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Zeng M, Yan S, Yang P, Li Q, Li J, Fan X, Liu X, Yao Y, Wang W, Chen R, Han G, Yang Y, Tang Z. Circular RNA transcriptome across multiple tissues reveal skeletal muscle-specific circPSME4 regulating myogenesis. Int J Biol Macromol 2023; 251:126322. [PMID: 37591436 DOI: 10.1016/j.ijbiomac.2023.126322] [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: 05/03/2023] [Revised: 08/01/2023] [Accepted: 08/03/2023] [Indexed: 08/19/2023]
Abstract
There are significant differences in meat production, growth rate and other traits between Western commercial pigs and Chinese local pigs. Comparative transcriptome approaches have identified many coding and non-coding candidate genes associated various traits. However, the expression and function of circular RNAs (circRNAs) in different pig tissues are largely unknown. In this study, we conducted a comprehensive analysis of the genome-wide circRNA expression profile across ten tissues in Luchuan (a Chinese local breed) and Duroc (a Western commercial breed) pigs. We identified a total of 56,254 circRNAs, of which 42.9 % were not previously annotated. We found that 33.7 % of these circRNAs were differentially expressed. Enrichment analysis revealed that differentially expressed circRNAs might contribute to the phenotypic differentiation between Luchuan and Duroc pigs. We identified 538 tissue-specific circRNAs, most of which were specifically expressed in the brain and skeletal muscle. Competitive endogenous RNA network analysis suggested that skeletal muscle-specific circPSME4 was co-expressed with MYOD1 and targeted by ssc-miR-181d-3p. Functional analysis revealed that circPSME4 knockdown could promote the proliferation and differentiation of myoblasts. Together, our findings provide valuable resources of circRNAs for animal breeding and biomedical research. We demonstrated that circPSME4 is a novel regulator of skeletal muscle development.
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Affiliation(s)
- Mu Zeng
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Shanying Yan
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Peng Yang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Qiaowei Li
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; School of Veterinary Medicine, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland
| | - Jiju Li
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Xinhao Fan
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Xiaoqin Liu
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yilong Yao
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Wei Wang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Ruipu Chen
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Guohao Han
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yalan Yang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China.
| | - Zhonglin Tang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan 528226, China; School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China.
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2
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Zhou X, St Pierre CL, Gonzales NM, Zou J, Cheng R, Chitre AS, Sokoloff G, Palmer AA. Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity. G3 (BETHESDA, MD.) 2020; 10:951-965. [PMID: 31974095 PMCID: PMC7056977 DOI: 10.1534/g3.119.400763] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 10/17/2019] [Indexed: 12/12/2022]
Abstract
There has been extensive discussion of the "Replication Crisis" in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner's Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.
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Affiliation(s)
- Xinzhu Zhou
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, 92092
| | - Celine L St Pierre
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63110
| | | | - Jennifer Zou
- Department of Computer Science, University of California, Los Angeles, CA, 90095
| | | | | | - Greta Sokoloff
- Department of Psychological & Brain Sciences, University of Iowa, Iowa City, IO, 52242
| | - Abraham A Palmer
- Department of Psychiatry,
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, 92037 and
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3
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Hernandez Cordero AI, Gonzales NM, Parker CC, Sokolof G, Vandenbergh DJ, Cheng R, Abney M, Sko A, Douglas A, Palmer AA, Gregory JS, Lionikas A. Genome-wide Associations Reveal Human-Mouse Genetic Convergence and Modifiers of Myogenesis, CPNE1 and STC2. Am J Hum Genet 2019; 105:1222-1236. [PMID: 31761296 PMCID: PMC6904802 DOI: 10.1016/j.ajhg.2019.10.014] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 10/28/2019] [Indexed: 12/11/2022] Open
Abstract
Muscle bulk in adult healthy humans is highly variable even after height, age, and sex are accounted for. Low muscle mass, due to fewer and/or smaller constituent muscle fibers, would exacerbate the impact of muscle loss occurring in aging or disease. Genetic variability substantially influences muscle mass differences, but causative genes remain largely unknown. In a genome-wide association study (GWAS) on appendicular lean mass (ALM) in a population of 85,750 middle-aged (aged 38-49 years) individuals from the UK Biobank (UKB), we found 182 loci associated with ALM (p < 5 × 10-8). We replicated associations for 78% of these loci (p < 5 × 10-8) with ALM in a population of 181,862 elderly (aged 60-74 years) individuals from UKB. We also conducted a GWAS on hindlimb skeletal muscle mass of 1,867 mice from an advanced intercross between two inbred strains (LG/J and SM/J); this GWAS identified 23 quantitative trait loci. Thirty-eight positional candidates distributed across five loci overlapped between the two species. In vitro studies of positional candidates confirmed CPNE1 and STC2 as modifiers of myogenesis. Collectively, these findings shed light on the genetics of muscle mass variability in humans and identify targets for the development of interventions for treatment of muscle loss. The overlapping results between humans and the mouse model GWAS point to shared genetic mechanisms across species.
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Affiliation(s)
- Ana I Hernandez Cordero
- School of Medicine, Medical Sciences, and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, UK AB24 3FX, UK
| | - Natalia M Gonzales
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Clarissa C Parker
- Department of Psychology, Middlebury College, Middlebury, VT 05753, USA; Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA
| | - Greta Sokolof
- Department of Psychological and Brain Sciences, The University of Iowa, Iowa City, IA 52242, USA
| | - David J Vandenbergh
- Department of Biobehavioral Health, Penn State Institute for the Neurosciences, and Molecular, Cellular, and Integrative Sciences Program, Pennsylvania State University, University Park, PA 16802, USA
| | - Riyan Cheng
- Department of Health Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Mark Abney
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Andrew Sko
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Alex Douglas
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, AB24 3FX, UK
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Jennifer S Gregory
- School of Medicine, Medical Sciences, and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, UK AB24 3FX, UK
| | - Arimantas Lionikas
- School of Medicine, Medical Sciences, and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, UK AB24 3FX, UK.
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4
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Abstract
In this chapter we will review both the rationale and experimental design for using Heterogeneous Stock (HS) populations for fine-mapping of complex traits in mice and rats. We define an HS as an outbred population derived from an intercross between two or more inbred strains. HS have been used to perform genome-wide association studies (GWAS) for multiple behavioral, physiological, and gene expression traits. GWAS using HS require four key steps, which we review: selection of an appropriate HS population, phenotyping, genotyping, and statistical analysis. We provide advice on the selection of an HS, comment on key issues related to phenotyping, discuss genotyping methods relevant to these populations, and describe statistical genetic analyses that are applicable to genetic analyses that use HS.
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5
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Vogel H, Kamitz A, Hallahan N, Lebek S, Schallschmidt T, Jonas W, Jähnert M, Gottmann P, Zellner L, Kanzleiter T, Damen M, Altenhofen D, Burkhardt R, Renner S, Dahlhoff M, Wolf E, Müller TD, Blüher M, Joost HG, Chadt A, Al-Hasani H, Schürmann A. A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes. Hum Mol Genet 2019; 27:3099-3112. [PMID: 29893858 PMCID: PMC6097155 DOI: 10.1093/hmg/ddy217] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Accepted: 05/29/2018] [Indexed: 12/16/2022] Open
Abstract
To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the outcross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes.
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Affiliation(s)
- Heike Vogel
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Anne Kamitz
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Nicole Hallahan
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Sandra Lebek
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Medical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Düsseldorf D-40225, Germany
| | - Tanja Schallschmidt
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Medical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Düsseldorf D-40225, Germany
| | - Wenke Jonas
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Markus Jähnert
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Pascal Gottmann
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Lisa Zellner
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Timo Kanzleiter
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Mareike Damen
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Medical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Düsseldorf D-40225, Germany
| | - Delsi Altenhofen
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Medical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Düsseldorf D-40225, Germany
| | - Ralph Burkhardt
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig D-04303, Germany
| | - Simone Renner
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Chair for Molecular Animal Breeding and Biotechnology, Gene Center.,Department of Veterinary Sciences, Center for Innovative Medical Models (CiMM), LMU Munich, D-81377 Munich, Germany
| | - Maik Dahlhoff
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Chair for Molecular Animal Breeding and Biotechnology, Gene Center.,Department of Veterinary Sciences, Center for Innovative Medical Models (CiMM), LMU Munich, D-81377 Munich, Germany
| | - Eckhard Wolf
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Chair for Molecular Animal Breeding and Biotechnology, Gene Center.,Department of Veterinary Sciences, Center for Innovative Medical Models (CiMM), LMU Munich, D-81377 Munich, Germany
| | - Timo D Müller
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Institute for Diabetes and Obesity, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg D-85764, Germany.,Division of Metabolic Diseases, Department of Medicine, Technische Universität München, Munich D-80333, Germany
| | - Matthias Blüher
- Department of Medicine, University of Leipzig, Leipzig D-04103, Germany
| | - Hans-Georg Joost
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany
| | - Alexandra Chadt
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Medical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Düsseldorf D-40225, Germany
| | - Hadi Al-Hasani
- German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Medical Faculty, Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Düsseldorf D-40225, Germany
| | - Annette Schürmann
- Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal D-14558, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg D-85764, Germany.,Institute of Nutritional Science, University of Potsdam, Nuthetal D-14558, Germany
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6
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Hernandez Cordero AI, Carbonetto P, Riboni Verri G, Gregory JS, Vandenbergh DJ, P Gyekis J, Blizard DA, Lionikas A. Replication and discovery of musculoskeletal QTLs in LG/J and SM/J advanced intercross lines. Physiol Rep 2019; 6. [PMID: 29479840 PMCID: PMC6430048 DOI: 10.14814/phy2.13561] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 12/02/2017] [Accepted: 12/05/2017] [Indexed: 12/14/2022] Open
Abstract
The genetics underlying variation in health‐related musculoskeletal phenotypes can be investigated in a mouse model. Quantitative trait loci (QTLs) affecting musculoskeletal traits in the LG/J and SM/J strain lineage remain to be refined and corroborated. The aim of this study was to map muscle and bone traits in males (n = 506) of the 50th filial generation of advanced intercross lines (LG/SM AIL) derived from the two strains. Genetic contribution to variation in all musculoskeletal traits was confirmed; the SNP heritability of muscle mass ranged between 0.46 and 0.56; and the SNP heritability of tibia length was 0.40. We used two analytical software, GEMMA and QTLRel, to map the underlying QTLs. GEMMA required substantially less computation and recovered all the QTLs identified by QTLRel. Seven significant QTLs were identified for muscle weight (Chr 1, 7, 11, 12, 13, 15, and 16), and two for tibia length, (Chr 1 and 13). Each QTL explained 4–5% of phenotypic variation. One muscle and both bone loci replicated previous findings; the remaining six were novel. Positional candidates for the replicated QTLs were prioritized based on in silico analyses and gene expression in muscle tissue. In summary, we replicated existing QTLs and identified novel QTLs affecting muscle weight, and replicated bone length QTLs in LG/SM AIL males. Heritability estimates substantially exceed the cumulative effect of the QTLs, hence a richer genetic architecture contributing to muscle and bone variability could be uncovered with a larger sample size.
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Affiliation(s)
- Ana I Hernandez Cordero
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Peter Carbonetto
- Research Computing Center and Department of Human Genetics, University of Chicago, Chicago, Illinois
| | - Gioia Riboni Verri
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Jennifer S Gregory
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - David J Vandenbergh
- Department of Biobehavioral Health, The Penn State Institute for the Neurosciences, Molecular and Cellular Integrative Biosciences Program, The Pennsylvania State University, University Park, Pennsylvania
| | - Joseph P Gyekis
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania
| | - David A Blizard
- Department of Biobehavioral Health, The Penn State Institute for the Neurosciences, Molecular and Cellular Integrative Biosciences Program, The Pennsylvania State University, University Park, Pennsylvania
| | - Arimantas Lionikas
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
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7
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Gonzales NM, Seo J, Hernandez Cordero AI, St Pierre CL, Gregory JS, Distler MG, Abney M, Canzar S, Lionikas A, Palmer AA. Genome wide association analysis in a mouse advanced intercross line. Nat Commun 2018; 9:5162. [PMID: 30514929 PMCID: PMC6279738 DOI: 10.1038/s41467-018-07642-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 11/15/2018] [Indexed: 12/14/2022] Open
Abstract
The LG/J x SM/J advanced intercross line of mice (LG x SM AIL) is a multigenerational outbred population. High minor allele frequencies, a simple genetic background, and the fully sequenced LG and SM genomes make it a powerful population for genome-wide association studies. Here we use 1,063 AIL mice to identify 126 significant associations for 50 traits relevant to human health and disease. We also identify thousands of cis- and trans-eQTLs in the hippocampus, striatum, and prefrontal cortex of ~200 mice. We replicate an association between locomotor activity and Csmd1, which we identified in an earlier generation of this AIL, and show that Csmd1 mutant mice recapitulate the locomotor phenotype. Our results demonstrate the utility of the LG x SM AIL as a mapping population, identify numerous novel associations, and shed light on the genetic architecture of mammalian behavior.
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Affiliation(s)
- Natalia M Gonzales
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Jungkyun Seo
- Center for Genomic & Computational Biology, Duke University, Durham, NC, 27708, USA
- Graduate Program in Computational Biology and Bioinformatics, Duke University, Durham, NC, 27708, USA
| | - Ana I Hernandez Cordero
- School of Medicine, Medical Sciences and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, AB25 2ZD, UK
| | - Celine L St Pierre
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Jennifer S Gregory
- School of Medicine, Medical Sciences and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, AB25 2ZD, UK
| | - Margaret G Distler
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Mark Abney
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Stefan Canzar
- Gene Center, Ludwig-Maximilians-Universität München, 81377, Munich, Germany
| | - Arimantas Lionikas
- School of Medicine, Medical Sciences and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, AB25 2ZD, UK
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
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