1
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Oh JW, Beer MA. Gapped-kmer sequence modeling robustly identifies regulatory vocabularies and distal enhancers conserved between evolutionarily distant mammals. Nat Commun 2024; 15:6464. [PMID: 39085231 PMCID: PMC11291912 DOI: 10.1038/s41467-024-50708-z] [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: 10/27/2023] [Accepted: 07/17/2024] [Indexed: 08/02/2024] Open
Abstract
Gene regulatory elements drive complex biological phenomena and their mutations are associated with common human diseases. The impacts of human regulatory variants are often tested using model organisms such as mice. However, mapping human enhancers to conserved elements in mice remains a challenge, due to both rapid enhancer evolution and limitations of current computational methods. We analyze distal enhancers across 45 matched human/mouse cell/tissue pairs from a comprehensive dataset of DNase-seq experiments, and show that while cell-specific regulatory vocabulary is conserved, enhancers evolve more rapidly than promoters and CTCF binding sites. Enhancer conservation rates vary across cell types, in part explainable by tissue specific transposable element activity. We present an improved genome alignment algorithm using gapped-kmer features, called gkm-align, and make genome wide predictions for 1,401,803 orthologous regulatory elements. We show that gkm-align discovers 23,660 novel human/mouse conserved enhancers missed by previous algorithms, with strong evidence of conserved functional activity.
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Affiliation(s)
- Jin Woo Oh
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Michael A Beer
- Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA.
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2
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Davidson BSA, Arcila-Galvis JE, Trevisan-Herraz M, Mikulasova A, Brackley CA, Russell LJ, Rico D. Evolutionarily conserved enhancer-associated features within the MYEOV locus suggest a regulatory role for this non-coding DNA region in cancer. Front Cell Dev Biol 2024; 12:1294510. [PMID: 39139450 PMCID: PMC11319300 DOI: 10.3389/fcell.2024.1294510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 07/01/2024] [Indexed: 08/15/2024] Open
Abstract
The myeloma overexpressed gene (MYEOV) has been proposed to be a proto-oncogene due to high RNA transcript levels found in multiple cancers, including myeloma, breast, lung, pancreas and esophageal cancer. The presence of an open reading frame (ORF) in humans and other primates suggests protein-coding potential. Yet, we still lack evidence of a functional MYEOV protein. It remains undetermined how MYEOV overexpression affects cancerous tissues. In this work, we show that MYEOV has likely originated and may still function as an enhancer, regulating CCND1 and LTO1. Firstly, MYEOV 3' enhancer activity was confirmed in humans using publicly available ATAC-STARR-seq data, performed on B-cell-derived GM12878 cells. We detected enhancer histone marks H3K4me1 and H3K27ac overlapping MYEOV in multiple healthy human tissues, which include B cells, liver and lung tissue. The analysis of 3D genome datasets revealed chromatin interactions between a MYEOV-3'-putative enhancer and the proto-oncogene CCND1. BLAST searches and multi-sequence alignment results showed that DNA sequence from this human enhancer element is conserved from the amphibians/amniotes divergence, with a 273 bp conserved region also found in all mammals, and even in chickens, where it is consistently located near the corresponding CCND1 orthologues. Furthermore, we observed conservation of an active enhancer state in the MYEOV orthologues of four non-human primates, dogs, rats, and mice. When studying this homologous region in mice, where the ORF of MYEOV is absent, we not only observed an enhancer chromatin state but also found interactions between the mouse enhancer homolog and Ccnd1 using 3D-genome interaction data. This is similar to the interaction observed in humans and, interestingly, coincides with CTCF binding sites in both species. Taken together, this suggests that MYEOV is a primate-specific gene with a de novo ORF that originated at an evolutionarily older enhancer region. This deeply conserved putative enhancer element could regulate CCND1 in both humans and mice, opening the possibility of studying MYEOV regulatory functions in cancer using non-primate animal models.
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Affiliation(s)
| | | | | | - Aneta Mikulasova
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Chris A. Brackley
- SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
| | - Lisa J. Russell
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Daniel Rico
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
- CABIMER, CSIC-Universidad de Sevilla-Universidad Pablo de Olavide-Junta de Andalucía, Seville, Spain
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3
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Li Y, Lyu R, Chen S, Wang Y, Sun MA. TEENA: an integrated web server for transposable element enrichment analysis in various model and non-model organisms. Nucleic Acids Res 2024; 52:W126-W131. [PMID: 38747349 PMCID: PMC11223789 DOI: 10.1093/nar/gkae411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 04/25/2024] [Accepted: 05/03/2024] [Indexed: 07/06/2024] Open
Abstract
Transposable elements (TEs) are abundant in the genomes of various eukaryote organisms. Increasing evidence suggests that TEs can play crucial regulatory roles-usually by creating cis-elements (e.g. enhancers and promoters) bound by distinct transcription factors (TFs). TE-derived cis-elements have gained unprecedented attentions recently, and one key step toward their understanding is to identify the enriched TEs in distinct genomic intervals (e.g. a set of enhancers or TF binding sites) as candidates for further study. Nevertheless, such analysis remains challenging for researchers unfamiliar with TEs or lack strong bioinformatic skills. Here, we present TEENA (Transposable Element ENrichment Analyzer) to streamline TE enrichment analysis in various organisms. It implements an optimized pipeline, hosts the genome/gene/TE annotations of almost one hundred species, and provides multiple parameters to enable its flexibility. Taking genomic interval data as the only user-supplied file, it can automatically retrieve the corresponding annotations and finish a routine analysis in a couple minutes. Multiple case studies demonstrate that it can produce highly reliable results matching previous knowledge. TEENA can be freely accessed at: https://sun-lab.yzu.edu.cn/TEENA. Due to its easy-to-use design, we expect it to facilitate the studies of the regulatory function of TEs in various model and non-model organisms.
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Affiliation(s)
- Yuzhuo Li
- Institute of Comparative Medicine, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009 Jiangsu, China
| | - Renzhe Lyu
- Institute of Comparative Medicine, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009 Jiangsu, China
| | - Shuai Chen
- Institute of Comparative Medicine, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009 Jiangsu, China
| | - Yejun Wang
- Youth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen 518060, China
| | - Ming-an Sun
- Institute of Comparative Medicine, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009 Jiangsu, China
- Joint International Research Laboratory of Important Animal Infectious Diseases and Zoonoses of Jiangsu Higher Education Institutions, Yangzhou University, Yangzhou 225009, China
- Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou 225009 Jiangsu, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009 Jiangsu, China
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4
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Kocher AA, Dutrow EV, Uebbing S, Yim KM, Rosales Larios MF, Baumgartner M, Nottoli T, Noonan JP. CpG island turnover events predict evolutionary changes in enhancer activity. Genome Biol 2024; 25:156. [PMID: 38872220 PMCID: PMC11170920 DOI: 10.1186/s13059-024-03300-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 06/04/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND Genetic changes that modify the function of transcriptional enhancers have been linked to the evolution of biological diversity across species. Multiple studies have focused on the role of nucleotide substitutions, transposition, and insertions and deletions in altering enhancer function. CpG islands (CGIs) have recently been shown to influence enhancer activity, and here we test how their turnover across species contributes to enhancer evolution. RESULTS We integrate maps of CGIs and enhancer activity-associated histone modifications obtained from multiple tissues in nine mammalian species and find that CGI content in enhancers is strongly associated with increased histone modification levels. CGIs show widespread turnover across species and species-specific CGIs are strongly enriched for enhancers exhibiting species-specific activity across all tissues and species. Genes associated with enhancers with species-specific CGIs show concordant biases in their expression, supporting that CGI turnover contributes to gene regulatory innovation. Our results also implicate CGI turnover in the evolution of Human Gain Enhancers (HGEs), which show increased activity in human embryonic development and may have contributed to the evolution of uniquely human traits. Using a humanized mouse model, we show that a highly conserved HGE with a large CGI absent from the mouse ortholog shows increased activity at the human CGI in the humanized mouse diencephalon. CONCLUSIONS Collectively, our results point to CGI turnover as a mechanism driving gene regulatory changes potentially underlying trait evolution in mammals.
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Affiliation(s)
- Acadia A Kocher
- Department of Genetics, Yale School of Medicine, New Haven, CT, 06510, USA
- Division of Molecular Genetics and Oncode Institute, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Emily V Dutrow
- Department of Genetics, Yale School of Medicine, New Haven, CT, 06510, USA
- Zoetis, Inc, 333 Portage St, Kalamazoo, MI, 49007, USA
| | - Severin Uebbing
- Department of Genetics, Yale School of Medicine, New Haven, CT, 06510, USA
- Genome Biology and Epigenetics, Institute of Biodynamics and Biocomplexity, Department of Biology, Utrecht University, Utrecht, The Netherlands
| | - Kristina M Yim
- Department of Genetics, Yale School of Medicine, New Haven, CT, 06510, USA
| | | | | | - Timothy Nottoli
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT, 06510, USA
- Yale Genome Editing Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | - James P Noonan
- Department of Genetics, Yale School of Medicine, New Haven, CT, 06510, USA.
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06520, USA.
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA.
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5
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Rimoldi M, Wang N, Zhang J, Villar D, Odom DT, Taipale J, Flicek P, Roller M. DNA methylation patterns of transcription factor binding regions characterize their functional and evolutionary contexts. Genome Biol 2024; 25:146. [PMID: 38844976 PMCID: PMC11155190 DOI: 10.1186/s13059-024-03218-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 03/15/2024] [Indexed: 06/10/2024] Open
Abstract
BACKGROUND DNA methylation is an important epigenetic modification which has numerous roles in modulating genome function. Its levels are spatially correlated across the genome, typically high in repressed regions but low in transcription factor (TF) binding sites and active regulatory regions. However, the mechanisms establishing genome-wide and TF binding site methylation patterns are still unclear. RESULTS Here we use a comparative approach to investigate the association of DNA methylation to TF binding evolution in mammals. Specifically, we experimentally profile DNA methylation and combine this with published occupancy profiles of five distinct TFs (CTCF, CEBPA, HNF4A, ONECUT1, FOXA1) in the liver of five mammalian species (human, macaque, mouse, rat, dog). TF binding sites are lowly methylated, but they often also have intermediate methylation levels. Furthermore, biding sites are influenced by the methylation status of CpGs in their wider binding regions even when CpGs are absent from the core binding motif. Employing a classification and clustering approach, we extract distinct and species-conserved patterns of DNA methylation levels at TF binding regions. CEBPA, HNF4A, ONECUT1, and FOXA1 share the same methylation patterns, while CTCF's differ. These patterns characterize alternative functions and chromatin landscapes of TF-bound regions. Leveraging our phylogenetic framework, we find DNA methylation gain upon evolutionary loss of TF occupancy, indicating coordinated evolution. Furthermore, each methylation pattern has its own evolutionary trajectory reflecting its genomic contexts. CONCLUSIONS Our epigenomic analyses indicate a role for DNA methylation in TF binding changes across species including that specific DNA methylation profiles characterize TF binding and are associated with their regulatory activity, chromatin contexts, and evolutionary trajectories.
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Affiliation(s)
- Martina Rimoldi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Ning Wang
- Department of Medical Biochemistry and Biophysics, Division of Functional Genomics and Systems Biology, Karolinska Institutet, Stockholm, SE, 141 83, Sweden
| | - Jilin Zhang
- Department of Medical Biochemistry and Biophysics, Division of Functional Genomics and Systems Biology, Karolinska Institutet, Stockholm, SE, 141 83, Sweden
| | - Diego Villar
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, 0RE, CB2, UK
- Present Address Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK
| | - Duncan T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, 0RE, CB2, UK
- Present address Division of Regulatory Genomics and Cancer Evolution, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany
| | - Jussi Taipale
- Department of Medical Biochemistry and Biophysics, Division of Functional Genomics and Systems Biology, Karolinska Institutet, Stockholm, SE, 141 83, Sweden
- Applied Tumor Genomics Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK.
| | - Maša Roller
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
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6
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Cornejo-Páramo P, Petrova V, Zhang X, Young RS, Wong ES. Emergence of enhancers at late DNA replicating regions. Nat Commun 2024; 15:3451. [PMID: 38658544 PMCID: PMC11043393 DOI: 10.1038/s41467-024-47391-5] [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: 10/23/2023] [Accepted: 03/26/2024] [Indexed: 04/26/2024] Open
Abstract
Enhancers are fast-evolving genomic sequences that control spatiotemporal gene expression patterns. By examining enhancer turnover across mammalian species and in multiple tissue types, we uncover a relationship between the emergence of enhancers and genome organization as a function of germline DNA replication time. While enhancers are most abundant in euchromatic regions, enhancers emerge almost twice as often in late compared to early germline replicating regions, independent of transposable elements. Using a deep learning sequence model, we demonstrate that new enhancers are enriched for mutations that alter transcription factor (TF) binding. Recently evolved enhancers appear to be mostly neutrally evolving and enriched in eQTLs. They also show more tissue specificity than conserved enhancers, and the TFs that bind to these elements, as inferred by binding sequences, also show increased tissue-specific gene expression. We find a similar relationship with DNA replication time in cancer, suggesting that these observations may be time-invariant principles of genome evolution. Our work underscores that genome organization has a profound impact in shaping mammalian gene regulation.
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Affiliation(s)
- Paola Cornejo-Páramo
- Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, Sydney, NSW, Australia
| | - Veronika Petrova
- Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, Sydney, NSW, Australia
| | - Xuan Zhang
- Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
| | - Robert S Young
- Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, United Kingdom
- Zhejiang University - University of Edinburgh Institute, Zhejiang University, 718 East Haizhou Road, 314400, Haining, PR China
| | - Emily S Wong
- Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia.
- School of Biotechnology and Biomolecular Sciences, Sydney, NSW, Australia.
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7
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Bell CG. Epigenomic insights into common human disease pathology. Cell Mol Life Sci 2024; 81:178. [PMID: 38602535 PMCID: PMC11008083 DOI: 10.1007/s00018-024-05206-2] [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: 01/19/2024] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/12/2024]
Abstract
The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.
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Affiliation(s)
- Christopher G Bell
- William Harvey Research Institute, Barts & The London Faculty of Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
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8
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Matsushima W, Planet E, Trono D. Ancestral genome reconstruction enhances transposable element annotation by identifying degenerate integrants. CELL GENOMICS 2024; 4:100497. [PMID: 38295789 PMCID: PMC10879028 DOI: 10.1016/j.xgen.2024.100497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/09/2023] [Accepted: 01/06/2024] [Indexed: 02/17/2024]
Abstract
Growing evidence indicates that transposable elements (TEs) play important roles in evolution by providing genomes with coding and non-coding sequences. Identification of TE-derived functional elements, however, has relied on TE annotations in individual species, which limits its scope to relatively intact TE sequences. Here, we report a novel approach to uncover previously unannotated degenerate TEs (degTEs) by probing multiple ancestral genomes reconstructed from hundreds of species. We applied this method to the human genome and achieved a 10.8% increase in coverage over the most recent annotation. Further, we discovered that degTEs contribute to various cis-regulatory elements and transcription factor binding sites, including those of a known TE-controlling family, the KRAB zinc-finger proteins. We also report unannotated chimeric transcripts between degTEs and human genes expressed in embryos. This study provides a novel methodology and a freely available resource that will facilitate the investigation of TE co-option events on a full scale.
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Affiliation(s)
- Wayo Matsushima
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
| | - Evarist Planet
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Didier Trono
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
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9
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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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10
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Tong B, Sun Y. Activation of Young LINE-1 Elements by CRISPRa. Int J Mol Sci 2023; 25:424. [PMID: 38203595 PMCID: PMC10778729 DOI: 10.3390/ijms25010424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/26/2023] [Accepted: 12/26/2023] [Indexed: 01/12/2024] Open
Abstract
Long interspersed element-1 (LINE-1; L1s) are mobile genetic elements that comprise nearly 20% of the human genome. L1s have been shown to have important functions in various biological processes, and their dysfunction is thought to be linked with diseases and cancers. However, the roles of the repetitive elements are largely not understood. While the CRISPR activation (CRISPRa) system based on catalytically deadCas9 (dCas9) is widely used for genome-wide interrogation of gene function and genetic interaction, few studies have been conducted on L1s. Here, we report using the CRISPRa method to efficiently activate L1s in human L02 cells, a derivative of the HeLa cancer cell line. After CRISPRa, the young L1 subfamilies such as L1HS/L1PA1 and L1PA2 are found to be expressed at higher levels than the older L1s. The L1s with high levels of transcription are closer to full-length and are more densely occupied by the YY1 transcription factor. The activated L1s can either be mis-spliced to form chimeric transcripts or act as alternative promoters or enhancers to facilitate the expression of neighboring genes. The method described here can be used for studying the functional roles of young L1s in cultured cells of interest.
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Affiliation(s)
- Bei Tong
- Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
| | - Yuhua Sun
- Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
- The Innovation of Seed Design, Chinese Academy of Sciences, Wuhan 430072, China
- Hubei Hongshan Laboratory, Wuhan 430070, China
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11
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Zu S, Li YE, Wang K, Armand EJ, Mamde S, Amaral ML, Wang Y, Chu A, Xie Y, Miller M, Xu J, Wang Z, Zhang K, Jia B, Hou X, Lin L, Yang Q, Lee S, Li B, Kuan S, Liu H, Zhou J, Pinto-Duarte A, Lucero J, Osteen J, Nunn M, Smith KA, Tasic B, Yao Z, Zeng H, Wang Z, Shang J, Behrens MM, Ecker JR, Wang A, Preissl S, Ren B. Single-cell analysis of chromatin accessibility in the adult mouse brain. Nature 2023; 624:378-389. [PMID: 38092917 PMCID: PMC10719105 DOI: 10.1038/s41586-023-06824-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023]
Abstract
Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.
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Affiliation(s)
- Songpeng Zu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yang Eric Li
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Department of Neurosurgery and Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Kangli Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Ethan J Armand
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Sainath Mamde
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Maria Luisa Amaral
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yuelai Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Andre Chu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Michael Miller
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Jie Xu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Kai Zhang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Bojing Jia
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Xiaomeng Hou
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Lin Lin
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Qian Yang
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Bin Li
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Samantha Kuan
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Jacinta Lucero
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Julia Osteen
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Michael Nunn
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | | | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Zihan Wang
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Jingbo Shang
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | | | - Joseph R Ecker
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Allen Wang
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA.
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA.
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12
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Buttler CA, Ramirez D, Dowell RD, Chuong EB. An intronic LINE-1 regulates IFNAR1 expression in human immune cells. Mob DNA 2023; 14:20. [PMID: 38037122 PMCID: PMC10688052 DOI: 10.1186/s13100-023-00308-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 11/13/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND Despite their origins as selfish parasitic sequences, some transposons in the human genome have been co-opted to serve as regulatory elements, contributing to the evolution of transcriptional networks. Most well-characterized examples of transposon-derived regulatory elements derive from endogenous retroviruses (ERVs), due to the intrinsic regulatory activity of proviral long terminal repeat regions. However, one subclass of transposable elements, the Long Interspersed Nuclear Elements (LINEs), have been largely overlooked in the search for functional regulatory transposons, and considered to be broadly epigenetically repressed. RESULTS We examined the chromatin state of LINEs by analyzing epigenomic data from human immune cells. Many LINEs are marked by the repressive H3K9me3 modification, but a subset exhibits evidence of enhancer activity in human immune cells despite also showing evidence of epigenetic repression. We hypothesized that these competing forces of repressive and activating epigenetic marks might lead to inducible enhancer activity. We investigated a specific L1M2a element located within the first intron of Interferon Alpha/Beta Receptor 1 (IFNAR1). This element shows epigenetic signatures of B cell-specific enhancer activity, despite being repressed by the Human Silencing Hub (HUSH) complex. CRISPR deletion of the element in B lymphoblastoid cells revealed that the element acts as an enhancer that regulates both steady state and interferon-inducible expression of IFNAR1. CONCLUSIONS Our study experimentally demonstrates that an L1M2a element was co-opted to function as an interferon-inducible enhancer of IFNAR1, creating a feedback loop wherein IFNAR1 is transcriptionally upregulated by interferon signaling. This finding suggests that other LINEs may exhibit cryptic cell type-specific or context-dependent enhancer activity. LINEs have received less attention than ERVs in the effort to understand the contribution of transposons to the regulatory landscape of cellular genomes, but these are likely important, lineage-specific players in the rapid evolution of immune system regulatory networks and deserve further study.
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Affiliation(s)
- Carmen A Buttler
- Department of Molecular, Cellular, and Developmental Biology and BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, 80309, USA
| | - Daniel Ramirez
- Department of Molecular, Cellular, and Developmental Biology and BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, 80309, USA
| | - Robin D Dowell
- Department of Molecular, Cellular, and Developmental Biology and BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, 80309, USA
| | - Edward B Chuong
- Department of Molecular, Cellular, and Developmental Biology and BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, 80309, USA.
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13
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Parey E, Fernandez-Aroca D, Frost S, Uribarren A, Park TJ, Zöttl M, St John Smith E, Berthelot C, Villar D. Phylogenetic modeling of enhancer shifts in African mole-rats reveals regulatory changes associated with tissue-specific traits. Genome Res 2023; 33:1513-1526. [PMID: 37625847 PMCID: PMC10620049 DOI: 10.1101/gr.277715.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 08/24/2023] [Indexed: 08/27/2023]
Abstract
Changes in gene regulation are thought to underlie most phenotypic differences between species. For subterranean rodents such as the naked mole-rat, proposed phenotypic adaptations include hypoxia tolerance, metabolic changes, and cancer resistance. However, it is largely unknown what regulatory changes may associate with these phenotypic traits, and whether these are unique to the naked mole-rat, the mole-rat clade, or are also present in other mammals. Here, we investigate regulatory evolution in the heart and liver from two African mole-rat species and two rodent outgroups using genome-wide epigenomic profiling. First, we adapted and applied a phylogenetic modeling approach to quantitatively compare epigenomic signals at orthologous regulatory elements and identified thousands of promoter and enhancer regions with differential epigenomic activity in mole-rats. These elements associate with known mole-rat adaptations in metabolic and functional pathways and suggest candidate genetic loci that may underlie mole-rat innovations. Second, we evaluated ancestral and species-specific regulatory changes in the study phylogeny and report several candidate pathways experiencing stepwise remodeling during the evolution of mole-rats, such as the insulin and hypoxia response pathways. Third, we report nonorthologous regulatory elements overlap with lineage-specific repetitive elements and appear to modify metabolic pathways by rewiring of HNF4 and RAR/RXR transcription factor binding sites in mole-rats. These comparative analyses reveal how mole-rat regulatory evolution informs previously reported phenotypic adaptations. Moreover, the phylogenetic modeling framework we propose here improves upon the state of the art by addressing known limitations of inter-species comparisons of epigenomic profiles and has broad implications in the field of comparative functional genomics.
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Affiliation(s)
- Elise Parey
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
| | - Diego Fernandez-Aroca
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, United Kingdom
| | - Stephanie Frost
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, United Kingdom
| | - Ainhoa Uribarren
- Cambridge Institute, Cancer Research UK and University of Cambridge, Cambridge CB2 0RE, United Kingdom
| | - Thomas J Park
- Department of Biological Sciences and Laboratory of Integrative Neuroscience, University of Illinois at Chicago, Chicago, Illinois 60607, USA
| | - Markus Zöttl
- Department of Biology and Environmental Science, Linnaeus University, 44054 Kalmar, Sweden
| | - Ewan St John Smith
- Department of Pharmacology, University of Cambridge, Cambridge CB2 1PD, United Kingdom
| | - Camille Berthelot
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France;
- Institut Pasteur, Université Paris Cité, CNRS UMR 3525, INSERM UA12, Comparative Functional Genomics Group, F-75015 Paris, France
| | - Diego Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, United Kingdom;
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14
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Guerra M, Meola L, Lattante S, Conte A, Sabatelli M, Sette C, Bernardini C. Characterization of SOD1-DT, a Divergent Long Non-Coding RNA in the Locus of the SOD1 Human Gene. Cells 2023; 12:2058. [PMID: 37626868 PMCID: PMC10453398 DOI: 10.3390/cells12162058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/03/2023] [Accepted: 08/06/2023] [Indexed: 08/27/2023] Open
Abstract
Researchers studying Amyotrophic Lateral Sclerosis (ALS) have made significant efforts to find a unique mechanism to explain the etiopathology of the different forms of the disease. However, despite several mutations associated with ALS having been discovered in recent years, the link between the mutated genes and its onset has not yet been fully elucidated. Among the genes associated with ALS, superoxide dismutase 1 (SOD1) was the first to be identified, but its role in the etiopathogenesis of the disease is still unclear. In recent years, research has been focused on the non-coding part of the genome to fully understand the mechanisms underlying gene regulation. Non-coding RNAs are conserved molecules and are not usually translated in protein. A total of 98% of the human genome is composed of non-protein coding sequences with roles in the transcriptional and post-transcriptional regulation of gene expression. In this study, we characterized a divergent nuclear lncRNA (SOD1-DT) transcribed in the antisense direction from the 5' region of the SOD1 coding gene in both the SH-SY5Y cell line and fibroblasts derived from ALS patients. Interestingly, this lncRNA seems to regulate gene expression, since its inhibition leads to the upregulation of surrounding genes including SOD1. SOD1-DT represents a very complex molecule, displaying allelic and transcriptional variability concerning transposable elements (TEs) included in its sequence, widening the scenario of gene expression regulation in ALS disease.
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Affiliation(s)
- Marika Guerra
- Department of Neuroscience, Section of Human Anatomy, Catholic University of the Sacred Hearth, 00168 Rome, Italy; (L.M.); (C.S.)
- GSTeP-Organoids Research Core Facility, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Lucia Meola
- Department of Neuroscience, Section of Human Anatomy, Catholic University of the Sacred Hearth, 00168 Rome, Italy; (L.M.); (C.S.)
| | - Serena Lattante
- Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy;
| | - Amelia Conte
- Adult NEMO Clinical Center, Unit of Neurology, Department of Aging, Neurological, Orthopedic and Head-Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (A.C.); (M.S.)
| | - Mario Sabatelli
- Adult NEMO Clinical Center, Unit of Neurology, Department of Aging, Neurological, Orthopedic and Head-Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (A.C.); (M.S.)
- Section of Neurology, Department of Neuroscience, Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Claudio Sette
- Department of Neuroscience, Section of Human Anatomy, Catholic University of the Sacred Hearth, 00168 Rome, Italy; (L.M.); (C.S.)
- GSTeP-Organoids Research Core Facility, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Camilla Bernardini
- Department of Neuroscience, Section of Human Anatomy, Catholic University of the Sacred Hearth, 00168 Rome, Italy; (L.M.); (C.S.)
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15
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Haghani A, Li CZ, Robeck TR, Zhang J, Lu AT, Ablaeva J, Acosta-Rodríguez VA, Adams DM, Alagaili AN, Almunia J, Aloysius A, Amor NM, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter G, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chavez AS, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke S, Cook JA, Cooper LN, Cossette ML, Day J, DeYoung J, Dirocco S, Dold C, Dunnum JL, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Fei Z, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Goya RG, Grant MJ, Green CB, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Belmonte JCI, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaître JF, Levine AJ, Li X, Li C, Lim AR, Lin DTS, Lindemann DM, Liphardt SW, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Murphy WJ, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, Nyamsuren B, O’Brien JK, Ginn PO, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pedersen AB, Pellegrini M, Peters KJ, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Shafer AB, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmohammadi E, Spangler ML, Spriggs M, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Vu H, Wallingford MC, Wang N, Wilkinson GS, Williams RW, Yan Q, Yao M, Young BG, Zhang B, Zhang Z, Zhao Y, Zhao P, Zhou W, Zoller JA, Ernst J, Seluanov A, Gorbunova V, Yang XW, Raj K, Horvath S. DNA methylation networks underlying mammalian traits. Science 2023; 381:eabq5693. [PMID: 37561875 PMCID: PMC11180965 DOI: 10.1126/science.abq5693] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Using DNA methylation profiles (n = 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels in HOXL subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.
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Affiliation(s)
- Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Caesar Z. Li
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Janssen Research & Development, Spring House, PA, USA
| | - Todd R. Robeck
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Joshua Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ake T. Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Julia Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Victoria A. Acosta-Rodríguez
- Department of Neuroscience, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Danielle M. Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - Abdulaziz N. Alagaili
- Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Javier Almunia
- Loro Parque Fundacion, Avenida Loro Parque, Puerto de la Cruz, Tenerife, Spain
| | - Ajoy Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - Nabil M.S. Amor
- Laboratory of Biodiversity, Parasitology, and Ecology, University of Tunis El Manar, Tunis, Tunisia
| | - Reza Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Adriana Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C. Scott Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - Gareth Banks
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Science and Innovation Campus, Oxfordshire, UK
| | - Katherine Belov
- School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Nigel C. Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | | | - Daniel T. Blumstein
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
- The Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - Eleanor K. Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | | | | | - Janine L. Brown
- Center for Species Survival, Smithsonian National Zoo and Conservation Biology, Front Royal, VA, USA
| | - Gerald Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - Alex Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, Otago, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, Otago, New Zealand
| | - Julie M. Cavin
- Gulf World Marine Park - Dolphin Company, Panama City Beach, FL, USA
| | - Lisa Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - Ioulia Chatzistamou
- Department of Pathology, Microbiology & Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - Andreas S. Chavez
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
- Translational Data Analytics Institute, The Ohio State University, Columbus, OH, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Kaiyang Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Priscila Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Oi-Wa Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Shannon Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, Otago, New Zealand
| | - Joseph A. Cook
- University of New Mexico, Department of Biology and Museum of Southwestern Biology, Albuquerque, NM, USA
| | - Lisa N. Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - Marie-Laurence Cossette
- Department of Environmental & Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - Joanna Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - Joseph DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Christopher Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Jonathan L. Dunnum
- University of New Mexico, Department of Biology and Museum of Southwestern Biology, Albuquerque, NM, USA
| | | | - Candice K. Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Stephan Emmrich
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Ebru Erbay
- Altos Labs, Bay Area Institute of Science, Redwood City, CA, USA
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | | | - Chris G. Faulkes
- School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Zhe Fei
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, CA, USA
| | - Steven H. Ferguson
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - Carrie J. Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - Jean-Michel Gaillard
- University of Lyon, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - Eva Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - Livia Gerber
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia
- Australian National Wildlife Collection, CSIRO, Canberra, Australia
| | - Vadim N. Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Rodolfo G. Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Matthew J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Carla B. Green
- Department of Neuroscience, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M. Bradley Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Daniel W. Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | | | | | - Andrew N. Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Carolyn J. Hogg
- School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Timothy A. Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - Taosheng Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | | | - Anna J. Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Division of Infectious Diseases, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Molecular Genetics, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Gareth Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - Olga Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | | | | | - Vimala Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - Hippokratis Kiaris
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - Michael S. Kobor
- Edwin S. H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Pawel Kordowitzki
- Institute of Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | | | - Michael Krützen
- Evolutionary Genetics Group, Department of Anthropology, University of Zurich, Zurich, Switzerland
| | - Soo Bin Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Brenda Larison
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sang-Goo Lee
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Marianne Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Jean-François Lemaître
- University of Lyon, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - Andrew J. Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Xinmin Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Cun Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - Andrea R. Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - David T. S. Lin
- Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | - Thomas J. Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | | | | | | | - Julie A. Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - June Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - Jennifer J. Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin Madison, Madison, WI, USA
| | - Gisele A. Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - Jason Munshi-South
- Louis Calder Center - Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - William J. Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, TX, USA
| | - Asieh Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - Martina Nagy
- Museum fur Naturkunde, Leibniz-Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Pritika Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Peter W. Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - Ngoc B. Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Christof Niehrs
- Institute of Molecular Biology (IMB), Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | | | - Justine K. O’Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | | | - Duncan T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Deutsches Krebsforschungszentrum, Division of Regulatory Genomics and Cancer Evolution, Heidelberg, Germany
| | | | | | - Elaine A. Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kim M. Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Kimberly C. Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Amy B. Pedersen
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - Matteo Pellegrini
- Department Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Katharina J. Peters
- Evolutionary Genetics Group, Department of Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, New South Wales, Australia
| | | | - Darren W. Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - Gabriela M. Pinho
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Jocelyn Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jesse R. Poganik
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Natalia A. Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - Pradeep Reddy
- Altos Labs, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Benjamin Rey
- University of Lyon, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - Beate R. Ritz
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | | | | | | | - Elena Rydkina
- Department of Biology, University of Rochester, Rochester, NY, USA
| | | | - Adam B. Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio, and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - Kyle M. Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Dennis Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | | | | | - Lawrence B. Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Karen E. Sears
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Aaron B.A. Shafer
- Department of Forensic Science, Environmental & Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - Anastasia V. Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Kavita Singh
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM’S NMIMS University, Mumbai, India
| | - Ishani Sinha
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Jesse Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - Russel G. Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Elham Soltanmohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | | | | | | | | | - Karen J. Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - Donald T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | | | - Balazs Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - Joseph S. Takahashi
- Department of Neuroscience, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Masaki Takasugi
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Emma C. Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin, Ireland
| | - Michael J. Thompson
- Department Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Bill Van Bonn
- Animal Care and Science Division, John G. Shedd Aquarium, Chicago, IL, USA
| | - Sonja C. Vernes
- School of Biology, The University of St. Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
| | - Diego Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Harry V. Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ha Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Nan Wang
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Robert W. Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - Qi Yan
- Altos Labs, San Diego, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Mingjia Yao
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Bohan Zhang
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Zhihui Zhang
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Yang Zhao
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Peng Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Jason Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrei Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - Vera Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - X. William Yang
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
- Altos Labs, Cambridge, UK
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16
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Zhao P, Peng C, Fang L, Wang Z, Liu GE. Taming transposable elements in livestock and poultry: a review of their roles and applications. Genet Sel Evol 2023; 55:50. [PMID: 37479995 PMCID: PMC10362595 DOI: 10.1186/s12711-023-00821-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 06/30/2023] [Indexed: 07/23/2023] Open
Abstract
Livestock and poultry play a significant role in human nutrition by converting agricultural by-products into high-quality proteins. To meet the growing demand for safe animal protein, genetic improvement of livestock must be done sustainably while minimizing negative environmental impacts. Transposable elements (TE) are important components of livestock and poultry genomes, contributing to their genetic diversity, chromatin states, gene regulatory networks, and complex traits of economic value. However, compared to other species, research on TE in livestock and poultry is still in its early stages. In this review, we analyze 72 studies published in the past 20 years, summarize the TE composition in livestock and poultry genomes, and focus on their potential roles in functional genomics. We also discuss bioinformatic tools and strategies for integrating multi-omics data with TE, and explore future directions, feasibility, and challenges of TE research in livestock and poultry. In addition, we suggest strategies to apply TE in basic biological research and animal breeding. Our goal is to provide a new perspective on the importance of TE in livestock and poultry genomes.
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Affiliation(s)
- Pengju Zhao
- Hainan Institute of Zhejiang University, Hainan Sanya, 572000, China
- College of Animal Sciences, Zhejiang University, Zhejiang, Hangzhou, People's Republic of China
| | - Chen Peng
- Hainan Institute of Zhejiang University, Hainan Sanya, 572000, China
- College of Animal Sciences, Zhejiang University, Zhejiang, Hangzhou, People's Republic of China
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark.
| | - Zhengguang Wang
- Hainan Institute of Zhejiang University, Hainan Sanya, 572000, China.
- College of Animal Sciences, Zhejiang University, Zhejiang, Hangzhou, People's Republic of China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA.
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17
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Carotti E, Carducci F, Barucca M, Canapa A, Biscotti MA. Transposable Elements: Epigenetic Silencing Mechanisms or Modulating Tools for Vertebrate Adaptations? Two Sides of the Same Coin. Int J Mol Sci 2023; 24:11591. [PMID: 37511347 PMCID: PMC10380595 DOI: 10.3390/ijms241411591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023] Open
Abstract
Transposable elements constitute one of the main components of eukaryotic genomes. In vertebrates, they differ in content, typology, and family diversity and played a crucial role in the evolution of this taxon. However, due to their transposition ability, TEs can be responsible for genome instability, and thus silencing mechanisms were evolved to allow the coexistence between TEs and eukaryotic host-coding genes. Several papers are highlighting in TEs the presence of regulatory elements involved in regulating nearby genes in a tissue-specific fashion. This suggests that TEs are not sequences merely to silence; rather, they can be domesticated for the regulation of host-coding gene expression, permitting species adaptation and resilience as well as ensuring human health. This review presents the main silencing mechanisms acting in vertebrates and the importance of exploiting these mechanisms for TE control to rewire gene expression networks, challenging the general view of TEs as threatening elements.
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Affiliation(s)
| | - Federica Carducci
- Dipartimento di Scienze della Vita e dell’Ambiente, Università Politecnica delle Marche, 60131 Ancona, Italy; (E.C.); (M.B.); (A.C.); (M.A.B.)
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18
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Kocher AA, Dutrow EV, Uebbing S, Yim KM, Larios MFR, Baumgartner M, Nottoli T, Noonan JP. CpG island turnover events predict evolutionary changes in enhancer activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.09.540063. [PMID: 37214934 PMCID: PMC10197647 DOI: 10.1101/2023.05.09.540063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Genetic changes that modify the function of transcriptional enhancers have been linked to the evolution of biological diversity across species. Multiple studies have focused on the role of nucleotide substitutions, transposition, and insertions and deletions in altering enhancer function. Here we show that turnover of CpG islands (CGIs), which contribute to enhancer activation, is broadly associated with changes in enhancer activity across mammals, including humans. We integrated maps of CGIs and enhancer activity-associated histone modifications obtained from multiple tissues in nine mammalian species and found that CGI content in enhancers was strongly associated with increased histone modification levels. CGIs showed widespread turnover across species and species-specific CGIs were strongly enriched for enhancers exhibiting species-specific activity across all tissues and species we examined. Genes associated with enhancers with species-specific CGIs showed concordant biases in their expression, supporting that CGI turnover contributes to gene regulatory innovation. Our results also implicate CGI turnover in the evolution of Human Gain Enhancers (HGEs), which show increased activity in human embryonic development and may have contributed to the evolution of uniquely human traits. Using a humanized mouse model, we show that a highly conserved HGE with a large CGI absent from the mouse ortholog shows increased activity at the human CGI in the humanized mouse diencephalon. Collectively, our results point to CGI turnover as a mechanism driving gene regulatory changes potentially underlying trait evolution in mammals.
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Affiliation(s)
- Acadia A. Kocher
- Department of Genetics, Yale School of Medicine, New Haven CT 06510, USA
| | - Emily V. Dutrow
- Department of Genetics, Yale School of Medicine, New Haven CT 06510, USA
- Present address: Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Severin Uebbing
- Department of Genetics, Yale School of Medicine, New Haven CT 06510, USA
| | - Kristina M. Yim
- Department of Genetics, Yale School of Medicine, New Haven CT 06510, USA
| | | | | | - Timothy Nottoli
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT 06510, USA
- Yale Genome Editing Center, Yale School of Medicine, New Haven, CT 06510, USA
| | - James P. Noonan
- Department of Genetics, Yale School of Medicine, New Haven CT 06510, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06510, USA
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19
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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] [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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20
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Kaplow IM, Lawler AJ, Schäffer DE, Srinivasan C, Sestili HH, Wirthlin ME, Phan BN, Prasad K, Brown AR, Zhang X, Foley K, Genereux DP, Karlsson EK, Lindblad-Toh K, Meyer WK, Pfenning AR, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning. Science 2023; 380:eabm7993. [PMID: 37104615 DOI: 10.1126/science.abm7993] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.
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Affiliation(s)
- Irene M Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Daniel E Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Chaitanya Srinivasan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Heather H Sestili
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Morgan E Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - BaDoi N Phan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kavya Prasad
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ashley R Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Kathleen Foley
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Diane P Genereux
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elinor K Karlsson
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Kerstin Lindblad-Toh
- Broad Institute, Cambridge, MA, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
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21
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Andrews G, Fan K, Pratt HE, Phalke N, Karlsson EK, Lindblad-Toh K, Gazal S, Moore JE, Weng Z, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Mammalian evolution of human cis-regulatory elements and transcription factor binding sites. Science 2023; 380:eabn7930. [PMID: 37104580 DOI: 10.1126/science.abn7930] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Understanding the regulatory landscape of the human genome is a long-standing objective of modern biology. Using the reference-free alignment across 241 mammalian genomes produced by the Zoonomia Consortium, we charted evolutionary trajectories for 0.92 million human candidate cis-regulatory elements (cCREs) and 15.6 million human transcription factor binding sites (TFBSs). We identified 439,461 cCREs and 2,024,062 TFBSs under evolutionary constraint. Genes near constrained elements perform fundamental cellular processes, whereas genes near primate-specific elements are involved in environmental interaction, including odor perception and immune response. About 20% of TFBSs are transposable element-derived and exhibit intricate patterns of gains and losses during primate evolution whereas sequence variants associated with complex traits are enriched in constrained TFBSs. Our annotations illuminate the regulatory functions of the human genome.
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Affiliation(s)
- Gregory Andrews
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Henry E Pratt
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Nishigandha Phalke
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elinor K Karlsson
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kerstin Lindblad-Toh
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132 Uppsala, Sweden
| | - Steven Gazal
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
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22
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Vakirlis N, Vance Z, Duggan KM, McLysaght A. De novo birth of functional microproteins in the human lineage. Cell Rep 2022; 41:111808. [PMID: 36543139 PMCID: PMC10073203 DOI: 10.1016/j.celrep.2022.111808] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 06/21/2022] [Accepted: 11/18/2022] [Indexed: 12/24/2022] Open
Abstract
Small open reading frames (sORFs) can encode functional "microproteins" that perform crucial biological tasks. However, their size makes them less amenable to genomic analysis, and their origins and conservation are poorly understood. Given their short length, it is plausible that some of these functional microproteins have recently originated entirely de novo from noncoding sequences. Here we sought to identify such cases in the human lineage by reconstructing the evolutionary origins of human microproteins previously found to have measurable, statistically significant fitness effects. By tracing the formation of each ORF and its transcriptional activation, we show that novel microproteins with significant phenotypic effects have emerged de novo throughout animal evolution, including two after the human-chimpanzee split. Notably, traditional methods for assessing coding potential would miss most of these cases. This evidence demonstrates that the functional potential intrinsic to sORFs can be relatively rapidly and frequently realized through de novo gene emergence.
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Affiliation(s)
- Nikolaos Vakirlis
- Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center "Alexander Fleming", Vari, Greece.
| | - Zoe Vance
- Smurfit Institute of Genetics, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Kate M Duggan
- Smurfit Institute of Genetics, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Aoife McLysaght
- Smurfit Institute of Genetics, Trinity College Dublin, University of Dublin, Dublin, Ireland.
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23
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Chen S, Liu S, Shi S, Jiang Y, Cao M, Tang Y, Li W, Liu J, Fang L, Yu Y, Zhang S. Comparative epigenomics reveals the impact of ruminant-specific regulatory elements on complex traits. BMC Biol 2022; 20:273. [PMID: 36482458 PMCID: PMC9730597 DOI: 10.1186/s12915-022-01459-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 11/07/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Insights into the genetic basis of complex traits and disease in both human and livestock species have been achieved over the past decade through detection of genetic variants in genome-wide association studies (GWAS). A majority of such variants were found located in noncoding genomic regions, and though the involvement of numerous regulatory elements (REs) has been predicted across multiple tissues in domesticated animals, their evolutionary conservation and effects on complex traits have not been fully elucidated, particularly in ruminants. Here, we systematically analyzed 137 epigenomic and transcriptomic datasets of six mammals, including cattle, sheep, goats, pigs, mice, and humans, and then integrated them with large-scale GWAS of complex traits. RESULTS Using 40 ChIP-seq datasets of H3K4me3 and H3K27ac, we detected 68,479, 58,562, 63,273, 97,244, 111,881, and 87,049 REs in the liver of cattle, sheep, goats, pigs, humans and mice, respectively. We then systematically characterized the dynamic functional landscapes of these REs by integrating multi-omics datasets, including gene expression, chromatin accessibility, and DNA methylation. We identified a core set (n = 6359) of ruminant-specific REs that are involved in liver development, metabolism, and immune processes. Genes with more complex cis-REs exhibited higher gene expression levels and stronger conservation across species. Furthermore, we integrated expression quantitative trait loci (eQTLs) and GWAS from 44 and 52 complex traits/diseases in cattle and humans, respectively. These results demonstrated that REs with different degrees of evolutionary conservation across species exhibited distinct enrichments for GWAS signals of complex traits. CONCLUSIONS We systematically annotated genome-wide functional REs in liver across six mammals and demonstrated the evolution of REs and their associations with transcriptional output and conservation. Detecting lineage-specific REs allows us to decipher the evolutionary and genetic basis of complex phenotypes in livestock and humans, which may benefit the discovery of potential biomedical models for functional variants and genes of specific human diseases.
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Affiliation(s)
- Siqian Chen
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Shuli Liu
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China ,grid.494629.40000 0004 8008 9315 School of Life Sciences, Westlake University, Hangzhou, China
| | - Shaolei Shi
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yifan Jiang
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Mingyue Cao
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yongjie Tang
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Wenlong Li
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jianfeng Liu
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lingzhao Fang
- grid.4305.20000 0004 1936 7988MRC Human Genetics Unit at the Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK ,grid.7048.b0000 0001 1956 2722Center for Quantitative Genetics and Genomics (QGG), Aarhus University, Aarhus, Denmark
| | - Ying Yu
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Shengli Zhang
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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24
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Premont A, Saadeh K, Edling C, Lewis R, Marr CM, Jeevaratnam K. Cardiac ion channel expression in the equine model - In-silico prediction utilising RNA sequencing data from mixed tissue samples. Physiol Rep 2022; 10:e15273. [PMID: 35880716 PMCID: PMC9316921 DOI: 10.14814/phy2.15273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/19/2022] [Accepted: 04/03/2022] [Indexed: 06/15/2023] Open
Abstract
Understanding cardiomyocyte ion channel expression is crucial to understanding normal cardiac electrophysiology and underlying mechanisms of cardiac pathologies particularly arrhythmias. Hitherto, equine cardiac ion channel expression has rarely been investigated. Therefore, we aim to predict equine cardiac ion channel gene expression. Raw RNAseq data from normal horses from 9 datasets was retrieved from ArrayExpress and European Nucleotide Archive and reanalysed. The normalised (FPKM) read counts for a gene in a mix of tissue were hypothesised to be the average of the expected expression in each tissue weighted by the proportion of the tissue in the mix. The cardiac-specific expression was predicted by estimating the mean expression in each other tissues. To evaluate the performance of the model, predicted gene expression values were compared to the human cardiac gene expression. Cardiac-specific expression could be predicted for 91 ion channels including most expressed Na+ channels, K+ channels and Ca2+ -handling proteins. These revealed interesting differences from what would be expected based on human studies. These differences included predominance of NaV 1.4 rather than NaV 1.5 channel, and RYR1, SERCA1 and CASQ1 rather than RYR2, SERCA2, CASQ2 Ca2+ -handling proteins. Differences in channel expression not only implicate potentially different regulatory mechanisms but also pathological mechanisms of arrhythmogenesis.
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Affiliation(s)
- Antoine Premont
- Faculty of Health and Medical SciencesUniversity of SurreyGuildfordSurreyUK
| | - Khalil Saadeh
- Faculty of Health and Medical SciencesUniversity of SurreyGuildfordSurreyUK
- School of Clinical MedicineUniversity of CambridgeCambridgeUK
| | - Charlotte Edling
- Faculty of Health and Medical SciencesUniversity of SurreyGuildfordSurreyUK
| | - Rebecca Lewis
- Faculty of Health and Medical SciencesUniversity of SurreyGuildfordSurreyUK
| | - Celia M. Marr
- Faculty of Health and Medical SciencesUniversity of SurreyGuildfordSurreyUK
- School of Clinical MedicineUniversity of CambridgeCambridgeUK
- Rossdales Equine Hospital and Diagnostic CentreExningSuffolkUK
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25
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The Role of Transposable Elements of the Human Genome in Neuronal Function and Pathology. Int J Mol Sci 2022; 23:ijms23105847. [PMID: 35628657 PMCID: PMC9148063 DOI: 10.3390/ijms23105847] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 05/17/2022] [Accepted: 05/19/2022] [Indexed: 12/13/2022] Open
Abstract
Transposable elements (TEs) have been extensively studied for decades. In recent years, the introduction of whole-genome and whole-transcriptome approaches, as well as single-cell resolution techniques, provided a breakthrough that uncovered TE involvement in host gene expression regulation underlying multiple normal and pathological processes. Of particular interest is increased TE activity in neuronal tissue, and specifically in the hippocampus, that was repeatedly demonstrated in multiple experiments. On the other hand, numerous neuropathologies are associated with TE dysregulation. Here, we provide a comprehensive review of literature about the role of TEs in neurons published over the last three decades. The first chapter of the present review describes known mechanisms of TE interaction with host genomes in general, with the focus on mammalian and human TEs; the second chapter provides examples of TE exaptation in normal neuronal tissue, including TE involvement in neuronal differentiation and plasticity; and the last chapter lists TE-related neuropathologies. We sought to provide specific molecular mechanisms of TE involvement in neuron-specific processes whenever possible; however, in many cases, only phenomenological reports were available. This underscores the importance of further studies in this area.
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26
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A retrotransposon storm marks clinical phenoconversion to late-onset Alzheimer's disease. GeroScience 2022; 44:1525-1550. [PMID: 35585302 PMCID: PMC9213607 DOI: 10.1007/s11357-022-00580-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 04/26/2022] [Indexed: 12/03/2022] Open
Abstract
Recent reports have suggested that the reactivation of otherwise transcriptionally silent transposable elements (TEs) might induce brain degeneration, either by dysregulating the expression of genes and pathways implicated in cognitive decline and dementia or through the induction of immune-mediated neuroinflammation resulting in the elimination of neural and glial cells. In the work we present here, we test the hypothesis that differentially expressed TEs in blood could be used as biomarkers of cognitive decline and development of AD. To this aim, we used a sample of aging subjects (age > 70) that developed late-onset Alzheimer’s disease (LOAD) over a relatively short period of time (12–48 months), for which blood was available before and after their phenoconversion, and a group of cognitive stable subjects as controls. We applied our developed and validated customized pipeline that allows the identification, characterization, and quantification of the differentially expressed (DE) TEs before and after the onset of manifest LOAD, through analyses of RNA-Seq data. We compared the level of DE TEs within more than 600,000 TE-mapping RNA transcripts from 25 individuals, whose specimens we obtained before and after their phenotypic conversion (phenoconversion) to LOAD, and discovered that 1790 TE transcripts showed significant expression differences between these two timepoints (logFC ± 1.5, logCMP > 5.3, nominal p value < 0.01). These DE transcripts mapped both over- and under-expressed TE elements. Occurring before the clinical phenoconversion, this TE storm features significant increases in DE transcripts of LINEs, LTRs, and SVAs, while those for SINEs are significantly depleted. These dysregulations end with signs of manifest LOAD. This set of highly DE transcripts generates a TE transcriptional profile that accurately discriminates the before and after phenoconversion states of these subjects. Our findings suggest that a storm of DE TEs occurs before phenoconversion from normal cognition to manifest LOAD in risk individuals compared to controls, and may provide useful blood-based biomarkers for heralding such a clinical transition, also suggesting that TEs can indeed participate in the complex process of neurodegeneration.
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27
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Simonsen L, Lau J, Kruse T, Guo T, McGuire J, Jeppesen JF, Niss K, Sauerberg P, Raun K, Dornonville de la Cour C. Preclinical evaluation of a protracted GLP-1/glucagon receptor co-agonist: Translational difficulties and pitfalls. PLoS One 2022; 17:e0264974. [PMID: 35245328 PMCID: PMC8896685 DOI: 10.1371/journal.pone.0264974] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 02/19/2022] [Indexed: 12/13/2022] Open
Abstract
During recent years combining GLP-1 and glucagon receptor agonism with the purpose of achieving superior weight loss and metabolic control compared to GLP-1 alone has received much attention. The superior efficacy has been shown by several in preclinical models but has been difficult to reproduce in humans. In this paper, we present the pre-clinical evaluation of NN1177, a long-acting GLP-1/glucagon receptor co-agonist previously tested in clinical trials. To further investigate the contribution from the respective receptors, two other co-agonists (NN1151, NN1359) with different GLP-1-to-glucagon receptor ratios were evaluated in parallel. In the process of characterizing NN1177, species differences and pitfalls in traditional pre-clinical evaluation methods were identified, highlighting the translational challenges in predicting the optimal receptor balance in humans. In diet-induced obese (DIO) mice, NN1177 induced a dose-dependent body weight loss, primarily due to loss of fat mass, and improvement in glucose tolerance. In DIO rats, NN1177 induced a comparable total body weight reduction, which was in contrast mainly caused by loss of lean mass, and glucose tolerance was impaired. Furthermore, despite long half-lives of the three co-agonists, glucose control during steady state was seen to depend on compound exposure at time of evaluation. When evaluated at higher compound exposure, glucose tolerance was similarly improved for all three co-agonists, independent of receptor balance. However, at lower compound exposure, glucose tolerance was gradually impaired with higher glucagon receptor preference. In addition, glucose tolerance was found to depend on study duration where the effect of glucagon on glucose control became more evident with time. To conclude, the pharmacodynamic effects at a given GLP-1-to-glucagon ratio differs between species, depends on compound exposure and study length, complicating the identification of an optimally balanced clinical candidate. The present findings could partly explain the low number of clinical successes for this dual agonism.
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Affiliation(s)
- Lotte Simonsen
- Global Obesity & Liver Disease Research, Novo Nordisk A/S, Måløv, Denmark
| | - Jesper Lau
- Research Chemistry, Novo Nordisk A/S, Måløv, Denmark
| | - Thomas Kruse
- Research Chemistry, Novo Nordisk A/S, Måløv, Denmark
| | - Tingqing Guo
- Discovery Biology, Novo Nordisk Research Centre, Beijing, China
| | - Jim McGuire
- Incretin Biology, Novo Nordisk A/S, Måløv, Denmark
| | | | - Kristoffer Niss
- Bioinformatics & Data Mining, Novo Nordisk A/S, Måløv, Denmark
| | - Per Sauerberg
- Project and Alliance Management, Novo Nordisk A/S, Måløv, Denmark
| | - Kirsten Raun
- Global Obesity & Liver Disease Research, Novo Nordisk A/S, Måløv, Denmark
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28
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Kaplow IM, Schäffer DE, Wirthlin ME, Lawler AJ, Brown AR, Kleyman M, Pfenning AR. Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin. BMC Genomics 2022; 23:291. [PMID: 35410163 PMCID: PMC8996547 DOI: 10.1186/s12864-022-08450-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 03/07/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation of many enhancers, distal regulatory elements that control spatial and temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high. RESULTS We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that can predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Next, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss of regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity have a stronger tendency than the general population to have predicted lineage-specific open chromatin. CONCLUSION The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.
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Affiliation(s)
- Irene M Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA. .,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Daniel E Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Morgan E Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA.,Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ashley R Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Michael Kleyman
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA. .,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA. .,Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA.
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29
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Almeida MV, Vernaz G, Putman AL, Miska EA. Taming transposable elements in vertebrates: from epigenetic silencing to domestication. Trends Genet 2022; 38:529-553. [DOI: 10.1016/j.tig.2022.02.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 02/14/2022] [Accepted: 02/15/2022] [Indexed: 12/20/2022]
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30
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Stephan T, Burgess SM, Cheng H, Danko CG, Gill CA, Jarvis ED, Koepfli KP, Koltes JE, Lyons E, Ronald P, Ryder OA, Schriml LM, Soltis P, VandeWoude S, Zhou H, Ostrander EA, Karlsson EK. Darwinian genomics and diversity in the tree of life. Proc Natl Acad Sci U S A 2022; 119:e2115644119. [PMID: 35042807 PMCID: PMC8795533 DOI: 10.1073/pnas.2115644119] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Genomics encompasses the entire tree of life, both extinct and extant, and the evolutionary processes that shape this diversity. To date, genomic research has focused on humans, a small number of agricultural species, and established laboratory models. Fewer than 18,000 of ∼2,000,000 eukaryotic species (<1%) have a representative genome sequence in GenBank, and only a fraction of these have ancillary information on genome structure, genetic variation, gene expression, epigenetic modifications, and population diversity. This imbalance reflects a perception that human studies are paramount in disease research. Yet understanding how genomes work, and how genetic variation shapes phenotypes, requires a broad view that embraces the vast diversity of life. We have the technology to collect massive and exquisitely detailed datasets about the world, but expertise is siloed into distinct fields. A new approach, integrating comparative genomics with cell and evolutionary biology, ecology, archaeology, anthropology, and conservation biology, is essential for understanding and protecting ourselves and our world. Here, we describe potential for scientific discovery when comparative genomics works in close collaboration with a broad range of fields as well as the technical, scientific, and social constraints that must be addressed.
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Affiliation(s)
- Taylorlyn Stephan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20817
| | - Shawn M Burgess
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20817
| | - Hans Cheng
- Avian Disease and Oncology Laboratory, Agricultural Research Service, US Department of Agriculture, East Lansing, MI 48823
| | - Charles G Danko
- Department of Biomedical Sciences, Baker Institute for Animal Health, Cornell University, Ithaca, NY 14850
| | - Clare A Gill
- Department of Animal Science, Texas A&M University, College Station, TX 77843
| | - Erich D Jarvis
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY 10065
- HHMI, Chevy Chase, MD 20815
| | - Klaus-Peter Koepfli
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630
- Smithsonian Conservation Biology Institute, National Zoological Park, Washington, DC 20008
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA 50011
| | - Eric Lyons
- School of Plant Sciences, BIO5 Institute, University of Arizona, Tucson, AZ 85721
| | - Pamela Ronald
- Department of Plant Pathology, University of California, Davis, CA 95616
- The Genome Center, University of California, Davis, CA 95616
- The Innovative Genomics Institute, University of California, Berkeley, CA 94720
- Grass Genetics, Joint Bioenergy Institute, Emeryville, CA 94608
| | - Oliver A Ryder
- San Diego Zoo Wildlife Alliance, Escondido, CA 92027
- Department of Evolution, Behavior, and Ecology, University of California San Diego, La Jolla, CA 92093
| | - Lynn M Schriml
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201
| | - Pamela Soltis
- Florida Museum of Natural History, University of Florida, Gainesville, FL 32611
| | - Sue VandeWoude
- Department of Micro-, Immuno-, and Pathology, Colorado State University, Fort Collins, CO 80532
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, CA 95616
| | - Elaine A Ostrander
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20817
| | - Elinor K Karlsson
- Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01655;
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01655
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
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31
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Farrell CM, Goldfarb T, Rangwala SH, Astashyn A, Ermolaeva OD, Hem V, Katz KS, Kodali VK, Ludwig F, Wallin CL, Pruitt KD, Murphy TD. RefSeq Functional Elements as experimentally assayed nongenic reference standards and functional interactions in human and mouse. Genome Res 2022; 32:175-188. [PMID: 34876495 PMCID: PMC8744684 DOI: 10.1101/gr.275819.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 12/02/2021] [Indexed: 11/25/2022]
Abstract
Eukaryotic genomes contain many nongenic elements that function in gene regulation, chromosome organization, recombination, repair, or replication, and mutation of those elements can affect genome function and cause disease. Although numerous epigenomic studies provide high coverage of gene regulatory regions, those data are not usually exposed in traditional genome annotation and can be difficult to access and interpret without field-specific expertise. The National Center for Biotechnology Information (NCBI) therefore provides RefSeq Functional Elements (RefSeqFEs), which represent experimentally validated human and mouse nongenic elements derived from the literature. The curated data set is comprised of richly annotated sequence records, descriptive records in the NCBI Gene database, reference genome feature annotation, and activity-based interactions between nongenic regions, target genes, and each other. The data set provides succinct functional details and transparent experimental evidence, leverages data from multiple experimental sources, is readily accessible and adaptable, and uses a flexible data model. The data have multiple uses for basic functional discovery, bioinformatics studies, genetic variant interpretation; as known positive controls for epigenomic data evaluation; and as reference standards for functional interactions. Comparisons to other gene regulatory data sets show that the RefSeqFE data set includes a wider range of feature types representing more areas of biology, but it is comparatively smaller and subject to data selection biases. RefSeqFEs thus provide an alternative and complementary resource for experimentally assayed functional elements, with future data set growth expected.
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Affiliation(s)
- Catherine M Farrell
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Tamara Goldfarb
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Sanjida H Rangwala
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Alexander Astashyn
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Olga D Ermolaeva
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Vichet Hem
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Kenneth S Katz
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Vamsi K Kodali
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Frank Ludwig
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Craig L Wallin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Kim D Pruitt
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Terence D Murphy
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
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32
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Playfoot CJ, Duc J, Sheppard S, Dind S, Coudray A, Planet E, Trono D. Transposable elements and their KZFP controllers are drivers of transcriptional innovation in the developing human brain. Genome Res 2021; 31:1531-1545. [PMID: 34400477 PMCID: PMC8415367 DOI: 10.1101/gr.275133.120] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Accepted: 07/15/2021] [Indexed: 11/25/2022]
Abstract
Transposable elements (TEs) account for more than 50% of the human genome and many have been co-opted throughout evolution to provide regulatory functions for gene expression networks. Several lines of evidence suggest that these networks are fine-tuned by the largest family of TE controllers, the KRAB-containing zinc finger proteins (KZFPs). One tissue permissive for TE transcriptional activation (termed "transposcription") is the adult human brain, however comprehensive studies on the extent of this process and its potential contribution to human brain development are lacking. To elucidate the spatiotemporal transposcriptome of the developing human brain, we have analyzed two independent RNA-seq data sets encompassing 16 brain regions from eight weeks postconception into adulthood. We reveal a distinct KZFP:TE transcriptional profile defining the late prenatal to early postnatal transition, and the spatiotemporal and cell type-specific activation of TE-derived alternative promoters driving the expression of neurogenesis-associated genes. Long-read sequencing confirmed these TE-driven isoforms as significant contributors to neurogenic transcripts. We also show experimentally that a co-opted antisense L2 element drives temporal protein relocalization away from the endoplasmic reticulum, suggestive of novel TE dependent protein function in primate evolution. This work highlights the widespread dynamic nature of the spatiotemporal KZFP:TE transcriptome and its importance throughout TE mediated genome innovation and neurotypical human brain development. To facilitate interactive exploration of these spatiotemporal gene and TE expression dynamics, we provide the "Brain TExplorer" web application freely accessible for the community.
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Affiliation(s)
- Christopher J Playfoot
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Julien Duc
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Shaoline Sheppard
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Sagane Dind
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Alexandre Coudray
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Evarist Planet
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Didier Trono
- School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
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Sarropoulos I, Sepp M, Frömel R, Leiss K, Trost N, Leushkin E, Okonechnikov K, Joshi P, Giere P, Kutscher LM, Cardoso-Moreira M, Pfister SM, Kaessmann H. Developmental and evolutionary dynamics of cis-regulatory elements in mouse cerebellar cells. Science 2021; 373:eabg4696. [PMID: 34446581 PMCID: PMC7611596 DOI: 10.1126/science.abg4696] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 07/14/2021] [Indexed: 12/13/2022]
Abstract
Organ development is orchestrated by cell- and time-specific gene regulatory networks. In this study, we investigated the regulatory basis of mouse cerebellum development from early neurogenesis to adulthood. By acquiring snATAC-seq (single-nucleus assay for transposase accessible chromatin using sequencing) profiles for ~90,000 cells spanning 11 stages, we mapped cerebellar cell types and identified candidate cis-regulatory elements (CREs). We detected extensive spatiotemporal heterogeneity among progenitor cells and a gradual divergence in the regulatory programs of cerebellar neurons during differentiation. Comparisons to vertebrate genomes and snATAC-seq profiles for ∼20,000 cerebellar cells from the marsupial opossum revealed a shared decrease in CRE conservation during development and differentiation as well as differences in constraint between cell types. Our work delineates the developmental and evolutionary dynamics of gene regulation in cerebellar cells and provides insights into mammalian organ development.
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Affiliation(s)
- Ioannis Sarropoulos
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany.
| | - Mari Sepp
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany.
| | - Robert Frömel
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
| | - Kevin Leiss
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
| | - Nils Trost
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
| | - Evgeny Leushkin
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
| | - Konstantin Okonechnikov
- Hopp Children's Cancer Center (KiTZ) Heidelberg, Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), and German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany
| | - Piyush Joshi
- Hopp Children's Cancer Center (KiTZ) Heidelberg, Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), and German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany
| | - Peter Giere
- Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Lena M Kutscher
- Hopp Children's Cancer Center (KiTZ) Heidelberg, Developmental Origins of Pediatric Cancer Group, German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany
| | - Margarida Cardoso-Moreira
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
- Evolutionary Developmental Biology Laboratory, Francis Crick Institute, London NW1 1AT, UK
| | - Stefan M Pfister
- Hopp Children's Cancer Center (KiTZ) Heidelberg, Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), and German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany.
- Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Henrik Kaessmann
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany.
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Ferrari R, Grandi N, Tramontano E, Dieci G. Retrotransposons as Drivers of Mammalian Brain Evolution. Life (Basel) 2021; 11:life11050376. [PMID: 33922141 PMCID: PMC8143547 DOI: 10.3390/life11050376] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 04/20/2021] [Accepted: 04/21/2021] [Indexed: 12/11/2022] Open
Abstract
Retrotransposons, a large and diverse class of transposable elements that are still active in humans, represent a remarkable force of genomic innovation underlying mammalian evolution. Among the features distinguishing mammals from all other vertebrates, the presence of a neocortex with a peculiar neuronal organization, composition and connectivity is perhaps the one that, by affecting the cognitive abilities of mammals, contributed mostly to their evolutionary success. Among mammals, hominids and especially humans display an extraordinarily expanded cortical volume, an enrichment of the repertoire of neural cell types and more elaborate patterns of neuronal connectivity. Retrotransposon-derived sequences have recently been implicated in multiple layers of gene regulation in the brain, from transcriptional and post-transcriptional control to both local and large-scale three-dimensional chromatin organization. Accordingly, an increasing variety of neurodevelopmental and neurodegenerative conditions are being recognized to be associated with retrotransposon dysregulation. We review here a large body of recent studies lending support to the idea that retrotransposon-dependent evolutionary novelties were crucial for the emergence of mammalian, primate and human peculiarities of brain morphology and function.
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Affiliation(s)
- Roberto Ferrari
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy;
| | - Nicole Grandi
- Laboratory of Molecular Virology, Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, 09042 Monserrato, Italy; (N.G.); (E.T.)
| | - Enzo Tramontano
- Laboratory of Molecular Virology, Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, 09042 Monserrato, Italy; (N.G.); (E.T.)
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042 Monserrato, Italy
| | - Giorgio Dieci
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, 43124 Parma, Italy;
- Correspondence:
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