1
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Cahill JA, Smith LA, Gottipati S, Torabi TS, Graim K. Bringing the Genomic Revolution to Comparative Oncology: Human and Dog Cancers. Annu Rev Biomed Data Sci 2024; 7:107-129. [PMID: 38648188 PMCID: PMC11343685 DOI: 10.1146/annurev-biodatasci-102423-111936] [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] [Indexed: 04/25/2024]
Abstract
Dogs are humanity's oldest friend, the first species we domesticated 20,000-40,000 years ago. In this unequaled collaboration, dogs have inadvertently but serendipitously been molded into a potent human cancer model. Unlike many common model species, dogs are raised in the same environment as humans and present with spontaneous tumors with human-like comorbidities, immunocompetency, and heterogeneity. In breast, bladder, blood, and several pediatric cancers, in-depth profiling of dog and human tumors has established the benefits of the dog model. In addition to this clinical and molecular similarity, veterinary studies indicate that domestic dogs have relatively high tumor incidence rates. As a result, there are a plethora of data for analysis, the statistical power of which is bolstered by substantial breed-specific variability. As such, dog tumors provide a unique opportunity to interrogate the molecular factors underpinning cancer and facilitate the modeling of new therapeutic targets. This review discusses the emerging field of comparative oncology, how it complements human and rodent cancer studies, and where challenges remain, given the rapid proliferation of genomic resources. Increasingly, it appears that human's best friend is becoming an irreplaceable component of oncology research.
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Affiliation(s)
- James A Cahill
- University of Florida Genetics Institute, University of Florida, Gainesville, Florida, USA;
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USA
| | - Leslie A Smith
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, USA
| | - Soumya Gottipati
- Department of Computer Science, Princeton University, Princeton, New Jersey, USA
| | - Tina Salehi Torabi
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, USA
| | - Kiley Graim
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, USA
- University of Florida Health Cancer Center, University of Florida, Gainesville, Florida, USA
- University of Florida Genetics Institute, University of Florida, Gainesville, Florida, USA;
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2
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Chucair-Elliott AJ, Ocañas SR, Pham K, Machalinski A, Plafker S, Stout MB, Elliott MH, Freeman WM. Age- and sex- divergent translatomic responses of the mouse retinal pigmented epithelium. Neurobiol Aging 2024; 140:41-59. [PMID: 38723422 PMCID: PMC11173338 DOI: 10.1016/j.neurobiolaging.2024.04.012] [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: 10/24/2023] [Revised: 04/22/2024] [Accepted: 04/23/2024] [Indexed: 05/18/2024]
Abstract
Aging is the main risk factor for age-related macular degeneration (AMD), a retinal neurodegenerative disease that leads to irreversible blindness, particularly in people over 60 years old. Retinal pigmented epithelium (RPE) atrophy is an AMD hallmark. Genome-wide chromatin accessibility, DNA methylation, and gene expression studies of AMD and control RPE demonstrate epigenomic/transcriptomic changes occur during AMD onset and progression. However, mechanisms by which molecular alterations of normal aging impair RPE function and contribute to AMD pathogenesis are unclear. Here, we specifically interrogate the RPE translatome with advanced age and across sexes in a novel RPE reporter mouse model. We find differential age- and sex- associated transcript expression with overrepresentation of pathways related to inflammation in the RPE. Concordant with impaired RPE function, the phenotypic changes in the aged translatome suggest that aged RPE becomes immunologically active, in both males and females, with some sex-specific signatures, which supports the need for sex representation for in vivo studies.
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Affiliation(s)
- Ana J Chucair-Elliott
- Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA.
| | - Sarah R Ocañas
- Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Kevin Pham
- Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Adeline Machalinski
- Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Scott Plafker
- Aging & Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Michael B Stout
- Aging & Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Michael H Elliott
- Department of Physiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Department of Ophthalmology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Willard M Freeman
- Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA; Oklahoma City Veterans Affairs Medical Center, Oklahoma City, OK, USA.
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3
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Cacheiro P, Pava D, Parkinson H, VanZanten M, Wilson R, Gunes O, The International Mouse Phenotyping Consortium, Smedley D. Computational identification of disease models through cross-species phenotype comparison. Dis Model Mech 2024; 17:dmm050604. [PMID: 38881316 PMCID: PMC11247498 DOI: 10.1242/dmm.050604] [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: 11/13/2023] [Accepted: 06/11/2024] [Indexed: 06/18/2024] Open
Abstract
The use of standardised phenotyping screens to identify abnormal phenotypes in mouse knockouts, together with the use of ontologies to describe such phenotypic features, allows the implementation of an automated and unbiased pipeline to identify new models of disease by performing phenotype comparisons across species. Using data from the International Mouse Phenotyping Consortium (IMPC), approximately half of mouse mutants are able to mimic, at least partially, the human ortholog disease phenotypes as computed by the PhenoDigm algorithm. We found the number of phenotypic abnormalities in the mouse and the corresponding Mendelian disorder, the pleiotropy and severity of the disease, and the viability and zygosity status of the mouse knockout to be associated with the ability of mouse models to recapitulate the human disorder. An analysis of the IMPC impact on disease gene discovery through a publication-tracking system revealed that the resource has been implicated in at least 109 validated rare disease-gene associations over the last decade.
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Affiliation(s)
- Pilar Cacheiro
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Diego Pava
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Helen Parkinson
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Maya VanZanten
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Robert Wilson
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Osman Gunes
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | - Damian Smedley
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
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4
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Krarup J, Araya L, Álvarez F, Bórquez DA, Urrutia PJ. A Brain Anti-Senescence Transcriptional Program Triggered by Hypothalamic-Derived Exosomal microRNAs. Int J Mol Sci 2024; 25:5467. [PMID: 38791505 PMCID: PMC11122052 DOI: 10.3390/ijms25105467] [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: 03/14/2024] [Revised: 05/08/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
In contrast to the hypothesis that aging results from cell-autonomous deterioration processes, the programmed longevity theory proposes that aging arises from a partial inactivation of a "longevity program" aimed at maintaining youthfulness in organisms. Supporting this hypothesis, age-related changes in organisms can be reversed by factors circulating in young blood. Concordantly, the endocrine secretion of exosomal microRNAs (miRNAs) by hypothalamic neural stem cells (htNSCs) regulates the aging rate by enhancing physiological fitness in young animals. However, the specific molecular mechanisms through which hypothalamic-derived miRNAs exert their anti-aging effects remain unexplored. Using experimentally validated miRNA-target gene interactions and single-cell transcriptomic data of brain cells during aging and heterochronic parabiosis, we identify the main pathways controlled by these miRNAs and the cell-type-specific gene networks that are altered due to age-related loss of htNSCs and the subsequent decline in specific miRNA levels in the cerebrospinal fluid (CSF). Our bioinformatics analysis suggests that these miRNAs modulate pathways associated with senescence and cellular stress response, targeting crucial genes such as Cdkn2a, Rps27, and Txnip. The oligodendrocyte lineage appears to be the most responsive to age-dependent loss of exosomal miRNA, leading to significant derepression of several miRNA target genes. Furthermore, heterochronic parabiosis can reverse age-related upregulation of specific miRNA-targeted genes, predominantly in brain endothelial cells, including senescence promoting genes such as Cdkn1a and Btg2. Our findings support the presence of an anti-senescence mechanism triggered by the endocrine secretion of htNSC-derived exosomal miRNAs, which is associated with a youthful transcriptional signature.
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Affiliation(s)
- Josefa Krarup
- Laboratory of Cell Signaling & Bioinformatics, Center for Biomedical Research, Faculty of Medicine, Universidad Diego Portales, Ejército Libertador 141, Santiago 8370007, Chile; (J.K.); (F.Á.)
| | - Lucas Araya
- Department of Biology, Faculty of Sciences, Universidad de Chile, Santiago 7810000, Chile;
| | - Felipe Álvarez
- Laboratory of Cell Signaling & Bioinformatics, Center for Biomedical Research, Faculty of Medicine, Universidad Diego Portales, Ejército Libertador 141, Santiago 8370007, Chile; (J.K.); (F.Á.)
| | - Daniel A. Bórquez
- Laboratory of Cell Signaling & Bioinformatics, Center for Biomedical Research, Faculty of Medicine, Universidad Diego Portales, Ejército Libertador 141, Santiago 8370007, Chile; (J.K.); (F.Á.)
| | - Pamela J. Urrutia
- Laboratory of Resilient Aging, Institute for Nutrition & Food Technology (INTA), Universidad de Chile, El Líbano 5524, Santiago 7830490, Chile
- Geroscience Center for Brain Health and Metabolism, Santiago 7800003, Chile
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5
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Olmos V, Thompson EN, Gogia N, Luttik K, Veeranki V, Ni L, Sim S, Chen K, Krause DS, Lim J. Dysregulation of alternative splicing in spinocerebellar ataxia type 1. Hum Mol Genet 2024; 33:138-149. [PMID: 37802886 PMCID: PMC10979408 DOI: 10.1093/hmg/ddad170] [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: 06/30/2023] [Revised: 09/29/2023] [Accepted: 10/02/2023] [Indexed: 10/08/2023] Open
Abstract
Spinocerebellar ataxia type 1 is caused by an expansion of the polyglutamine tract in ATAXIN-1. Ataxin-1 is broadly expressed throughout the brain and is involved in regulating gene expression. However, it is not yet known if mutant ataxin-1 can impact the regulation of alternative splicing events. We performed RNA sequencing in mouse models of spinocerebellar ataxia type 1 and identified that mutant ataxin-1 expression abnormally leads to diverse splicing events in the mouse cerebellum of spinocerebellar ataxia type 1. We found that the diverse splicing events occurred in a predominantly cell autonomous manner. A majority of the transcripts with misregulated alternative splicing events were previously unknown, thus allowing us to identify overall new biological pathways that are distinctive to those affected by differential gene expression in spinocerebellar ataxia type 1. We also provide evidence that the splicing factor Rbfox1 mediates the effect of mutant ataxin-1 on misregulated alternative splicing and that genetic manipulation of Rbfox1 expression modifies neurodegenerative phenotypes in a Drosophila model of spinocerebellar ataxia type 1 in vivo. Together, this study provides novel molecular mechanistic insight into the pathogenesis of spinocerebellar ataxia type 1 and identifies potential therapeutic strategies for spinocerebellar ataxia type 1.
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Affiliation(s)
- Victor Olmos
- Department of Genetics, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, United States
| | - Evrett N Thompson
- Department of Cell Biology, Yale School of Medicine, 10 Amistad Street, New Haven, CT 06510, United States
- Yale Stem Cell Center, Yale School of Medicine, 10 Amistad Street, New Haven, CT 06510, United States
| | - Neha Gogia
- Department of Genetics, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, United States
| | - Kimberly Luttik
- Interdepartmental Neuroscience Program, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, United States
- Department of Neuroscience, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, USA
| | - Vaishnavi Veeranki
- Department of Genetics, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, United States
| | - Luhan Ni
- Department of Genetics, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, United States
| | - Serena Sim
- Yale College, 433 Temple Street, New Haven, CT 06510, United States
| | - Kelly Chen
- Yale College, 433 Temple Street, New Haven, CT 06510, United States
| | - Diane S Krause
- Department of Cell Biology, Yale School of Medicine, 10 Amistad Street, New Haven, CT 06510, United States
- Yale Stem Cell Center, Yale School of Medicine, 10 Amistad Street, New Haven, CT 06510, United States
- Department of Pathology, Yale School of Medicine, 10 Amistad Street, New Haven, CT 06510, United States
- Department of Laboratory Medicine, Yale School of Medicine, 10 Amistad Street, New Haven, CT 06510, United States
| | - Janghoo Lim
- Department of Genetics, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, United States
- Yale Stem Cell Center, Yale School of Medicine, 10 Amistad Street, New Haven, CT 06510, United States
- Interdepartmental Neuroscience Program, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, United States
- Department of Neuroscience, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, USA
- Program in Cellular Neuroscience, Neurodegeneration, and Repair, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06510, United States
- Wu Tsai Institute, Yale School of Medicine, 100 College, New Haven, CT 06510, United States
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6
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Bult CJ, Sternberg PW. The alliance of genome resources: transforming comparative genomics. Mamm Genome 2023; 34:531-544. [PMID: 37666946 PMCID: PMC10628019 DOI: 10.1007/s00335-023-10015-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/11/2023] [Indexed: 09/06/2023]
Abstract
Comparing genomic and biological characteristics across multiple species is essential to using model systems to investigate the molecular and cellular mechanisms underlying human biology and disease and to translate mechanistic insights from studies in model organisms for clinical applications. Building a scalable knowledge commons platform that supports cross-species comparison of rich, expertly curated knowledge regarding gene function, phenotype, and disease associations available for model organisms and humans is the primary mission of the Alliance of Genome Resources (the Alliance). The Alliance is a consortium of seven model organism knowledgebases (mouse, rat, yeast, nematode, zebrafish, frog, fruit fly) and the Gene Ontology resource. The Alliance uses a common set of gene ortholog assertions as the basis for comparing biological annotations across the organisms represented in the Alliance. The major types of knowledge associated with genes that are represented in the Alliance database currently include gene function, phenotypic alleles and variants, human disease associations, pathways, gene expression, and both protein-protein and genetic interactions. The Alliance has enhanced the ability of researchers to easily compare biological annotations for common data types across model organisms and human through the implementation of shared programmatic access mechanisms, data-specific web pages with a unified "look and feel", and interactive user interfaces specifically designed to support comparative biology. The modular infrastructure developed by the Alliance allows the resource to serve as an extensible "knowledge commons" capable of expanding to accommodate additional model organisms.
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7
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Ruffinatti FA, Scarpellino G, Chinigò G, Visentin L, Munaron L. The Emerging Concept of Transportome: State of the Art. Physiology (Bethesda) 2023; 38:0. [PMID: 37668550 DOI: 10.1152/physiol.00010.2023] [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: 04/12/2023] [Revised: 09/01/2023] [Accepted: 09/01/2023] [Indexed: 09/06/2023] Open
Abstract
The array of ion channels and transporters expressed in cell membranes, collectively referred to as the transportome, is a complex and multifunctional molecular machinery; in particular, at the plasma membrane level it finely tunes the exchange of biomolecules and ions, acting as a functionally adaptive interface that accounts for dynamic plasticity in the response to environmental fluctuations and stressors. The transportome is responsible for the definition of membrane potential and its variations, participates in the transduction of extracellular signals, and acts as a filter for most of the substances entering and leaving the cell, thus enabling the homeostasis of many cellular parameters. For all these reasons, physiologists have long been interested in the expression and functionality of ion channels and transporters, in both physiological and pathological settings and across the different domains of life. Today, thanks to the high-throughput technologies of the postgenomic era, the omics approach to the study of the transportome is becoming increasingly popular in different areas of biomedical research, allowing for a more comprehensive, integrated, and functional perspective of this complex cellular apparatus. This article represents a first effort for a systematic review of the scientific literature on this topic. Here we provide a brief overview of all those studies, both primary and meta-analyses, that looked at the transportome as a whole, regardless of the biological problem or the models they used. A subsequent section is devoted to the methodological aspect by reviewing the most important public databases annotating ion channels and transporters, along with the tools they provide to retrieve such information. Before conclusions, limitations and future perspectives are also discussed.
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Affiliation(s)
- Federico Alessandro Ruffinatti
- Turin Cell Physiology Laboratory (TCP-Lab), Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy
| | - Giorgia Scarpellino
- Turin Cell Physiology Laboratory (TCP-Lab), Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy
| | - Giorgia Chinigò
- Turin Cell Physiology Laboratory (TCP-Lab), Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy
| | - Luca Visentin
- Turin Cell Physiology Laboratory (TCP-Lab), Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy
| | - Luca Munaron
- Turin Cell Physiology Laboratory (TCP-Lab), Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy
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8
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Ahmed SH, Deng AT, Huntley RP, Campbell NH, Lovering RC. Capturing heart valve development with Gene Ontology. Front Genet 2023; 14:1251902. [PMID: 37915827 PMCID: PMC10616796 DOI: 10.3389/fgene.2023.1251902] [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: 07/02/2023] [Accepted: 09/29/2023] [Indexed: 11/03/2023] Open
Abstract
Introduction: The normal development of all heart valves requires highly coordinated signaling pathways and downstream mediators. While genomic variants can be responsible for congenital valve disease, environmental factors can also play a role. Later in life valve calcification is a leading cause of aortic valve stenosis, a progressive disease that may lead to heart failure. Current research into the causes of both congenital valve diseases and valve calcification is using a variety of high-throughput methodologies, including transcriptomics, proteomics and genomics. High quality genetic data from biological knowledge bases are essential to facilitate analyses and interpretation of these high-throughput datasets. The Gene Ontology (GO, http://geneontology.org/) is a major bioinformatics resource used to interpret these datasets, as it provides structured, computable knowledge describing the role of gene products across all organisms. The UCL Functional Gene Annotation team focuses on GO annotation of human gene products. Having identified that the GO annotations included in transcriptomic, proteomic and genomic data did not provide sufficient descriptive information about heart valve development, we initiated a focused project to address this issue. Methods: This project prioritized 138 proteins for GO annotation, which led to the curation of 100 peer-reviewed articles and the creation of 400 heart valve development-relevant GO annotations. Results: While the focus of this project was heart valve development, around 600 of the 1000 annotations created described the broader cellular role of these proteins, including those describing aortic valve morphogenesis, BMP signaling and endocardial cushion development. Our functional enrichment analysis of the 28 proteins known to have a role in bicuspid aortic valve disease confirmed that this annotation project has led to an improved interpretation of a heart valve genetic dataset. Discussion: To address the needs of the heart valve research community this project has provided GO annotations to describe the specific roles of key proteins involved in heart valve development. The breadth of GO annotations created by this project will benefit many of those seeking to interpret a wide range of cardiovascular genomic, transcriptomic, proteomic and metabolomic datasets.
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Affiliation(s)
- Saadullah H. Ahmed
- Functional Gene Annotation, Pre-clinical and Fundamental Science, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Alexander T. Deng
- Department of Clinical Genetics, Guy’s and St Thomas’s NHS Foundation Trust, London, United Kingdom
| | - Rachael P. Huntley
- SciBite Limited, BioData Innovation Centre, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | | | - Ruth C. Lovering
- Functional Gene Annotation, Pre-clinical and Fundamental Science, Institute of Cardiovascular Science, University College London, London, United Kingdom
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9
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Wright SN, Leger BS, Rosenthal SB, Liu SN, Jia T, Chitre AS, Polesskaya O, Holl K, Gao J, Cheng R, Garcia Martinez A, George A, Gileta AF, Han W, Netzley AH, King CP, Lamparelli A, Martin C, St Pierre CL, Wang T, Bimschleger H, Richards J, Ishiwari K, Chen H, Flagel SB, Meyer P, Robinson TE, Solberg Woods LC, Kreisberg JF, Ideker T, Palmer AA. Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks. Cell Rep 2023; 42:112873. [PMID: 37527041 PMCID: PMC10546330 DOI: 10.1016/j.celrep.2023.112873] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 07/05/2023] [Accepted: 07/11/2023] [Indexed: 08/03/2023] Open
Abstract
A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.
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Affiliation(s)
- Sarah N Wright
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA 92093, USA
| | - Brittany S Leger
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Program in Biomedical Sciences, University of California San Diego, La Jolla, CA 93093, USA
| | - Sara Brin Rosenthal
- Center for Computational Biology & Bioinformatics, Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sophie N Liu
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Tongqiu Jia
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Apurva S Chitre
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Katie Holl
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jianjun Gao
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Riyan Cheng
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Angel Garcia Martinez
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Anthony George
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA
| | - Alexander F Gileta
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Wenyan Han
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Alesa H Netzley
- Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA
| | - Christopher P King
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | | | - Connor Martin
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | | | - Tengfei Wang
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Hannah Bimschleger
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Jerry Richards
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA
| | - Keita Ishiwari
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Pharmacology and Toxicology, University at Buffalo, Buffalo, NY 14203, USA
| | - Hao Chen
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Shelly B Flagel
- Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Paul Meyer
- Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | - Terry E Robinson
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Leah C Solberg Woods
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Jason F Kreisberg
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Trey Ideker
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA.
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA.
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10
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Wang W, Liu R, Zhu Y, Wang L, Tang Y, Dou B, Tian S, Wang F. YuNü-Jian attenuates diabetes-induced cardiomyopathy: integrating network pharmacology and experimental validation. Front Endocrinol (Lausanne) 2023; 14:1195149. [PMID: 37288289 PMCID: PMC10242144 DOI: 10.3389/fendo.2023.1195149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/02/2023] [Indexed: 06/09/2023] Open
Abstract
Introduction Diabetic cardiomyopathy (DCM) is one of the most prevalent complications of diabetes with complex pathogenesis. YuNü-Jian (YNJ) is a traditional Chinese medicinal formula widely used for diabetes with hypoglycemic and cardioprotective effects. This study aims to investigate the actions and mechanisms of YNJ against DCM which has never been reported. Methods Network pharmacology approach was used to predict the potential pathways and targets of YNJ on DCM. Molecular docking between hub targets and active components of YNJ was performed and visualized by AutoDock Vina and PyMOL. Then type 2 diabetic model was employed and intervened with YNJ for 10 weeks to further validate these critical targets. Results First, a total of 32 main ingredients of YNJ were identified and 700 potential targets were screened to construct herb-compound-target network. Then 94 differentially expressed genes of DCM were identified from GEO database. After that, PPI network of DCM and YNJ were generated from which hub genes (SIRT1, Nrf2, NQO1, MYC and APP) were assessed by topology analysis. Next, functional and pathway analysis indicated that the candidate targets were enriched in response to oxidative stress and Nrf2 signaling pathway. Furthermore, molecular docking revealed strong affinity between core targets and active components of YNJ. Finally, in rats with type 2 diabetes, YNJ obviously attenuated cardiac collagen accumulation and degree of fibrosis. Meanwhile, YNJ significantly upregulated protein expression of SIRT1, Nrf2 and NQO1 in diabetic myocardium. Discussion Collectively, our findings suggested that YNJ could effectively ameliorate cardiomyopathy induced by diabetes possibly through SIRT1/Nrf2/NQO1 signaling.
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Affiliation(s)
- Wei Wang
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Ruixia Liu
- Department of Geriatric Medicine, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yingying Zhu
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Lina Wang
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yu Tang
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Baolei Dou
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Shuo Tian
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Furong Wang
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
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11
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Jones TEM, Yates B, Braschi B, Gray K, Tweedie S, Seal RL, Bruford EA. The VGNC: expanding standardized vertebrate gene nomenclature. Genome Biol 2023; 24:115. [PMID: 37173739 PMCID: PMC10176861 DOI: 10.1186/s13059-023-02957-2] [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: 08/10/2022] [Accepted: 04/28/2023] [Indexed: 05/15/2023] Open
Abstract
The Vertebrate Gene Nomenclature Committee (VGNC) was established in 2016 as a sister project to the HUGO Gene Nomenclature Committee, to approve gene nomenclature in vertebrate species without an existing dedicated nomenclature committee. The VGNC aims to harmonize gene nomenclature across selected vertebrate species in line with human gene nomenclature, with orthologs assigned the same nomenclature where possible. This article presents an overview of the VGNC project and discussion of key findings resulting from this work to date. VGNC-approved nomenclature is accessible at https://vertebrate.genenames.org and is additionally displayed by the NCBI, Ensembl, and UniProt databases.
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Affiliation(s)
- Tamsin E. M. Jones
- HUGO Gene Nomenclature Committee, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD Cambridgeshire UK
| | - Bethan Yates
- HUGO Gene Nomenclature Committee, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD Cambridgeshire UK
- Current address: Tree of Life, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA Cambridgeshire UK
| | - Bryony Braschi
- HUGO Gene Nomenclature Committee, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD Cambridgeshire UK
| | - Kristian Gray
- HUGO Gene Nomenclature Committee, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD Cambridgeshire UK
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0AW Cambridgeshire UK
| | - Susan Tweedie
- HUGO Gene Nomenclature Committee, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD Cambridgeshire UK
| | - Ruth L. Seal
- HUGO Gene Nomenclature Committee, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD Cambridgeshire UK
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0AW Cambridgeshire UK
| | - Elspeth A. Bruford
- HUGO Gene Nomenclature Committee, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD Cambridgeshire UK
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0AW Cambridgeshire UK
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12
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Rivetti C, Houghton J, Basili D, Hodges G, Campos B. Genes-to-Pathways Species Conservation Analysis: Enabling the Exploration of Conservation of Biological Pathways and Processes Across Species. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2023; 42:1152-1166. [PMID: 36861224 DOI: 10.1002/etc.5600] [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: 12/05/2022] [Revised: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
The last two decades have witnessed a strong momentum toward integration of cell-based and computational approaches in safety assessments. This is fueling a global regulatory paradigm shift toward reduction and replacement of the use of animals in toxicity tests while promoting the use of new approach methodologies. The understanding of conservation of molecular targets and pathways provides an opportunity to extrapolate effects across species and ultimately to determine the taxonomic applicability domain of assays and biological effects. Despite the wealth of genome-linked data available, there is a compelling need for improved accessibility, while ensuring that it reflects the underpinning biology. We present the novel pipeline Genes-to-Pathways Species Conservation Analysis (G2P-SCAN) to further support understanding on cross-species extrapolation of biological processes. This R package extracts, synthetizes, and structures the data available from different databases, that is, gene orthologs, protein families, entities, and reactions, linked to human genes and respective pathways across six relevant model species. The use of G2P-SCAN enables the overall analysis of orthology and functional families to substantiate the identification of conservation and susceptibility at the pathway level. In the present study we discuss five case studies, demonstrating the validity of the developed pipeline and its potential use as species extrapolation support. We foresee this pipeline will provide valuable biological insights and create space for the use of mechanistically based data to inform potential species susceptibility for research and safety decision purposes. Environ Toxicol Chem 2023;42:1152-1166. © 2023 UNILEVER GLOBAL IP LTD. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Affiliation(s)
- Claudia Rivetti
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
| | - Jade Houghton
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
| | - Danilo Basili
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
| | - Geoff Hodges
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
| | - Bruno Campos
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
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13
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Brünger T, Pérez-Palma E, Montanucci L, Nothnagel M, Møller RS, Schorge S, Zuberi S, Symonds J, Lemke JR, Brunklaus A, Traynelis SF, May P, Lal D. Conserved patterns across ion channels correlate with variant pathogenicity and clinical phenotypes. Brain 2023; 146:923-934. [PMID: 36036558 PMCID: PMC9976975 DOI: 10.1093/brain/awac305] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 07/29/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. As a consequence, therapeutic decision-making is challenging without molecular testing of each variant. Our biophysical knowledge of ion-channel structures and function is just emerging, and it is currently not well understood which amino acid residues cause disease when mutated. We sought to systematically identify biological properties associated with variant pathogenicity across all major voltage and ligand-gated ion-channel families. We collected and curated 3049 pathogenic variants from hundreds of neurodevelopmental and other disorders and 12 546 population variants for 30 ion channel or channel subunits for which a high-quality protein structure was available. Using a wide range of bioinformatics approaches, we computed 163 structural features and tested them for pathogenic variant enrichment. We developed a novel 3D spatial distance scoring approach that enables comparisons of pathogenic and population variant distribution across protein structures. We discovered and independently replicated that several pore residue properties and proximity to the pore axis were most significantly enriched for pathogenic variants compared to population variants. Using our 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5Å distance from the pore axis centre and not involved in gating. Within the subset of residues located at the pore, the hydrophobicity of the pore was the feature most strongly associated with variant pathogenicity. We also found an association between the identified properties and both clinical phenotypes and functional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N-methyl-D-aspartate receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1422 neurodevelopmental disorder pathogenic patient variants and 679 electrophysiological experiments, we show that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain versus loss-of-channel function. In summary, we identified biological properties associated with ion-channel malfunction and show that these are correlated with in vitro functional readouts and clinical phenotypes in patients with neurodevelopmental disorders. Our results suggest that clinical decision support algorithms that predict variant pathogenicity and function are feasible in the future.
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Affiliation(s)
- Tobias Brünger
- Cologne Center for Genomics, University of Cologne, 50931 Cologne, Germany
| | - Eduardo Pérez-Palma
- Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, Universidad de Desarrollo, Santiago 7590943, Chile
| | - Ludovica Montanucci
- Lerner Research Institute Cleveland Clinic, Genomic Medicine Institute, Cleveland, OH 44195, USA
| | - Michael Nothnagel
- Cologne Center for Genomics, University of Cologne, 50931 Cologne, Germany
- University Hospital Cologne, 50937 Cologne, Germany
| | - Rikke S Møller
- Department of Epilepsy Genetics and Personalized Treatment, the Danish Epilepsy Center, DK 4293 Dianalund, Denmark
| | - Stephanie Schorge
- Department of Neuroscience, Physiology and Pharmacology, UCL, London WC1E 6BT, UK
| | - Sameer Zuberi
- The Paediatric Neurosciences Research Group, Royal Hospital for Children, Glasgow, UK
- Institute of Health and Wellbeing, University of Glasgow, UK
| | - Joseph Symonds
- The Paediatric Neurosciences Research Group, Royal Hospital for Children, Glasgow, UK
- Institute of Health and Wellbeing, University of Glasgow, UK
| | - Johannes R Lemke
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
- Center for Rare Diseases, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Andreas Brunklaus
- The Paediatric Neurosciences Research Group, Royal Hospital for Children, Glasgow, UK
- Institute of Health and Wellbeing, University of Glasgow, UK
| | - Stephen F Traynelis
- Department of Pharmacology, Emory University School of Medicine, Rollins Research Center, Atlanta, GA 30322-3090, USA
| | - Patrick May
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg
| | - Dennis Lal
- Cologne Center for Genomics, University of Cologne, 50931 Cologne, Germany
- Lerner Research Institute Cleveland Clinic, Genomic Medicine Institute, Cleveland, OH 44195, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
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14
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Bruford EA, Braschi B, Haim-Vilmovsky L, Jones TEM, Seal RL, Tweedie S. The importance of being the HGNC. Hum Genomics 2022; 16:58. [PMID: 36380364 PMCID: PMC9664783 DOI: 10.1186/s40246-022-00432-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/07/2022] [Indexed: 11/16/2022] Open
Abstract
The HUGO Gene Nomenclature Committee (HGNC) has been providing standardized symbols and names for human genes since the late 1970s. As funding agencies change their priorities, finding financial support for critical biomedical resources such as the HGNC becomes ever more challenging. In this article, we outline the key roles the HGNC currently plays in aiding communication and the need for these activities to be maintained.
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Affiliation(s)
- Elspeth A. Bruford
- grid.5335.00000000121885934Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0PT UK ,grid.52788.300000 0004 0427 7672HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, EMBL-EBI, Wellcome Genome Campus, Hinxton, CB10 1SD UK
| | - Bryony Braschi
- grid.52788.300000 0004 0427 7672HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, EMBL-EBI, Wellcome Genome Campus, Hinxton, CB10 1SD UK
| | - Liora Haim-Vilmovsky
- grid.52788.300000 0004 0427 7672HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, EMBL-EBI, Wellcome Genome Campus, Hinxton, CB10 1SD UK
| | - Tamsin E. M. Jones
- grid.52788.300000 0004 0427 7672HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, EMBL-EBI, Wellcome Genome Campus, Hinxton, CB10 1SD UK
| | - Ruth L. Seal
- grid.5335.00000000121885934Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0PT UK ,grid.52788.300000 0004 0427 7672HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, EMBL-EBI, Wellcome Genome Campus, Hinxton, CB10 1SD UK
| | - Susan Tweedie
- grid.52788.300000 0004 0427 7672HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, EMBL-EBI, Wellcome Genome Campus, Hinxton, CB10 1SD UK
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15
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Seal RL, Braschi B, Gray K, Jones TEM, Tweedie S, Haim-Vilmovsky L, Bruford EA. Genenames.org: the HGNC resources in 2023. Nucleic Acids Res 2022; 51:D1003-D1009. [PMID: 36243972 PMCID: PMC9825485 DOI: 10.1093/nar/gkac888] [Citation(s) in RCA: 136] [Impact Index Per Article: 68.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 09/28/2022] [Accepted: 10/03/2022] [Indexed: 01/30/2023] Open
Abstract
The HUGO Gene Nomenclature Committee (HGNC) assigns unique symbols and names to human genes. The HGNC database (www.genenames.org) currently contains over 43 000 approved gene symbols, over 19 200 of which are assigned to protein-coding genes, 14 000 to pseudogenes and nearly 9000 to non-coding RNA genes. The public website, www.genenames.org, displays all approved nomenclature within Symbol Reports that contain data curated by HGNC nomenclature advisors and links to related genomic, clinical, and proteomic information. Here, we describe updates to our resource, including improvements to our search facility and new download features.
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Affiliation(s)
- Ruth L Seal
- To whom correspondence should be addressed. Tel: +44 1223 494444; Fax: +44 1223 494446;
| | - Bryony Braschi
- HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Kristian Gray
- HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK,Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge CB2 0PT, UK
| | - Tamsin E M Jones
- HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Susan Tweedie
- HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Liora Haim-Vilmovsky
- HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Elspeth A Bruford
- HUGO Gene Nomenclature Committee, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK,Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge CB2 0PT, UK
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16
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Nevers Y, Jones TEM, Jyothi D, Yates B, Ferret M, Portell-Silva L, Codo L, Cosentino S, Marcet-Houben M, Vlasova A, Poidevin L, Kress A, Hickman M, Persson E, Piližota I, Guijarro-Clarke C, Iwasaki W, Lecompte O, Sonnhammer E, Roos DS, Gabaldón T, Thybert D, Thomas PD, Hu Y, Emms DM, Bruford E, Capella-Gutierrez S, Martin MJ, Dessimoz C, Altenhoff A. The Quest for Orthologs orthology benchmark service in 2022. Nucleic Acids Res 2022; 50:W623-W632. [PMID: 35552456 PMCID: PMC9252809 DOI: 10.1093/nar/gkac330] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 04/07/2022] [Accepted: 04/30/2022] [Indexed: 11/15/2022] Open
Abstract
The Orthology Benchmark Service (https://orthology.benchmarkservice.org) is the gold standard for orthology inference evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform.
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Affiliation(s)
- Yannis Nevers
- To whom correspondence should be addressed. Tel: +41 21 692 5449;
| | - Tamsin E M Jones
- HUGO Gene Nomenclature Committee (HGNC), European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Dushyanth Jyothi
- Protein Function development, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Bethan Yates
- HUGO Gene Nomenclature Committee (HGNC), European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Meritxell Ferret
- Barcelona Supercomputing Centre (BSC-CNS). Plaça Eusebi Güell, 1-3 08034 Barcelona, Spain
| | - Laura Portell-Silva
- Barcelona Supercomputing Centre (BSC-CNS). Plaça Eusebi Güell, 1-3 08034 Barcelona, Spain
| | - Laia Codo
- Barcelona Supercomputing Centre (BSC-CNS). Plaça Eusebi Güell, 1-3 08034 Barcelona, Spain
| | - Salvatore Cosentino
- Department of Biological Sciences, Graduate School of Science, the University of Tokyo, Tokyo, Japan
| | - Marina Marcet-Houben
- Barcelona Supercomputing Centre (BSC-CNS). Plaça Eusebi Güell, 1-3 08034 Barcelona, Spain,Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Anna Vlasova
- Barcelona Supercomputing Centre (BSC-CNS). Plaça Eusebi Güell, 1-3 08034 Barcelona, Spain,Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Laetitia Poidevin
- Department of Computer Science, ICube, UMR 7357, Centre de Recherche en Biomédecine de Strasbourg, University of Strasbourg, CNRS, Strasbourg, France,BiGEst-ICube Platform, ICube, UMR 7357, Centre de Recherche en Biomédecine de Strasbourg, University of Strasbourg, CNRS, Strasbourg, France
| | - Arnaud Kress
- Department of Computer Science, ICube, UMR 7357, Centre de Recherche en Biomédecine de Strasbourg, University of Strasbourg, CNRS, Strasbourg, France,BiGEst-ICube Platform, ICube, UMR 7357, Centre de Recherche en Biomédecine de Strasbourg, University of Strasbourg, CNRS, Strasbourg, France
| | - Mark Hickman
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Emma Persson
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden
| | - Ivana Piližota
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Cristina Guijarro-Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | | | - Wataru Iwasaki
- Department of Biological Sciences, Graduate School of Science, the University of Tokyo, Tokyo, Japan,Department of Integrated Biosciences, Graduate School of Frontier Sciences, the University of Tokyo, Kashiwa, Japan
| | - Odile Lecompte
- Department of Computer Science, ICube, UMR 7357, Centre de Recherche en Biomédecine de Strasbourg, University of Strasbourg, CNRS, Strasbourg, France
| | - Erik Sonnhammer
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden
| | - David S Roos
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Toni Gabaldón
- Barcelona Supercomputing Centre (BSC-CNS). Plaça Eusebi Güell, 1-3 08034 Barcelona, Spain,Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain,Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain,Centro de Investigaciones Biomédicas en Red de Enfermedades Infecciosas, Barcelona, Spain
| | - David Thybert
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Paul D Thomas
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90032, USA
| | - Yanhui Hu
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
| | - David M Emms
- Department of Plant Sciences, University of Oxford, Oxford OX1 3RB, UK
| | - Elspeth Bruford
- HUGO Gene Nomenclature Committee (HGNC), European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK,Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | | | - Maria J Martin
- Protein Function development, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Christophe Dessimoz
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland,Swiss Institute for Bioinformatics, University of Lausanne, Lausanne, Switzerland,Department of Computer Science, University College London, London, UK,Centre for Life's Origins and Evolution, Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Adrian Altenhoff
- Swiss Institute for Bioinformatics, University of Lausanne, Lausanne, Switzerland,Computer Science Department, ETH Zurich, Zurich, Switzerland
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17
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Thomas PD, Ebert D, Muruganujan A, Mushayahama T, Albou L, Mi H. PANTHER: Making genome-scale phylogenetics accessible to all. Protein Sci 2022; 31:8-22. [PMID: 34717010 PMCID: PMC8740835 DOI: 10.1002/pro.4218] [Citation(s) in RCA: 582] [Impact Index Per Article: 291.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 10/24/2021] [Accepted: 10/26/2021] [Indexed: 02/03/2023]
Abstract
Phylogenetics is a powerful tool for analyzing protein sequences, by inferring their evolutionary relationships to other proteins. However, phylogenetics analyses can be challenging: they are computationally expensive and must be performed carefully in order to avoid systematic errors and artifacts. Protein Analysis THrough Evolutionary Relationships (PANTHER; http://pantherdb.org) is a publicly available, user-focused knowledgebase that stores the results of an extensive phylogenetic reconstruction pipeline that includes computational and manual processes and quality control steps. First, fully reconciled phylogenetic trees (including ancestral protein sequences) are reconstructed for a set of "reference" protein sequences obtained from fully sequenced genomes of organisms across the tree of life. Second, the resulting phylogenetic trees are manually reviewed and annotated with function evolution events: inferred gains and losses of protein function along branches of the phylogenetic tree. Here, we describe in detail the current contents of PANTHER, how those contents are generated, and how they can be used in a variety of applications. The PANTHER knowledgebase can be downloaded or accessed via an extensive API. In addition, PANTHER provides software tools to facilitate the application of the knowledgebase to common protein sequence analysis tasks: exploring an annotated genome by gene function; performing "enrichment analysis" of lists of genes; annotating a single sequence or large batch of sequences by homology; and assessing the likelihood that a genetic variant at a particular site in a protein will have deleterious effects.
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Affiliation(s)
- Paul D. Thomas
- Division of Bioinformatics, Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Dustin Ebert
- Division of Bioinformatics, Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Anushya Muruganujan
- Division of Bioinformatics, Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Tremayne Mushayahama
- Division of Bioinformatics, Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Laurent‐Philippe Albou
- Division of Bioinformatics, Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Huaiyu Mi
- Division of Bioinformatics, Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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18
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Ringwald M, Richardson JE, Baldarelli RM, Blake JA, Kadin JA, Smith C, Bult CJ. Mouse Genome Informatics (MGI): latest news from MGD and GXD. Mamm Genome 2021; 33:4-18. [PMID: 34698891 PMCID: PMC8913530 DOI: 10.1007/s00335-021-09921-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/21/2021] [Indexed: 12/01/2022]
Abstract
The Mouse Genome Informatics (MGI) database system combines multiple expertly curated community data resources into a shared knowledge management ecosystem united by common metadata annotation standards. MGI's mission is to facilitate the use of the mouse as an experimental model for understanding the genetic and genomic basis of human health and disease. MGI is the authoritative source for mouse gene, allele, and strain nomenclature and is the primary source of mouse phenotype annotations, functional annotations, developmental gene expression information, and annotations of mouse models with human diseases. MGI maintains mouse anatomy and phenotype ontologies and contributes to the development of the Gene Ontology and Disease Ontology and uses these ontologies as standard terminologies for annotation. The Mouse Genome Database (MGD) and the Gene Expression Database (GXD) are MGI's two major knowledgebases. Here, we highlight some of the recent changes and enhancements to MGD and GXD that have been implemented in response to changing needs of the biomedical research community and to improve the efficiency of expert curation. MGI can be accessed freely at http://www.informatics.jax.org .
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