how CTCF binding patterns stably fixed by evolution in each species contribute to the establishment and evolutionary dynamics of TAD boundaries. We perform CTCF ChIP-seq in multiple mouse species to create genome-wide binding profiles and associate them with TAD boundaries. Our analyses reveal that CTCF binding is maintained at TAD boundaries by a balance of selective constraints and dynamic evolutionary processes. Regardless of their conservation across species, CTCF binding sites at TAD boundaries are subject to stronger sequence and functional constraints compared to other CTCF sites. TAD boundaries frequently harbor dynamically evolving clusters containing both evolutionarily old and young CTCF sites as a result of the repeated acquisition of new species-specific sites close to conserved ones. The overwhelming majority of clustered CTCF sites colocalize with cohesin and are significantly closer to gene transcription start sites than nonclustered CTCF sites, suggesting that CTCF clusters particularly contribute to cohesin stabilization and transcriptional regulation. CONCLUSIONS Dynamic conservation of CTCF site clusters is an apparently important feature of CTCF binding evolution that is critical to the functional stability of a higher-order chromatin structure.
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Affiliation(s)
- Elissavet Kentepozidou
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, CB10 1SD UK
| | - Sarah J. Aitken
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE UK
- Department of Histopathology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge, CB2 0QQ UK
| | - Christine Feig
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE UK
| | - Klara Stefflova
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE UK
| | - Ximena Ibarra-Soria
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE UK
| | - Duncan T. Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE UK
- Division Regulatory Genomics and Cancer Evolution, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Maša Roller
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, CB10 1SD UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, CB10 1SD UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA UK
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20
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Catalán A, Briscoe AD, Höhna S. Drift and Directional Selection Are the Evolutionary Forces Driving Gene Expression Divergence in Eye and Brain Tissue of Heliconius Butterflies. Genetics 2019; 213:581-594. [PMID: 31467133 PMCID: PMC6781903 DOI: 10.1534/genetics.119.302493] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 08/24/2019] [Indexed: 01/05/2023] Open
Abstract
Investigating gene expression evolution over micro- and macroevolutionary timescales will expand our understanding of the role of gene expression in adaptation and speciation. In this study, we characterized the evolutionary forces acting on gene expression levels in eye and brain tissue of five Heliconius butterflies with divergence times of ∼5-12 MYA. We developed and applied Brownian motion (BM) and Ornstein-Uhlenbeck (OU) models to identify genes whose expression levels are evolving through drift, stabilizing selection, or a lineage-specific shift. We found that 81% of the genes evolve under genetic drift. When testing for branch-specific shifts in gene expression, we detected 368 (16%) shift events. Genes showing a shift toward upregulation have significantly lower gene expression variance than those genes showing a shift leading toward downregulation. We hypothesize that directional selection is acting in shifts causing upregulation, since transcription is costly. We further uncovered through simulations that parameter estimation of OU models is biased when using small phylogenies and only becomes reliable with phylogenies having ≥ 50 taxa. Therefore, we developed a new statistical test based on BM to identify highly conserved genes (i.e., evolving under strong stabilizing selection), which comprised 3% of the orthoclusters. In conclusion, we found that drift is the dominant evolutionary force driving gene expression evolution in eye and brain tissue in Heliconius Nevertheless, the higher proportion of genes evolving under directional than under stabilizing selection might reflect species-specific selective pressures on vision and the brain that are necessary to fulfill species-specific requirements.
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Affiliation(s)
- Ana Catalán
- Department of Evolutionary Biology, Evolutionary Biology Centre (EBC), Uppsala University, 75236, Sweden
- Division of Evolutionary Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried 82152, Germany
| | - Adriana D Briscoe
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California 92697
| | - Sebastian Höhna
- Division of Evolutionary Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried 82152, Germany
- Department of Earth and Environmental Sciences, Paleontology and Geobiology, 80333 Munich, Germany
- GeoBio-Center, Ludwig-Maximilians-Universität München, 80333 Munich, Germany
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21
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Lan T, Yuan K, Yan X, Xu L, Liao H, Hao X, Wang J, Liu H, Chen X, Xie K, Li J, Liao M, Huang J, Zeng Y, Wu H. LncRNA SNHG10 Facilitates Hepatocarcinogenesis and Metastasis by Modulating Its Homolog SCARNA13 via a Positive Feedback Loop. Cancer Res 2019; 79:3220-3234. [PMID: 31101763 DOI: 10.1158/0008-5472.can-18-4044] [Citation(s) in RCA: 82] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2018] [Revised: 04/19/2019] [Accepted: 05/13/2019] [Indexed: 02/05/2023]
Abstract
Understanding the roles of noncoding RNAs (ncRNA) in tumorigenesis and metastasis would establish novel avenues to identify diagnostic and therapeutic targets. Here, we aimed to identify hepatocellular carcinoma (HCC)-specific ncRNA and to investigate their roles in hepatocarcinogenesis and metastasis. RNA-seq of xenografts generated by lung metastasis identified long noncoding RNA small nucleolar RNA host gene 10 (SNHG10) and its homolog SCARNA13 as novel drivers for the development and metastasis of HCC. SNHG10 expression positively correlated with SCARNA13 expression in 64 HCC cases, and high expression of SNHG10 or SCARNA13 was associated with poor overall survival. As SCARNA13 showed significant rise and decline after overexpression and knockdown of SNHG10, respectively, we hypothesized that SNHG10 might act as an upstream regulator of SCARNA13. SNHG10 and SCARNA13 coordinately contributed to the malignant phenotype of HCC cells, where SNHG10 served as a sponge for miR-150-5p and interacted with RPL4 mRNA to increase the expression and activity of c-Myb. Reciprocally, upregulated and hyperactivated c-Myb enhanced SNHG10 and SCARNA13 expression by regulating SNHG10 promoter activity, forming a positive feedback loop and continuously stimulating SCARNA13 expression. SCARNA13 mediated SNHG10-driven HCC cell proliferation, invasion, and migration and facilitated the cell cycle and epithelial-mesenchymal transition of HCC cells by regulating SOX9. Overall, we identified a complex circuitry underlying the concomitant upregulation of SNHG10 and its homolog SCARNA13 in HCC in the process of hepatocarcinogenesis and metastasis. SIGNIFICANCE: These findings unveil the role of a noncoding RNA in carcinogenesis and metastasis of hepatocellular carcinoma.
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Affiliation(s)
- Tian Lan
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Kefei Yuan
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China.,Laboratory of Liver Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Xiaokai Yan
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Lin Xu
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China.,Laboratory of Liver Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Haotian Liao
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Xiangyong Hao
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China.,Department of General Surgery, Gansu Provincial Hospital, Lanzhou, China
| | - Jinju Wang
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Hong Liu
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Xiangzheng Chen
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China.,Laboratory of Liver Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Kunlin Xie
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Jiaxin Li
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Mingheng Liao
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Jiwei Huang
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Yong Zeng
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China. .,Laboratory of Liver Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Hong Wu
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China. .,Laboratory of Liver Surgery, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
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22
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Chen J, Swofford R, Johnson J, Cummings BB, Rogel N, Lindblad-Toh K, Haerty W, Palma FD, Regev A. A quantitative framework for characterizing the evolutionary history of mammalian gene expression. Genome Res 2018; 29:53-63. [PMID: 30552105 PMCID: PMC6314168 DOI: 10.1101/gr.237636.118] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 11/27/2018] [Indexed: 01/09/2023]
Abstract
The evolutionary history of a gene helps predict its function and relationship to phenotypic traits. Although sequence conservation is commonly used to decipher gene function and assess medical relevance, methods for functional inference from comparative expression data are lacking. Here, we use RNA-seq across seven tissues from 17 mammalian species to show that expression evolution across mammals is accurately modeled by the Ornstein–Uhlenbeck process, a commonly proposed model of continuous trait evolution. We apply this model to identify expression pathways under neutral, stabilizing, and directional selection. We further demonstrate novel applications of this model to quantify the extent of stabilizing selection on a gene's expression, parameterize the distribution of each gene's optimal expression level, and detect deleterious expression levels in expression data from individual patients. Our work provides a statistical framework for interpreting expression data across species and in disease.
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Affiliation(s)
- Jenny Chen
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Division of Health Science and Technology, MIT, Cambridge, Massachusetts 02139, USA
| | - Ross Swofford
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Jeremy Johnson
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Beryl B Cummings
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Noga Rogel
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Kerstin Lindblad-Toh
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 752 36 Uppsala, Sweden
| | | | - Federica di Palma
- Earlham Institute, Norwich NR4 7UZ, United Kingdom.,Department of Biological and Medical Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Department of Biology and Koch Institute, MIT, Cambridge, Massachusetts 02142, USA.,Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, USA
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23
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Dynamic evolution of regulatory element ensembles in primate CD4 + T cells. Nat Ecol Evol 2018; 2:537-548. [PMID: 29379187 DOI: 10.1038/s41559-017-0447-5] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Accepted: 12/08/2017] [Indexed: 12/12/2022]
Abstract
How evolutionary changes at enhancers affect the transcription of target genes remains an important open question. Previous comparative studies of gene expression have largely measured the abundance of messenger RNA, which is affected by post-transcriptional regulatory processes, hence limiting inferences about the mechanisms underlying expression differences. Here, we directly measured nascent transcription in primate species, allowing us to separate transcription from post-transcriptional regulation. We used precision run-on and sequencing to map RNA polymerases in resting and activated CD4+ T cells in multiple human, chimpanzee and rhesus macaque individuals, with rodents as outgroups. We observed general conservation in coding and non-coding transcription, punctuated by numerous differences between species, particularly at distal enhancers and non-coding RNAs. Genes regulated by larger numbers of enhancers are more frequently transcribed at evolutionarily stable levels, despite reduced conservation at individual enhancers. Adaptive nucleotide substitutions are associated with lineage-specific transcription and at one locus, SGPP2, we predict and experimentally validate that multiple substitutions contribute to human-specific transcription. Collectively, our findings suggest a pervasive role for evolutionary compensation across ensembles of enhancers that jointly regulate target genes.
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24
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Berthelot C, Villar D, Horvath JE, Odom DT, Flicek P. Complexity and conservation of regulatory landscapes underlie evolutionary resilience of mammalian gene expression. Nat Ecol Evol 2018; 2:152-163. [PMID: 29180706 PMCID: PMC5733139 DOI: 10.1038/s41559-017-0377-2] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 10/10/2017] [Indexed: 02/02/2023]
Abstract
To gain insight into how mammalian gene expression is controlled by rapidly evolving regulatory elements, we jointly analysed promoter and enhancer activity with downstream transcription levels in liver samples from 15 species. Genes associated with complex regulatory landscapes generally exhibit high expression levels that remain evolutionarily stable. While the number of regulatory elements is the key driver of transcriptional output and resilience, regulatory conservation matters: elements active across mammals most effectively stabilize gene expression. In contrast, recently evolved enhancers typically contribute weakly, consistent with their high evolutionary plasticity. These effects are observed across the entire mammalian clade and are robust to potential confounders, such as the gene expression level. Using liver as a representative somatic tissue, our results illuminate how the evolutionary stability of gene expression is profoundly entwined with both the number and conservation of surrounding promoters and enhancers.
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Affiliation(s)
- Camille Berthelot
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
- Institut de Biologie de l'Ecole Normale Supérieure, Centre National de la Recherche Scientifique UMR8197, Institut National de la Santé et de la Recherche Médicale U1024, 46 Rue d'Ulm, 75230, Paris, Cedex 05, France
| | - Diego Villar
- University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, CB2 0RE, UK
| | - Julie E Horvath
- Biological and Biomedical Sciences, North Carolina Central University, Durham, NC, 27707, USA
- North Carolina Museum of Natural Sciences, Raleigh, NC, 27601, USA
- Evolutionary Anthropology Department, Duke University, Durham, NC, 27707, USA
| | - Duncan T Odom
- University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, CB2 0RE, UK.
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
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25
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Martín-Gálvez D, Dunoyer de Segonzac D, Ma MCJ, Kwitek AE, Thybert D, Flicek P. Genome variation and conserved regulation identify genomic regions responsible for strain specific phenotypes in rat. BMC Genomics 2017; 18:986. [PMID: 29272997 PMCID: PMC5741965 DOI: 10.1186/s12864-017-4351-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2017] [Accepted: 11/27/2017] [Indexed: 11/10/2022] Open
Abstract
Background The genomes of laboratory rat strains are characterised by a mosaic haplotype structure caused by their unique breeding history. These mosaic haplotypes have been recently mapped by extensive sequencing of key strains. Comparison of genomic variation between two closely related rat strains with different phenotypes has been proposed as an effective strategy for the discovery of candidate strain-specific regions involved in phenotypic differences. We developed a method to prioritise strain-specific haplotypes by integrating genomic variation and genomic regulatory data predicted to be involved in specific phenotypes. Specifically, we aimed to identify genomic regions associated with Metabolic Syndrome (MetS), a disorder of energy utilization and storage affecting several organ systems. Results We compared two Lyon rat strains, Lyon Hypertensive (LH) which is susceptible to MetS, and Lyon Low pressure (LL), which is susceptible to obesity as an intermediate MetS phenotype, with a third strain (Lyon Normotensive, LN) that is resistant to both MetS and obesity. Applying a novel metric, we ranked the identified strain-specific haplotypes using evolutionary conservation of the occupancy three liver-specific transcription factors (HNF4A, CEBPA, and FOXA1) in five rodents including rat. Consideration of regulatory information effectively identified regions with liver-associated genes and rat orthologues of human GWAS variants related to obesity and metabolic traits. We attempted to find possible causative variants and compared them with the candidate genes proposed by previous studies. In strain-specific regions with conserved regulation, we found a significant enrichment for published evidence to obesity—one of the metabolic symptoms shown by the Lyon strains—amongst the genes assigned to promoters with strain-specific variation. Conclusions Our results show that the use of functional regulatory conservation is a potentially effective approach to select strain-specific genomic regions associated with phenotypic differences among Lyon rats and could be extended to other systems. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-4351-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- David Martín-Gálvez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Denis Dunoyer de Segonzac
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Man Chun John Ma
- Department of Pharmacology, University of Iowa, Iowa City, IA, USA.,Iowa Institute of Human Genetics, University of Iowa, Iowa City, IA, USA.,Present address: MD Anderson Cancer Center, University of Texas, Houston, TX, USA
| | - Anne E Kwitek
- Department of Pharmacology, University of Iowa, Iowa City, IA, USA.,Iowa Institute of Human Genetics, University of Iowa, Iowa City, IA, USA
| | - David Thybert
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. .,Present address: Earlham Institute, Norwich research Park, Norwich, NR4 7UH, UK.
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
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26
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The rewiring of transcription circuits in evolution. Curr Opin Genet Dev 2017; 47:121-127. [PMID: 29120735 DOI: 10.1016/j.gde.2017.09.004] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Revised: 09/13/2017] [Accepted: 09/14/2017] [Indexed: 12/24/2022]
Abstract
The binding of transcription regulators to cis-regulatory sequences is a key step through which all cells regulate expression of their genes. Due to gains and losses of cis-regulatory sequences and changes in the transcription regulators themselves, the binding connections between regulators and their target genes rapidly change over evolutionary time and constitute a major source of biological novelty. This review covers recent work, carried out in a wide range of species, that addresses the overall extent of these evolutionary changes, their consequences, and some of the molecular mechanisms that lie behind them.
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27
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Wong ES, Schmitt BM, Kazachenka A, Thybert D, Redmond A, Connor F, Rayner TF, Feig C, Ferguson-Smith AC, Marioni JC, Odom DT, Flicek P. Interplay of cis and trans mechanisms driving transcription factor binding and gene expression evolution. Nat Commun 2017; 8:1092. [PMID: 29061983 PMCID: PMC5653656 DOI: 10.1038/s41467-017-01037-x] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Accepted: 08/09/2017] [Indexed: 12/23/2022] Open
Abstract
Noncoding regulatory variants play a central role in the genetics of human diseases and in evolution. Here we measure allele-specific transcription factor binding occupancy of three liver-specific transcription factors between crosses of two inbred mouse strains to elucidate the regulatory mechanisms underlying transcription factor binding variations in mammals. Our results highlight the pre-eminence of cis-acting variants on transcription factor occupancy divergence. Transcription factor binding differences linked to cis-acting variants generally exhibit additive inheritance, while those linked to trans-acting variants are most often dominantly inherited. Cis-acting variants lead to local coordination of transcription factor occupancies that decay with distance; distal coordination is also observed and may be modulated by long-range chromatin contacts. Our results reveal the regulatory mechanisms that interplay to drive transcription factor occupancy, chromatin state, and gene expression in complex mammalian cell states.
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Affiliation(s)
- Emily S Wong
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Bianca M Schmitt
- University of Cambridge, Cancer Research UK-Cambridge Institute, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | | | - David Thybert
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Aisling Redmond
- University of Cambridge, Cancer Research UK-Cambridge Institute, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Frances Connor
- University of Cambridge, Cancer Research UK-Cambridge Institute, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Tim F Rayner
- University of Cambridge, Cancer Research UK-Cambridge Institute, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Christine Feig
- University of Cambridge, Cancer Research UK-Cambridge Institute, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | | | - John C Marioni
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
- University of Cambridge, Cancer Research UK-Cambridge Institute, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Duncan T Odom
- University of Cambridge, Cancer Research UK-Cambridge Institute, Li Ka Shing Centre, Cambridge, CB2 0RE, UK.
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.
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28
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Chiang IKN, Fritzsche M, Pichol-Thievend C, Neal A, Holmes K, Lagendijk A, Overman J, D'Angelo D, Omini A, Hermkens D, Lesieur E, Liu K, Ratnayaka I, Corada M, Bou-Gharios G, Carroll J, Dejana E, Schulte-Merker S, Hogan B, Beltrame M, De Val S, Francois M. SoxF factors induce Notch1 expression via direct transcriptional regulation during early arterial development. Development 2017; 144:2629-2639. [PMID: 28619820 PMCID: PMC5536923 DOI: 10.1242/dev.146241] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Accepted: 06/07/2017] [Indexed: 12/30/2022]
Abstract
Arterial specification and differentiation are influenced by a number of regulatory pathways. While it is known that the Vegfa-Notch cascade plays a central role, the transcriptional hierarchy controlling arterial specification has not been fully delineated. To elucidate the direct transcriptional regulators of Notch receptor expression in arterial endothelial cells, we used histone signatures, DNaseI hypersensitivity and ChIP-seq data to identify enhancers for the human NOTCH1 and zebrafish notch1b genes. These enhancers were able to direct arterial endothelial cell-restricted expression in transgenic models. Genetic disruption of SoxF binding sites established a clear requirement for members of this group of transcription factors (SOX7, SOX17 and SOX18) to drive the activity of these enhancers in vivo Endogenous deletion of the notch1b enhancer led to a significant loss of arterial connections to the dorsal aorta in Notch pathway-deficient zebrafish. Loss of SoxF function revealed that these factors are necessary for NOTCH1 and notch1b enhancer activity and for correct endogenous transcription of these genes. These findings position SoxF transcription factors directly upstream of Notch receptor expression during the acquisition of arterial identity in vertebrates.
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MESH Headings
- Amino Acid Sequence
- Animals
- Animals, Genetically Modified
- Arteries/embryology
- Arteries/metabolism
- Arteriovenous Malformations/embryology
- Arteriovenous Malformations/genetics
- Arteriovenous Malformations/metabolism
- Enhancer Elements, Genetic
- Female
- Gene Expression Regulation, Developmental
- Human Umbilical Vein Endothelial Cells
- Humans
- Male
- Mice
- Mice, Inbred C57BL
- Mice, Knockout
- Mice, Transgenic
- Pregnancy
- Receptor, Notch1/deficiency
- Receptor, Notch1/genetics
- Receptor, Notch1/metabolism
- SOXF Transcription Factors/deficiency
- SOXF Transcription Factors/genetics
- SOXF Transcription Factors/metabolism
- Sequence Homology, Amino Acid
- Signal Transduction
- Zebrafish
- Zebrafish Proteins/deficiency
- Zebrafish Proteins/genetics
- Zebrafish Proteins/metabolism
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Affiliation(s)
- Ivy Kim-Ni Chiang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Martin Fritzsche
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, The University of Oxford, Oxford OX3 7DQ, UK
| | - Cathy Pichol-Thievend
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Alice Neal
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, The University of Oxford, Oxford OX3 7DQ, UK
| | - Kelly Holmes
- Cancer Research UK, The University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK
| | - Anne Lagendijk
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Jeroen Overman
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Donatella D'Angelo
- Dipartimento di Bioscienze, Universita' degli Studi di Milano, Via Celoria 26, 20133 Milano, Italy
| | - Alice Omini
- Dipartimento di Bioscienze, Universita' degli Studi di Milano, Via Celoria 26, 20133 Milano, Italy
| | - Dorien Hermkens
- University of Münster, 48149 Münster, Germany Institute for Cardiovascular Organogenesis and Regeneration, Faculty of Medicine, Westfälische Wilhelms-Universität Münster (WWU), Mendelstrasse 7, 48149 Münster and CiM Cluster of Excellence, Germany
| | - Emmanuelle Lesieur
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Ke Liu
- Institute of Aging and Chronic Disease, University of Liverpool, Liverpool L69 3GA, UK
| | - Indrika Ratnayaka
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, The University of Oxford, Oxford OX3 7DQ, UK
| | - Monica Corada
- IFOM, FIRC Institute of Molecular Oncology, 1620139 Milan, Italy
| | - George Bou-Gharios
- Institute of Aging and Chronic Disease, University of Liverpool, Liverpool L69 3GA, UK
| | - Jason Carroll
- Cancer Research UK, The University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK
| | - Elisabetta Dejana
- IFOM, FIRC Institute of Molecular Oncology, 1620139 Milan, Italy
- Department of Immunology Genetics and Pathology, Uppsala University, 75185 Uppsala, Sweden
| | - Stefan Schulte-Merker
- University of Münster, 48149 Münster, Germany Institute for Cardiovascular Organogenesis and Regeneration, Faculty of Medicine, Westfälische Wilhelms-Universität Münster (WWU), Mendelstrasse 7, 48149 Münster and CiM Cluster of Excellence, Germany
| | - Benjamin Hogan
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Monica Beltrame
- Dipartimento di Bioscienze, Universita' degli Studi di Milano, Via Celoria 26, 20133 Milano, Italy
| | - Sarah De Val
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, The University of Oxford, Oxford OX3 7DQ, UK
| | - Mathias Francois
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
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29
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Romanovskaya EV, Vikhnina MV, Grishina TV, Ivanov MP, Leonova LE, Tsvetkova EV. Transcription factors of the NF1 family: Possible mechanisms of inducible gene expression in the evolutionary lineage of multicellular animals. J EVOL BIOCHEM PHYS+ 2017. [DOI: 10.1134/s123456781702001x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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30
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Aken BL, Ayling S, Barrell D, Clarke L, Curwen V, Fairley S, Fernandez Banet J, Billis K, García Girón C, Hourlier T, Howe K, Kähäri A, Kokocinski F, Martin FJ, Murphy DN, Nag R, Ruffier M, Schuster M, Tang YA, Vogel JH, White S, Zadissa A, Flicek P, Searle SMJ. The Ensembl gene annotation system. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2016; 2016:baw093. [PMID: 27337980 PMCID: PMC4919035 DOI: 10.1093/database/baw093] [Citation(s) in RCA: 714] [Impact Index Per Article: 89.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Accepted: 05/09/2016] [Indexed: 12/12/2022]
Abstract
The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail.Database URL: http://www.ensembl.org/index.html.
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Affiliation(s)
- Bronwen L Aken
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Sarah Ayling
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK Present addresses: The Genome Analysis Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Daniel Barrell
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK Eagle Genomics Ltd, Babraham Research Campus, Cambridge CB22 3AT, UK
| | - Laura Clarke
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Valery Curwen
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Susan Fairley
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Julio Fernandez Banet
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK Pfizer Inc, 10646 Science Center Dr, San Diego, CA 92121, USA
| | - Konstantinos Billis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Carlos García Girón
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Kevin Howe
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Andreas Kähäri
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK Institutionen för cell-och molekylärbiologi, Uppsala University, Husargatan 3, Uppsala 752 37, Sweden
| | - Felix Kokocinski
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Daniel N Murphy
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Rishi Nag
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Magali Ruffier
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Michael Schuster
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna a-1090, Austria
| | - Y Amy Tang
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jan-Hinnerk Vogel
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK Genentech Inc, 1 DNA Way, South San Francisco, CA 94080, USA
| | - Simon White
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Amonida Zadissa
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Stephen M J Searle
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
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31
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Hartley SW, Mullikin JC. Detection and visualization of differential splicing in RNA-Seq data with JunctionSeq. Nucleic Acids Res 2016; 44:e127. [PMID: 27257077 PMCID: PMC5009739 DOI: 10.1093/nar/gkw501] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 05/24/2016] [Indexed: 12/14/2022] Open
Abstract
Although RNA-Seq data provide unprecedented isoform-level expression information, detection of alternative isoform regulation (AIR) remains difficult, particularly when working with an incomplete transcript annotation. We introduce JunctionSeq, a new method that builds on the statistical techniques used by the well-established DEXSeq package to detect differential usage of both exonic regions and splice junctions. In particular, JunctionSeq is capable of detecting differential usage of novel splice junctions without the need for an additional isoform assembly step, greatly improving performance when the available transcript annotation is flawed or incomplete. JunctionSeq also provides a powerful and streamlined visualization toolset that allows bioinformaticians to quickly and intuitively interpret their results. We tested our method on publicly available data from several experiments performed on the rat pineal gland and Toxoplasma gondii, successfully detecting known and previously validated AIR genes in 19 out of 19 gene-level hypothesis tests. Due to its ability to query novel splice sites, JunctionSeq is still able to detect these differences even when all alternative isoforms for these genes were not included in the transcript annotation. JunctionSeq thus provides a powerful method for detecting alternative isoform regulation even with low-quality annotations. An implementation of JunctionSeq is available as an R/Bioconductor package.
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Affiliation(s)
- Stephen W Hartley
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - James C Mullikin
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
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32
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Young RS. Lineage-specific genomics: Frequent birth and death in the human genome: The human genome contains many lineage-specific elements created by both sequence and functional turnover. Bioessays 2016; 38:654-63. [PMID: 27231054 PMCID: PMC4949557 DOI: 10.1002/bies.201500192] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Frequent evolutionary birth and death events have created a large quantity of biologically important, lineage‐specific DNA within mammalian genomes. The birth and death of DNA sequences is so frequent that the total number of these insertions and deletions in the human population remains unknown, although there are differences between these groups, e.g. transposable elements contribute predominantly to sequence insertion. Functional turnover – where the activity of a locus is specific to one lineage, but the underlying DNA remains conserved – can also drive birth and death. However, this does not appear to be a major driver of divergent transcriptional regulation. Both sequence and functional turnover have contributed to the birth and death of thousands of functional promoters in the human and mouse genomes. These findings reveal the pervasive nature of evolutionary birth and death and suggest that lineage‐specific regions may play an important but previously underappreciated role in human biology and disease.
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Affiliation(s)
- Robert S Young
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, UK
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33
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Douglas GM, Wilson MD, Moses AM. Decreased Transcription Factor Binding Levels Nearby Primate Pseudogenes Suggest Regulatory Degeneration. Mol Biol Evol 2016; 33:1478-85. [PMID: 26882985 PMCID: PMC4868113 DOI: 10.1093/molbev/msw030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Characteristics of pseudogene degeneration at the coding level are well-known, such as a shift toward neutral rates of nonsynonymous substitutions and gain of frameshift mutations. In contrast, degeneration of pseudogene transcriptional regulation is not well understood. Here, we test two predictions of regulatory degeneration along a pseudogenized lineage: 1) Decreased transcription factor (TF) binding and 2) accelerated evolution in putative cis-regulatory regions.We find evidence for decreased TF binding levels nearby two primate pseudogenes compared with functional liver genes. However, the majority of TF-bound sequences nearby pseudogenes do not show evidence for lineage-specific accelerated rates of evolution. We conclude that decreases in TF binding level could be a marker for regulatory degeneration, while sequence degeneration in primate cis-regulatory modules may be obscured by background rates of TF binding site turnover.
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Affiliation(s)
- Gavin M Douglas
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
| | - Michael D Wilson
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, Canada Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Alan M Moses
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada
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34
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Moyers BA, Zhang J. Evaluating Phylostratigraphic Evidence for Widespread De Novo Gene Birth in Genome Evolution. Mol Biol Evol 2016; 33:1245-56. [PMID: 26758516 DOI: 10.1093/molbev/msw008] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
The source of genetic novelty is an area of wide interest and intense investigation. Although gene duplication is conventionally thought to dominate the production of new genes, this view was recently challenged by a proposal of widespread de novo gene origination in eukaryotic evolution. Specifically, distributions of various gene properties such as coding sequence length, expression level, codon usage, and probability of being subject to purifying selection among groups of genes with different estimated ages were reported to support a model in which new protein-coding proto-genes arise from noncoding DNA and gradually integrate into cellular networks. Here we show that the genomic patterns asserted to support widespread de novo gene origination are largely attributable to biases in gene age estimation by phylostratigraphy, because such patterns are also observed in phylostratigraphic analysis of simulated genes bearing identical ages. Furthermore, there is no evidence of purifying selection on very young de novo genes previously claimed to show such signals. Together, these findings are consistent with the prevailing view that de novo gene birth is a relatively minor contributor to new genes in genome evolution. They also illustrate the danger of using phylostratigraphy in the study of new gene origination without considering its inherent bias.
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Affiliation(s)
- Bryan A Moyers
- Department of Computational Medicine and Bioinformatics, University of Michigan
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan
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35
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Carvunis AR, Wang T, Skola D, Yu A, Chen J, Kreisberg JF, Ideker T. Evidence for a common evolutionary rate in metazoan transcriptional networks. eLife 2015; 4. [PMID: 26682651 PMCID: PMC4764585 DOI: 10.7554/elife.11615] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Accepted: 12/17/2015] [Indexed: 12/13/2022] Open
Abstract
Genome sequences diverge more rapidly in mammals than in other animal lineages, such as birds or insects. However, the effect of this rapid divergence on transcriptional evolution remains unclear. Recent reports have indicated a faster divergence of transcription factor binding in mammals than in insects, but others found the reverse for mRNA expression. Here, we show that these conflicting interpretations resulted from differing methodologies. We performed an integrated analysis of transcriptional network evolution by examining mRNA expression, transcription factor binding and cis-regulatory motifs across >25 animal species, including mammals, birds and insects. Strikingly, we found that transcriptional networks evolve at a common rate across the three animal lineages. Furthermore, differences in rates of genome divergence were greatly reduced when restricting comparisons to chromatin-accessible sequences. The evolution of transcription is thus decoupled from the global rate of genome sequence evolution, suggesting that a small fraction of the genome regulates transcription. DOI:http://dx.doi.org/10.7554/eLife.11615.001 The genetic information that makes each individual unique is encoded in DNA molecules. Cells read this molecular instruction manual by a process called transcription, in which proteins called transcription factors bind to DNA in specific places and regulate which sections of the DNA will be expressed. These 'transcripts' are active molecules that determine the cell’s – and ultimately the individual’s – characteristics. However, it is not well understood how alterations in the DNA of different individuals or species can lead to changes in where the transcription factors bind, and in which transcripts are expressed. Carvunis, Wang, Skola et al. set out to determine if there is a relationship between how often DNA changes and how often transcription changes during the evolution of animals. The experiments examined the abundance of transcripts in the cells of a variety of animal species with close or distant evolutionary relationships. For example, the house mouse was compared to a close relative called the Algerian mouse, to another species of rodent (rat) and to humans. The experiments show that the changes in transcript abundances are happening at similar rates in mammals, birds and insects, even though DNA changes at very different rates in these groups of animals. This similarity was also observed for other aspects of transcription, such as in changes to where transcription factors bind to DNA. The next challenges are to find out what makes transcription evolve at such similar rates in these groups of animals, and whether these findings extend to other species and to other processes in cells. DOI:http://dx.doi.org/10.7554/eLife.11615.002
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Affiliation(s)
| | - Tina Wang
- Department of Medicine, University of California, San Diego, La Jolla, United States
| | - Dylan Skola
- Department of Medicine, University of California, San Diego, La Jolla, United States
| | - Alice Yu
- Department of Medicine, University of California, San Diego, La Jolla, United States
| | - Jonathan Chen
- Department of Medicine, University of California, San Diego, La Jolla, United States
| | - Jason F Kreisberg
- Department of Medicine, University of California, San Diego, La Jolla, United States
| | - Trey Ideker
- Department of Medicine, University of California, San Diego, La Jolla, United States
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Prescott SL, Srinivasan R, Marchetto MC, Grishina I, Narvaiza I, Selleri L, Gage FH, Swigut T, Wysocka J. Enhancer divergence and cis-regulatory evolution in the human and chimp neural crest. Cell 2015; 163:68-83. [PMID: 26365491 DOI: 10.1016/j.cell.2015.08.036] [Citation(s) in RCA: 235] [Impact Index Per Article: 26.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Revised: 05/06/2015] [Accepted: 07/21/2015] [Indexed: 01/23/2023]
Abstract
cis-regulatory changes play a central role in morphological divergence, yet the regulatory principles underlying emergence of human traits remain poorly understood. Here, we use epigenomic profiling from human and chimpanzee cranial neural crest cells to systematically and quantitatively annotate divergence of craniofacial cis-regulatory landscapes. Epigenomic divergence is often attributable to genetic variation within TF motifs at orthologous enhancers, with a novel motif being most predictive of activity biases. We explore properties of this cis-regulatory change, revealing the role of particular retroelements, uncovering broad clusters of species-biased enhancers near genes associated with human facial variation, and demonstrating that cis-regulatory divergence is linked to quantitative expression differences of crucial neural crest regulators. Our work provides a wealth of candidates for future evolutionary studies and demonstrates the value of "cellular anthropology," a strategy of using in-vitro-derived embryonic cell types to elucidate both fundamental and evolving mechanisms underlying morphological variation in higher primates.
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Affiliation(s)
- Sara L Prescott
- Department of Chemical and Systems Biology and Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Rajini Srinivasan
- Department of Chemical and Systems Biology and Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Maria Carolina Marchetto
- Laboratory of Genetics, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Irina Grishina
- Department of Cell and Developmental Biology, Weill Cornell Medical College, Cornell University, New York, NY 10065, USA
| | - Iñigo Narvaiza
- Laboratory of Genetics, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Licia Selleri
- Department of Cell and Developmental Biology, Weill Cornell Medical College, Cornell University, New York, NY 10065, USA
| | - Fred H Gage
- Laboratory of Genetics, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA 92037, USA; Center for Academic Research and Training in Anthropogeny (CARTA), University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Tomek Swigut
- Department of Chemical and Systems Biology and Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA.
| | - Joanna Wysocka
- Department of Chemical and Systems Biology and Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Institute of Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
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Thompson D, Regev A, Roy S. Comparative analysis of gene regulatory networks: from network reconstruction to evolution. Annu Rev Cell Dev Biol 2015; 31:399-428. [PMID: 26355593 DOI: 10.1146/annurev-cellbio-100913-012908] [Citation(s) in RCA: 95] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Regulation of gene expression is central to many biological processes. Although reconstruction of regulatory circuits from genomic data alone is therefore desirable, this remains a major computational challenge. Comparative approaches that examine the conservation and divergence of circuits and their components across strains and species can help reconstruct circuits as well as provide insights into the evolution of gene regulatory processes and their adaptive contribution. In recent years, advances in genomic and computational tools have led to a wealth of methods for such analysis at the sequence, expression, pathway, module, and entire network level. Here, we review computational methods developed to study transcriptional regulatory networks using comparative genomics, from sequence to functional data. We highlight how these methods use evolutionary conservation and divergence to reliably detect regulatory components as well as estimate the extent and rate of divergence. Finally, we discuss the promise and open challenges in linking regulatory divergence to phenotypic divergence and adaptation.
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Affiliation(s)
- Dawn Thompson
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
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Naval-Sánchez M, Potier D, Hulselmans G, Christiaens V, Aerts S. Identification of Lineage-Specific Cis-Regulatory Modules Associated with Variation in Transcription Factor Binding and Chromatin Activity Using Ornstein-Uhlenbeck Models. Mol Biol Evol 2015; 32:2441-55. [PMID: 25944915 PMCID: PMC4540964 DOI: 10.1093/molbev/msv107] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Scoring the impact of noncoding variation on the function of cis-regulatory regions, on their chromatin state, and on the qualitative and quantitative expression levels of target genes is a fundamental problem in evolutionary genomics. A particular challenge is how to model the divergence of quantitative traits and to identify relationships between the changes across the different levels of the genome, the chromatin activity landscape, and the transcriptome. Here, we examine the use of the Ornstein-Uhlenbeck (OU) model to infer selection at the level of predicted cis-regulatory modules (CRMs), and link these with changes in transcription factor binding and chromatin activity. Using publicly available cross-species ChIP-Seq and STARR-Seq data we show how OU can be applied genome-wide to identify candidate transcription factors for which binding site and CRM turnover is correlated with changes in regulatory activity. Next, we profile open chromatin in the developing eye across three Drosophila species. We identify the recognition motifs of the chromatin remodelers, Trithorax-like and Grainyhead as mostly correlating with species-specific changes in open chromatin. In conclusion, we show in this study that CRM scores can be used as quantitative traits and that motif discovery approaches can be extended towards more complex models of divergence.
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Affiliation(s)
- Marina Naval-Sánchez
- Laboratory of Computational Biology, Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Delphine Potier
- Laboratory of Computational Biology, Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Gert Hulselmans
- Laboratory of Computational Biology, Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Valerie Christiaens
- Laboratory of Computational Biology, Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Stein Aerts
- Laboratory of Computational Biology, Department of Human Genetics, University of Leuven, Leuven, Belgium
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