1
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Morgan AP, Hughes JJ, Didion JP, Jolley WJ, Campbell KJ, Threadgill DW, Bonhomme F, Searle JB, de Villena FPM. Population structure and inbreeding in wild house mice (Mus musculus) at different geographic scales. Heredity (Edinb) 2022; 129:183-194. [PMID: 35764696 PMCID: PMC9411160 DOI: 10.1038/s41437-022-00551-z] [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] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 11/08/2022] Open
Abstract
House mice (Mus musculus) have spread globally as a result of their commensal relationship with humans. In the form of laboratory strains, both inbred and outbred, they are also among the most widely used model organisms in biomedical research. Although the general outlines of house mouse dispersal and population structure are well known, details have been obscured by either limited sample size or small numbers of markers. Here we examine ancestry, population structure, and inbreeding using SNP microarray genotypes in a cohort of 814 wild mice spanning five continents and all major subspecies of Mus, with a focus on M. m. domesticus. We find that the major axis of genetic variation in M. m. domesticus is a south-to-north gradient within Europe and the Mediterranean. The dominant ancestry component in North America, Australia, New Zealand, and various small offshore islands are of northern European origin. Next we show that inbreeding is surprisingly pervasive and highly variable, even between nearby populations. By inspecting the length distribution of homozygous segments in individual genomes, we find that inbreeding in commensal populations is mostly due to consanguinity. Our results offer new insight into the natural history of an important model organism for medicine and evolutionary biology.
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Affiliation(s)
- Andrew P Morgan
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA.
- Department of Medicine, Duke University Hospital, Durham, NC, USA.
| | - Jonathan J Hughes
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
| | - John P Didion
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
- Independent Scientist, San Diego, CA, USA
| | | | | | - David W Threadgill
- Institute for Genome Sciences and Society, Texas A&M University, College Station, TX, USA
| | - Francois Bonhomme
- Institut des Sciences de l'Évolution Montpellier, Université de Montpellier, Montpellier, France
| | - Jeremy B Searle
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
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2
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Currin KW, Erdos MR, Narisu N, Rai V, Vadlamudi S, Perrin HJ, Idol JR, Yan T, Albanus RD, Broadaway KA, Etheridge AS, Bonnycastle LL, Orchard P, Didion JP, Chaudhry AS, Innocenti F, Schuetz EG, Scott LJ, Parker SCJ, Collins FS, Mohlke KL. Genetic effects on liver chromatin accessibility identify disease regulatory variants. Am J Hum Genet 2021; 108:1169-1189. [PMID: 34038741 PMCID: PMC8323023 DOI: 10.1016/j.ajhg.2021.05.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [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: 10/26/2020] [Accepted: 05/04/2021] [Indexed: 02/02/2023] Open
Abstract
Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTLs) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTLs have been identified in a limited set of human tissues. Here we mapped caQTLs in human liver tissue in 20 liver samples and identified 3,123 caQTLs. The caQTL variants are enriched in liver tissue promoter and enhancer states and frequently disrupt binding motifs of transcription factors expressed in liver. We predicted target genes for 861 caQTL peaks using proximity, chromatin interactions, correlation with promoter accessibility or gene expression, and colocalization with expression QTLs. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTLs and GWAS signals, 56 of which contained a predicted caPeak target gene. At the LITAF LDL-cholesterol GWAS locus, we validated that a caQTL variant showed allelic differences in protein binding and transcriptional activity. These caQTLs contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.
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Affiliation(s)
- Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Michael R Erdos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Vivek Rai
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Hannah J Perrin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jacqueline R Idol
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Tingfen Yan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Amy S Etheridge
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Lori L Bonnycastle
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Peter Orchard
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - John P Didion
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Amarjit S Chaudhry
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Federico Innocenti
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Erin G Schuetz
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Stephen C J Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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3
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Rai V, Quang DX, Erdos MR, Cusanovich DA, Daza RM, Narisu N, Zou LS, Didion JP, Guan Y, Shendure J, Parker SCJ, Collins FS. Single-cell ATAC-Seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures. Mol Metab 2020; 32:109-121. [PMID: 32029221 PMCID: PMC6961712 DOI: 10.1016/j.molmet.2019.12.006] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 12/12/2019] [Accepted: 12/12/2019] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVE Type 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome-wide association studies (GWAS) have identified > 400 independent signals that encode genetic predisposition. More than 90% of associated single-nucleotide polymorphisms (SNPs) localize to non-coding regions and are enriched in chromatin-defined islet enhancer elements, indicating a strong transcriptional regulatory component to disease susceptibility. Pancreatic islets are a mixture of cell types that express distinct hormonal programs, so each cell type may contribute differentially to the underlying regulatory processes that modulate T2D-associated transcriptional circuits. Existing chromatin profiling methods such as ATAC-seq and DNase-seq, applied to islets in bulk, produce aggregate profiles that mask important cellular and regulatory heterogeneity. METHODS We present genome-wide single-cell chromatin accessibility profiles in >1,600 cells derived from a human pancreatic islet sample using single-cell combinatorial indexing ATAC-seq (sci-ATAC-seq). We also developed a deep learning model based on U-Net architecture to accurately predict open chromatin peak calls in rare cell populations. RESULTS We show that sci-ATAC-seq profiles allow us to deconvolve alpha, beta, and delta cell populations and identify cell-type-specific regulatory signatures underlying T2D. Particularly, T2D GWAS SNPs are significantly enriched in beta cell-specific and across cell-type shared islet open chromatin, but not in alpha or delta cell-specific open chromatin. We also demonstrate, using less abundant delta cells, that deep learning models can improve signal recovery and feature reconstruction of rarer cell populations. Finally, we use co-accessibility measures to nominate the cell-specific target genes at 104 non-coding T2D GWAS signals. CONCLUSIONS Collectively, we identify the islet cell type of action across genetic signals of T2D predisposition and provide higher-resolution mechanistic insights into genetically encoded risk pathways.
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Affiliation(s)
- Vivek Rai
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Daniel X Quang
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Michael R Erdos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Darren A Cusanovich
- Department of Genome Sciences, University of Washington, Seattle, WA, 98109, USA
| | - Riza M Daza
- Department of Genome Sciences, University of Washington, Seattle, WA, 98109, USA
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Luli S Zou
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - John P Didion
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Yuanfang Guan
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, 98109, USA
| | - Stephen C J Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA.
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
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4
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Zou LS, Erdos MR, Taylor DL, Chines PS, Varshney A, Parker SCJ, Collins FS, Didion JP. BoostMe accurately predicts DNA methylation values in whole-genome bisulfite sequencing of multiple human tissues. BMC Genomics 2018; 19:390. [PMID: 29792182 PMCID: PMC5966887 DOI: 10.1186/s12864-018-4766-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Accepted: 05/08/2018] [Indexed: 01/14/2023] Open
Abstract
Background Bisulfite sequencing is widely employed to study the role of DNA methylation in disease; however, the data suffer from biases due to coverage depth variability. Imputation of methylation values at low-coverage sites may mitigate these biases while also identifying important genomic features associated with predictive power. Results Here we describe BoostMe, a method for imputing low-quality DNA methylation estimates within whole-genome bisulfite sequencing (WGBS) data. BoostMe uses a gradient boosting algorithm, XGBoost, and leverages information from multiple samples for prediction. We find that BoostMe outperforms existing algorithms in speed and accuracy when applied to WGBS of human tissues. Furthermore, we show that imputation improves concordance between WGBS and the MethylationEPIC array at low WGBS depth, suggesting improved WGBS accuracy after imputation. Conclusions Our findings support the use of BoostMe as a preprocessing step for WGBS analysis. Electronic supplementary material The online version of this article (10.1186/s12864-018-4766-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Luli S Zou
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Michael R Erdos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - D Leland Taylor
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.,European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Peter S Chines
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Arushi Varshney
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
| | | | - Stephen C J Parker
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - John P Didion
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
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5
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Abstract
A key step in the transformation of raw sequencing reads into biological insights is the trimming of adapter sequences and low-quality bases. Read trimming has been shown to increase the quality and reliability while decreasing the computational requirements of downstream analyses. Many read trimming software tools are available; however, no tool simultaneously provides the accuracy, computational efficiency, and feature set required to handle the types and volumes of data generated in modern sequencing-based experiments. Here we introduce Atropos and show that it trims reads with high sensitivity and specificity while maintaining leading-edge speed. Compared to other state-of-the-art read trimming tools, Atropos achieves significant increases in trimming accuracy while remaining competitive in execution times. Furthermore, Atropos maintains high accuracy even when trimming data with elevated rates of sequencing errors. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of Illumina, ABI SOLiD, and other current-generation short-read sequencing datasets. Atropos is open source and free software written in Python (3.3+) and available at https://github.com/jdidion/atropos.
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Affiliation(s)
- John P Didion
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Marcel Martin
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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6
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Morgan AP, Holt JM, McMullan RC, Bell TA, Clayshulte AMF, Didion JP, Yadgary L, Thybert D, Odom DT, Flicek P, McMillan L, de Villena FPM. The Evolutionary Fates of a Large Segmental Duplication in Mouse. Genetics 2016; 204:267-85. [PMID: 27371833 PMCID: PMC5012392 DOI: 10.1534/genetics.116.191007] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [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: 04/29/2016] [Accepted: 06/27/2016] [Indexed: 01/21/2023] Open
Abstract
Gene duplication and loss are major sources of genetic polymorphism in populations, and are important forces shaping the evolution of genome content and organization. We have reconstructed the origin and history of a 127-kbp segmental duplication, R2d, in the house mouse (Mus musculus). R2d contains a single protein-coding gene, Cwc22 De novo assembly of both the ancestral (R2d1) and the derived (R2d2) copies reveals that they have been subject to nonallelic gene conversion events spanning tens of kilobases. R2d2 is also a hotspot for structural variation: its diploid copy number ranges from zero in the mouse reference genome to >80 in wild mice sampled from around the globe. Hemizygosity for high copy-number alleles of R2d2 is associated in cis with meiotic drive; suppression of meiotic crossovers; and copy-number instability, with a mutation rate in excess of 1 per 100 transmissions in some laboratory populations. Our results provide a striking example of allelic diversity generated by duplication and demonstrate the value of de novo assembly in a phylogenetic context for understanding the mutational processes affecting duplicate genes.
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Affiliation(s)
- Andrew P Morgan
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - J Matthew Holt
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Rachel C McMullan
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Timothy A Bell
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Amelia M-F Clayshulte
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - John P Didion
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Liran Yadgary
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - David Thybert
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge, CB10 1SD, United Kingdom
| | - Duncan T Odom
- Cancer Research United Kingdom Cambridge Institute, University of Cambridge, CB2 0RE, United Kingdom Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, United Kingdom
| | - Paul Flicek
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge, CB10 1SD, United Kingdom Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, United Kingdom
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
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7
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Didion JP, Morgan AP, Yadgary L, Bell TA, McMullan RC, Ortiz de Solorzano L, Britton-Davidian J, Bult CJ, Campbell KJ, Castiglia R, Ching YH, Chunco AJ, Crowley JJ, Chesler EJ, Förster DW, French JE, Gabriel SI, Gatti DM, Garland T, Giagia-Athanasopoulou EB, Giménez MD, Grize SA, Gündüz İ, Holmes A, Hauffe HC, Herman JS, Holt JM, Hua K, Jolley WJ, Lindholm AK, López-Fuster MJ, Mitsainas G, da Luz Mathias M, McMillan L, Ramalhinho MDGM, Rehermann B, Rosshart SP, Searle JB, Shiao MS, Solano E, Svenson KL, Thomas-Laemont P, Threadgill DW, Ventura J, Weinstock GM, Pomp D, Churchill GA, Pardo-Manuel de Villena F. R2d2 Drives Selfish Sweeps in the House Mouse. Mol Biol Evol 2016; 33:1381-95. [PMID: 26882987 PMCID: PMC4868115 DOI: 10.1093/molbev/msw036] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
A selective sweep is the result of strong positive selection driving newly occurring or standing genetic variants to fixation, and can dramatically alter the pattern and distribution of allelic diversity in a population. Population-level sequencing data have enabled discoveries of selective sweeps associated with genes involved in recent adaptations in many species. In contrast, much debate but little evidence addresses whether “selfish” genes are capable of fixation—thereby leaving signatures identical to classical selective sweeps—despite being neutral or deleterious to organismal fitness. We previously described R2d2, a large copy-number variant that causes nonrandom segregation of mouse Chromosome 2 in females due to meiotic drive. Here we show population-genetic data consistent with a selfish sweep driven by alleles of R2d2 with high copy number (R2d2HC) in natural populations. We replicate this finding in multiple closed breeding populations from six outbred backgrounds segregating for R2d2 alleles. We find that R2d2HC rapidly increases in frequency, and in most cases becomes fixed in significantly fewer generations than can be explained by genetic drift. R2d2HC is also associated with significantly reduced litter sizes in heterozygous mothers, making it a true selfish allele. Our data provide direct evidence of populations actively undergoing selfish sweeps, and demonstrate that meiotic drive can rapidly alter the genomic landscape in favor of mutations with neutral or even negative effects on overall Darwinian fitness. Further study will reveal the incidence of selfish sweeps, and will elucidate the relative contributions of selfish genes, adaptation and genetic drift to evolution.
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Affiliation(s)
- John P Didion
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Andrew P Morgan
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Liran Yadgary
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Timothy A Bell
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Rachel C McMullan
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Lydia Ortiz de Solorzano
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Janice Britton-Davidian
- Institut des Sciences de l'Evolution, Université De Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | | | - Karl J Campbell
- Island Conservation, Puerto Ayora, Galápagos Island, Ecuador School of Geography, Planning & Environmental Management, The University of Queensland, St Lucia, QLD, Australia
| | - Riccardo Castiglia
- Department of Biology and Biotechnologies "Charles Darwin", University of Rome "La Sapienza", Rome, Italy
| | - Yung-Hao Ching
- Department of Molecular Biology and Human Genetics, Tzu Chi University, Hualien City, Taiwan
| | | | - James J Crowley
- Department of Genetics, The University of North Carolina at Chapel Hill
| | | | - Daniel W Förster
- Department of Evolutionary Genetics, Leibniz-Institute for Zoo and Wildlife Research, Berlin, Germany
| | - John E French
- National Toxicology Program, National Institute of Environmental Sciences, NIH, Research Triangle Park, NC
| | - Sofia I Gabriel
- Department of Animal Biology & CESAM - Centre for Environmental and Marine Studies, Faculty of Sciences, University of Lisbon, Lisboa, Portugal
| | | | | | | | - Mabel D Giménez
- Instituto de Biología Subtropical, CONICET - Universidad Nacional de Misiones, Posadas, Misiones, Argentina
| | - Sofia A Grize
- Institute of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - İslam Gündüz
- Department of Biology, Faculty of Arts and Sciences, University of Ondokuz Mayis, Samsun, Turkey
| | - Andrew Holmes
- Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcohol Abuse and Alcoholism, NIH, Bethesda, MD
| | - Heidi C Hauffe
- Department of Biodiversity and Molecular Ecology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, TN, Italy
| | - Jeremy S Herman
- Department of Natural Sciences, National Museums Scotland, Edinburgh, United Kingdom
| | - James M Holt
- Department of Computer Science, The University of North Carolina at Chapel Hill
| | - Kunjie Hua
- Department of Genetics, The University of North Carolina at Chapel Hill
| | | | - Anna K Lindholm
- Institute of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | | | - George Mitsainas
- Section of Animal Biology, Department of Biology, University of Patras, Patras, Greece
| | - Maria da Luz Mathias
- Department of Animal Biology & CESAM - Centre for Environmental and Marine Studies, Faculty of Sciences, University of Lisbon, Lisboa, Portugal
| | - Leonard McMillan
- Department of Computer Science, The University of North Carolina at Chapel Hill
| | - Maria da Graça Morgado Ramalhinho
- Department of Animal Biology & CESAM - Centre for Environmental and Marine Studies, Faculty of Sciences, University of Lisbon, Lisboa, Portugal
| | - Barbara Rehermann
- Immunology Section, Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD
| | - Stephan P Rosshart
- Immunology Section, Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD
| | - Jeremy B Searle
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY
| | - Meng-Shin Shiao
- Research Center, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Emanuela Solano
- Department of Biology and Biotechnologies "Charles Darwin", University of Rome "La Sapienza", Rome, Italy
| | | | | | - David W Threadgill
- Department of Veterinary Pathobiology, Texas A&M University, College Station Department of Molecular and Cellular Medicine, Texas A&M University, College Station
| | - Jacint Ventura
- Departament de Biologia Animal, de Biologia Vegetal y de Ecologia, Facultat de Biociències, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Daniel Pomp
- Department of Genetics, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | | | - Fernando Pardo-Manuel de Villena
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
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8
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Crowley JJ, Zhabotynsky V, Sun W, Huang S, Pakatci IK, Kim Y, Wang JR, Morgan AP, Calaway JD, Aylor DL, Yun Z, Bell TA, Buus RJ, Calaway ME, Didion JP, Gooch TJ, Hansen SD, Robinson NN, Shaw GD, Spence JS, Quackenbush CR, Barrick CJ, Nonneman RJ, Kim K, Xenakis J, Xie Y, Valdar W, Lenarcic AB, Wang W, Welsh CE, Fu CP, Zhang Z, Holt J, Guo Z, Threadgill DW, Tarantino LM, Miller DR, Zou F, McMillan L, Sullivan PF, de Villena FPM. Corrigendum: analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nat Genet 2015; 47:690. [PMID: 26018903 DOI: 10.1038/ng0615-690a] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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9
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Crowley JJ, Zhabotynsky V, Sun W, Huang S, Pakatci IK, Kim Y, Wang JR, Morgan AP, Calaway JD, Aylor DL, Yun Z, Bell TA, Buus RJ, Calaway ME, Didion JP, Gooch TJ, Hansen SD, Robinson NN, Shaw GD, Spence JS, Quackenbush CR, Barrick CJ, Nonneman RJ, Kim K, Xenakis J, Xie Y, Valdar W, Lenarcic AB, Wang W, Welsh CE, Fu CP, Zhang Z, Holt J, Guo Z, Threadgill DW, Tarantino LM, Miller DR, Zou F, McMillan L, Sullivan PF, Pardo-Manuel de Villena F. Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nat Genet 2015; 47:353-60. [PMID: 25730764 PMCID: PMC4380817 DOI: 10.1038/ng.3222] [Citation(s) in RCA: 162] [Impact Index Per Article: 18.0] [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: 09/17/2014] [Accepted: 01/26/2015] [Indexed: 12/15/2022]
Abstract
Complex human traits are influenced by variation in regulatory DNA through mechanisms that are not fully understood. Since regulatory elements are conserved between humans and mice, a thorough annotation of cis regulatory variants in mice could aid in this process. Here we provide a detailed portrait of mouse gene expression across multiple tissues in a three-way diallel. Greater than 80% of mouse genes have cis regulatory variation. These effects influence complex traits and usually extend to the human ortholog. Further, we estimate that at least one in every thousand SNPs creates a cis regulatory effect. We also observe two types of parent-of-origin effects, including classical imprinting and a novel, global allelic imbalance in favor of the paternal allele. We conclude that, as with humans, pervasive regulatory variation influences complex genetic traits in mice and provide a new resource toward understanding the genetic control of transcription in mammals.
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Affiliation(s)
- James J Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Vasyl Zhabotynsky
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Wei Sun
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Shunping Huang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Isa Kemal Pakatci
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yunjung Kim
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jeremy R Wang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Andrew P Morgan
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - John D Calaway
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - David L Aylor
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zaining Yun
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Timothy A Bell
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ryan J Buus
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mark E Calaway
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - John P Didion
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Terry J Gooch
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Stephanie D Hansen
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nashiya N Robinson
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ginger D Shaw
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jason S Spence
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Corey R Quackenbush
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Cordelia J Barrick
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Randal J Nonneman
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Kyungsu Kim
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James Xenakis
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yuying Xie
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - William Valdar
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Alan B Lenarcic
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Wei Wang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Catherine E Welsh
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Chen-Ping Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zhaojun Zhang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James Holt
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zhishan Guo
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - David W Threadgill
- Department of Molecular and Cellular Medicine, Texas A&M Health Science Center, College Station, Texas, USA
| | - Lisa M Tarantino
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Darla R Miller
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Fei Zou
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Patrick F Sullivan
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [4] Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fernando Pardo-Manuel de Villena
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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10
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Didion JP, Morgan AP, Clayshulte AMF, Mcmullan RC, Yadgary L, Petkov PM, Bell TA, Gatti DM, Crowley JJ, Hua K, Aylor DL, Bai L, Calaway M, Chesler EJ, French JE, Geiger TR, Gooch TJ, Garland T, Harrill AH, Hunter K, McMillan L, Holt M, Miller DR, O'Brien DA, Paigen K, Pan W, Rowe LB, Shaw GD, Simecek P, Sullivan PF, Svenson KL, Weinstock GM, Threadgill DW, Pomp D, Churchill GA, Pardo-Manuel de Villena F. A multi-megabase copy number gain causes maternal transmission ratio distortion on mouse chromosome 2. PLoS Genet 2015; 11:e1004850. [PMID: 25679959 PMCID: PMC4334553 DOI: 10.1371/journal.pgen.1004850] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [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: 05/02/2014] [Accepted: 10/24/2014] [Indexed: 12/29/2022] Open
Abstract
Significant departures from expected Mendelian inheritance ratios (transmission ratio distortion, TRD) are frequently observed in both experimental crosses and natural populations. TRD on mouse Chromosome (Chr) 2 has been reported in multiple experimental crosses, including the Collaborative Cross (CC). Among the eight CC founder inbred strains, we found that Chr 2 TRD was exclusive to females that were heterozygous for the WSB/EiJ allele within a 9.3 Mb region (Chr 2 76.9 - 86.2 Mb). A copy number gain of a 127 kb-long DNA segment (designated as responder to drive, R2d) emerged as the strongest candidate for the causative allele. We mapped R2d sequences to two loci within the candidate interval. R2d1 is located near the proximal boundary, and contains a single copy of R2d in all strains tested. R2d2 maps to a 900 kb interval, and the number of R2d copies varies from zero in classical strains (including the mouse reference genome) to more than 30 in wild-derived strains. Using real-time PCR assays for the copy number, we identified a mutation (R2d2WSBdel1) that eliminates the majority of the R2d2WSB copies without apparent alterations of the surrounding WSB/EiJ haplotype. In a three-generation pedigree segregating for R2d2WSBdel1, the mutation is transmitted to the progeny and Mendelian segregation is restored in females heterozygous for R2d2WSBdel1, thus providing direct evidence that the copy number gain is causal for maternal TRD. We found that transmission ratios in R2d2WSB heterozygous females vary between Mendelian segregation and complete distortion depending on the genetic background, and that TRD is under genetic control of unlinked distorter loci. Although the R2d2WSB transmission ratio was inversely correlated with average litter size, several independent lines of evidence support the contention that female meiotic drive is the cause of the distortion. We discuss the implications and potential applications of this novel meiotic drive system.
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Affiliation(s)
- John P. Didion
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Andrew P. Morgan
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Amelia M.-F. Clayshulte
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Rachel C. Mcmullan
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Liran Yadgary
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Petko M. Petkov
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Timothy A. Bell
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Daniel M. Gatti
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - James J. Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kunjie Hua
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - David L. Aylor
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Ling Bai
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Mark Calaway
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | | - John E. French
- National Toxicology Program, National Institute of Environmental Sciences, NIH, Research Triangle Park, North Carolina, United States of America
| | - Thomas R. Geiger
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Terry J. Gooch
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Theodore Garland
- Department of Biology, University of California Riverside, Riverside, California, United States of America
| | - Alison H. Harrill
- Department of Environmental and Occupational Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America
| | - Kent Hunter
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Matt Holt
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Darla R. Miller
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Deborah A. O'Brien
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kenneth Paigen
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Wenqi Pan
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Lucy B. Rowe
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Ginger D. Shaw
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Petr Simecek
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Karen L Svenson
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - George M. Weinstock
- Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America
| | - David W. Threadgill
- Department of Veterinary Pathobiology and Department of Molecular and Cellular Medicine, Texas A&M University, College Station, Texas, United States of America
| | - Daniel Pomp
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | | - Fernando Pardo-Manuel de Villena
- 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
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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11
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Chandler RL, Damrauer JS, Raab JR, Schisler JC, Wilkerson MD, Didion JP, Starmer J, Serber D, Yee D, Xiong J, Darr DB, Pardo-Manuel de Villena F, Kim WY, Magnuson T. Coexistent ARID1A-PIK3CA mutations promote ovarian clear-cell tumorigenesis through pro-tumorigenic inflammatory cytokine signalling. Nat Commun 2015; 6:6118. [PMID: 25625625 PMCID: PMC4308813 DOI: 10.1038/ncomms7118] [Citation(s) in RCA: 224] [Impact Index Per Article: 24.9] [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: 05/20/2014] [Accepted: 12/17/2014] [Indexed: 12/13/2022] Open
Abstract
Ovarian clear-cell carcinoma (OCCC) is an aggressive form of ovarian cancer with high ARID1A mutation rates. Here we present a mutant mouse model of OCCC. We find that ARID1A inactivation is not sufficient for tumour formation, but requires concurrent activation of the phosphoinositide 3-kinase catalytic subunit, PIK3CA. Remarkably, the mice develop highly penetrant tumours with OCCC-like histopathology, culminating in haemorrhagic ascites and a median survival period of 7.5 weeks. Therapeutic treatment with the pan-PI3K inhibitor, BKM120, prolongs mouse survival by inhibiting the tumour cell growth. Cross-species gene expression comparisons support a role for IL-6 inflammatory cytokine signalling in OCCC pathogenesis. We further show that ARID1A and PIK3CA mutations cooperate to promote tumour growth through sustained IL-6 overproduction. Our findings establish an epistatic relationship between SWI/SNF chromatin remodelling and PI3K pathway mutations in OCCC and demonstrate that these pathways converge on pro-tumorigenic cytokine signalling. We propose that ARID1A protects against inflammation-driven tumorigenesis.
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Affiliation(s)
- Ronald L Chandler
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Jeffrey S Damrauer
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Jesse R Raab
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Jonathan C Schisler
- 1] McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Matthew D Wilkerson
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - John P Didion
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Joshua Starmer
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Daniel Serber
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Della Yee
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Jessie Xiong
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - David B Darr
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Fernando Pardo-Manuel de Villena
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - William Y Kim
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [3] Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Terry Magnuson
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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12
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Didion JP, Buus RJ, Naghashfar Z, Threadgill DW, Morse HC, de Villena FPM. SNP array profiling of mouse cell lines identifies their strains of origin and reveals cross-contamination and widespread aneuploidy. BMC Genomics 2014; 15:847. [PMID: 25277546 PMCID: PMC4198738 DOI: 10.1186/1471-2164-15-847] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [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: 06/24/2014] [Accepted: 09/29/2014] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The crisis of Misidentified and contaminated cell lines have plagued the biological research community for decades. Some repositories and journals have heeded calls for mandatory authentication of human cell lines, yet misidentification of mouse cell lines has received little publicity despite their importance in sponsored research. Short tandem repeat (STR) profiling is the standard authentication method, but it may fail to distinguish cell lines derived from the same inbred strain of mice. Additionally, STR profiling does not reveal karyotypic changes that occur in some high-passage lines and may have functional consequences. Single nucleotide polymorphism (SNP) profiling has been suggested as a more accurate and versatile alternative to STR profiling; however, a high-throughput method for SNP-based authentication of mouse cell lines has not been described. RESULTS We have developed computational methods (Cell Line Authentication by SNP Profiling, CLASP) for cell line authentication and copy number analysis based on a cost-efficient SNP array, and we provide a reference database of commonly used mouse strains and cell lines. We show that CLASP readily discriminates among cell lines of diverse taxonomic origins, including multiple cell lines derived from a single inbred strain, intercross or wild caught mouse. CLASP is also capable of detecting contaminants present at concentrations as low as 5%. Of the 99 cell lines we tested, 15 exhibited substantial divergence from the reported genetic background. In all cases, we were able to distinguish whether the authentication failure was due to misidentification (one cell line, Ba/F3), the presence of multiple strain backgrounds (five cell lines), contamination by other cells and/or the presence of aneuploid chromosomes (nine cell lines). CONCLUSIONS Misidentification and contamination of mouse cell lines is potentially as widespread as it is in human cell culture. This may have substantial implications for studies that are dependent on the expected background of their cell cultures. Laboratories can mitigate these risks by regular authentication of their cell cultures. Our results demonstrate that SNP array profiling is an effective method to combat cell line misidentification.
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Affiliation(s)
- John P Didion
- />Department of Genetics, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
- />Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
- />Carolina Center for Genome Science, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
| | - Ryan J Buus
- />Department of Genetics, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
- />Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
- />Carolina Center for Genome Science, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
| | - Zohreh Naghashfar
- />Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Twinbrook I, Room 1421, 5640 Fishers Lane, Rockville, MD 20852 USA
| | - David W Threadgill
- />Department of Veterinary Pathobiology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843 USA
- />Department of Molecular and Cellular Medicine, College of Medicine, Texas A&M University, College Station, TX 77843 USA
| | - Herbert C Morse
- />Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Twinbrook I, Room 1421, 5640 Fishers Lane, Rockville, MD 20852 USA
| | - Fernando Pardo-Manuel de Villena
- />Department of Genetics, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
- />Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
- />Carolina Center for Genome Science, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, NC 27599-7264 USA
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13
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Didion JP, de Villena FPM. Deconstructing Mus gemischus: advances in understanding ancestry, structure, and variation in the genome of the laboratory mouse. Mamm Genome 2013; 24:1-20. [PMID: 23223940 PMCID: PMC4034049 DOI: 10.1007/s00335-012-9441-z] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2012] [Accepted: 11/05/2012] [Indexed: 01/26/2023]
Abstract
The laboratory mouse is an artificial construct with a complex relationship to its natural ancestors. In 2002, the mouse became the first mammalian model organism with a reference genome. Importantly, the mouse genome sequence was assembled from data on a single inbred laboratory strain, C57BL/6. Several large-scale genetic variant discovery efforts have been conducted, resulting in a catalog of tens of millions of SNPs and structural variants. High-density genotyping arrays covering a subset of those variants have been used to produce hundreds of millions of genotypes in laboratory stocks and a small number of wild mice. These landmark resources now enable us to determine relationships among laboratory mice, assign local ancestry at fine scale, resolve important controversies, and identify a new set of challenges-most importantly, the troubling scarcity of genetic data on the very natural populations from which the laboratory mouse was derived. Our aim with this review is to provide the reader with an historical context for the mouse as a model organism and to explain how practical decisions made in the past have influenced both the architecture of the laboratory mouse genome and the design and execution of current large-scale resources. We also provide examples on how the accomplishments of the past decade can be used by researchers to streamline the use of mice in their experiments and correctly interpret results. Finally, we propose future steps that will enable the mouse community to extend its successes in the decade to come.
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Affiliation(s)
- John P. Didion
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Didion JP, Yang H, Sheppard K, Fu CP, McMillan L, de Villena FPM, Churchill GA. Discovery of novel variants in genotyping arrays improves genotype retention and reduces ascertainment bias. BMC Genomics 2012; 13:34. [PMID: 22260749 PMCID: PMC3305361 DOI: 10.1186/1471-2164-13-34] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [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: 10/04/2011] [Accepted: 01/19/2012] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND High-density genotyping arrays that measure hybridization of genomic DNA fragments to allele-specific oligonucleotide probes are widely used to genotype single nucleotide polymorphisms (SNPs) in genetic studies, including human genome-wide association studies. Hybridization intensities are converted to genotype calls by clustering algorithms that assign each sample to a genotype class at each SNP. Data for SNP probes that do not conform to the expected pattern of clustering are often discarded, contributing to ascertainment bias and resulting in lost information - as much as 50% in a recent genome-wide association study in dogs. RESULTS We identified atypical patterns of hybridization intensities that were highly reproducible and demonstrated that these patterns represent genetic variants that were not accounted for in the design of the array platform. We characterized variable intensity oligonucleotide (VINO) probes that display such patterns and are found in all hybridization-based genotyping platforms, including those developed for human, dog, cattle, and mouse. When recognized and properly interpreted, VINOs recovered a substantial fraction of discarded probes and counteracted SNP ascertainment bias. We developed software (MouseDivGeno) that identifies VINOs and improves the accuracy of genotype calling. MouseDivGeno produced highly concordant genotype calls when compared with other methods but it uniquely identified more than 786000 VINOs in 351 mouse samples. We used whole-genome sequence from 14 mouse strains to confirm the presence of novel variants explaining 28000 VINOs in those strains. We also identified VINOs in human HapMap 3 samples, many of which were specific to an African population. Incorporating VINOs in phylogenetic analyses substantially improved the accuracy of a Mus species tree and local haplotype assignment in laboratory mouse strains. CONCLUSION The problems of ascertainment bias and missing information due to genotyping errors are widely recognized as limiting factors in genetic studies. We have conducted the first formal analysis of the effect of novel variants on genotyping arrays, and we have shown that these variants account for a large portion of miscalled and uncalled genotypes. Genetic studies will benefit from substantial improvements in the accuracy of their results by incorporating VINOs in their analyses.
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Affiliation(s)
- John P Didion
- Department of Genetics, University of North Carolina at Chapel Hill, CB 7264, Chapel Hill, North Carolina, 27599-7264, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, North Carolina, 27599-7295, USA
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, CB 7264, Chapel Hill, North Carolina, 27599-7264, USA
| | - Hyuna Yang
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Box 2721, Durham, NC, 27710, USA
| | - Keith Sheppard
- Center for Genome Dynamics, The Jackson Laboratory, 600 Main Street, Bar Harbor, Maine, 04609, USA
| | - Chen-Ping Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, CB 3175, Chapel Hill, North Carolina, 27599-3175, USA
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina at Chapel Hill, CB 3175, Chapel Hill, North Carolina, 27599-3175, USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, CB 7264, Chapel Hill, North Carolina, 27599-7264, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, CB 7295, Chapel Hill, North Carolina, 27599-7295, USA
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, CB 7264, Chapel Hill, North Carolina, 27599-7264, USA
| | - Gary A Churchill
- Center for Genome Dynamics, The Jackson Laboratory, 600 Main Street, Bar Harbor, Maine, 04609, USA
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Yang H, Wang JR, Didion JP, Buus RJ, Bell TA, Welsh CE, Bonhomme F, Yu AHT, Nachman MW, Pialek J, Tucker P, Boursot P, McMillan L, Churchill GA, de Villena FPM. Subspecific origin and haplotype diversity in the laboratory mouse. Nat Genet 2011; 43:648-55. [PMID: 21623374 PMCID: PMC3125408 DOI: 10.1038/ng.847] [Citation(s) in RCA: 336] [Impact Index Per Article: 25.8] [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: 07/13/2010] [Accepted: 05/05/2011] [Indexed: 11/09/2022]
Abstract
Here we provide a genome-wide, high-resolution map of the phylogenetic origin of the genome of most extant laboratory mouse inbred strains. Our analysis is based on the genotypes of wild-caught mice from three subspecies of Mus musculus. We show that classical laboratory strains are derived from a few fancy mice with limited haplotype diversity. Their genomes are overwhelmingly Mus musculus domesticus in origin, and the remainder is mostly of Japanese origin. We generated genome-wide haplotype maps based on identity by descent from fancy mice and show that classical inbred strains have limited and non-randomly distributed genetic diversity. In contrast, wild-derived laboratory strains represent a broad sampling of diversity within M. musculus. Intersubspecific introgression is pervasive in these strains, and contamination by laboratory stocks has played a role in this process. The subspecific origin, haplotype diversity and identity by descent maps can be visualized using the Mouse Phylogeny Viewer (see URLs).
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Affiliation(s)
- Hyuna Yang
- The Jackson Laboratory, Bar Harbor, Maine, USA
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Eisener-Dorman AF, Didion JP, Santos C, Calaway JD. The 23rd International Mammalian Genome Conference meeting report. Mamm Genome 2010; 21:217-23. [PMID: 20496149 PMCID: PMC2890982 DOI: 10.1007/s00335-010-9265-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2010] [Accepted: 05/06/2010] [Indexed: 11/27/2022]
Affiliation(s)
- Amy F Eisener-Dorman
- Department of Psychiatry, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA.
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