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Zhang G, Deighan A, Raj A, Robinson L, Donato HJ, Garland G, Leland M, Martin-McNulty B, Kolumam GA, Riegler J, Freund A, Wright KM, Churchill GA. Intermittent fasting and caloric restriction interact with genetics to shape physiological health in mice. Genetics 2022; 220:iyab157. [PMID: 34791228 PMCID: PMC8733459 DOI: 10.1093/genetics/iyab157] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 08/10/2021] [Indexed: 11/20/2022] Open
Abstract
Dietary interventions can dramatically affect physiological health and organismal lifespan. The degree to which organismal health is improved depends upon genotype and the severity of dietary intervention, but neither the effects of these factors, nor their interaction, have been quantified in an outbred population. Moreover, it is not well understood what physiological changes occur shortly after dietary change and how these may affect the health of an adult population. In this article, we investigated the effect of 6-month exposure of either caloric restriction (CR) or intermittent fasting (IF) on a broad range of physiological traits in 960 1-year old Diversity Outbred mice. We found CR and IF affected distinct aspects of physiology and neither the magnitude nor the direction (beneficial or detrimental) of effects were concordant with the severity of the intervention. In addition to the effects of diet, genetic variation significantly affected 31 of 36 traits (heritabilities ranged from 0.04 to 0.65). We observed significant covariation between many traits that was due to both diet and genetics and quantified these effects with phenotypic and genetic correlations. We genetically mapped 16 diet-independent and 2 diet-dependent significant quantitative trait loci, both of which were associated with cardiac physiology. Collectively, these results demonstrate the degree to which diet and genetics interact to shape the physiological health of adult mice following 6 months of dietary intervention.
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Affiliation(s)
- Guozhu Zhang
- Calico Life Sciences LLC, South San Francisco, CA 94080, USA
| | | | - Anil Raj
- Calico Life Sciences LLC, South San Francisco, CA 94080, USA
| | | | | | | | | | | | | | | | - Adam Freund
- Calico Life Sciences LLC, South San Francisco, CA 94080, USA
| | - Kevin M Wright
- Calico Life Sciences LLC, South San Francisco, CA 94080, USA
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Mosedale M, Cai Y, Eaddy JS, Kirby PJ, Wolenski FS, Dragan Y, Valdar W. Human-relevant mechanisms and risk factors for TAK-875-Induced liver injury identified via a gene pathway-based approach in Collaborative Cross mice. Toxicology 2021; 461:152902. [PMID: 34418498 PMCID: PMC8936092 DOI: 10.1016/j.tox.2021.152902] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/05/2021] [Accepted: 08/16/2021] [Indexed: 10/20/2022]
Abstract
Development of TAK-875 was discontinued when a small number of serious drug-induced liver injury (DILI) cases were observed in Phase 3 clinical trials. Subsequent studies have identified hepatocellular oxidative stress, mitochondrial dysfunction, altered bile acid homeostasis, and immune response as mechanisms of TAK-875 DILI and the contribution of genetic risk factors in oxidative response and mitochondrial pathways to the toxicity susceptibility observed in patients. We tested the hypothesis that a novel preclinical approach based on gene pathway analysis in the livers of Collaborative Cross mice could be used to identify human-relevant mechanisms of toxicity and genetic risk factors at the level of the hepatocyte as reported in a human genome-wide association study. Eight (8) male mice (4 matched pairs) from each of 45 Collaborative Cross lines were treated with a single oral (gavage) dose of either vehicle or 600 mg/kg TAK-875. As expected, liver injury was not detected histologically and few changes in plasma biomarkers of hepatotoxicity were observed. However, gene expression profiling in the liver identified hundreds of transcripts responsive to TAK-875 treatment across all strains reflecting alterations in immune response and bile acid homeostasis and the interaction of treatment and strain reflecting oxidative stress and mitochondrial dysfunction. Fold-change expression values were then used to develop pathway-based phenotypes for genetic mapping which identified candidate risk factor genes for TAK-875 toxicity susceptibility at the level of the hepatocyte. Taken together, these findings support our hypothesis that a gene pathway-based approach using Collaborative Cross mice could inform sensitive strains, human-relevant mechanisms of toxicity, and genetic risk factors for TAK-875 DILI. This novel preclinical approach may be helpful in understanding, predicting, and ultimately preventing clinical DILI for other drugs.
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Affiliation(s)
- Merrie Mosedale
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, Chapel Hill, NC, 27599, United States.
| | - Yanwei Cai
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States.
| | - J Scott Eaddy
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, Chapel Hill, NC, 27599, United States.
| | - Patrick J Kirby
- Takeda Pharmaceuticals International Co., Cambridge, MA, 02139, United States.
| | - Francis S Wolenski
- Takeda Pharmaceuticals International Co., Cambridge, MA, 02139, United States.
| | - Yvonne Dragan
- Takeda Pharmaceuticals International Co., Cambridge, MA, 02139, United States.
| | - William Valdar
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States.
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4
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Mosedale M, Cai Y, Eaddy JS, Corty RW, Nautiyal M, Watkins PB, Valdar W. Identification of Candidate Risk Factor Genes for Human Idelalisib Toxicity Using a Collaborative Cross Approach. Toxicol Sci 2020; 172:265-278. [PMID: 31501888 DOI: 10.1093/toxsci/kfz199] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Idelalisib is a phosphatidylinositol 3-kinase inhibitor highly selective for the delta isoform that has shown good efficacy in treating chronic lymphocytic leukemia and follicular lymphoma. In clinical trials, however, idelalisib was associated with rare, but potentially serious liver and lung toxicities. In this study, we used the Collaborative Cross (CC) mouse population to identify genetic factors associated with the drug response that may inform risk management strategies for idelalisib in humans. Eight male mice (4 matched pairs) from 50 CC lines were treated once daily for 14 days by oral gavage with either vehicle or idelalisib at a dose selected to achieve clinically relevant peak plasma concentrations (150 mg/kg/day). The drug was well tolerated across all CC lines, and there were no observations of overt liver injury. Differences across CC lines were seen in drug concentration in plasma samples collected at the approximate Tmax on study Days 1, 7, and 14. There were also small but statistically significant treatment-induced alterations in plasma total bile acids and microRNA-122, and these may indicate early hepatocellular stress required for immune-mediated hepatotoxicity in humans. Idelalisib treatment further induced significant elevations in the total cell count of terminal bronchoalveolar lavage fluid, which may be analogous to pneumonitis observed in the clinic. Genetic mapping identified loci associated with interim plasma idelalisib concentration and the other 3 treatment-related endpoints. Thirteen priority candidate quantitative trait genes identified in CC mice may now guide interrogation of risk factors for adverse drug responses associated with idelalisib in humans.
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Affiliation(s)
- Merrie Mosedale
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709.,Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, Chapel Hill, North Carolina 27599
| | - Yanwei Cai
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709.,Department of Genetics
| | - John Scott Eaddy
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709
| | | | - Manisha Nautiyal
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709
| | - Paul B Watkins
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709.,Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, Chapel Hill, North Carolina 27599
| | - William Valdar
- Department of Genetics.,Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599
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5
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Keele GR, Quach BC, Israel JW, Chappell GA, Lewis L, Safi A, Simon JM, Cotney P, Crawford GE, Valdar W, Rusyn I, Furey TS. Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation. PLoS Genet 2020; 16:e1008537. [PMID: 31961859 PMCID: PMC7010298 DOI: 10.1371/journal.pgen.1008537] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 02/10/2020] [Accepted: 11/23/2019] [Indexed: 01/08/2023] Open
Abstract
Gene transcription profiles across tissues are largely defined by the activity of regulatory elements, most of which correspond to regions of accessible chromatin. Regulatory element activity is in turn modulated by genetic variation, resulting in variable transcription rates across individuals. The interplay of these factors, however, is poorly understood. Here we characterize expression and chromatin state dynamics across three tissues-liver, lung, and kidney-in 47 strains of the Collaborative Cross (CC) mouse population, examining the regulation of these dynamics by expression quantitative trait loci (eQTL) and chromatin QTL (cQTL). QTL whose allelic effects were consistent across tissues were detected for 1,101 genes and 133 chromatin regions. Also detected were eQTL and cQTL whose allelic effects differed across tissues, including local-eQTL for Pik3c2g detected in all three tissues but with distinct allelic effects. Leveraging overlapping measurements of gene expression and chromatin accessibility on the same mice from multiple tissues, we used mediation analysis to identify chromatin and gene expression intermediates of eQTL effects. Based on QTL and mediation analyses over multiple tissues, we propose a causal model for the distal genetic regulation of Akr1e1, a gene involved in glycogen metabolism, through the zinc finger transcription factor Zfp985 and chromatin intermediates. This analysis demonstrates the complexity of transcriptional and chromatin dynamics and their regulation over multiple tissues, as well as the value of the CC and related genetic resource populations for identifying specific regulatory mechanisms within cells and tissues.
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Affiliation(s)
- Gregory R. Keele
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Bryan C. Quach
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Center for Omics Discovery and Epidemiology, Research Triangle Institute (RTI) International, Research Triangle Park, North Carolina, United States of America
| | - Jennifer W. Israel
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Grace A. Chappell
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, United States of America
| | - Lauren Lewis
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, United States of America
| | - Alexias Safi
- Department of Pediatrics, Duke University, Durham, North Carolina, United States of America
- Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America
| | - Jeremy M. Simon
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Paul Cotney
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Gregory E. Crawford
- Department of Pediatrics, Duke University, Durham, North Carolina, United States of America
- Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America
| | - William Valdar
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ivan Rusyn
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, United States of America
| | - Terrence S. Furey
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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6
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Shorter JR, Najarian ML, Bell TA, Blanchard M, Ferris MT, Hock P, Kashfeen A, Kirchoff KE, Linnertz CL, Sigmon JS, Miller DR, McMillan L, Pardo-Manuel de Villena F. Whole Genome Sequencing and Progress Toward Full Inbreeding of the Mouse Collaborative Cross Population. G3 (BETHESDA, MD.) 2019; 9:1303-1311. [PMID: 30858237 PMCID: PMC6505143 DOI: 10.1534/g3.119.400039] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 03/08/2019] [Indexed: 12/20/2022]
Abstract
Two key features of recombinant inbred panels are well-characterized genomes and reproducibility. Here we report on the sequenced genomes of six additional Collaborative Cross (CC) strains and on inbreeding progress of 72 CC strains. We have previously reported on the sequences of 69 CC strains that were publicly available, bringing the total of CC strains with whole genome sequence up to 75. The sequencing of these six CC strains updates the efforts toward inbreeding undertaken by the UNC Systems Genetics Core. The timing reflects our competing mandates to release to the public as many CC strains as possible while achieving an acceptable level of inbreeding. The new six strains have a higher than average founder contribution from non-domesticus strains than the previously released CC strains. Five of the six strains also have high residual heterozygosity (>14%), which may be related to non-domesticus founder contributions. Finally, we report on updated estimates on residual heterozygosity across the entire CC population using a novel, simple and cost effective genotyping platform on three mice from each strain. We observe a reduction in residual heterozygosity across all previously released CC strains. We discuss the optimal use of different genetic resources available for the CC population.
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Affiliation(s)
| | | | - Timothy A Bell
- Department of Genetics
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
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A Diallel of the Mouse Collaborative Cross Founders Reveals Strong Strain-Specific Maternal Effects on Litter Size. G3-GENES GENOMES GENETICS 2019; 9:1613-1622. [PMID: 30877080 PMCID: PMC6505174 DOI: 10.1534/g3.118.200847] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Reproductive success in the eight founder strains of the Collaborative Cross (CC) was measured using a diallel-mating scheme. Over a 48-month period we generated 4,448 litters, and provided 24,782 weaned pups for use in 16 different published experiments. We identified factors that affect the average litter size in a cross by estimating the overall contribution of parent-of-origin, heterosis, inbred, and epistatic effects using a Bayesian zero-truncated overdispersed Poisson mixed model. The phenotypic variance of litter size has a substantial contribution (82%) from unexplained and environmental sources, but no detectable effect of seasonality. Most of the explained variance was due to additive effects (9.2%) and parental sex (maternal vs. paternal strain; 5.8%), with epistasis accounting for 3.4%. Within the parental effects, the effect of the dam's strain explained more than the sire's strain (13.2% vs. 1.8%), and the dam's strain effects account for 74.2% of total variation explained. Dams from strains C57BL/6J and NOD/ShiLtJ increased the expected litter size by a mean of 1.66 and 1.79 pups, whereas dams from strains WSB/EiJ, PWK/PhJ, and CAST/EiJ reduced expected litter size by a mean of 1.51, 0.81, and 0.90 pups. Finally, there was no strong evidence for strain-specific effects on sex ratio distortion. Overall, these results demonstrate that strains vary substantially in their reproductive ability depending on their genetic background, and that litter size is largely determined by dam's strain rather than sire's strain effects, as expected. This analysis adds to our understanding of factors that influence litter size in mammals, and also helps to explain breeding successes and failures in the extinct lines and surviving CC strains.
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R/qtl2: Software for Mapping Quantitative Trait Loci with High-Dimensional Data and Multiparent Populations. Genetics 2018; 211:495-502. [PMID: 30591514 PMCID: PMC6366910 DOI: 10.1534/genetics.118.301595] [Citation(s) in RCA: 235] [Impact Index Per Article: 39.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 12/21/2018] [Indexed: 12/22/2022] Open
Abstract
R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely-used R/qtl software package to include multiparental populations, better handles modern high-dimensional data.... R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely used R/qtl software package to include multiparent populations derived from more than two founder strains, such as the Collaborative Cross and Diversity Outbred mice, heterogeneous stocks, and MAGIC plant populations. R/qtl2 is designed to handle modern high-density genotyping data and high-dimensional molecular phenotypes, including gene expression and proteomics. R/qtl2 includes the ability to perform genome scans using a linear mixed model to account for population structure, and also includes features to impute SNPs based on founder strain genomes and to carry out association mapping. The R/qtl2 software provides all of the basic features needed for QTL mapping, including graphical displays and summary reports, and it can be extended through the creation of add-on packages. R/qtl2, which is free and open source software written in the R and C++ programming languages, comes with a test framework.
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Reciprocal F1 Hybrids of Two Inbred Mouse Strains Reveal Parent-of-Origin and Perinatal Diet Effects on Behavior and Expression. G3-GENES GENOMES GENETICS 2018; 8:3447-3468. [PMID: 30171036 PMCID: PMC6222572 DOI: 10.1534/g3.118.200135] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Parent-of-origin effects (POE) in mammals typically arise from maternal effects or imprinting. In some instances, such POE have been associated with psychiatric disorders, as well as with changes in a handful of animal behaviors. However, POE on complex traits such as behavior remain largely uncharacterized. Moreover, although both behavior and epigenetic effects are known to be modified by perinatal environmental exposures such as nutrient deficiency, the architecture of such environment-by-POE is mostly unexplored. To study POE and environment-by-POE, we employ a relatively neglected but especially powerful experimental system for POE-detection: reciprocal F1 hybrids (RF1s). We exposed female NOD/ShiLtJ×C57Bl/6J and C57Bl/6J×NOD/ShiLtJ mice, perinatally, to one of four different diets, then after weaning recorded a set of behaviors that model psychiatric disease. Whole-brain microarray expression data revealed an imprinting-enriched set of 15 genes subject to POE. The most-significant expression POE, on the non-imprinted gene Carmil1 (a.k.a. Lrrc16a), was validated using qPCR in the same and in a new set of mice. Several behaviors, especially locomotor behaviors, also showed POE. Bayesian mediation analysis suggested Carmil1 expression suppresses behavioral POE, and that the imprinted gene Airn suppresses POE on Carmil1 expression. A suggestive diet-by-POE was observed on percent center time in the open field test, and a significant diet-by-POE was observed on one imprinted gene, Mir341, and on 16 non-imprinted genes. The relatively small, tractable set of POE and diet-by-POE detected on behavior and expression here motivates further studies examining such effects across RF1s on multiple genetic backgrounds.
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Leist SR, Baric RS. Giving the Genes a Shuffle: Using Natural Variation to Understand Host Genetic Contributions to Viral Infections. Trends Genet 2018; 34:777-789. [PMID: 30131185 PMCID: PMC7114642 DOI: 10.1016/j.tig.2018.07.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 07/15/2018] [Accepted: 07/19/2018] [Indexed: 01/01/2023]
Abstract
The laboratory mouse has proved an invaluable model to identify host factors that regulate the progression and outcome of virus-induced disease. The paradigm is to use single-gene knockouts in inbred mouse strains or genetic mapping studies using biparental mouse populations. However, genetic variation among these mouse strains is limited compared with the diversity seen in human populations. To address this disconnect, a multiparental mouse population has been developed to specifically dissect the multigenetic regulation of complex disease traits. The Collaborative Cross (CC) population of recombinant inbred mouse strains is a well-suited systems-genetics tool to identify susceptibility alleles that control viral and microbial infection outcomes and immune responses and to test the promise of personalized medicine.
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Affiliation(s)
- Sarah R Leist
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Ralph S Baric
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; https://sph.unc.edu/adv_profile/ralph-s-baric-phd/
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11
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Back to the Future: Multiparent Populations Provide the Key to Unlocking the Genetic Basis of Complex Traits. Genetics 2018; 206:527-529. [PMID: 28592493 PMCID: PMC5494722 DOI: 10.1534/genetics.117.203265] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
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Arends D, Hesse D, Brockmann GA. Invited review: Genetic and genomic mouse models for livestock research. Arch Anim Breed 2018. [DOI: 10.5194/aab-61-87-2018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Abstract. Knowledge about the function and functioning of single or
multiple interacting genes is of the utmost significance for understanding the
organism as a whole and for accurate livestock improvement through genomic
selection. This includes, but is not limited to, understanding the
ontogenetic and environmentally driven regulation of gene action
contributing to simple and complex traits. Genetically modified mice, in
which
the functions of single genes are annotated; mice with reduced genetic
complexity; and simplified structured populations are tools to gain
fundamental knowledge of inheritance patterns and whole system genetics and
genomics. In this review, we briefly describe existing mouse resources and
discuss their value for fundamental and applied research in livestock.
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Bayesian Diallel Analysis Reveals Mx1-Dependent and Mx1-Independent Effects on Response to Influenza A Virus in Mice. G3-GENES GENOMES GENETICS 2018; 8:427-445. [PMID: 29187420 PMCID: PMC5919740 DOI: 10.1534/g3.117.300438] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Influenza A virus (IAV) is a respiratory pathogen that causes substantial morbidity and mortality during both seasonal and pandemic outbreaks. Infection outcomes in unexposed populations are affected by host genetics, but the host genetic architecture is not well understood. Here, we obtain a broad view of how heritable factors affect a mouse model of response to IAV infection using an 8 × 8 diallel of the eight inbred founder strains of the Collaborative Cross (CC). Expanding on a prior statistical framework for modeling treatment response in diallels, we explore how a range of heritable effects modify acute host response to IAV through 4 d postinfection. Heritable effects in aggregate explained ∼57% of the variance in IAV-induced weight loss. Much of this was attributable to a pattern of additive effects that became more prominent through day 4 postinfection and was consistent with previous reports of antiinfluenza myxovirus resistance 1 (Mx1) polymorphisms segregating between these strains; these additive effects largely recapitulated haplotype effects observed at the Mx1 locus in a previous study of the incipient CC, and are also replicated here in a CC recombinant intercross population. Genetic dominance of protective Mx1 haplotypes was observed to differ by subspecies of origin: relative to the domesticus null Mx1 allele, musculus acts dominantly whereas castaneus acts additively. After controlling for Mx1, heritable effects, though less distinct, accounted for ∼34% of the phenotypic variance. Implications for future mapping studies are discussed.
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Chiu WA, Rusyn I. Advancing chemical risk assessment decision-making with population variability data: challenges and opportunities. Mamm Genome 2018; 29:182-189. [PMID: 29299621 PMCID: PMC5849521 DOI: 10.1007/s00335-017-9731-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Accepted: 12/27/2017] [Indexed: 02/06/2023]
Abstract
Characterizing population variability, including identifying susceptible populations and quantifying their increased susceptibility, is an important aspect of chemical risk assessment, but one that is challenging with traditional experimental models and risk assessment methods. New models and methods to address population variability can be used to advance the human health assessments of chemicals in three key areas. First, with respect to hazard identification, evaluating toxicity using population-based in vitro and in vivo models can potentially reduce both false positive and false negative signals. Second, with respect to evaluating mechanisms of toxicity, enhanced ability to do genetic mapping using these models allows for the identification of key biological pathways and mechanisms that may be involved in toxicity and/or susceptibility. Third, with respect to dose-response assessment, population-based toxicity data can serve as a surrogate for human variability, and thus be used to quantitatively estimate the degree of human toxicokinetic/toxicodynamic variability and thereby increase confidence in setting health-protective exposure limits. A number of case studies have been published that demonstrate the potential opportunities for improving risk assessment and decision-making, and include studies using Collaborative Cross and Diversity Outbred mice, as well as populations of human cell lines from the 1000 Genomes project. Key challenges include the need to apply more sophisticated computational and statistical models analyzing population-based toxicity data, and the need to integrate these more complex analyses into risk assessments and decision-making.
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Affiliation(s)
- Weihsueh A Chiu
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA.
| | - Ivan Rusyn
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA
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15
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Male Infertility Is Responsible for Nearly Half of the Extinction Observed in the Mouse Collaborative Cross. Genetics 2017; 206:557-572. [PMID: 28592496 DOI: 10.1534/genetics.116.199596] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Accepted: 03/09/2017] [Indexed: 11/18/2022] Open
Abstract
The goal of the Collaborative Cross (CC) project was to generate and distribute over 1000 independent mouse recombinant inbred strains derived from eight inbred founders. With inbreeding nearly complete, we estimated the extinction rate among CC lines at a remarkable 95%, which is substantially higher than in the derivation of other mouse recombinant inbred populations. Here, we report genome-wide allele frequencies in 347 extinct CC lines. Contrary to expectations, autosomes had equal allelic contributions from the eight founders, but chromosome X had significantly lower allelic contributions from the two inbred founders with underrepresented subspecific origins (PWK/PhJ and CAST/EiJ). By comparing extinct CC lines to living CC strains, we conclude that a complex genetic architecture is driving extinction, and selection pressures are different on the autosomes and chromosome X Male infertility played a large role in extinction as 47% of extinct lines had males that were infertile. Males from extinct lines had high variability in reproductive organ size, low sperm counts, low sperm motility, and a high rate of vacuolization of seminiferous tubules. We performed QTL mapping and identified nine genomic regions associated with male fertility and reproductive phenotypes. Many of the allelic effects in the QTL were driven by the two founders with underrepresented subspecific origins, including a QTL on chromosome X for infertility that was driven by the PWK/PhJ haplotype. We also performed the first example of cross validation using complementary CC resources to verify the effect of sperm curvilinear velocity from the PWK/PhJ haplotype on chromosome 2 in an independent population across multiple generations. While selection typically constrains the examination of reproductive traits toward the more fertile alleles, the CC extinct lines provided a unique opportunity to study the genetic architecture of fertility in a widely genetically variable population. We hypothesize that incompatibilities between alleles with different subspecific origins is a key driver of infertility. These results help clarify the factors that drove strain extinction in the CC, reveal the genetic regions associated with poor fertility in the CC, and serve as a resource to further study mammalian infertility.
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Abstract
The Collaborative Cross (CC) is a multiparent panel of recombinant inbred (RI) mouse strains derived from eight founder laboratory strains. RI panels are popular because of their long-term genetic stability, which enhances reproducibility and integration of data collected across time and conditions. Characterization of their genomes can be a community effort, reducing the burden on individual users. Here we present the genomes of the CC strains using two complementary approaches as a resource to improve power and interpretation of genetic experiments. Our study also provides a cautionary tale regarding the limitations imposed by such basic biological processes as mutation and selection. A distinct advantage of inbred panels is that genotyping only needs to be performed on the panel, not on each individual mouse. The initial CC genome data were haplotype reconstructions based on dense genotyping of the most recent common ancestors (MRCAs) of each strain followed by imputation from the genome sequence of the corresponding founder inbred strain. The MRCA resource captured segregating regions in strains that were not fully inbred, but it had limited resolution in the transition regions between founder haplotypes, and there was uncertainty about founder assignment in regions of limited diversity. Here we report the whole genome sequence of 69 CC strains generated by paired-end short reads at 30× coverage of a single male per strain. Sequencing leads to a substantial improvement in the fine structure and completeness of the genomes of the CC. Both MRCAs and sequenced samples show a significant reduction in the genome-wide haplotype frequencies from two wild-derived strains, CAST/EiJ and PWK/PhJ. In addition, analysis of the evolution of the patterns of heterozygosity indicates that selection against three wild-derived founder strains played a significant role in shaping the genomes of the CC. The sequencing resource provides the first description of tens of thousands of new genetic variants introduced by mutation and drift in the CC genomes. We estimate that new SNP mutations are accumulating in each CC strain at a rate of 2.4 ± 0.4 per gigabase per generation. The fixation of new mutations by genetic drift has introduced thousands of new variants into the CC strains. The majority of these mutations are novel compared to currently sequenced laboratory stocks and wild mice, and some are predicted to alter gene function. Approximately one-third of the CC inbred strains have acquired large deletions (>10 kb) many of which overlap known coding genes and functional elements. The sequence of these mice is a critical resource to CC users, increases threefold the number of mouse inbred strain genomes available publicly, and provides insight into the effect of mutation and drift on common resources.
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Oas1b-dependent Immune Transcriptional Profiles of West Nile Virus Infection in the Collaborative Cross. G3-GENES GENOMES GENETICS 2017; 7:1665-1682. [PMID: 28592649 PMCID: PMC5473748 DOI: 10.1534/g3.117.041624] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The oligoadenylate-synthetase (Oas) gene locus provides innate immune resistance to virus infection. In mouse models, variation in the Oas1b gene influences host susceptibility to flavivirus infection. However, the impact of Oas variation on overall innate immune programming and global gene expression among tissues and in different genetic backgrounds has not been defined. We examined how Oas1b acts in spleen and brain tissue to limit West Nile virus (WNV) susceptibility and disease across a range of genetic backgrounds. The laboratory founder strains of the mouse Collaborative Cross (CC) (A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, and NZO/HlLtJ) all encode a truncated, defective Oas1b, whereas the three wild-derived inbred founder strains (CAST/EiJ, PWK/PhJ, and WSB/EiJ) encode a full-length OAS1B protein. We assessed disease profiles and transcriptional signatures of F1 hybrids derived from these founder strains. F1 hybrids included wild-type Oas1b (F/F), homozygous null Oas1b (N/N), and heterozygous offspring of both parental combinations (F/N and N/F). These mice were challenged with WNV, and brain and spleen samples were harvested for global gene expression analysis. We found that the Oas1b haplotype played a role in WNV susceptibility and disease metrics, but the presence of a functional Oas1b allele in heterozygous offspring did not absolutely predict protection against disease. Our results indicate that Oas1b status as wild-type or truncated, and overall Oas1b gene dosage, link with novel innate immune gene signatures that impact specific biological pathways for the control of flavivirus infection and immunity through both Oas1b-dependent and independent processes.
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Back to the Future: Multiparent Populations Provide the Key to Unlocking the Genetic Basis of Complex Traits. G3-GENES GENOMES GENETICS 2017; 7:1617-1618. [PMID: 28592643 PMCID: PMC5473742 DOI: 10.1534/g3.117.042846] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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Allelic Variation in the Toll-Like Receptor Adaptor Protein Ticam2 Contributes to SARS-Coronavirus Pathogenesis in Mice. G3-GENES GENOMES GENETICS 2017; 7:1653-1663. [PMID: 28592648 PMCID: PMC5473747 DOI: 10.1534/g3.117.041434] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Host genetic variation is known to contribute to differential pathogenesis following infection. Mouse models allow direct assessment of host genetic factors responsible for susceptibility to Severe Acute Respiratory Syndrome coronavirus (SARS-CoV). Based on an assessment of early stage lines from the Collaborative Cross mouse multi-parent population, we identified two lines showing highly divergent susceptibilities to SARS-CoV: the resistant CC003/Unc and the susceptible CC053/Unc. We generated 264 F2 mice between these strains, and infected them with SARS-CoV. Weight loss, pulmonary hemorrhage, and viral load were all highly correlated disease phenotypes. We identified a quantitative trait locus of major effect on chromosome 18 (27.1–58.6 Mb) which affected weight loss, viral titer and hemorrhage. Additionally, each of these three phenotypes had distinct quantitative trait loci [Chr 9 (weight loss), Chrs 7 and 12 (virus titer), and Chr 15 (hemorrhage)]. We identified Ticam2, an adaptor protein in the TLR signaling pathways, as a candidate driving differential disease at the Chr 18 locus. Ticam2−/− mice were highly susceptible to SARS-CoV infection, exhibiting increased weight loss and more pulmonary hemorrhage than control mice. These results indicate a critical role for Ticam2 in SARS-CoV disease, and highlight the importance of host genetic variation in disease responses.
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