1
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Chen Q, Zhang W, Cai J, Ni Y, Xiao L, Zhang J. Transcriptome analysis in comparing carcass and meat quality traits of Jiaxing Black Pig and Duroc × Duroc × Berkshire × Jiaxing Black Pig crosses. Gene 2022; 808:145978. [PMID: 34592352 DOI: 10.1016/j.gene.2021.145978] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 08/31/2021] [Accepted: 09/24/2021] [Indexed: 01/17/2023]
Abstract
This study compares two typical strains: Chinese local excellent meat quality of Jiaxing Black (JXB) Pig and quadratic crossbred pig strain Duroc × Duroc × Berkshire × Jiaxing Black (DDBJ). It was found that between the two pig strains, carcass traits and meat quality traits differed significantly. This is exemplified by the leanness and dressing out percent of DDBJ that were significantly higher than JXB pigs of the same age (P < 0.05) and the better growth rate of DDBJ pigs as to JXB pigs was shown by quantifying muscle proliferation and differentiation of longissimus dorsi muscle employing Hematoxylin and Eosin staining of longissimus dorsi muscle. Nutrients such as inosinic acid, intramuscular fat, and free amino acids in the longissimus dorsi muscle were significantly higher in JXB pigs than DDBJ pigs (p < 0.0001); saturated fatty acids were higher in JXB than in DDBJ pigs (p = 0.0097); essential amino acids and fresh taste amino acids (serine, glutamic acid, proline, glycine, alanine) of JXB pigs was higher than that of DDBJ pigs (p < 0.0001) and amino acids in longissimus dorsi muscle of JXB pigs surpasses the amino acid concentration of DDBJ pigs (p < 0.0001), thus showing the superiority of JXB in terms of meat quality. However, the content of polyunsaturated fatty acids, which is responsible for poor meat quality, was significantly higher in the longissimus dorsi muscle of DDBJ pig than JXB pigs (p < 0.0001); RNA-seq analysis of 5 biological replicates from two of the strains was performed. The screening of 164 up-regulated genes and 183 down-regulated genes found in longissimus dorsi muscle of DDBJ was done and the results identified differentially expressed genes related to muscle development, adipogenesis, amino acid metabolism, fatty acid metabolism and inosine synthesis. In conclusion, the study identified functional genes, elucidated the mechanisms associated with carcass quality traits, meat quality traits and other related traits, and provided means of genetic enhancement to improve meat quality traits and carcass traits in Chinese commercial pigs.
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Affiliation(s)
- Qiangqiang Chen
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China.
| | - Wei Zhang
- Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou 310058, China.
| | - Jianfeng Cai
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China.
| | - Yifan Ni
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Lixia Xiao
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China.
| | - Jinzhi Zhang
- College of Animal Sciences, Zhejiang University, Hangzhou 310058, China.
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2
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Kumar M, Srivastav AK, Parmar D. Genetic analysis and epistatic interaction association of lipid traits in a C57xBalb/c F2 mice. GENE REPORTS 2020. [DOI: 10.1016/j.genrep.2020.100729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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3
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Chao T, Liu Z, Zhang Y, Zhang L, Huang R, He L, Gu Y, Chen Z, Zheng Q, Shi L, Zheng W, Qi X, Kong E, Zhang Z, Lawrence T, Liang Y, Lu L. Precise and Rapid Validation of Candidate Gene by Allele Specific Knockout With CRISPR/Cas9 in Wild Mice. Front Genet 2019; 10:124. [PMID: 30838037 PMCID: PMC6390232 DOI: 10.3389/fgene.2019.00124] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Accepted: 02/04/2019] [Indexed: 11/13/2022] Open
Abstract
It is a tempting goal to identify causative genes underlying phenotypic differences among inbred strains of mice, which is a huge reservoir of genetic resources to understand mammalian pathophysiology. In particular, the wild-derived mouse strains harbor enormous genetic variations that have been acquired during evolutionary divergence over 100s of 1000s of years. However, validating the genetic variation in non-classical strains was extremely difficult, until the advent of CRISPR/Cas9 genome editing tools. In this study, we first describe a T cell phenotype in both wild-derived PWD/PhJ parental mice and F1 hybrids, from a cross to C57BL/6 (B6) mice, and we isolate a genetic locus on Chr2, using linkage mapping and chromosome substitution mice. Importantly, we validate the identification of the functional gene controlling this T cell phenotype, Cd44, by allele specific knockout of the PWD copy, leaving the B6 copy completely intact. Our experiments using F1 mice with a dominant phenotype, allowed rapid validation of candidate genes by designing sgRNA PAM sequences that only target the DNA of the PWD genome. We obtained 10 animals derived from B6 eggs fertilized with PWD sperm cells which were subjected to microinjection of CRISPR/Cas9 gene targeting machinery. In the newborns of F1 hybrids, 80% (n = 10) had allele specific knockout of the candidate gene Cd44 of PWD origin, and no mice showed mistargeting of the B6 copy. In the resultant allele-specific knockout F1 mice, we observe full recovery of T cell phenotype. Therefore, our study provided a precise and rapid approach to functionally validate genes that could facilitate gene discovery in classic mouse genetics. More importantly, as we succeeded in genetic manipulation of mice, allele specific knockout could provide the possibility to inactivate disease alleles while keeping the normal allele of the gene intact in human cells.
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Affiliation(s)
- Tianzhu Chao
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Zhuangzhuang Liu
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Yu Zhang
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Lichen Zhang
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Rong Huang
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Le He
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Yanrong Gu
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Zhijun Chen
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Qianqian Zheng
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Lijin Shi
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Wenping Zheng
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Xinhui Qi
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Eryan Kong
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China
| | - Zhongjian Zhang
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China
| | - Toby Lawrence
- Centre for Inflammation Biology and Cancer Immunology, King's College London, London, United Kingdom
| | - Yinming Liang
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China.,Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
| | - Liaoxun Lu
- Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China.,Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, China
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4
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Identification of Quantitative Trait Loci That Determine Plasma Total-Cholesterol and Triglyceride Concentrations in DDD/Sgn and C57BL/6J Inbred Mice. CHOLESTEROL 2017. [PMID: 28642824 PMCID: PMC5469984 DOI: 10.1155/2017/3178204] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
DDD/Sgn mice have significantly higher plasma lipid concentrations than C57BL/6J mice. In the present study, we performed quantitative trait loci (QTL) mapping for plasma total-cholesterol (CHO) and triglyceride (TG) concentrations in reciprocal F2 male intercross populations between the two strains. By single-QTL scans, we identified four significant QTL on chromosomes (Chrs) 1, 5, 17, and 19 for CHO and two significant QTL on Chrs 1 and 12 for TG. By including cross direction as an interactive covariate, we identified separate significant QTL on Chr 17 for CHO but none for TG. When the large phenotypic effect of QTL on Chr 1 was controlled by composite interval mapping, we identified three additional significant QTL on Chrs 3, 4, and 9 for CHO but none for TG. QTL on Chr 19 was a novel QTL for CHO and the allelic effect of this QTL significantly differed between males and females. Whole-exome sequence analysis in DDD/Sgn mice suggested that Apoa2 and Acads were the plausible candidate genes underlying CHO QTL on Chrs 1 and 5, respectively. Thus, we identified a multifactorial basis for plasma lipid concentrations in male mice. These findings will provide insight into the genetic mechanisms of plasma lipid metabolism.
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5
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Nault R, Fader KA, Lydic TA, Zacharewski TR. Lipidomic Evaluation of Aryl Hydrocarbon Receptor-Mediated Hepatic Steatosis in Male and Female Mice Elicited by 2,3,7,8-Tetrachlorodibenzo-p-dioxin. Chem Res Toxicol 2017; 30:1060-1075. [PMID: 28238261 PMCID: PMC5896278 DOI: 10.1021/acs.chemrestox.6b00430] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) induces hepatic steatosis mediated by the aryl hydrocarbon receptor. To further characterize TCDD-elicited hepatic lipid accumulation, mice were gavaged with TCDD every 4 days for 28 days. Liver samples were examined using untargeted lipidomics with structural confirmation of lipid species by targeted high-resolution MS/MS, and data were integrated with complementary RNA-Seq analyses. Approximately 936 unique spectral features were detected, of which 379 were confirmed as unique lipid species. Both male and female samples exhibited similar qualitative changes (lipid species) but differed in quantitative changes. A shift to higher mass lipid species was observed, indicative of increased free fatty acid (FFA) packaging. For example, of the 13 lipid classes examined, triglycerides increased from 46 to 48% of total lipids to 68-83% in TCDD treated animals. Hepatic cholesterol esters increased 11.3-fold in male mice with moieties consisting largely of dietary fatty acids (FAs) (i.e., linolenate, palmitate, and oleate). Phosphatidylserines, phosphatidylethanolamines, phosphatidic acids, and cardiolipins decreased 4.1-, 5.0-, 5.4- and 7.4-fold, respectively, while ceramides increased 6.6-fold. Accordingly, the integration of lipidomic data with differential gene expression associated with lipid metabolism suggests that in addition to the repression of de novo fatty acid synthesis and β-oxidation, TCDD also increased hepatic uptake and packaging of lipids, while inhibiting VLDL secretion, consistent with hepatic fat accumulation and the progression to steatohepatitis with fibrosis.
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Affiliation(s)
- Rance Nault
- Biochemistry & Molecular Biology, Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan 48824, United States
| | - Kelly A. Fader
- Biochemistry & Molecular Biology, Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan 48824, United States
| | - Todd A. Lydic
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824, United States
| | - Timothy R. Zacharewski
- Biochemistry & Molecular Biology, Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan 48824, United States
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6
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Massett MP, Avila JJ, Kim SK. Exercise Capacity and Response to Training Quantitative Trait Loci in a NZW X 129S1 Intercross and Combined Cross Analysis of Inbred Mouse Strains. PLoS One 2015; 10:e0145741. [PMID: 26710100 PMCID: PMC4692404 DOI: 10.1371/journal.pone.0145741] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2015] [Accepted: 12/08/2015] [Indexed: 02/06/2023] Open
Abstract
Genetic factors determining exercise capacity and the magnitude of the response to exercise training are poorly understood. The aim of this study was to identify quantitative trait loci (QTL) associated with exercise training in mice. Based on marked differences in training responses in inbred NZW (-0.65 ± 1.73 min) and 129S1 (6.18 ± 3.81 min) mice, a reciprocal intercross breeding scheme was used to generate 285 F2 mice. All F2 mice completed an exercise performance test before and after a 4-week treadmill running program, resulting in an increase in exercise capacity of 1.54 ± 3.69 min (range = -10 to +12 min). Genome-wide linkage scans were performed for pre-training, post-training, and change in run time. For pre-training exercise time, suggestive QTL were identified on Chromosomes 5 (57.4 cM, 2.5 LOD) and 6 (47.8 cM, 2.9 LOD). A significant QTL for post-training exercise capacity was identified on Chromosome 5 (43.4 cM, 4.1 LOD) and a suggestive QTL on Chromosomes 1 (55.7 cM, 2.3 LOD) and 8 (66.1 cM, 2.2 LOD). A suggestive QTL for the change in run time was identified on Chromosome 6 (37.8 cM, 2.7 LOD). To identify shared QTL, this data set was combined with data from a previous F2 cross between B6 and FVB strains. In the combined cross analysis, significant novel QTL for pre-training exercise time and change in exercise time were identified on Chromosome 12 (54.0 cM, 3.6 LOD) and Chromosome 6 (28.0 cM, 3.7 LOD), respectively. Collectively, these data suggest that combined cross analysis can be used to identify novel QTL and narrow the confidence interval of QTL for exercise capacity and responses to training. Furthermore, these data support the use of larger and more diverse mapping populations to identify the genetic basis for exercise capacity and responses to training.
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Affiliation(s)
- Michael P. Massett
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas, United States of America
- * E-mail:
| | - Joshua J. Avila
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas, United States of America
| | - Seung Kyum Kim
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas, United States of America
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7
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A forest-based feature screening approach for large-scale genome data with complex structures. BMC Genet 2015; 16:148. [PMID: 26698561 PMCID: PMC4690313 DOI: 10.1186/s12863-015-0294-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2015] [Accepted: 11/13/2015] [Indexed: 01/06/2023] Open
Abstract
Background Genome-wide association studies (GWAS) interrogate large-scale whole genome to characterize the complex genetic architecture for biomedical traits. When the number of SNPs dramatically increases to half million but the sample size is still limited to thousands, the traditional p-value based statistical approaches suffer from unprecedented limitations. Feature screening has proved to be an effective and powerful approach to handle ultrahigh dimensional data statistically, yet it has not received much attention in GWAS. Feature screening reduces the feature space from millions to hundreds by removing non-informative noise. However, the univariate measures used to rank features are mainly based on individual effect without considering the mutual interactions with other features. In this article, we explore the performance of a random forest (RF) based feature screening procedure to emphasize the SNPs that have complex effects for a continuous phenotype. Results Both simulation and real data analysis are conducted to examine the power of the forest-based feature screening. We compare it with five other popular feature screening approaches via simulation and conclude that RF can serve as a decent feature screening tool to accommodate complex genetic effects such as nonlinear, interactive, correlative, and joint effects. Unlike the traditional p-value based Manhattan plot, we use the Permutation Variable Importance Measure (PVIM) to display the relative significance and believe that it will provide as much useful information as the traditional plot. Conclusion Most complex traits are found to be regulated by epistatic and polygenic variants. The forest-based feature screening is proven to be an efficient, easily implemented, and accurate approach to cope whole genome data with complex structures. Our explorations should add to a growing body of enlargement of feature screening better serving the demands of contemporary genome data.
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8
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Bennett BJ, Davis RC, Civelek M, Orozco L, Wu J, Qi H, Pan C, Packard RRS, Eskin E, Yan M, Kirchgessner T, Wang Z, Li X, Gregory JC, Hazen SL, Gargalovic PS, Lusis AJ. Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains. PLoS Genet 2015; 11:e1005711. [PMID: 26694027 PMCID: PMC4687930 DOI: 10.1371/journal.pgen.1005711] [Citation(s) in RCA: 103] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Accepted: 11/06/2015] [Indexed: 12/15/2022] Open
Abstract
Common forms of atherosclerosis involve multiple genetic and environmental factors. While human genome-wide association studies have identified numerous loci contributing to coronary artery disease and its risk factors, these studies are unable to control environmental factors or examine detailed molecular traits in relevant tissues. We now report a study of natural variations contributing to atherosclerosis and related traits in over 100 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). The mice were made hyperlipidemic by transgenic expression of human apolipoprotein E-Leiden (APOE-Leiden) and human cholesteryl ester transfer protein (CETP). The mice were examined for lesion size and morphology as well as plasma lipid, insulin and glucose levels, and blood cell profiles. A subset of mice was studied for plasma levels of metabolites and cytokines. We also measured global transcript levels in aorta and liver. Finally, the uptake of acetylated LDL by macrophages from HMDP mice was quantitatively examined. Loci contributing to the traits were mapped using association analysis, and relationships among traits were examined using correlation and statistical modeling. A number of conclusions emerged. First, relationships among atherosclerosis and the risk factors in mice resemble those found in humans. Second, a number of trait-loci were identified, including some overlapping with previous human and mouse studies. Third, gene expression data enabled enrichment analysis of pathways contributing to atherosclerosis and prioritization of candidate genes at associated loci in both mice and humans. Fourth, the data provided a number of mechanistic inferences; for example, we detected no association between macrophage uptake of acetylated LDL and atherosclerosis. Fifth, broad sense heritability for atherosclerosis was much larger than narrow sense heritability, indicating an important role for gene-by-gene interactions. Sixth, stepwise linear regression showed that the combined variations in plasma metabolites, including LDL/VLDL-cholesterol, trimethylamine N-oxide (TMAO), arginine, glucose and insulin, account for approximately 30 to 40% of the variation in atherosclerotic lesion area. Overall, our data provide a rich resource for studies of complex interactions underlying atherosclerosis. While recent genetic association studies in human populations have succeeded in identifying genetic loci that contribute to coronary artery disease (CAD) and related phenotypes, these loci explain only a small fraction of the genetic variation in CAD and associated traits. Here, we present a complementary approach using association analysis of atherosclerotic traits among inbred strains of mice. A strength of this approach is that it enables in-depth phenotypic characterization including gene expression and metabolic profiling across a variety of tissues, and integration of these molecular phenotypes with coronary artery disease itself. A striking finding was the large fraction of atherosclerosis that was explained by genetic interactions. Association analysis allowed us to identify genetic loci for atherosclerotic lesion area as well as transcript, cytokine and metabolite levels, and relationships among the traits were examined by correlation and network modeling. The plasma metabolites associated with atherosclerosis in mice, namely, LDL/VLDL-cholesterol, TMAO, arginine, glucose and insulin, overlapped with those observed in humans and accounted for approximately 30 to 40% of the observed variation in atherosclerotic lesion area. In summary, our data provide a detailed overview of the genetic architecture of atherosclerosis in mice and a rich resource for studies of the complex genetic and metabolic interactions that underlie the disease.
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Affiliation(s)
- Brian J. Bennett
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Richard C. Davis
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Mete Civelek
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Luz Orozco
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Judy Wu
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Hannah Qi
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Calvin Pan
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - René R. Sevag Packard
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Eleazar Eskin
- Department of Computer Science, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Mujing Yan
- Department of Cardiovascular Drug Discovery, Bristol-Myers Squibb, Princeton, New Jersey, United States of America
| | - Todd Kirchgessner
- Department of Cardiovascular Drug Discovery, Bristol-Myers Squibb, Princeton, New Jersey, United States of America
| | - Zeneng Wang
- Department of Cellular and Molecular Medicine (NC10), Cleveland Clinic Lerner Research Institute, Cleveland, Ohio, United States of America
| | - Xinmin Li
- Department of Cellular and Molecular Medicine (NC10), Cleveland Clinic Lerner Research Institute, Cleveland, Ohio, United States of America
| | - Jill C. Gregory
- Department of Cellular and Molecular Medicine (NC10), Cleveland Clinic Lerner Research Institute, Cleveland, Ohio, United States of America
| | - Stanley L. Hazen
- Department of Cellular and Molecular Medicine (NC10), Cleveland Clinic Lerner Research Institute, Cleveland, Ohio, United States of America
| | - Peter S. Gargalovic
- Department of Cardiovascular Drug Discovery, Bristol-Myers Squibb, Princeton, New Jersey, United States of America
| | - Aldons J. Lusis
- Departments of Medicine, Human Genetics, and Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
- * E-mail:
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9
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Saunders G, Fu G, Stevens JR. A graphical weighted power improving multiplicity correction approach for SNP selections. Curr Genomics 2014; 15:380-9. [PMID: 25435800 PMCID: PMC4245697 DOI: 10.2174/138920291505141106103959] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2014] [Revised: 09/08/2014] [Accepted: 09/08/2014] [Indexed: 11/22/2022] Open
Abstract
Controlling for the multiplicity effect is an essential part of determining statistical significance in large-scale single-locus association genome scans on Single Nucleotide Polymorphisms (SNPs). Bonferroni adjustment is a commonly used approach due to its simplicity, but is conservative and has low power for large-scale tests. The permutation test, which is a powerful and popular tool, is computationally expensive and may mislead in the presence of family structure. We propose a computationally efficient and powerful multiple testing correction approach for Linkage Disequilibrium (LD) based Quantitative Trait Loci (QTL) mapping on the basis of graphical weighted-Bonferroni methods. The proposed multiplicity adjustment method synthesizes weighted Bonferroni-based closed testing procedures into a powerful and versatile graphical approach. By tailoring different priorities for the two hypothesis tests involved in LD based QTL mapping, we are able to increase power and maintain computational efficiency and conceptual simplicity. The proposed approach enables strong control of the familywise error rate (FWER). The performance of the proposed approach as compared to the standard Bonferroni correction is illustrated by simulation and real data. We observe a consistent and moderate increase in power under all simulated circumstances, among different sample sizes, heritabilities, and number of SNPs. We also applied the proposed method to a real outbred mouse HDL cholesterol QTL mapping project where we detected the significant QTLs that were highlighted in the literature, while still ensuring strong control of the FWER.
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Affiliation(s)
- Garrett Saunders
- Department of Mathematics and Statistics, Utah State University, Logan, UT 84322, USA
| | - Guifang Fu
- Department of Mathematics and Statistics, Utah State University, Logan, UT 84322, USA
| | - John R Stevens
- Department of Mathematics and Statistics, Utah State University, Logan, UT 84322, USA
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10
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Kayashima Y, Tomita H, Zhilicheva S, Kim S, Kim HS, Bennett BJ, Maeda N. Quantitative trait loci affecting atherosclerosis at the aortic root identified in an intercross between DBA2J and 129S6 apolipoprotein E-null mice. PLoS One 2014; 9:e88274. [PMID: 24586312 PMCID: PMC3930552 DOI: 10.1371/journal.pone.0088274] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2013] [Accepted: 01/09/2014] [Indexed: 12/23/2022] Open
Abstract
Apolipoprotein E-null mice on a DBA/2J genetic background (DBA-apoE) are highly susceptible to atherosclerosis in the aortic root area compared with those on a 129S6 background (129-apoE). To explore atherosclerosis-responsible genetic regions, we performed a quantitative trait locus (QTL) analysis using 172 male and 137 female F2 derived from an intercross between DBA-apoE and 129-apoE mice. A genome-wide scan identified two significant QTL for the size of lesions at the root: one is Ath44 on Chromosome (Chr) 1 at 158 Mb, and the other Ath45 on Chr 2 at 162 Mb. Ath44 co-localizes with but appears to be independent of a previously reported QTL, Ath1, while Ath45 is a novel QTL. DBA alleles of both Ath44 and Ath45 confer atherosclerosis-susceptibility. In addition, a QTL on Chr 14 at 73 Mb was found significant only in males, and 129 allele conferring susceptibility. Further analysis detected female-specific interactions between a second QTL on Chr 1 at 73 Mb and a QTL on Chr 3 at 21 Mb, and between Chr 7 at 84 Mb and Chr 12 at 77 Mb. These loci for the root atherosclerosis were independent of QTLs for plasma total cholesterol and QTLs for triglycerides, but a QTL for HDL (Chr 1 at 126 Mb) overlapped with the Ath44. Notably, haplotype analysis among 129S6, DBA/2J and C57BL/6 genomes and their gene expression data narrowed the candidate regions for Ath44 and Ath45 to less than 5 Mb intervals where multiple genome wide associations with cardiovascular phenotypes have also been reported in humans. SNPs in or near Fmo3, Sele and Selp for Ath44, and Lbp and Pkig for Ath45 were suggested for further investigation as potential candidates underlying the atherosclerosis susceptibility.
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Affiliation(s)
- Yukako Kayashima
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Hirofumi Tomita
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Svetlana Zhilicheva
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Shinja Kim
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Hyung-Suk Kim
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Brian J. Bennett
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Nobuyo Maeda
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- * E-mail:
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11
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Identification of a novel polymorphism in X-linked sterol-4-alpha-carboxylate 3-dehydrogenase (Nsdhl) associated with reduced high-density lipoprotein cholesterol levels in I/LnJ mice. G3-GENES GENOMES GENETICS 2013; 3:1819-25. [PMID: 23979938 PMCID: PMC3789806 DOI: 10.1534/g3.113.007567] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Loci controlling plasma lipid concentrations were identified by performing a quantitative trait locus analysis on genotypes from 233 mice from a F2 cross between KK/HlJ and I/LnJ, two strains known to differ in their high-density lipoprotein (HDL) cholesterol levels. When fed a standard diet, HDL cholesterol concentration was affected by two significant loci, the Apoa2 locus on Chromosome (Chr) 1 and a novel locus on Chr X, along with one suggestive locus on Chr 6. Non-HDL concentration also was affected by loci on Chr 1 and X along with a suggestive locus on Chr 3. Additional loci that may be sex-specific were identified for HDL cholesterol on Chr 2, 3, and 4 and for non-HDL cholesterol on Chr 5, 7, and 14. Further investigation into the potential causative gene on Chr X for reduced HDL cholesterol levels revealed a novel, I/LnJ-specific nonsynonymous polymorphism in Nsdhl, which codes for sterol-4-alpha-carboxylate 3-dehydrogenase in the cholesterol synthesis pathway. Although many lipid quantitative trait locus have been reported previously, these data suggest there are additional genes left to be identified that control lipid levels and that can provide new pharmaceutical targets.
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12
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Ackert-Bicknell C, Paigen B, Korstanje R. Recalculation of 23 mouse HDL QTL datasets improves accuracy and allows for better candidate gene analysis. J Lipid Res 2013; 54:984-94. [PMID: 23393305 DOI: 10.1194/jlr.m033035] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
In the past 15 years, the quantitative trait locus (QTL) mapping approach has been applied to crosses between different inbred mouse strains to identify genetic loci associated with plasma HDL cholesterol levels. Although successful, a disadvantage of this method is low mapping resolution, as often several hundred candidate genes fall within the confidence interval for each locus. Methods have been developed to narrow these loci by combining the data from the different crosses, but they rely on the accurate mapping of the QTL and the treatment of the data in a consistent manner. We collected 23 raw datasets used for the mapping of previously published HDL QTL and reanalyzed the data from each cross using a consistent method and the latest mouse genetic map. By utilizing this approach, we identified novel QTL and QTL that were mapped to the wrong part of chromosomes. Our new HDL QTL map allows for reliable combining of QTL data and candidate gene analysis, which we demonstrate by identifying Grin3a and Etv6, as candidate genes for QTL on chromosomes 4 and 6, respectively. In addition, we were able to narrow a QTL on Chr 19 to five candidates.
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13
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Abstract
Genome-wide association studies (GWASs) have transformed the field of human genetics and have led to the discovery of hundreds of genes that are implicated in human disease. The technological advances that drove this revolution are now poised to transform genetic studies in model organisms, including mice. However, the design of GWASs in mouse strains is fundamentally different from the design of human GWASs, creating new challenges and opportunities. This Review gives an overview of the novel study designs for mouse GWASs, which dramatically improve both the statistical power and resolution compared to classical gene-mapping approaches.
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Affiliation(s)
- Jonathan Flint
- The Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, UK
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14
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Kraja AT, Lawson HA, Arnett DK, Borecki IB, Broeckel U, de las Fuentes L, Hunt SC, Province MA, Cheverud J, Rao D. Obesity-insulin targeted genes in the 3p26-25 region in human studies and LG/J and SM/J mice. Metabolism 2012; 61:1129-41. [PMID: 22386932 PMCID: PMC3586585 DOI: 10.1016/j.metabol.2012.01.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2011] [Revised: 01/05/2012] [Accepted: 01/06/2012] [Indexed: 01/05/2023]
Abstract
Identifying metabolic syndrome (MetS) genes is important for novel drug development and health care. This study extends the findings on human chromosome 3p26-25 for an identified obesity-insulin factor QTL, with an LOD score above 3. A focused association analysis comprising up to 9578 African American and Caucasian subjects from the HyperGEN Network (908 African Americans and 1025 whites), the Family Heart Study (3035 whites in time 1 and 1943 in time 2), and the Framingham Heart Study (1317 in Offspring and 1320 in Generation 3) was performed. The homologous mouse region was explored in an F(16) generation of an advanced intercross between the LG/J and SM/J inbred strains, in an experiment where 1002 animals were fed low-fat (247 males; 254 females) or high-fat (253 males; 248 females) diets. Association results in humans indicate pleiotropic effects for SNPs within or surrounding CNTN4 on obesity, lipids and blood pressure traits and for SNPs near IL5RA, TRNT1, CRBN, and LRRN1 on central obesity and blood pressure. Linkage analyses of this region in LG/J×SM/J mice identify a highly significant pleiotropic QTL peak for insulin and glucose levels, as well as response to glucose challenge. The mouse results show that insulin and glucose levels interact with high and low fat diets and differential gene expression was identified for Crbn and Arl8b. In humans, ARL8B resides ~137kbps away from BHLHE40, expression of which shows up-regulation in response to insulin treatment. This focused human genetic analysis, incorporating mouse research evidenced that 3p26-25 has important genetic contributions to MetS components. Several of the candidate genes have functions in the brain. Their interaction with MetS and the brain warrants further investigation.
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Affiliation(s)
- Aldi T. Kraja
- Division of Statistical Genomics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Corresponding authors. Aldi Kraja, is to be contacted at Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO 63110 USA. Heather Lawson, Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Heather A. Lawson
- Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Corresponding authors. Aldi Kraja, is to be contacted at Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO 63110 USA. Heather Lawson, Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Donna K. Arnett
- Department of Epidemiology, University of Alabama, Birmingham, AL 35294, USA
| | - Ingrid B. Borecki
- Division of Statistical Genomics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ulrich Broeckel
- Individualized Medicine Institute, Medical College of Wisconsin, WI 53226, USA
| | - Lisa de las Fuentes
- Cardiovascular Division Department of Medicine, Cardiovascular Imaging and Clinical Research Core Laboratory, Washington University School of Medicine 63110, St. Louis, MO, USA
| | - Steven C. Hunt
- Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
| | - Michael A. Province
- Division of Statistical Genomics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - James Cheverud
- Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - D.C. Rao
- Division of Biostatistics, Washington University School of Medicine 63110, St. Louis, MO, USA
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15
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Leduc MS, Blair RH, Verdugo RA, Tsaih SW, Walsh K, Churchill GA, Paigen B. Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross. J Lipid Res 2012; 53:1163-75. [PMID: 22498810 DOI: 10.1194/jlr.m025833] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification.
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16
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Stylianou IM, Bauer RC, Reilly MP, Rader DJ. Genetic basis of atherosclerosis: insights from mice and humans. Circ Res 2012; 110:337-55. [PMID: 22267839 DOI: 10.1161/circresaha.110.230854] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Atherosclerosis is a complex and heritable disease involving multiple cell types and the interactions of many different molecular pathways. The genetic and molecular mechanisms of atherosclerosis have, in part, been elucidated by mouse models; at least 100 different genes have been shown to influence atherosclerosis in mice. Importantly, unbiased genome-wide association studies have recently identified a number of novel loci robustly associated with atherosclerotic coronary artery disease. Here, we review the genetic data elucidated from mouse models of atherosclerosis, as well as significant associations for human coronary artery disease. Furthermore, we discuss in greater detail some of these novel human coronary artery disease loci. The combination of mouse and human genetics has the potential to identify and validate novel genes that influence atherosclerosis, some of which may be candidates for new therapeutic approaches.
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Affiliation(s)
- Ioannis M Stylianou
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, 654 BRBII/III Labs, 421 Curie Boulevard, Philadelphia, Pennsylvania, 19104-6160, USA
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17
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Genome-wide association mapping of quantitative traits in outbred mice. G3-GENES GENOMES GENETICS 2012; 2:167-74. [PMID: 22384395 PMCID: PMC3284324 DOI: 10.1534/g3.111.001792] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2011] [Accepted: 10/06/2011] [Indexed: 11/18/2022]
Abstract
Recent developments in high-density genotyping and statistical analysis methods that have enabled genome-wide association studies in humans can also be applied to outbred mouse populations. Increased recombination in outbred populations is expected to provide greater mapping resolution than traditional inbred line crosses, improving prospects for identifying the causal genes. We carried out genome-wide association mapping by using 288 mice from a commercially available outbred stock; NMRI mice were genotyped with a high-density single-nucleotide polymorphism array to map loci influencing high-density lipoprotein cholesterol, systolic blood pressure, triglyceride levels, glucose, and urinary albumin-to-creatinine ratios. We found significant associations (P < 10(-5)) with high-density lipoprotein cholesterol and identified Apoa2 and Scarb1, both of which have been previously reported, as candidate genes for these associations. Additional suggestive associations (P < 10(-3)) identified in this study were also concordant with published quantitative trait loci, suggesting that we are sampling from a limited pool of genetic diversity that has already been well characterized. These findings dampen our enthusiasm for currently available commercial outbred stocks as genetic mapping resources and highlight the need for new outbred populations with greater genetic diversity. Despite the lack of novel associations in the NMRI population, our analysis strategy illustrates the utility of methods that could be applied to genome-wide association studies in humans.
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18
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Ackert-Bicknell CL. HDL cholesterol and bone mineral density: is there a genetic link? Bone 2012; 50:525-33. [PMID: 21810493 PMCID: PMC3236254 DOI: 10.1016/j.bone.2011.07.002] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2011] [Revised: 06/27/2011] [Accepted: 07/04/2011] [Indexed: 12/16/2022]
Abstract
Overwhelming evidence has linked cardiovascular disease and osteoporosis, but the shared root cause of these two diseases of the elderly remains unknown. Low levels of high density lipoprotein cholesterol (HDL) and bone mineral density (BMD) are risk factors for cardiovascular disease and osteoporosis respectively. A number of correlation studies have attempted to determine if there is a relationship between serum HDL and BMD but these studies are confounded by a number of variables including age, diet, genetic background, gender and hormonal status. Collectively, these data suggest that there is a relationship between these two phenotypes, but that the nature of this relationship is context specific. Studies in mice plainly demonstrate that genetic loci for BMD and HDL co-map and transgenic mouse models have been used to show that a single gene can affect both serum HDL and BMD. Work completed to date has demonstrated that HDL can interact directly with both osteoblasts and osteoclasts, but no direct evidence links bone back to the regulation of HDL levels. Understanding the genetic relationship between BMD and HDL has huge implications for understanding the clinical relationship between CVD and osteoporosis and for the development of safe treatment options for both diseases.
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19
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Boell L, Gregorova S, Forejt J, Tautz D. A comparative assessment of mandible shape in a consomic strain panel of the house mouse (Mus musculus)--implications for epistasis and evolvability of quantitative traits. BMC Evol Biol 2011; 11:309. [PMID: 22011306 PMCID: PMC3212827 DOI: 10.1186/1471-2148-11-309] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2011] [Accepted: 10/19/2011] [Indexed: 11/16/2022] Open
Abstract
Background Expectations of repeatedly finding associations between given genes and phenotypes have been borne out by studies of parallel evolution, especially for traits involving absence or presence of characters. However, it has rarely been asked whether the genetic basis of quantitative trait variation is conserved at the intra- or even at the interspecific level. This question is especially relevant for shape, where the high dimensionality of variation seems to require a highly complex genetic architecture involving many genes. Results We analyse here the genetic effects of chromosome substitution strains carrying M. m. musculus chromosomes in a largely M. m. domesticus background on mandible shape and compare them to the results of previously published QTL mapping data between M. m. domesticus strains. We find that the distribution of genetic effects and effect sizes across the genome is consistent between the studies, while the specific shape changes associated with the chromosomes are different. We find also that the sum of the effects from the different M. m. musculus chromosomes is very different from the shape of the strain from which they were derived, as well as all known wild type shapes. Conclusions Our results suggest that the relative chromosome-wide effect sizes are comparable between the long separated subspecies M. m. domesticus and M. m. musculus, hinting at a relative stability of genes involved in this complex trait. However, the absolute effect sizes and the effect directions may be allele-dependent, or are context dependent, i.e. epistatic interactions appear to play an important role in controlling shape.
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Affiliation(s)
- Louis Boell
- Max-Planck Institut für Evolutionsbiologie, August-Thienemannstrasse 2, 24306 Plön, Germany
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20
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Berndt A, Savage HS, Stearns TM, Paigen B. Genetic analysis of lung function in inbred mice suggests vitamin D receptor as a candidate gene. Mol Genet Genomics 2011; 286:237-46. [PMID: 21850575 PMCID: PMC3175031 DOI: 10.1007/s00438-011-0642-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2011] [Accepted: 08/04/2011] [Indexed: 01/25/2023]
Abstract
Vitamin D receptor (VDR) polymorphisms are associated with an increased asthma incidence in human populations; however, observations in Vdr knockout mice are unclear. The aim of our study was to determine the influence of the genetic variation in Vdr among inbred strains on lung resistance (i.e., dynamic and airway resistance). In an intercross between the strains C57BL/6J (B6) and KK/HlJ (KK), we identified that a significant QTL for dynamic resistance on Chr X was interacting with a QTL on Chr 15. The Chr 15 QTL peak was located in close proximity to the Vdr locus. We further examined if phenotypes of several inbred strains with varying Vdr genotypes differed. Strains with a B6-like genotype on the Vdr locus had significantly lower airway resistance than strains with a KK-like genotype. Vdr knockout mice were examined for dynamic resistance and showed significantly higher resistance than mice with one (i.e., heterozygous) or both copies (i.e., wild-type) of the Vdr. In comparison to B6, the strain A/J is more resistant but carries the same genotype at the Vdr locus. Dietary vitamin D manipulation in the strain A/J did not rescue the high airway resistance phenotype. Finally, we observed that serum vitamin D does not correlate significantly with lung resistance parameters in a survey of 18 strains. Conclusively, Vdr contributes to the phenotypic variation of lung resistance in inbred mice but other molecules in the Vdr pathway and extended network [i.e., Chr X gene(s)] may contribute as well.
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21
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Langfelder P, Castellani LW, Zhou Z, Paul E, Davis R, Schadt EE, Lusis AJ, Horvath S, Mehrabian M. A systems genetic analysis of high density lipoprotein metabolism and network preservation across mouse models. Biochim Biophys Acta Mol Cell Biol Lipids 2011; 1821:435-47. [PMID: 21807117 DOI: 10.1016/j.bbalip.2011.07.014] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2011] [Revised: 07/14/2011] [Accepted: 07/15/2011] [Indexed: 01/22/2023]
Abstract
We report a systems genetic analysis of high density lipoprotein (HDL) levels in an F2 intercross between inbred strains CAST/EiJ and C57BL/6J. We previously showed that there are dramatic differences in HDL metabolism in a cross between these strains, and we now report co-expression network analysis of HDL that integrates global expression data from liver and adipose with relevant metabolic traits. Using data from a total of 293 F2 intercross mice, we constructed weighted gene co-expression networks and identified modules (subnetworks) associated with HDL and clinical traits. These were examined for genes implicated in HDL levels based on large human genome-wide associations studies (GWAS) and examined with respect to conservation between tissue and sexes in a total of 9 data sets. We identify genes that are consistently ranked high by association with HDL across the 9 data sets. We focus in particular on two genes, Wfdc2 and Hdac3, that are located in close proximity to HDL QTL peaks where causal testing indicates that they may affect HDL. Our results provide a rich resource for studies of complex metabolic interactions involving HDL. This article is part of a Special Issue entitled Advances in High Density Lipoprotein Formation and Metabolism: A Tribute to John F. Oram (1945-2010).
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Affiliation(s)
- Peter Langfelder
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Gonda (Goldschmied) Neuroscience and Genetics Research Center, 695 Charles E. Young Drive South, Box 708822, Los Angeles, CA 90095-7088, USA.
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22
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Abstract
PURPOSE OF REVIEW Comparative genomics allows researchers to combine genome-wide association data from humans with studies in animal models in order to assist in the identification of the genes and the genetic variants that modify susceptibility to dyslipidemia and atherosclerosis. RECENT FINDINGS Association and linkage studies in human and rodent species have been successful in identifying genetic loci associated with complex traits, but have been less robust in identifying and validating the responsible gene and/or genetic variants. Recent technological advancements have assisted in the development of comparative genomic approaches, which rely on the combination of human and rodent datasets and bioinformatics tools, followed by the narrowing of concordant loci and improved identification of candidate genes and genetic variants. Additionally, candidate genes and genetic variants identified by these methods have been further validated and functionally investigated in animal models, a process that is not feasible in humans. SUMMARY Comparative genomic approaches have led to the identification and validation of several new genes, including a few not previously implicated, as modifiers of plasma lipid levels and atherosclerosis, yielding new insights into the biological mechanisms of these complex traits.
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Affiliation(s)
- Stela Z Berisha
- Department of Cell Biology, Lerner Research Institute, Cleveland Clinic, Ohio, USA
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23
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Leduc MS, Lyons M, Darvishi K, Walsh K, Sheehan S, Amend S, Cox A, Orho-Melander M, Kathiresan S, Paigen B, Korstanje R. The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol. J Lipid Res 2011; 52:1139-1149. [PMID: 21444760 DOI: 10.1194/jlr.m009175] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Genome-wide association (GWA) studies represent a powerful strategy for identifying susceptibility genes for complex diseases in human populations but results must be confirmed and replicated. Because of the close homology between mouse and human genomes, the mouse can be used to add evidence to genes suggested by human studies. We used the mouse quantitative trait loci (QTL) map to interpret results from a GWA study for genes associated with plasma HDL cholesterol levels. We first positioned single nucleotide polymorphisms (SNPs) from a human GWA study on the genomic map for mouse HDL QTL. We then used mouse bioinformatics, sequencing, and expression studies to add evidence for one well-known HDL gene (Abca1) and three newly identified genes (Galnt2, Wwox, and Cdh13), thus supporting the results of the human study. For GWA peaks that occur in human haplotype blocks with multiple genes, we examined the homologous regions in the mouse to prioritize the genes using expression, sequencing, and bioinformatics from the mouse model, showing that some genes were unlikely candidates and adding evidence for candidate genes Mvk and Mmab in one haplotype block and Fads1 and Fads2 in the second haplotype block. Our study highlights the value of mouse genetics for evaluating genes found in human GWA studies.
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24
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Dow HC, Kreibich AS, Kaercher KA, Sankoorikal GMV, Pauley ED, Lohoff FW, Ferraro TN, Li H, Brodkin ES. Genetic dissection of intermale aggressive behavior in BALB/cJ and A/J mice. GENES, BRAIN, AND BEHAVIOR 2011; 10:57-68. [PMID: 20731721 PMCID: PMC3017637 DOI: 10.1111/j.1601-183x.2010.00640.x] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Aggressive behaviors are disabling, treatment refractory, and sometimes lethal symptoms of several neuropsychiatric disorders. However, currently available treatments for patients are inadequate, and the underlying genetics and neurobiology of aggression is only beginning to be elucidated. Inbred mouse strains are useful for identifying genomic regions, and ultimately the relevant gene variants (alleles) in these regions, that affect mammalian aggressive behaviors, which, in turn, may help to identify neurobiological pathways that mediate aggression. The BALB/cJ inbred mouse strain exhibits relatively high levels of intermale aggressive behaviors and shows multiple brain and behavioral phenotypes relevant to neuropsychiatric syndromes associated with aggression. The A/J strain shows very low levels of aggression. We hypothesized that a cross between BALB/cJ and A/J inbred strains would reveal genomic loci that influence the tendency to initiate intermale aggressive behavior. To identify such loci, we conducted a genomewide scan in an F2 population of 660 male mice bred from BALB/cJ and A/J inbred mouse strains. Three significant loci on chromosomes 5, 10 and 15 that influence aggression were identified. The chromosome 5 and 15 loci are completely novel, and the chromosome 10 locus overlaps an aggression locus mapped in our previous study that used NZB/B1NJ and A/J as progenitor strains. Haplotype analysis of BALB/cJ, NZB/B1NJ and A/J strains showed three positional candidate genes in the chromosome 10 locus. Future studies involving fine genetic mapping of these loci as well as additional candidate gene analysis may lead to an improved biological understanding of mammalian aggressive behaviors.
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Affiliation(s)
- Holly C. Dow
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, Translational Research Laboratory, 125 South 31 Street, Room 2220, Philadelphia, PA 19104-3403 USA
| | - Arati Sadalge Kreibich
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, Translational Research Laboratory, 125 South 31 Street, Room 2220, Philadelphia, PA 19104-3403 USA
| | - Kristin A. Kaercher
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, Translational Research Laboratory, 125 South 31 Street, Room 2220, Philadelphia, PA 19104-3403 USA
| | - Geena Mary V. Sankoorikal
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, Translational Research Laboratory, 125 South 31 Street, Room 2220, Philadelphia, PA 19104-3403 USA
| | - Eric D. Pauley
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, Translational Research Laboratory, 125 South 31 Street, Room 2220, Philadelphia, PA 19104-3403 USA
| | - Falk W. Lohoff
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, Translational Research Laboratory, 125 South 31 Street, Room 2220, Philadelphia, PA 19104-3403 USA
| | - Thomas N. Ferraro
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, Translational Research Laboratory, 125 South 31 Street, Room 2220, Philadelphia, PA 19104-3403 USA
| | - Hongzhe Li
- Statistical Genetics and Genomics Laboratory, Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, 215 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021 USA
| | - Edward S. Brodkin
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, Translational Research Laboratory, 125 South 31 Street, Room 2220, Philadelphia, PA 19104-3403 USA
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Li RH, Churchill GA. Epistasis contributes to the genetic buffering of plasma HDL cholesterol in mice. Physiol Genomics 2010; 42A:228-34. [PMID: 20858711 DOI: 10.1152/physiolgenomics.00044.2010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Stressful environmental factors, such as a high-fat diet, can induce responses in the expression of genes that act to maintain physiological homeostasis. We observed variation in plasma concentrations of high-density lipoprotein (HDL) cholesterol across inbred mouse strains in response to high dietary fat intake. Several strains, including C57BL/6J, have stable levels of plasma HDL independent of diet, whereas other strains, including DBA2/J, show marked changes in plasma HDL. To explore this phenomenon further, we used publicly available data from a C57BL/6J × DBA/2J intercross to identify genetic factors that associate with HDL under high-fat diet conditions. Our analysis identified an epistatic interaction that plays a role in the buffering of HDL levels in C57BL/6J mice, and we have identified Arl4d as a candidate gene that mediates this effect. Structural modeling further elucidates the interaction of genetic factors that contribute to the robustness of HDL in response to high-fat diet in the C57BL/6J strain.
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Affiliation(s)
- Renhua H Li
- The Jackson Laboratory, Bar Harbor, Maine, USA.
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26
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Ackert-Bicknell CL, Karasik D, Li Q, Smith RV, Hsu YH, Churchill GA, Paigen BJ, Tsaih SW. Mouse BMD quantitative trait loci show improved concordance with human genome-wide association loci when recalculated on a new, common mouse genetic map. J Bone Miner Res 2010; 25:1808-20. [PMID: 20200990 PMCID: PMC3153351 DOI: 10.1002/jbmr.72] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Bone mineral density (BMD) is a heritable trait, and in mice, over 100 quantitative trait loci (QTLs) have been reported, but candidate genes have been identified for only a small percentage. Persistent errors in the mouse genetic map have negatively affected QTL localization, spurring the development of a new, corrected map. In this study, QTLs for BMD were remapped in 11 archival mouse data sets using this new genetic map. Since these QTLs all were mapped in a comparable way, direct comparisons of QTLs for concordance would be valid. We then compared human genome-wide association study (GWAS) BMD loci with the mouse QTLs. We found that 26 of the 28 human GWAS loci examined were located within the confidence interval of a mouse QTL. Furthermore, 14 of the GWAS loci mapped to within 3 cM of a mouse QTL peak. Lastly, we demonstrated that these newly remapped mouse QTLs can substantiate a candidate gene for a human GWAS locus, for which the peak single-nucleotide polymorphism (SNP) fell in an intergenic region. Specifically, we suggest that MEF2C (human chromosome 5, mouse chromosome 13) should be considered a candidate gene for the genetic regulation of BMD. In conclusion, use of the new mouse genetic map has improved the localization of mouse BMD QTLs, and these remapped QTLs show high concordance with human GWAS loci. We believe that this is an opportune time for a renewed effort by the genetics community to identify the causal variants regulating BMD using a synergistic mouse-human approach.
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Su Z, Leduc MS, Korstanje R, Paigen B. Untangling HDL quantitative trait loci on mouse chromosome 5 and identifying Scarb1 and Acads as the underlying genes. J Lipid Res 2010; 51:2706-13. [PMID: 20562441 DOI: 10.1194/jlr.m008110] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Two high-density lipoprotein cholesterol quantitative trait loci (QTL), Hdlq1 at 125 Mb and Hdlq8 at 113 Mb, were previously identified on mouse distal chromosome 5. Our objective was to identify the underlying genes. We first used bioinformatics to narrow the Hdlq1 locus to 56 genes. The most likely candidate, Scarb1 (scavenger receptor B1), was supported by gene expression data consistent with knockout and transgenic mouse models. Then we confirmed Hdlq8 as an independent QTL by detecting it in an intercross between NZB and NZW (LOD = 12.7), two mouse strains that have identical genotypes for Scarb1. Haplotyping narrowed this QTL to 9 genes; the most likely candidate was Acads (acyl-coenzymeA dehydrogenase, short chain). Sequencing showed that Acads had an amino acid polymorphism, Gly94Asp, in a conserved region; Western blotting showed that protein levels were significantly different between parental strains. A previously known spontaneous deletion causes loss of ACADS activity in BALB/cBy mice. We showed that HDL levels were significantly elevated in BALB/cBy compared with BALB/c mice and that this HDL difference cosegregated with the Acads mutation. We confirmed that Hdlq1 and Hdlq8 are independent QTL on mouse chromosome 5 and demonstrated that Scarb1 and Acads are the underlying genes.
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Affiliation(s)
- Zhiguang Su
- Laboratory of Cardiovascular Research, West China Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu City, P.R. China
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Eisener-Dorman AF, Grabowski-Boase L, Steffy BM, Wiltshire T, Tarantino LM. Quantitative trait locus and haplotype mapping in closely related inbred strains identifies a locus for open field behavior. Mamm Genome 2010; 21:231-46. [DOI: 10.1007/s00335-010-9260-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2010] [Accepted: 04/09/2010] [Indexed: 10/19/2022]
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Stylianou IM, Svenson KL, VanOrman SK, Langle Y, Millar JS, Paigen B, Rader DJ. Novel ENU-induced point mutation in scavenger receptor class B, member 1, results in liver specific loss of SCARB1 protein. PLoS One 2009; 4:e6521. [PMID: 19654867 PMCID: PMC2715880 DOI: 10.1371/journal.pone.0006521] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2009] [Accepted: 07/05/2009] [Indexed: 01/22/2023] Open
Abstract
Cardiovascular disease (CVD) is the largest cause of premature death in human populations throughout the world. Circulating plasma lipid levels, specifically high levels of LDL or low levels of HDL, are predictive of susceptibility to CVD. The scavenger receptor class B member 1 (SCARB1) is the primary receptor for the selective uptake of HDL cholesterol by liver and steroidogenic tissues. Hepatic SCARB1 influences plasma HDL-cholesterol levels and is vital for reverse cholesterol transport. Here we describe the mapping of a novel N-ethyl-N-nitrosourea (ENU) induced point mutation in the Scarb1 gene identified in a C57BL/6J background. The mutation is located in a highly conserved amino acid in the extracellular loop and leads to the conversion of an isoleucine to an asparagine (I179N). Homozygous mutant mice express normal Scarb1 mRNA levels and are fertile. SCARB1 protein levels are markedly reduced in liver (∼90%), but not in steroidogenic tissues. This leads to ∼70% increased plasma HDL levels due to reduced HDL cholesteryl ester selective uptake. Pdzk1 knockout mice have liver-specific reduction of SCARB1 protein as does this mutant; however, in vitro analysis of the mutation indicates that the regulation of SCARB1 protein in this mutant is independent of PDZK1. This new Scarb1 model may help further our understanding of post-translational and tissue-specific regulation of SCARB1 that may aid the important clinical goal of raising functional HDL.
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Affiliation(s)
- Ioannis M Stylianou
- School of Medicine, Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
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