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Lv J, Kou N, Li Y, Qiu K, Guo X, Zhang L, Zhang Z, He S, Yuan Y. Identification and Verification of Endoplasmic Reticulum Stress-Related Genes as Novel Signatures for Osteoarthritis Diagnosis and Therapy: A Bioinformatics Analysis-Oriented Pilot Study. Biochem Genet 2024:10.1007/s10528-024-10818-1. [PMID: 38734758 DOI: 10.1007/s10528-024-10818-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 04/17/2024] [Indexed: 05/13/2024]
Abstract
BACKGROUND AND PURPOSE Endoplasmic reticulum stress (ERS) has been reported to be closely associated with the development of osteoarthritis (OA), but the underlying mechanisms are not fully delineated. The present study was designed to investigate the involvement of ERS-related genes in regulating OA progression. METHODS The expression profiles of OA patients and normal people were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) in datasets GSE55457 and GSE55235 were screened and identified by R software with the construction of the protein-protein interaction (PPI) networks. Through the STRING and Venn diagram analysis, hub ERS-related genes were obtained. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed. Biomarkers with high diagnostic values of osteoarthritis (OA) were studied. The hematoxylin and eosin (H&E) staining and micro-CT were applied to evaluate the establishment of the OA model. The expression levels of biomarkers were validated with the use of reverse transcription‑quantitative polymerase chain reaction (RT-qPCR) and western blot. Finally, we evaluated the correlations of hub ERS-related genes with the immune infiltration cells via the CIBERSORT algorithm. RESULTS A total of 60 downregulated and 52 upregulated DEGs were identified, and the following GO and KEGG pathway analyses verified that those DEGs were mainly enriched in biological process (BP), cellular component (CC), molecular function (MF), and inflammation-associated signal pathways. Interestingly, among all the DEGs, six ER stress-associated genes, including activating transcription factor 3 (ATF3), DEAD-Box Helicase 3 X-Linked (DDX3X), AP-1 transcription factor subunit (JUN), eukaryotic initiation factor 4 (EIF4A1), KDEL endoplasmic reticulum protein retention receptor 3 (KDELR3), and vascular endothelial growth factor A (VEGFA), were found to be closely associated with OA progression, and the following RT-qPCR and Western Blot analysis confirmed that DDX3X, JUN, and VEGFA were upregulated, whereas KDELR3, EIF4A1, and ATF3 were downregulated in OA rats tissues compared to the normal tissues, which were in accordance with our bioinformatics findings. Furthermore, our receiver operating characteristic (ROC) curve analysis verified that the above six ER stress-associated genes could be used as ideal biomarkers for OA diagnosis and those genes also potentially regulated immune responses by influencing the biological functions of mast cells and macrophages. CONCLUSION Collectively, the present study firstly identified six ER stress-associated genes (ATF3, DDX3X, JUN, EIF4A1, KDELR3, and VEGFA) that may play critical role in regulating the progression of OA.
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Affiliation(s)
- Jia Lv
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China
| | - Nannan Kou
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China
| | - Yunxuan Li
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China
| | - Kejia Qiu
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China
| | - Xiang Guo
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China
| | - Li Zhang
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China
| | - Zhichao Zhang
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China
| | - Shaoxuan He
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China.
| | - Yong Yuan
- Department of Trauma Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Yunnan-Myanmar Avenue, Kunming, 650101, China.
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Feng X, Diao S, Liu Y, Xu Z, Li G, Ma Y, Su Z, Liu X, Li J, Zhang Z. Exploring the mechanism of artificial selection signature in Chinese indigenous pigs by leveraging multiple bioinformatics database tools. BMC Genomics 2023; 24:743. [PMID: 38053015 DOI: 10.1186/s12864-023-09848-7] [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: 02/23/2023] [Accepted: 11/27/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND Chinese indigenous pigs in Yunnan exhibit considerable phenotypic diversity, but their population structure and the biological interpretation of signatures of artificial selection require further investigation. To uncover population genetic diversity, migration events, and artificial selection signatures in Chinese domestic pigs, we sampled 111 Yunnan pigs from four breeds in Yunnan which is considered to be one of the centres of livestock domestication in China, and genotyped them using Illumina Porcine SNP60K BeadChip. We then leveraged multiple bioinformatics database tools to further investigate the signatures and associated complex traits. RESULTS Population structure and migration analyses showed that Diannanxiaoer pigs had different genetic backgrounds from other Yunnan pigs, and Gaoligongshan may undergone the migration events from Baoshan and Saba pigs. Intriguingly, we identified a possible common target of sharing artificial selection on a 265.09 kb region on chromosome 5 in Yunnan indigenous pigs, and the genes on this region were associated with cardiovascular and immune systems. We also detected several candidate genes correlated with dietary adaptation, body size (e.g., PASCIN1, GRM4, ITPR2), and reproductive performance. In addition, the breed-sharing gene MMP16 was identified to be a human-mediated gene. Multiple lines of evidence at the mammalian genome, transcriptome, and phenome levels further supported the evidence for the causality between MMP16 variants and the metabolic diseases, brain development, and cartilage tissues in Chinese pigs. Our results suggested that the suppression of MMP16 would directly lead to inactivity and insensitivity of neuronal activity and skeletal development in Chinese indigenous pigs. CONCLUSION In this study, the population genetic analyses and identification of artificial selection signatures of Yunnan indigenous pigs help to build an understanding of the effect of human-mediated selection mechanisms on phenotypic traits in Chinese indigenous pigs. Further studies are needed to fully characterize the process of human-mediated genes and biological mechanisms.
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Affiliation(s)
- Xueyan Feng
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Shuqi Diao
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yuqiang Liu
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Zhiting Xu
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Guangzhen Li
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Ye Ma
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Zhanqin Su
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Xiaohong Liu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Jiaqi Li
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
| | - Zhe Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
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Doolittle ML, Khosla S, Saul D. Single-Cell Integration of BMD GWAS Results Prioritize Candidate Genes Influencing Age-Related Bone Loss. JBMR Plus 2023; 7:e10795. [PMID: 37808401 PMCID: PMC10556272 DOI: 10.1002/jbm4.10795] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 05/17/2023] [Accepted: 06/19/2023] [Indexed: 10/10/2023] Open
Abstract
The regulation of bone mineral density (BMD) is highly influenced by genetics and age. Although genome-wide association studies (GWAS) for BMD have uncovered many genes through their proximity to associated variants (variant nearest-neighbor [VNN] genes), the cell-specific mechanisms of each VNN gene remain unclear. This is primarily due to the inability to prioritize these genes by cell type and age-related expression. Using age-related transcriptomics, we found that the expression of many VNN genes was upregulated in the bone and marrow from aged mice. Candidate genes from GWAS were investigated using single-cell RNA-sequencing (scRNA-seq) datasets to enrich for cell-specific expression signatures. VNN candidate genes are highly enriched in osteo-lineage cells, osteocytes, hypertrophic chondrocytes, and Lepr+ mesenchymal stem cells. These data were used to generate a "blueprint" for Cre-loxp mouse line selection for functional validation of candidate genes and further investigation of their role in BMD maintenance throughout aging. In VNN-gene-enriched cells, Sparc, encoding the extracellular matrix (ECM) protein osteonectin, was robustly expressed. This, along with expression of numerous other ECM genes, indicates that many VNN genes likely have roles in ECM deposition by osteoblasts. Overall, we provide data supporting streamlined translation of GWAS candidate genes to potential novel therapeutic targets for the treatment of osteoporosis. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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Affiliation(s)
- Madison L. Doolittle
- Division of EndocrinologyMayo ClinicRochesterMinnesotaUSA
- Robert and Arlene Kogod Center on AgingMayo ClinicRochesterMinnesotaUSA
| | - Sundeep Khosla
- Division of EndocrinologyMayo ClinicRochesterMinnesotaUSA
- Robert and Arlene Kogod Center on AgingMayo ClinicRochesterMinnesotaUSA
| | - Dominik Saul
- Division of EndocrinologyMayo ClinicRochesterMinnesotaUSA
- Robert and Arlene Kogod Center on AgingMayo ClinicRochesterMinnesotaUSA
- Department for Trauma and Reconstructive SurgeryBG Clinic, University of TuebingenTuebingenGermany
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La Manna F, Hanhart D, Kloen P, van Wijnen AJ, Thalmann GN, Kruithof-de Julio M, Chouvardas P. Molecular profiling of osteoprogenitor cells reveals FOS as a master regulator of bone non-union. Gene 2023; 874:147481. [PMID: 37182560 DOI: 10.1016/j.gene.2023.147481] [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: 02/28/2023] [Revised: 04/25/2023] [Accepted: 05/08/2023] [Indexed: 05/16/2023]
Abstract
Despite the advances in bone fracture treatment, a significant fraction of fracture patients will develop non-union. Most non-unions are treated with surgery since identifying the molecular causes of these defects is exceptionally challenging. In this study, compared with marrow bone, we generated a transcriptional atlas of human osteoprogenitor cells derived from healing callus and non-union fractures. Detailed comparison among the three conditions revealed a substantial similarity of callus and nonunion at the gene expression level. Nevertheless, when assayed functionally, they showed different osteogenic potential. Utilizing longitudinal transcriptional profiling of the osteoprogenitor cells, we identified FOS as a putative master regulator of non-union fractures. We validated FOS activity by profiling a validation cohort of 31 tissue samples. Our work identified new molecular targets for non-union classification and treatment while providing a valuable resource to better understand human bone healing biology.
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Affiliation(s)
- Federico La Manna
- Department for BioMedical Research, Urology Research Laboratory, University of Bern, Bern, Switzerland
| | - Daniel Hanhart
- Department for BioMedical Research, Urology Research Laboratory, University of Bern, Bern, Switzerland
| | - Peter Kloen
- Department of Orthopedic Surgery and Sports Medicine, Amsterdam University Medical Centers, Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | | | - George N Thalmann
- Department of Urology, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Marianna Kruithof-de Julio
- Department for BioMedical Research, Urology Research Laboratory, University of Bern, Bern, Switzerland; Department of Urology, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Panagiotis Chouvardas
- Department for BioMedical Research, Urology Research Laboratory, University of Bern, Bern, Switzerland.
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Lindovsky J, Nichtova Z, Dragano NRV, Pajuelo Reguera D, Prochazka J, Fuchs H, Marschall S, Gailus-Durner V, Sedlacek R, Hrabě de Angelis M, Rozman J, Spielmann N. A review of standardized high-throughput cardiovascular phenotyping with a link to metabolism in mice. Mamm Genome 2023; 34:107-122. [PMID: 37326672 PMCID: PMC10290615 DOI: 10.1007/s00335-023-09997-w] [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: 04/20/2023] [Accepted: 05/03/2023] [Indexed: 06/17/2023]
Abstract
Cardiovascular diseases cause a high mortality rate worldwide and represent a major burden for health care systems. Experimental rodent models play a central role in cardiovascular disease research by effectively simulating human cardiovascular diseases. Using mice, the International Mouse Phenotyping Consortium (IMPC) aims to target each protein-coding gene and phenotype multiple organ systems in single-gene knockout models by a global network of mouse clinics. In this review, we summarize the current advances of the IMPC in cardiac research and describe in detail the diagnostic requirements of high-throughput electrocardiography and transthoracic echocardiography capable of detecting cardiac arrhythmias and cardiomyopathies in mice. Beyond that, we are linking metabolism to the heart and describing phenotypes that emerge in a set of known genes, when knocked out in mice, such as the leptin receptor (Lepr), leptin (Lep), and Bardet-Biedl syndrome 5 (Bbs5). Furthermore, we are presenting not yet associated loss-of-function genes affecting both, metabolism and the cardiovascular system, such as the RING finger protein 10 (Rfn10), F-box protein 38 (Fbxo38), and Dipeptidyl peptidase 8 (Dpp8). These extensive high-throughput data from IMPC mice provide a promising opportunity to explore genetics causing metabolic heart disease with an important translational approach.
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Affiliation(s)
- Jiri Lindovsky
- Czech Centre for Phenogenomics, Institute of Molecular Genetics, Czech Academy of Sciences, Prumyslova 595, 252 50 Vestec, Czech Republic
| | - Zuzana Nichtova
- Czech Centre for Phenogenomics, Institute of Molecular Genetics, Czech Academy of Sciences, Prumyslova 595, 252 50 Vestec, Czech Republic
| | - Nathalia R. V. Dragano
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Center Munich, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - David Pajuelo Reguera
- Czech Centre for Phenogenomics, Institute of Molecular Genetics, Czech Academy of Sciences, Prumyslova 595, 252 50 Vestec, Czech Republic
| | - Jan Prochazka
- Czech Centre for Phenogenomics, Institute of Molecular Genetics, Czech Academy of Sciences, Prumyslova 595, 252 50 Vestec, Czech Republic
| | - Helmut Fuchs
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Center Munich, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Susan Marschall
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Center Munich, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Valerie Gailus-Durner
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Center Munich, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Radislav Sedlacek
- Czech Centre for Phenogenomics, Institute of Molecular Genetics, Czech Academy of Sciences, Prumyslova 595, 252 50 Vestec, Czech Republic
| | - Martin Hrabě de Angelis
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Center Munich, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Jan Rozman
- Czech Centre for Phenogenomics, Institute of Molecular Genetics, Czech Academy of Sciences, Prumyslova 595, 252 50 Vestec, Czech Republic
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Nadine Spielmann
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Center Munich, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
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Dong C, Shen S, Keleş S. AdaLiftOver: high-resolution identification of orthologous regulatory elements with Adaptive liftOver. Bioinformatics 2023; 39:btad149. [PMID: 37004197 PMCID: PMC10085516 DOI: 10.1093/bioinformatics/btad149] [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: 05/11/2022] [Revised: 03/02/2023] [Accepted: 03/20/2023] [Indexed: 04/03/2023] Open
Abstract
MOTIVATION Elucidating functionally similar orthologous regulatory regions for human and model organism genomes is critical for exploiting model organism research and advancing our understanding of results from genome-wide association studies (GWAS). Sequence conservation is the de facto approach for finding orthologous non-coding regions between human and model organism genomes. However, existing methods for mapping non-coding genomic regions across species are challenged by the multi-mapping, low precision, and low mapping rate issues. RESULTS We develop Adaptive liftOver (AdaLiftOver), a large-scale computational tool for identifying functionally similar orthologous non-coding regions across species. AdaLiftOver builds on the UCSC liftOver framework to extend the query regions and prioritizes the resulting candidate target regions based on the conservation of the epigenomic and the sequence grammar features. Evaluations of AdaLiftOver with multiple case studies, spanning both genomic intervals from epigenome datasets across a wide range of model organisms and GWAS SNPs, yield AdaLiftOver as a versatile method for deriving hard-to-obtain human epigenome datasets as well as reliably identifying orthologous loci for GWAS SNPs. AVAILABILITY AND IMPLEMENTATION The R package and the data for AdaLiftOver is available from https://github.com/keleslab/AdaLiftOver.
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Affiliation(s)
- Chenyang Dong
- Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA
| | - Siqi Shen
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WARF Room 201, 610 Walnut Street, Madison, WI 53706, USA
| | - Sündüz Keleş
- Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WARF Room 201, 610 Walnut Street, Madison, WI 53706, USA
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Multiple Genetic Loci Associated with Pug Dog Thoracolumbar Myelopathy. Genes (Basel) 2023; 14:genes14020385. [PMID: 36833311 PMCID: PMC9957375 DOI: 10.3390/genes14020385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 01/24/2023] [Accepted: 01/27/2023] [Indexed: 02/04/2023] Open
Abstract
Pug dogs with thoracolumbar myelopathy (PDM) present with a specific clinical phenotype that includes progressive pelvic limb ataxia and paresis, commonly accompanied by incontinence. Vertebral column malformations and lesions, excessive scar tissue of the meninges, and central nervous system inflammation have been described. PDM has a late onset and affects more male than female dogs. The breed-specific presentation of the disorder suggests that genetic risk factors are involved in the disease development. To perform a genome-wide search for PDM-associated loci, we applied a Bayesian model adapted for mapping complex traits (BayesR) and a cross-population extended haplotype homozygosity test (XP-EHH) in 51 affected and 38 control pugs. Nineteen associated loci (harboring 67 genes in total, including 34 potential candidate genes) and three candidate regions under selection (with four genes within or next to the signal) were identified. The multiple candidate genes identified have implicated functions in bone homeostasis, fibrotic scar tissue, inflammatory responses, or the formation, regulation, and differentiation of cartilage, suggesting the potential relevance of these processes to the pathogenesis of PDM.
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Groza T, Gomez FL, Mashhadi HH, Muñoz-Fuentes V, Gunes O, Wilson R, Cacheiro P, Frost A, Keskivali-Bond P, Vardal B, McCoy A, Cheng TK, Santos L, Wells S, Smedley D, Mallon AM, Parkinson H. The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease. Nucleic Acids Res 2023; 51:D1038-D1045. [PMID: 36305825 PMCID: PMC9825559 DOI: 10.1093/nar/gkac972] [Citation(s) in RCA: 109] [Impact Index Per Article: 109.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/05/2022] [Accepted: 10/14/2022] [Indexed: 01/30/2023] Open
Abstract
The International Mouse Phenotyping Consortium (IMPC; https://www.mousephenotype.org/) web portal makes available curated, integrated and analysed knockout mouse phenotyping data generated by the IMPC project consisting of 85M data points and over 95,000 statistically significant phenotype hits mapped to human diseases. The IMPC portal delivers a substantial reference dataset that supports the enrichment of various domain-specific projects and databases, as well as the wider research and clinical community, where the IMPC genotype-phenotype knowledge contributes to the molecular diagnosis of patients affected by rare disorders. Data from 9,000 mouse lines and 750 000 images provides vital resources enabling the interpretation of the ignorome, and advancing our knowledge on mammalian gene function and the mechanisms underlying phenotypes associated with human diseases. The resource is widely integrated and the lines have been used in over 4,600 publications indicating the value of the data and the materials.
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Affiliation(s)
- Tudor Groza
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Federico Lopez Gomez
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Hamed Haseli Mashhadi
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Violeta Muñoz-Fuentes
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Osman Gunes
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Robert Wilson
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Pilar Cacheiro
- William Harvey Research Institute, Queen Mary University of London, London EC1M 6BQ, UK
| | - Anthony Frost
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | | | - Bora Vardal
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | - Aaron McCoy
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | - Tsz Kwan Cheng
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | - Luis Santos
- Research Data Team, The Turing Institute, 96 Euston Rd, London NW1 2DB, UK
| | - Sara Wells
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | - Damian Smedley
- William Harvey Research Institute, Queen Mary University of London, London EC1M 6BQ, UK
| | - Ann-Marie Mallon
- Research Data Team, The Turing Institute, 96 Euston Rd, London NW1 2DB, UK
| | - Helen Parkinson
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
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Gridley T, Murray SA. Mouse mutagenesis and phenotyping to generate models of development and disease. Curr Top Dev Biol 2022; 148:1-12. [PMID: 35461561 DOI: 10.1016/bs.ctdb.2022.02.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
For many years, the laboratory mouse has been the favored model organism to study mammalian development, biology and disease. Among its advantages for these studies are its close concordance with human biology, the syntenic relationship between the mouse and other mammalian genomes, the existence of many inbred strains, its short gestation period, its relatively low cost for housing and husbandry, and the wide array of tools for genome modification, mutagenesis, and for cryopreserving embryos, sperm and eggs. The advent of CRISPR genome modification techniques has considerably broadened the landscape of model organisms available for study, including other mammalian species. However, the mouse remains the most popular and utilized system to model human development, biology, and disease processes. In this review, we will briefly summarize the long history of mice as a preferred mammalian genetic and model system, and review current large-scale mutagenesis efforts using genome modification to produce improved models for mammalian development and disease.
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Affiliation(s)
- Thomas Gridley
- Center for Clinical and Translational Research, Maine Medical Center Research Institute, Scarborough, ME, United States.
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10
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Kasher M, Freidin MB, Williams FM, Cherny SS, Malkin I, Livshits G. Shared Genetic Architecture Between Rheumatoid Arthritis and Varying Osteoporotic Phenotypes. J Bone Miner Res 2022; 37:440-453. [PMID: 34910834 DOI: 10.1002/jbmr.4491] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 11/19/2021] [Accepted: 12/08/2021] [Indexed: 11/08/2022]
Abstract
Rheumatoid arthritis (RA) and low bone mineral density (BMD), an indicator of osteoporosis (OP), appear epidemiologically associated. Shared genetic factors may explain this association. This study aimed to investigate the presence of pleiotropy to clarify the potential genetic association between RA and OP. We examined BMDs at varying skeletal sites reported in UK Biobank as well as OP fracture acquired from the Genetic Factors for Osteoporosis (GEFOS) Consortium and the TwinsUK study. PRSice-2 was used to assess the potential shared genetic overlap between RA and OP. The presence of pleiotropy was examined using colocalization analysis. PRSice-2 revealed that RA was significantly associated with OP fracture (β = 351.6 ± 83.9, p value = 2.76E-05), total BMD (β = -1763.5 ± 612.8, p = 4.00E-03), spine BMD (β = -919.8 ± 264.6, p value = 5.09E-04), and forearm BMD (β = -66.09 ± 31.40, p value = 3.53E-02). Through colocalization analysis, the same causal genetic variants, associated with both RA and OP, were apparent in 12 genes: PLCL1, BOLL, AC011997.1, TNFAIP3, RP11-158I9.1, CDK6, CHCHD4P2, RP11-505C13.1, PHF19, TRAF1, C5, and C11orf49 with moderate posterior probabilities (>50%). Pleiotropy is involved in the association between RA and OP phenotypes. These findings contribute to the understanding of disease mechanisms and provide insight into possible therapeutic advancements and enhanced screening measures. © 2021 American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Melody Kasher
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Maxim B Freidin
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
| | - Frances Mk Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
| | - Stacey S Cherny
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ida Malkin
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Gregory Livshits
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK.,Adelson Medical School, Ariel University, Ariel, Israel
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11
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Peterson KA, Murray SA. Progress towards completing the mutant mouse null resource. Mamm Genome 2022; 33:123-134. [PMID: 34698892 PMCID: PMC8913489 DOI: 10.1007/s00335-021-09905-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 08/10/2021] [Indexed: 11/13/2022]
Abstract
The generation of a comprehensive catalog of null alleles covering all protein-coding genes is the goal of the International Mouse Phenotyping Consortium. Over the past 20 years, significant progress has been made towards achieving this goal through the combined efforts of many large-scale programs that built an embryonic stem cell resource to generate knockout mice and more recently employed CRISPR/Cas9-based mutagenesis to delete critical regions predicted to result in frameshift mutations, thus, ablating gene function. The IMPC initiative builds on prior and ongoing work by individual research groups creating gene knockouts in the mouse. Here, we analyze the collective efforts focusing on the combined null allele resource resulting from strains developed by the research community and large-scale production programs. Based upon this pooled analysis, we examine the remaining fraction of protein-coding genes focusing on clearly defined mouse-human orthologs as the highest priority for completing the mutant mouse null resource. In summary, we find that there are less than 3400 mouse-human orthologs remaining in the genome without a targeted null allele that can be further prioritized to achieve our overall goal of the complete functional annotation of the protein-coding portion of a mammalian genome.
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12
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Functional Validation of Osteoporosis Genetic Findings Using Small Fish Models. Genes (Basel) 2022; 13:genes13020279. [PMID: 35205324 PMCID: PMC8872034 DOI: 10.3390/genes13020279] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/26/2022] [Accepted: 01/27/2022] [Indexed: 12/11/2022] Open
Abstract
The advancement of human genomics has revolutionized our understanding of the genetic architecture of many skeletal diseases, including osteoporosis. However, interpreting results from human association studies remains a challenge, since index variants often reside in non-coding regions of the genome and do not possess an obvious regulatory function. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary, such as the one offered by animal models. These models enable us to identify causal mechanisms, clarify the underlying biology, and apply interventions. Over the past several decades, small teleost fishes, mostly zebrafish and medaka, have emerged as powerful systems for modeling the genetics of human diseases. Due to their amenability to genetic intervention and the highly conserved genetic and physiological features, fish have become indispensable for skeletal genomic studies. The goal of this review is to summarize the evidence supporting the utility of Zebrafish (Danio rerio) for accelerating our understanding of human skeletal genomics and outlining the remaining gaps in knowledge. We provide an overview of zebrafish skeletal morphophysiology and gene homology, shedding light on the advantages of human skeletal genomic exploration and validation. Knowledge of the biology underlying osteoporosis through animal models will lead to the translation into new, better and more effective therapeutic approaches.
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13
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Hines TJ, Lutz C, Murray SA, Burgess RW. An Integrated Approach to Studying Rare Neuromuscular Diseases Using Animal and Human Cell-Based Models. Front Cell Dev Biol 2022; 9:801819. [PMID: 35047510 PMCID: PMC8762301 DOI: 10.3389/fcell.2021.801819] [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: 10/25/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
As sequencing technology improves, the identification of new disease-associated genes and new alleles of known genes is rapidly increasing our understanding of the genetic underpinnings of rare diseases, including neuromuscular diseases. However, precisely because these disorders are rare and often heterogeneous, they are difficult to study in patient populations. In parallel, our ability to engineer the genomes of model organisms, such as mice or rats, has gotten increasingly efficient through techniques such as CRISPR/Cas9 genome editing, allowing the creation of precision human disease models. Such in vivo model systems provide an efficient means for exploring disease mechanisms and identifying therapeutic strategies. Furthermore, animal models provide a platform for preclinical studies to test the efficacy of those strategies. Determining whether the same mechanisms are involved in the human disease and confirming relevant parameters for treatment ideally involves a human experimental system. One system currently being used is induced pluripotent stem cells (iPSCs), which can then be differentiated into the relevant cell type(s) for in vitro confirmation of disease mechanisms and variables such as target engagement. Here we provide a demonstration of these approaches using the example of tRNA-synthetase-associated inherited peripheral neuropathies, rare forms of Charcot-Marie-Tooth disease (CMT). Mouse models have led to a better understanding of both the genetic and cellular mechanisms underlying the disease. To determine if the mechanisms are similar in human cells, we will use genetically engineered iPSC-based models. This will allow comparisons of different CMT-associated GARS alleles in the same genetic background, reducing the variability found between patient samples and simplifying the availability of cell-based models for a rare disease. The necessity of integrating mouse and human models, strategies for accomplishing this integration, and the challenges of doing it at scale are discussed using recently published work detailing the cellular mechanisms underlying GARS-associated CMT as a framework.
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14
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Al-Barghouthi BM, Rosenow WT, Du KP, Heo J, Maynard R, Mesner L, Calabrese G, Nakasone A, Senwar B, Gerstenfeld L, Larner J, Ferguson V, Ackert-Bicknell C, Morgan E, Brautigan D, Farber CR. Transcriptome-wide association study and eQTL colocalization identify potentially causal genes responsible for human bone mineral density GWAS associations. eLife 2022; 11:77285. [PMID: 36416764 PMCID: PMC9683789 DOI: 10.7554/elife.77285] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 11/16/2022] [Indexed: 11/24/2022] Open
Abstract
Genome-wide association studies (GWASs) for bone mineral density (BMD) in humans have identified over 1100 associations to date. However, identifying causal genes implicated by such studies has been challenging. Recent advances in the development of transcriptome reference datasets and computational approaches such as transcriptome-wide association studies (TWASs) and expression quantitative trait loci (eQTL) colocalization have proven to be informative in identifying putatively causal genes underlying GWAS associations. Here, we used TWAS/eQTL colocalization in conjunction with transcriptomic data from the Genotype-Tissue Expression (GTEx) project to identify potentially causal genes for the largest BMD GWAS performed to date. Using this approach, we identified 512 genes as significant using both TWAS and eQTL colocalization. This set of genes was enriched for regulators of BMD and members of bone relevant biological processes. To investigate the significance of our findings, we selected PPP6R3, the gene with the strongest support from our analysis which was not previously implicated in the regulation of BMD, for further investigation. We observed that Ppp6r3 deletion in mice decreased BMD. In this work, we provide an updated resource of putatively causal BMD genes and demonstrate that PPP6R3 is a putatively causal BMD GWAS gene. These data increase our understanding of the genetics of BMD and provide further evidence for the utility of combined TWAS/colocalization approaches in untangling the genetics of complex traits.
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Affiliation(s)
- Basel Maher Al-Barghouthi
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States,Department of Biochemistry and Molecular Genetics, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Will T Rosenow
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Kang-Ping Du
- Department of Radiation Oncology, University of VirginiaCharlottesvilleUnited States
| | - Jinho Heo
- Department of Microbiology, Immunology, and Cancer Biology, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Robert Maynard
- Department of Orthopedics, Anschutz Medical Campus, University of ColoradoAuroraUnited States
| | - Larry Mesner
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States,Department of Public Health Sciences, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Gina Calabrese
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Aaron Nakasone
- Department of Mechanical Engineering, Boston UniversityBostonUnited States
| | - Bhavya Senwar
- Department of Mechanical Engineering, University of Colorado BoulderBoulderUnited States
| | - Louis Gerstenfeld
- Department of Orthopaedic Surgery, Boston University Medical CenterBostonUnited States
| | - James Larner
- Department of Radiation Oncology, University of VirginiaCharlottesvilleUnited States
| | - Virginia Ferguson
- Department of Mechanical Engineering, University of Colorado BoulderBoulderUnited States
| | - Cheryl Ackert-Bicknell
- Department of Orthopedics, Anschutz Medical Campus, University of ColoradoAuroraUnited States
| | - Elise Morgan
- Department of Mechanical Engineering, Boston UniversityBostonUnited States
| | - David Brautigan
- Department of Microbiology, Immunology, and Cancer Biology, School of Medicine, University of VirginiaCharlottesvilleUnited States
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of VirginiaCharlottesvilleUnited States,Department of Biochemistry and Molecular Genetics, School of Medicine, University of VirginiaCharlottesvilleUnited States,Department of Public Health Sciences, School of Medicine, University of VirginiaCharlottesvilleUnited States
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15
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Kague E. Finding the genes for fragile bones. eLife 2022; 11:85161. [PMID: 36562688 PMCID: PMC9788804 DOI: 10.7554/elife.85161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Combining transcriptomic data with the analysis of large genome-wide association studies helps identify genes that are likely important for regulating bone mineral density.
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Affiliation(s)
- Erika Kague
- School of Physiology, Pharmacology and Neuroscience, University of BristolBristolUnited Kingdom
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16
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Brown SDM. Advances in mouse genetics for the study of human disease. Hum Mol Genet 2021; 30:R274-R284. [PMID: 34089057 PMCID: PMC8490014 DOI: 10.1093/hmg/ddab153] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 05/28/2021] [Accepted: 06/01/2021] [Indexed: 01/11/2023] Open
Abstract
The mouse is the pre-eminent model organism for studies of mammalian gene function and has provided an extraordinarily rich range of insights into basic genetic mechanisms and biological systems. Over several decades, the characterization of mouse mutants has illuminated the relationship between gene and phenotype, providing transformational insights into the genetic bases of disease. However, if we are to deliver the promise of genomic and precision medicine, we must develop a comprehensive catalogue of mammalian gene function that uncovers the dark genome and elucidates pleiotropy. Advances in large-scale mouse mutagenesis programmes allied to high-throughput mouse phenomics are now addressing this challenge and systematically revealing novel gene function and multi-morbidities. Alongside the development of these pan-genomic mutational resources, mouse genetics is employing a range of diversity resources to delineate gene–gene and gene–environment interactions and to explore genetic context. Critically, mouse genetics is a powerful tool for assessing the functional impact of human genetic variation and determining the causal relationship between variant and disease. Together these approaches provide unique opportunities to dissect in vivo mechanisms and systems to understand pathophysiology and disease. Moreover, the provision and utility of mouse models of disease has flourished and engages cumulatively at numerous points across the translational spectrum from basic mechanistic studies to pre-clinical studies, target discovery and therapeutic development.
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