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King CP, Chitre AS, Leal-Gutiérrez JD, Tripi JA, Hughson AR, Horvath AP, Lamparelli AC, George A, Martin C, Pierre CLS, Sanches T, Bimschleger HV, Gao J, Cheng R, Nguyen KM, Holl KL, Polesskaya O, Ishiwari K, Chen H, Woods LCS, Palmer AA, Robinson TE, Flagel SB, Meyer PJ. Genomic Loci Influencing Cue-Reactivity in Heterogeneous Stock Rats. bioRxiv 2024:2024.03.13.584852. [PMID: 38559127 PMCID: PMC10980002 DOI: 10.1101/2024.03.13.584852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Addiction vulnerability is associated with the tendency to attribute incentive salience to reward predictive cues; both addiction and the attribution of incentive salience are influenced by environmental and genetic factors. To characterize the genetic contributions to incentive salience attribution, we performed a genome-wide association study (GWAS) in a cohort of 1,645 genetically diverse heterogeneous stock (HS) rats. We tested HS rats in a Pavlovian conditioned approach task, in which we characterized the individual responses to food-associated stimuli ("cues"). Rats exhibited either cue-directed "sign-tracking" behavior or food-cup directed "goal-tracking" behavior. We then used the conditioned reinforcement procedure to determine whether rats would perform a novel operant response for unrewarded presentations of the cue. We found that these measures were moderately heritable (SNP heritability, h2 = .189-.215). GWAS identified 14 quantitative trait loci (QTLs) for 11 of the 12 traits we examined. Interval sizes of these QTLs varied widely. 7 traits shared a QTL on chromosome 1 that contained a few genes (e.g. Tenm4, Mir708) that have been associated with substance use disorders and other mental health traits in humans. Other candidate genes (e.g. Wnt11, Pak1) in this region had coding variants and expression-QTLs in mesocorticolimbic regions of the brain. We also conducted a Phenome-Wide Association Study (PheWAS) on other behavioral measures in HS rats and found that regions containing QTLs on chromosome 1 were also associated with nicotine self-administration in a separate cohort of HS rats. These results provide a starting point for the molecular genetic dissection of incentive salience and provide further support for a relationship between attribution of incentive salience and drug abuse-related traits.
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Affiliation(s)
- Christopher P. King
- Department of Psychology, University at Buffalo, Buffalo, USA
- Clinical and Research Institute on Addictions, Buffalo, USA
| | - Apurva S. Chitre
- Department of Psychiatry, University of California San Diego, La Jolla, USA
| | | | - Jordan A. Tripi
- Department of Psychology, University at Buffalo, Buffalo, USA
| | - Alesa R. Hughson
- Department of Psychology, University of Michigan, Ann Arbor, USA
| | - Aidan P. Horvath
- Department of Psychology, University of Michigan, Ann Arbor, USA
| | | | - Anthony George
- Clinical and Research Institute on Addictions, Buffalo, USA
| | - Connor Martin
- Clinical and Research Institute on Addictions, Buffalo, USA
| | | | - Thiago Sanches
- Department of Psychiatry, University of California San Diego, La Jolla, USA
| | | | - Jianjun Gao
- Department of Psychiatry, University of California San Diego, La Jolla, USA
| | - Riyan Cheng
- Department of Psychiatry, University of California San Diego, La Jolla, USA
| | - Khai-Minh Nguyen
- Department of Psychiatry, University of California San Diego, La Jolla, USA
| | - Katie L. Holl
- Department of Physiology, Medical College of Wisconsin, Milwaukee, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, USA
| | - Keita Ishiwari
- Clinical and Research Institute on Addictions, Buffalo, USA
- Department of Pharmacology and Toxicology, University at Buffalo, Buffalo USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, USA
| | - Leah C. Solberg Woods
- Department of Internal Medicine, Molecular Medicine, Center on Diabetes, Obesity and Metabolism, Wake Forest School of Medicine, Winston-Salem, USA
| | - Abraham A. Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, USA
| | | | - Shelly B. Flagel
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, USA
| | - Paul J. Meyer
- Department of Psychology, University at Buffalo, Buffalo, USA
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Radyk MD, Spatz LB, Adkins-Threats ML, Cates K, St Pierre CL. Evaluation of an 8-week high school science communication course designed to read, write, and present scientific research. Adv Physiol Educ 2023; 47:910-918. [PMID: 37769043 PMCID: PMC10854798 DOI: 10.1152/advan.00085.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/06/2023] [Accepted: 09/25/2023] [Indexed: 09/30/2023]
Abstract
The development of science writing and presentation skills is necessary for a successful science career. Too often these skills are not included in pre- or postsecondary science, technology, engineering, and mathematics (STEM) education, leading to a disconnect between high schoolers' expectations for college preparedness and the skills needed to succeed in college. The Young Scientist Program Summer Focus recruits high school students from historically marginalized backgrounds to participate in 8-week summer internships at Washington University in St. Louis. Students conduct hands-on biomedical research projects under the mentorship of Washington University scientists (graduate students, postdoctorates, lab staff). Here, we present the curriculum for a science communication course that accompanies this early research experience. The course is designed to strengthen students' communication skills (critical reading, writing, presenting, and peer review) through a combination of weekly lectures and active learning methods. It prepares students for the capstone of their summer internship: writing a scientific paper and presenting their results at a closing symposium. We administered pre- and postprogram surveys to four Summer Focus cohorts to determine whether the course met its learning objectives. We found significant improvements in students' self-confidence in reading, interpreting, and communicating scientific data. Thus, this course provides a successful model for introducing science literacy and communication skills that are necessary for any career in STEM. We provide a detailed outline of the course structure and content so that this training can be incorporated into any undergraduate and graduate research programs.NEW & NOTEWORTHY Strong communication skills are necessary for a successful scientific career. Here, we describe the curriculum for a science communication course designed to accompany high school students participating in a summer biomedical research program. The course aims to improve their scientific literacy and communication skills. Students learn to read and understand scientific literature, write a paper about their summer research project, present their results, and provide feedback to peers. We found significant improvements in students' self-confidence in reading, interpreting, and communicating scientific data after completing the course. This successful model serves as a guide for students participating in their first research experience and provides the skills for success in future science, technology, engineering, and mathematics education and careers. The curriculum presented here can be easily adapted for any research program, including undergraduate summer research experiences and graduate student laboratory rotations.
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Affiliation(s)
- Megan D Radyk
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan, United States
| | - Lillian B Spatz
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, Missouri, United States
| | - Mahliyah L Adkins-Threats
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, Missouri, United States
| | - Kitra Cates
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, Missouri, United States
| | - Celine L St Pierre
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States
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Wright SN, Leger BS, Rosenthal SB, Liu SN, Jia T, Chitre AS, Polesskaya O, Holl K, Gao J, Cheng R, Garcia Martinez A, George A, Gileta AF, Han W, Netzley AH, King CP, Lamparelli A, Martin C, St Pierre CL, Wang T, Bimschleger H, Richards J, Ishiwari K, Chen H, Flagel SB, Meyer P, Robinson TE, Solberg Woods LC, Kreisberg JF, Ideker T, Palmer AA. Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks. Cell Rep 2023; 42:112873. [PMID: 37527041 PMCID: PMC10546330 DOI: 10.1016/j.celrep.2023.112873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 07/05/2023] [Accepted: 07/11/2023] [Indexed: 08/03/2023] Open
Abstract
A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.
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Affiliation(s)
- Sarah N Wright
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA 92093, USA
| | - Brittany S Leger
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Program in Biomedical Sciences, University of California San Diego, La Jolla, CA 93093, USA
| | - Sara Brin Rosenthal
- Center for Computational Biology & Bioinformatics, Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sophie N Liu
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Tongqiu Jia
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Apurva S Chitre
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Katie Holl
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jianjun Gao
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Riyan Cheng
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Angel Garcia Martinez
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Anthony George
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA
| | - Alexander F Gileta
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Wenyan Han
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Alesa H Netzley
- Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA
| | - Christopher P King
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | | | - Connor Martin
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | | | - Tengfei Wang
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Hannah Bimschleger
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA
| | - Jerry Richards
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA
| | - Keita Ishiwari
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, NY 14203, USA; Department of Pharmacology and Toxicology, University at Buffalo, Buffalo, NY 14203, USA
| | - Hao Chen
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Shelly B Flagel
- Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Paul Meyer
- Department of Psychology, University at Buffalo, Buffalo, NY 14260, USA
| | - Terry E Robinson
- Department of Psychology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Leah C Solberg Woods
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Jason F Kreisberg
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Trey Ideker
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA.
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA 93093, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA.
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Freda PJ, Ghosh A, Zhang E, Luo T, Chitre AS, Polesskaya O, St Pierre CL, Gao J, Martin CD, Chen H, Garcia-Martinez AG, Wang T, Han W, Ishiwari K, Meyer P, Lamparelli A, King CP, Palmer AA, Li R, Moore JH. Automated quantitative trait locus analysis (AutoQTL). BioData Min 2023; 16:14. [PMID: 37038201 PMCID: PMC10088184 DOI: 10.1186/s13040-023-00331-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/31/2023] [Indexed: 04/12/2023] Open
Abstract
BACKGROUND Quantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complicated decisions related to analysis of complex traits and generate solutions to describe relationships that exist in genetic data. RESULTS Using a publicly available dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus, AutoQTL captures the phenotypic variance explained under a standard additive model. AutoQTL also detects evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions in simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL. CONCLUSIONS This proof-of-concept illustrates that automated machine learning techniques can complement standard approaches and have the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection and feature engineering strategies.
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Affiliation(s)
- Philip J Freda
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, 700 N. San Vicente Blvd., Pacific Design Center, Suite G540, West Hollywood, CA, 90069, USA
| | - Attri Ghosh
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, 700 N. San Vicente Blvd., Pacific Design Center, Suite G540, West Hollywood, CA, 90069, USA
| | - Elizabeth Zhang
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, 700 N. San Vicente Blvd., Pacific Design Center, Suite G540, West Hollywood, CA, 90069, USA
| | - Tianhao Luo
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, 700 N. San Vicente Blvd., Pacific Design Center, Suite G540, West Hollywood, CA, 90069, USA
| | - Apurva S Chitre
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., Mail Code: 0667, La Jolla, CA, 92093-0667, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., Mail Code: 0667, La Jolla, CA, 92093-0667, USA
| | - Celine L St Pierre
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., Mail Code: 0667, La Jolla, CA, 92093-0667, USA
| | - Jianjun Gao
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., Mail Code: 0667, La Jolla, CA, 92093-0667, USA
| | - Connor D Martin
- Department of Pharmacology & Toxicology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, 955 Main Street, Suite 3102, Buffalo, NY, 14203, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Translational Research Building, 71 South Manassas, Memphis, TN, 38163, USA
| | - Angel G Garcia-Martinez
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Translational Research Building, 71 South Manassas, Memphis, TN, 38163, USA
| | - Tengfei Wang
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Translational Research Building, 71 South Manassas, Memphis, TN, 38163, USA
| | - Wenyan Han
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Translational Research Building, 71 South Manassas, Memphis, TN, 38163, USA
| | - Keita Ishiwari
- Department of Pharmacology & Toxicology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, 955 Main Street, Suite 3102, Buffalo, NY, 14203, USA
- Clinical and Research Institute on Addictions, University at Buffalo, 1021 Main Street, Buffalo, NY, 14203-1016, USA
| | - Paul Meyer
- Department of Psychology, University at Buffalo, 204 Park Hall, North Campus, Buffalo, NY, 14260-4110, USA
| | - Alexander Lamparelli
- Department of Psychology, University at Buffalo, 204 Park Hall, North Campus, Buffalo, NY, 14260-4110, USA
| | - Christopher P King
- Department of Psychology, University at Buffalo, 204 Park Hall, North Campus, Buffalo, NY, 14260-4110, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., Mail Code: 0667, La Jolla, CA, 92093-0667, USA
- Institute for Genomic Medicine, University of California San Diego, 9500 Gilman Dr., Mail Code: 0667, La Jolla, CA, 92093-0667, USA
| | - Ruowang Li
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, 700 N. San Vicente Blvd., Pacific Design Center, Suite G540, West Hollywood, CA, 90069, USA
| | - Jason H Moore
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, 700 N. San Vicente Blvd., Pacific Design Center, Suite G540, West Hollywood, CA, 90069, USA.
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Fowler S, Wang T, Munro D, Kumar A, Chitre AS, Hollingsworth TJ, Garcia Martinez A, St. Pierre CL, Bimschleger H, Gao J, Cheng R, Mohammadi P, Chen H, Palmer AA, Polesskaya O, Jablonski MM. Genome-wide association study finds multiple loci associated with intraocular pressure in HS rats. Front Genet 2023; 13:1029058. [PMID: 36793389 PMCID: PMC9922724 DOI: 10.3389/fgene.2022.1029058] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 12/28/2022] [Indexed: 02/03/2023] Open
Abstract
Elevated intraocular pressure (IOP) is influenced by environmental and genetic factors. Increased IOP is a major risk factor for most types of glaucoma, including primary open angle glaucoma (POAG). Investigating the genetic basis of IOP may lead to a better understanding of the molecular mechanisms of POAG. The goal of this study was to identify genetic loci involved in regulating IOP using outbred heterogeneous stock (HS) rats. HS rats are a multigenerational outbred population derived from eight inbred strains that have been fully sequenced. This population is ideal for a genome-wide association study (GWAS) owing to the accumulated recombinations among well-defined haplotypes, the relatively high allele frequencies, the accessibility to a large collection of tissue samples, and the large allelic effect size compared to human studies. Both male and female HS rats (N = 1,812) were used in the study. Genotyping-by-sequencing was used to obtain ∼3.5 million single nucleotide polymorphisms (SNP) from each individual. SNP heritability for IOP in HS rats was 0.32, which agrees with other studies. We performed a GWAS for the IOP phenotype using a linear mixed model and used permutation to determine a genome-wide significance threshold. We identified three genome-wide significant loci for IOP on chromosomes 1, 5, and 16. Next, we sequenced the mRNA of 51 whole eye samples to find cis-eQTLs to aid in identification of candidate genes. We report 5 candidate genes within those loci: Tyr, Ctsc, Plekhf2, Ndufaf6 and Angpt2. Tyr, Ndufaf6 and Angpt2 genes have been previously implicated by human GWAS of IOP-related conditions. Ctsc and Plekhf2 genes represent novel findings that may provide new insight into the molecular basis of IOP. This study highlights the efficacy of HS rats for investigating the genetics of elevated IOP and identifying potential candidate genes for future functional testing.
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Affiliation(s)
- Samuel Fowler
- Hamilton Eye Institute Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee, United states
| | - Tengfei Wang
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, Tennessee, United states
| | - Daniel Munro
- Department of Psychiatry, University of California, San Diego, San Diego, California, United states,Department of Integrative Structural and Computational Biology, Scripps Research, San Diego, California, United states
| | - Aman Kumar
- Hamilton Eye Institute Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee, United states
| | - Apurva S. Chitre
- Department of Psychiatry, University of California, San Diego, San Diego, California, United states
| | - T. J. Hollingsworth
- Hamilton Eye Institute Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee, United states
| | - Angel Garcia Martinez
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, Tennessee, United states
| | - Celine L. St. Pierre
- Department of Psychiatry, University of California, San Diego, San Diego, California, United states
| | - Hannah Bimschleger
- Department of Psychiatry, University of California, San Diego, San Diego, California, United states
| | - Jianjun Gao
- Department of Psychiatry, University of California, San Diego, San Diego, California, United states
| | - Riyan Cheng
- Department of Psychiatry, University of California, San Diego, San Diego, California, United states
| | - Pejman Mohammadi
- Department of Integrative Structural and Computational Biology, Scripps Research, San Diego, California, United states,Scripps Research Translational Institute, Scripps Research, San Diego, California, United states
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, Tennessee, United states
| | - Abraham A. Palmer
- Department of Psychiatry, University of California, San Diego, San Diego, California, United states,Institute for Genomic Medicine, University of California, San Diego, San Diego, California, United states
| | - Oksana Polesskaya
- Department of Psychiatry, University of California, San Diego, San Diego, California, United states
| | - Monica M. Jablonski
- Hamilton Eye Institute Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee, United states,*Correspondence: Monica M. Jablonski,
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St Pierre CL, Macias-Velasco JF, Wayhart JP, Yin L, Semenkovich CF, Lawson HA. Genetic, epigenetic, and environmental mechanisms govern allele-specific gene expression. Genome Res 2022; 32:1042-1057. [PMID: 35501130 PMCID: PMC9248887 DOI: 10.1101/gr.276193.121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 04/14/2022] [Indexed: 12/03/2022]
Abstract
Allele-specific expression (ASE) is a phenomenon in which one allele is preferentially expressed over the other. Genetic and epigenetic factors cause ASE by altering the final composition of a gene's product, leading to expression imbalances that can have functional consequences on phenotypes. Environmental signals also impact allele-specific expression, but how they contribute to this cross talk remains understudied. Here, we explored how genotype, parent-of-origin, tissue, sex, and dietary fat simultaneously influence ASE biases. Male and female mice from a F1 reciprocal cross of the LG/J and SM/J strains were fed a high or low fat diet. We harnessed strain-specific variants to distinguish between two ASE classes: parent-of-origin-dependent (unequal expression based on parental origin) and sequence-dependent (unequal expression based on nucleotide identity). We present a comprehensive map of ASE patterns in 2853 genes across three tissues and nine environmental contexts. We found that both ASE classes are highly dependent on tissue and environmental context. They vary across metabolically relevant tissues, between males and females, and in response to dietary fat. We also found 45 genes with inconsistent ASE biases that switched direction across tissues and/or environments. Finally, we integrated ASE and QTL data from published intercrosses of the LG/J and SM/J strains. Our ASE genes are often enriched in QTLs for metabolic and musculoskeletal traits, highlighting how this orthogonal approach can prioritize candidate genes. Together, our results provide novel insights into how genetic, epigenetic, and environmental mechanisms govern allele-specific expression, which is an essential step toward deciphering the genotype-to-phenotype map.
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Affiliation(s)
| | | | | | - Li Yin
- Washington University in Saint Louis
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7
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Macias-Velasco JF, St Pierre CL, Wayhart JP, Yin L, Spears L, Miranda MA, Carson C, Funai K, Cheverud JM, Semenkovich CF, Lawson HA. Parent-of-origin effects propagate through networks to shape metabolic traits. eLife 2022; 11:e72989. [PMID: 35356864 PMCID: PMC9075957 DOI: 10.7554/elife.72989] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 03/25/2022] [Indexed: 11/16/2022] Open
Abstract
Parent-of-origin effects are unexpectedly common in complex traits, including metabolic and neurological traits. Parent-of-origin effects can be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific parent-of-origin effects on metabolic traits were mapped in the F16 generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these parent-of-origin effects phenomena. We propose that non-imprinted genes can generate complex parent-of-origin effects on metabolic traits through interactions with imprinted genes. Here, we employ data from mouse populations at different levels of intercrossing (F0, F1, F2, F16) of the LG/J and SM/J inbred mouse lines to test this hypothesis. Using multiple populations and incorporating genetic, genomic, and physiological data, we leverage orthogonal evidence to identify networks of genes through which parent-of-origin effects propagate. We identify a network comprised of three imprinted and six non-imprinted genes that show parent-of-origin effects. This epistatic network forms a nutritional responsive pathway and the genes comprising it jointly serve cellular functions associated with growth. We focus on two genes, Nnat and F2r, whose interaction associates with serum glucose levels across generations in high-fat-fed females. Single-cell RNAseq reveals that Nnat expression increases and F2r expression decreases in pre-adipocytes along an adipogenic trajectory, a result that is consistent with our observations in bulk white adipose tissue.
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Affiliation(s)
- Juan F Macias-Velasco
- Department of Genetics, Washington University School of MedicineSaint LouisUnited States
| | - Celine L St Pierre
- Department of Genetics, Washington University School of MedicineSaint LouisUnited States
| | - Jessica P Wayhart
- Department of Genetics, Washington University School of MedicineSaint LouisUnited States
| | - Li Yin
- Department of Medicine, Washington University School of MedicineSaint LouisUnited States
| | - Larry Spears
- Department of Medicine, Washington University School of MedicineSaint LouisUnited States
| | - Mario A Miranda
- Department of Genetics, Washington University School of MedicineSaint LouisUnited States
| | - Caryn Carson
- Department of Genetics, Washington University School of MedicineSaint LouisUnited States
| | - Katsuhiko Funai
- Diabetes and Metabolism Research Center, University of UtahSalt Lake CityUnited States
| | | | - Clay F Semenkovich
- Department of Medicine, Washington University School of MedicineSaint LouisUnited States
| | - Heather A Lawson
- Department of Genetics, Washington University School of MedicineSaint LouisUnited States
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8
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Mortazavi M, Ren Y, Saini S, Antaki D, St. Pierre CL, Williams A, Sohni A, Wilkinson MF, Gymrek M, Sebat J, Palmer AA. SNPs, short tandem repeats, and structural variants are responsible for differential gene expression across C57BL/6 and C57BL/10 substrains. Cell Genom 2022; 2:100102. [PMID: 35720252 PMCID: PMC9205302 DOI: 10.1016/j.xgen.2022.100102] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 11/22/2021] [Accepted: 02/02/2022] [Indexed: 12/13/2022]
Abstract
Mouse substrains are an invaluable model for understanding disease. We compared C57BL/6J, which is the most commonly used inbred mouse strain, with eight C57BL/6 and five C57BL/10 closely related inbred substrains. Whole-genome sequencing and RNA-sequencing analysis yielded 352,631 SNPs, 109,096 indels, 150,344 short tandem repeats (STRs), 3,425 structural variants (SVs), and 2,826 differentially expressed genes (DE genes) among these 14 strains; 312,981 SNPs (89%) distinguished the B6 and B10 lineages. These SNPs were clustered into 28 short segments that are likely due to introgressed haplotypes rather than new mutations. Outside of these introgressed regions, we identified 53 SVs, protein-truncating SNPs, and frameshifting indels that were associated with DE genes. Our results can be used for both forward and reverse genetic approaches and illustrate how introgression and mutational processes give rise to differences among these widely used inbred substrains.
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Affiliation(s)
- Milad Mortazavi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Yangsu Ren
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Shubham Saini
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Danny Antaki
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Celine L. St. Pierre
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - April Williams
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Abhishek Sohni
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
| | - Miles F. Wilkinson
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Melissa Gymrek
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Jonathan Sebat
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine and Pediatrics, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Abraham A. Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
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9
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Sigmon JS, Blanchard MW, Baric RS, Bell TA, Brennan J, Brockmann GA, Burks AW, Calabrese JM, Caron KM, Cheney RE, Ciavatta D, Conlon F, Darr DB, Faber J, Franklin C, Gershon TR, Gralinski L, Gu B, Gaines CH, Hagan RS, Heimsath EG, Heise MT, Hock P, Ideraabdullah F, Jennette JC, Kafri T, Kashfeen A, Kulis M, Kumar V, Linnertz C, Livraghi-Butrico A, Lloyd KCK, Lutz C, Lynch RM, Magnuson T, Matsushima GK, McMullan R, Miller DR, Mohlke KL, Moy SS, Murphy CEY, Najarian M, O'Brien L, Palmer AA, Philpot BD, Randell SH, Reinholdt L, Ren Y, Rockwood S, Rogala AR, Saraswatula A, Sassetti CM, Schisler JC, Schoenrock SA, Shaw GD, Shorter JR, Smith CM, St Pierre CL, Tarantino LM, Threadgill DW, Valdar W, Vilen BJ, Wardwell K, Whitmire JK, Williams L, Zylka MJ, Ferris MT, McMillan L, Manuel de Villena FP. Content and Performance of the MiniMUGA Genotyping Array: A New Tool To Improve Rigor and Reproducibility in Mouse Research. Genetics 2020; 216:905-930. [PMID: 33067325 PMCID: PMC7768238 DOI: 10.1534/genetics.120.303596] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 10/06/2020] [Indexed: 12/14/2022] Open
Abstract
The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.
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Affiliation(s)
- John Sebastian Sigmon
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Matthew W Blanchard
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Mutant Mouse Resource and Research Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Ralph S Baric
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Jennifer Brennan
- Mutant Mouse Resource and Research Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - A Wesley Burks
- Department of Pediatrics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - J Mauro Calabrese
- Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Kathleen M Caron
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Richard E Cheney
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Dominic Ciavatta
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Frank Conlon
- Department of Biology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - David B Darr
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - James Faber
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Craig Franklin
- Department of Veterinary Pathobiology, University of Missouri, Columbia, Missouri 65211
| | - Timothy R Gershon
- Department of Neurology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Lisa Gralinski
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Bin Gu
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Christiann H Gaines
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Robert S Hagan
- Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Ernest G Heimsath
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Mark T Heise
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Folami Ideraabdullah
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
- Department of Nutrition, Gillings School of Public Health, University of North Carolina, Chapel Hill, North Carolina 27599
| | - J Charles Jennette
- Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Tal Kafri
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, North Carolina 27599
- Gene Therapy Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Anwica Kashfeen
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Mike Kulis
- Department of Pediatrics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Vivek Kumar
- The Jackson Laboratory, Bar Harbor, Maine 04609
| | - Colton Linnertz
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Alessandra Livraghi-Butrico
- Marsico Lung Institute/UNC Cystic Fibrosis Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - K C Kent Lloyd
- Department of Surgery, University of California Davis, Davis, California 95616
- School of Medicine, University of California Davis, California 95616
- Mouse Biology Program, University of California Davis, California 95616
| | | | - Rachel M Lynch
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Terry Magnuson
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Mutant Mouse Resource and Research Center, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Glenn K Matsushima
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, North Carolina 27599
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Rachel McMullan
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Darla R Miller
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Sheryl S Moy
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina 27599
- Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Caroline E Y Murphy
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Maya Najarian
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Lori O'Brien
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - Benjamin D Philpot
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
- Marsico Lung Institute/UNC Cystic Fibrosis Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Scott H Randell
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - Yuyu Ren
- University of California San Diego, La Jolla, California 92093
| | | | - Allison R Rogala
- Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
- Division of Comparative Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Avani Saraswatula
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Christopher M Sassetti
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts 01655
| | - Jonathan C Schisler
- Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Sarah A Schoenrock
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - John R Shorter
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Clare M Smith
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts 01655
| | | | - Lisa M Tarantino
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina 27599
| | - David W Threadgill
- University of California San Diego, La Jolla, California 92093
- Department of Biochemistry and Biophysics, Texas A&M University, Texas 77843
| | - William Valdar
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Barbara J Vilen
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - Jason K Whitmire
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Lucy Williams
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Mark J Zylka
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Martin T Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Fernando Pardo Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Mutant Mouse Resource and Research Center, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
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10
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Carson C, Macias-Velasco JF, Gunawardana S, Miranda MA, Oyama S, St Pierre CL, Schmidt H, Wayhart JP, Lawson HA. Brown Adipose Expansion and Remission of Glycemic Dysfunction in Obese SM/J Mice. Cell Rep 2020; 33:108237. [PMID: 33027654 PMCID: PMC7594587 DOI: 10.1016/j.celrep.2020.108237] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 08/09/2020] [Accepted: 09/15/2020] [Indexed: 12/27/2022] Open
Abstract
We leverage the SM/J mouse to understand glycemic control in obesity. High-fat-fed SM/J mice initially develop poor glucose homeostasis relative to controls. Strikingly, their glycemic dysfunction resolves by 30 weeks of age despite persistent obesity. The mice dramatically expand their brown adipose depots as they resolve glycemic dysfunction. This occurs naturally and spontaneously on a high-fat diet, with no temperature or genetic manipulation. Removal of the brown adipose depot impairs insulin sensitivity, indicating that the expanded tissue is functioning as an insulin-stimulated glucose sink. We describe morphological, physiological, and transcriptomic changes that occur during the brown adipose expansion and remission of glycemic dysfunction, and focus on Sfrp1 (secreted frizzled-related protein 1) as a compelling candidate that may underlie this phenomenon. Understanding how the expanded brown adipose contributes to glycemic control in SM/J mice will open the door for innovative therapies aimed at improving metabolic complications in obesity.
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Affiliation(s)
- Caryn Carson
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA
| | - Juan F Macias-Velasco
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA
| | - Subhadra Gunawardana
- Department of Cell Biology and Physiology, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA
| | - Mario A Miranda
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA
| | - Sakura Oyama
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA
| | - Celine L St Pierre
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA
| | - Heather Schmidt
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA
| | - Jessica P Wayhart
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA
| | - Heather A Lawson
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave., Saint Louis, MO 63108, USA.
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11
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Miranda MA, Carson C, St. Pierre CL, Macias‐Velasco JF, Hughes JW, Kunzmann M, Schmidt H, Wayhart JP, Lawson HA. Spontaneous restoration of functional β-cell mass in obese SM/J mice. Physiol Rep 2020; 8:e14573. [PMID: 33113267 PMCID: PMC7592878 DOI: 10.14814/phy2.14573] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 08/08/2020] [Indexed: 12/23/2022] Open
Abstract
Maintenance of functional β-cell mass is critical to preventing diabetes, but the physiological mechanisms that cause β-cell populations to thrive or fail in the context of obesity are unknown. High fat-fed SM/J mice spontaneously transition from hyperglycemic-obese to normoglycemic-obese with age, providing a unique opportunity to study β-cell adaptation. Here, we characterize insulin homeostasis, islet morphology, and β-cell function during SM/J's diabetic remission. As they resolve hyperglycemia, obese SM/J mice dramatically increase circulating and pancreatic insulin levels while improving insulin sensitivity. Immunostaining of pancreatic sections reveals that obese SM/J mice selectively increase β-cell mass but not α-cell mass. Obese SM/J mice do not show elevated β-cell mitotic index, but rather elevated α-cell mitotic index. Functional assessment of isolated islets reveals that obese SM/J mice increase glucose-stimulated insulin secretion, decrease basal insulin secretion, and increase islet insulin content. These results establish that β-cell mass expansion and improved β-cell function underlie the resolution of hyperglycemia, indicating that obese SM/J mice are a valuable tool for exploring how functional β-cell mass can be recovered in the context of obesity.
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Affiliation(s)
- Mario A. Miranda
- Department of GeneticsWashington University School of MedicineSaint LouisMOUSA
| | - Caryn Carson
- Department of GeneticsWashington University School of MedicineSaint LouisMOUSA
| | | | | | - Jing W. Hughes
- Department of MedicineWashington University School of MedicineSaint LouisMOUSA
| | - Marcus Kunzmann
- Department of GeneticsWashington University School of MedicineSaint LouisMOUSA
| | - Heather Schmidt
- Department of GeneticsWashington University School of MedicineSaint LouisMOUSA
| | - Jessica P. Wayhart
- Department of GeneticsWashington University School of MedicineSaint LouisMOUSA
| | - Heather A. Lawson
- Department of GeneticsWashington University School of MedicineSaint LouisMOUSA
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12
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Chitre AS, Polesskaya O, Holl K, Gao J, Cheng R, Bimschleger H, Garcia Martinez A, George T, Gileta AF, Han W, Horvath A, Hughson A, Ishiwari K, King CP, Lamparelli A, Versaggi CL, Martin C, St Pierre CL, Tripi JA, Wang T, Chen H, Flagel SB, Meyer P, Richards J, Robinson TE, Palmer AA, Solberg Woods LC. Genome-Wide Association Study in 3,173 Outbred Rats Identifies Multiple Loci for Body Weight, Adiposity, and Fasting Glucose. Obesity (Silver Spring) 2020; 28:1964-1973. [PMID: 32860487 PMCID: PMC7511439 DOI: 10.1002/oby.22927] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 05/03/2020] [Accepted: 05/04/2020] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Obesity is influenced by genetic and environmental factors. Despite the success of human genome-wide association studies, the specific genes that confer obesity remain largely unknown. The objective of this study was to use outbred rats to identify the genetic loci underlying obesity and related morphometric and metabolic traits. METHODS This study measured obesity-relevant traits, including body weight, body length, BMI, fasting glucose, and retroperitoneal, epididymal, and parametrial fat pad weight in 3,173 male and female adult N/NIH heterogeneous stock (HS) rats across three institutions, providing data for the largest rat genome-wide association study to date. Genetic loci were identified using a linear mixed model to account for the complex family relationships of the HS and using covariates to account for differences among the three phenotyping centers. RESULTS This study identified 32 independent loci, several of which contained only a single gene (e.g., Epha5, Nrg1, Klhl14) or obvious candidate genes (e.g., Adcy3, Prlhr). There were strong phenotypic and genetic correlations among obesity-related traits, and there was extensive pleiotropy at individual loci. CONCLUSIONS This study demonstrates the utility of HS rats for investigating the genetics of obesity-related traits across institutions and identify several candidate genes for future functional testing.
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Affiliation(s)
- Apurva S Chitre
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - Katie Holl
- Human and Molecular Genetic Center, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Jianjun Gao
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - Riyan Cheng
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - Hannah Bimschleger
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - Angel Garcia Martinez
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Tony George
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, New York, USA
| | - Alexander F Gileta
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
- Department of Human Genetics, University of Chicago, Chicago, Illinois, USA
| | - Wenyan Han
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Aidan Horvath
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Alesa Hughson
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Keita Ishiwari
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, New York, USA
| | | | | | | | - Connor Martin
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, New York, USA
| | | | - Jordan A Tripi
- Department of Psychology, University at Buffalo, Buffalo, New York, USA
| | - Tengfei Wang
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Hao Chen
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Shelly B Flagel
- Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Paul Meyer
- Department of Psychology, University at Buffalo, Buffalo, New York, USA
| | - Jerry Richards
- Clinical and Research Institute on Addictions, University at Buffalo, Buffalo, New York, USA
| | - Terry E Robinson
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Leah C Solberg Woods
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
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13
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Gileta AF, Gao J, Chitre AS, Bimschleger HV, St Pierre CL, Gopalakrishnan S, Palmer AA. Adapting Genotyping-by-Sequencing and Variant Calling for Heterogeneous Stock Rats. G3 (Bethesda) 2020; 10:2195-2205. [PMID: 32398234 PMCID: PMC7341140 DOI: 10.1534/g3.120.401325] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 05/01/2020] [Indexed: 02/06/2023]
Abstract
The heterogeneous stock (HS) is an outbred rat population derived from eight inbred rat strains. HS rats are ideally suited for genome wide association studies; however, only a few genotyping microarrays have ever been designed for rats and none of them are currently in production. To address the need for an efficient and cost effective method of genotyping HS rats, we have adapted genotype-by-sequencing (GBS) to obtain genotype information at large numbers of single nucleotide polymorphisms (SNPs). In this paper, we have outlined the laboratory and computational steps we took to optimize double digest genotype-by-sequencing (ddGBS) for use in rats. We evaluated multiple existing computational tools and explain the workflow we have used to call and impute over 3.7 million SNPs. We have also compared various rat genetic maps, which are necessary for imputation, including a recently developed map specific to the HS. Using our approach, we obtained concordance rates of 99% with data obtained using data from a genotyping array. The principles and computational pipeline that we describe could easily be adapted for use in other species for which reliable reference genome sets are available.
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Affiliation(s)
- Alexander F Gileta
- Department of Psychiatry
- Institute for Genomic Medicine, University of California San Diego, La Jolla, California, 92093
| | | | | | | | | | - Shyam Gopalakrishnan
- Department of Human Genetics, University of Chicago, Chicago, Illinois, 60637, and
| | - Abraham A Palmer
- Department of Psychiatry,
- Natural History Museum of Denmark, University of Copenhagen, 2200 København N, Denmark
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14
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Zhou X, St Pierre CL, Gonzales NM, Zou J, Cheng R, Chitre AS, Sokoloff G, Palmer AA. Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity. G3 (Bethesda) 2020; 10:951-965. [PMID: 31974095 PMCID: PMC7056977 DOI: 10.1534/g3.119.400763] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 10/17/2019] [Indexed: 12/12/2022]
Abstract
There has been extensive discussion of the "Replication Crisis" in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner's Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.
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Affiliation(s)
- Xinzhu Zhou
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, 92092
| | - Celine L St Pierre
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63110
| | | | - Jennifer Zou
- Department of Computer Science, University of California, Los Angeles, CA, 90095
| | | | | | - Greta Sokoloff
- Department of Psychological & Brain Sciences, University of Iowa, Iowa City, IO, 52242
| | - Abraham A Palmer
- Department of Psychiatry,
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, 92037 and
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15
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Johnson EC, St Pierre CL, Meyers JL, Aliev F, McCutcheon VV, Lai D, Dick DM, Goate AM, Kramer J, Kuperman S, Nurnberger JI, Schuckit MA, Porjesz B, Edenberg HJ, Bucholz KK, Agrawal A. The Genetic Relationship Between Alcohol Consumption and Aspects of Problem Drinking in an Ascertained Sample. Alcohol Clin Exp Res 2019; 43:1113-1125. [PMID: 30994927 PMCID: PMC6560626 DOI: 10.1111/acer.14064] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 04/04/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Genomewide association studies (GWAS) have begun to identify loci related to alcohol consumption, but little is known about whether this genetic propensity overlaps with specific indices of problem drinking in ascertained samples. METHODS In 6,731 European Americans who had been exposed to alcohol, we examined whether polygenic risk scores (PRS) from a GWAS of weekly alcohol consumption in the UK Biobank predicted variance in 6 alcohol-related phenotypes: alcohol use, maximum drinks within 24 hours (MAXD), total score on the Self-Rating of the Effects of Ethanol Questionnaire (SRE-T), DSM-IV alcohol dependence (DSM4AD), DSM-5 alcohol use disorder symptom counts (DSM5AUDSX), and reduction/cessation of problematic drinking. We also examined the extent to which an single nucleotide polymorphism (rs1229984) in ADH1B, which is strongly associated with both alcohol consumption and dependence, contributed to the polygenic association with these phenotypes and whether PRS interacted with sex, age, or family history of alcoholism to predict alcohol-related outcomes. We performed mixed-effect regression analyses, with family membership and recruitment site included as random effects, as well as survival modeling of age of onset of DSM4AD. RESULTS PRS for alcohol consumption significantly predicted variance in 5 of the 6 outcomes: alcohol use (Δmarginal R2 = 1.39%, Δ area under the curve [AUC] = 0.011), DSM4AD (Δmarginal R2 = 0.56%; ΔAUC = 0.003), DSM5AUDSX (Δmarginal R2 = 0.49%), MAXD (Δmarginal R2 = 0.31%), and SRE-T (Δmarginal R2 = 0.22%). PRS were also associated with onset of DSM4AD (hazard ratio = 1.11, p = 2.08e-5). The inclusion of rs1229984 attenuated the effects of the alcohol consumption PRS, particularly for DSM4AD and DSM5AUDSX, but the PRS continued to exert an independent effect for all 5 alcohol measures (Δmarginal R2 after controlling for ADH1B = 0.14 to 1.22%). Interactions between PRS and sex, age, or family history were nonsignificant. CONCLUSIONS Genetic propensity for typical alcohol consumption was associated with alcohol use and was also associated with 4 of the additional 5 outcomes, though the variance explained in this sample was modest. Future GWAS that focus on the multifaceted nature of AUD, which goes beyond consumption, might reveal additional information regarding the polygenic underpinnings of problem drinking.
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Affiliation(s)
- Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Celine L St Pierre
- Division of Biological and Biomedical Sciences, Washington University School of Medicine, Saint Louis, Missouri
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, New York
| | - Fazil Aliev
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
- Department of Actuarial and Risk Management, Faculty of Business, Karabuk University, Karabük, Turkey
| | - Vivia V McCutcheon
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Danielle M Dick
- Department of Psychology and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Alison M Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York
| | - John Kramer
- Department of Psychiatry, Roy J and Lucille A Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Samuel Kuperman
- Department of Psychiatry, Roy J and Lucille A Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - John I Nurnberger
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana
| | - Marc A Schuckit
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, New York
| | - Howard J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Kathleen K Bucholz
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
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16
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Gonzales NM, Seo J, Hernandez Cordero AI, St Pierre CL, Gregory JS, Distler MG, Abney M, Canzar S, Lionikas A, Palmer AA. Genome wide association analysis in a mouse advanced intercross line. Nat Commun 2018; 9:5162. [PMID: 30514929 PMCID: PMC6279738 DOI: 10.1038/s41467-018-07642-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 11/15/2018] [Indexed: 12/14/2022] Open
Abstract
The LG/J x SM/J advanced intercross line of mice (LG x SM AIL) is a multigenerational outbred population. High minor allele frequencies, a simple genetic background, and the fully sequenced LG and SM genomes make it a powerful population for genome-wide association studies. Here we use 1,063 AIL mice to identify 126 significant associations for 50 traits relevant to human health and disease. We also identify thousands of cis- and trans-eQTLs in the hippocampus, striatum, and prefrontal cortex of ~200 mice. We replicate an association between locomotor activity and Csmd1, which we identified in an earlier generation of this AIL, and show that Csmd1 mutant mice recapitulate the locomotor phenotype. Our results demonstrate the utility of the LG x SM AIL as a mapping population, identify numerous novel associations, and shed light on the genetic architecture of mammalian behavior.
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Affiliation(s)
- Natalia M Gonzales
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Jungkyun Seo
- Center for Genomic & Computational Biology, Duke University, Durham, NC, 27708, USA
- Graduate Program in Computational Biology and Bioinformatics, Duke University, Durham, NC, 27708, USA
| | - Ana I Hernandez Cordero
- School of Medicine, Medical Sciences and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, AB25 2ZD, UK
| | - Celine L St Pierre
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Jennifer S Gregory
- School of Medicine, Medical Sciences and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, AB25 2ZD, UK
| | - Margaret G Distler
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Mark Abney
- Department of Human Genetics, University of Chicago, Chicago, IL, 60637, USA
| | - Stefan Canzar
- Gene Center, Ludwig-Maximilians-Universität München, 81377, Munich, Germany
| | - Arimantas Lionikas
- School of Medicine, Medical Sciences and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, AB25 2ZD, UK
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
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