ALBERT

Description:    Consomic strains, in which one chromosome is derived from a donor strain and the other chromosomes are derived from the recipient strain, provide a powerful tool for the dissection of complex genetic traits. In this study we established ten consomic strains (A-2 SM , A-6 SM , A-11 SM , A-12 SM , A-13 SM , A-15 SM , A-17 SM , A-18 SM , A-19 SM , A-Y SM ) using the SM/J strain as the donor and the A/J strain as the recipient; these are the parental strains of a set of SMXA recombinant inbred (RI) strains that we had developed previously. We analyzed body weights and blood lipid levels in the consomic and parental strains. The mean values for each trait showed a continuous range of variation in the consomic strains suggesting that they are controlled by multiple genes. We previously identified suggestive QTLs for body weight on chromosome 6 in SMXA RI strains and (SM/J × A/J)F 2 mice. The observation that the A-6 SM consomic strain had a significantly lower mean body weight than the A/J strain supports the presence of this QTL on chromosome 6. Similarly, the higher blood triglyceride level in the A-11 SM strain shows the existence of a previously mapped QTL on chromosome 11, and the A-12 SM strain provides evidence of a QTL for blood total cholesterol level on chromosome 12. These consomic strains, along with the previously developed set of SMXA RI strains from A/J and SM/J mice, offer an invaluable and powerful resource for the analysis of complex genetic traits in mice. Content Type Journal Article Pages 1-6 DOI 10.1007/s00335-012-9435-x Authors Tamio Ohno, Division of Experimental Animals, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan Keiko Hata, Division of Experimental Animals, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan Taisuke Baba, Division of Experimental Animals, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan Fusayo Io, Department of Applied Molecular Bioscience, Graduate School of Bioagricultural Sciences, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601 Japan Misato Kobayashi, Department of Applied Molecular Bioscience, Graduate School of Bioagricultural Sciences, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601 Japan Fumihiko Horio, Department of Applied Molecular Bioscience, Graduate School of Bioagricultural Sciences, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601 Japan Masahiko Nishimura, Division of Experimental Animals, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description: Erratum to: Beyond knockouts: cre resources for conditional mutagenesis Content Type Journal Article Category Erratum Pages 1-1 DOI 10.1007/s00335-012-9434-y Authors Stephen A. Murray, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA Janan T. Eppig, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA Damian Smedley, The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK Elizabeth M. Simpson, Departments of Medical Genetics and Psychiatry, Centre for Molecular Medicine and Therapeutics at the Child & Family Research Institute, University of British Columbia, Vancouver, BC V5Z 4H4, Canada Nadia Rosenthal, National Heart and Lung Institute, Imperial College London, London, W12 0NN UK Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description:    The International Mouse Phenotyping Consortium (IMPC) ( http://www.mousephenotype.org ) will reveal the pleiotropic functions of every gene in the mouse genome and uncover the wider role of genetic loci within diverse biological systems. Comprehensive informatics solutions are vital to ensuring that this vast array of data is captured in a standardised manner and made accessible to the scientific community for interrogation and analysis. Here we review the existing EuroPhenome and WTSI phenotype informatics systems and the IKMC portal, and present plans for extending these systems and lessons learned to the development of a robust IMPC informatics infrastructure. Content Type Journal Article Pages 1-12 DOI 10.1007/s00335-012-9428-9 Authors Ann-Marie Mallon, Mammalian Genetics Unit, Medical Research Council Harwell, Harwell, Oxfordshire, OX11 0RD UK Vivek Iyer, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH UK David Melvin, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH UK Hugh Morgan, Mammalian Genetics Unit, Medical Research Council Harwell, Harwell, Oxfordshire, OX11 0RD UK Helen Parkinson, European Bioinformatics Institute, Hinxton, Cambridge, CB10 1ST UK Steve D. M. Brown, Mammalian Genetics Unit, Medical Research Council Harwell, Harwell, Oxfordshire, OX11 0RD UK Paul Flicek, European Bioinformatics Institute, Hinxton, Cambridge, CB10 1ST UK William C. Skarnes, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH UK Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description:    Mouse gene expression data are complex and voluminous. To maximize the utility of these data, they must be made readily accessible through databases, and those resources need to place the expression data in the larger biological context. Here we describe two community resources that approach these problems in different but complementary ways: BioGPS and the Mouse Gene Expression Database (GXD). BioGPS connects its large and homogeneous microarray gene expression reference data sets via plugins with a heterogeneous collection of external gene centric resources, thus casting a wide but loose net. GXD acquires different types of expression data from many sources and integrates these data tightly with other types of data in the Mouse Genome Informatics (MGI) resource, with a strong emphasis on consistency checks and manual curation. We describe and contrast the “loose” and “tight” data integration strategies employed by BioGPS and GXD, respectively, and discuss the challenges and benefits of data integration. BioGPS is freely available at http://biogps.org . GXD is freely available through the MGI web site ( www.informatics.jax.org ) or directly at www.informatics.jax.org/expression.shtml . Content Type Journal Article Pages 1-9 DOI 10.1007/s00335-012-9408-0 Authors Martin Ringwald, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA Chunlei Wu, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA Andrew I. Su, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description:    The Collaborative Cross (CC) is a panel of recombinant inbred lines derived from eight genetically diverse laboratory inbred strains. Recently, the genetic architecture of the CC population was reported based on the genotype of a single male per line, and other publications reported incompletely inbred CC mice that have been used to map a variety of traits. The three breeding sites, in the US, Israel, and Australia, are actively collaborating to accelerate the inbreeding process through marker-assisted inbreeding and to expedite community access of CC lines deemed to have reached defined thresholds of inbreeding. Plans are now being developed to provide access to this novel genetic reference population through distribution centers. Here we provide a description of the distribution efforts by the University of North Carolina Systems Genetics Core, Tel Aviv University, Israel and the University of Western Australia. Content Type Journal Article Pages 1-7 DOI 10.1007/s00335-012-9410-6 Authors Catherine E. Welsh, Department of Computer Science, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Darla R. Miller, Department of Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Kenneth F. Manly, Department of Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Jeremy Wang, Department of Computer Science, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Leonard McMillan, Department of Computer Science, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Grant Morahan, The Western Australian Institute for Medical Research and Centre for Medical Research, University of Western Australia, Perth, WA, Australia Richard Mott, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN UK Fuad A. Iraqi, Department of Human Microbiology, Tel Aviv University, Ramat Aviv, 69978 Tel Aviv, Israel David W. Threadgill, Department of Genetics, North Carolina State University, Raleigh, NC 27695, USA Fernando Pardo-Manuel de Villena, Department of Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description:    We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5 % of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches. Content Type Journal Article Pages 1-13 DOI 10.1007/s00335-012-9411-5 Authors Anatole Ghazalpour, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Christoph D. Rau, Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, CA, USA Charles R. Farber, Departments of Medicine and Biochemistry and Molecular Genetics, and Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA Brian J. Bennett, Department of Genetics, and Nutrition Research Institute, University of North Carolina, Chapel Hill, NC, USA Luz D. Orozco, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Atila van Nas, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Calvin Pan, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Hooman Allayee, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA Simon W. Beaven, Division of Digestive Diseases, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Mete Civelek, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Richard C. Davis, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Thomas A. Drake, Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Rick A. Friedman, Department of Otology/Skull Base Surgery, House Research Institute, Los Angeles, CA, USA Nick Furlotte, Department of Computer Sciences, University of California, Los Angeles, CA, USA Simon T. Hui, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA J. David Jentsch, Department of Psychology & Behavioral Neuroscience and Psychiatry & Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Emrah Kostem, Department of Computer Sciences, University of California, Los Angeles, CA, USA Hyun Min Kang, Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA Eun Yong Kang, Department of Computer Sciences, University of California, Los Angeles, CA, USA Jong Wha Joo, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Vyacheslav A. Korshunov, Department of Medicine, Aab Cardiovascular Research Institute, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA Rick E. Laughlin, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA Lisa J. Martin, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Jeffrey D. Ohmen, Department of Cell Biology and Genetics, House Research Institute, Los Angeles, CA, USA Brian W. Parks, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Matteo Pellegrini, Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, CA, USA Karen Reue, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Desmond J. Smith, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Sotirios Tetradis, Molecular Biology Institute, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Jessica Wang, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Yibin Wang, Division of Molecular Medicine, Department of Anesthesiology, Physiology and Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA James N. Weiss, Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, CA, USA Todd Kirchgessner, Department of Cardiovascular Drug Discovery, Bristol-Myers Squibb Co, Pennington, NJ, USA Peter S. Gargalovic, Department of Cardiovascular Drug Discovery, Bristol-Myers Squibb Co, Pennington, NJ, USA Eleazar Eskin, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Aldons J. Lusis, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA Renée C. LeBoeuf, Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington, 850 Republican Street, Seattle, WA 98109-4725, USA Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description:    Mammalian SWI/SNF complexes utilize either BRG1 or BRM as alternative catalytic subunits with DNA-dependent ATPase activity to remodel chromatin. Although the two proteins are 75 % identical, broadly expressed, and have similar biochemical activities in vitro, BRG1 is essential for mouse embryonic development, while BRM is dispensable. To investigate whether BRG1 and BRM have overlapping functions during mouse embryogenesis, we performed double-heterozygous intercrosses using constitutive null mutations previously created by gene targeting. The progeny of these crosses had a distribution of genotypes that was significantly skewed relative to their combined gene dosage. This was most pronounced at the top and bottom of the gene dosage hierarchy, with a 1.5-fold overrepresentation of Brg1 + / + ;Brm + / + mice and a corresponding 1.6-fold underrepresentation of Brg1 + / − ;Brm − / − mice. To account for the underrepresentation of Brg1 + / − ;Brm − / − mice, timed matings and blastocyst outgrowth assays demonstrated that ~50 % of these embryos failed to develop beyond the peri-implantation stage. These results challenge the idea that BRG1 is the exclusive catalytic subunit of SWI/SNF complexes in ES cells and suggest that BRM also interacts with the pluripotency transcription factors to facilitate self-renewal of the inner cell mass. In contrast to implantation, the Brm genotype did not influence an exencephaly phenotype that arises because of Brg1 haploinsufficiency during neural tube closure and that results in peri-natal lethality. Taken together, these results support the idea that BRG1 and BRM have overlapping functions for certain developmental processes but not others during embryogenesis. Content Type Journal Article Pages 1-9 DOI 10.1007/s00335-012-9433-z Authors Stephanie L. Smith-Roe, Department of Genetics, University of North Carolina, Chapel Hill, NC, USA Scott J. Bultman, Department of Genetics, University of North Carolina, Chapel Hill, NC, USA Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description:    Beef with yellow fat is considered undesirable by consumers in most European and Asian markets. β-Carotene is the major carotenoid deposited in the adipose tissue and milk fat of cattle ( Bos taurus ), which can result in the yellowness. The effects of retinal short-chain dehydrogenase reductase ( RDHE2 ) and β, β-carotene 9′,10-dioxygenase ( BCO2 ) were considered jointly as major candidate genes for causing the yellow fat colour, based on their genomic locations in the fat colour quantitative trait loci (QTL) and their roles in the metabolism of β-carotene. In a secondary pathway, BCO2 cleaves β-carotene into retinoic acid, the most potent form of vitamin A. RDHE2 converts trans-retinol to trans-retinal, a less active form of vitamin A. We evaluated the effects of two amino acid variants of the RDHE2 gene (V6A and V33A) along with a mutation in the BCO2 gene that results in a stop codon (W80X) in seven cattle populations. The RDHE2 V6A genotype affected several fat colour traits but the size of the effect varied in the populations studied. The genotype effect of the RDHE2 V33A variant was observed only in New Zealand samples of unknown breed. In general, the individual effects of RDHE2 V6A and V33A SNPs genotypes were greater in the random New Zealand samples than in samples from pedigreed Jersey-Limousin backcross progeny, accounting for 8–17 % of the variance in one population. Epistasis between the BCO2 W80X and RDHE2 variants was observed, and in some populations this explained more of the variation than the effects of the individual RDHE2 variants. Content Type Journal Article Pages 1-9 DOI 10.1007/s00335-012-9396-0 Authors Rugang Tian, School of Animal & Veterinary Sciences, University of Adelaide, Roseworthy Campus, Roseworthy, SA 5371, Australia Neil G. Cullen, AgResearch, Ruakura Research Centre, P.B. 3123, Hamilton, 3240 New Zealand Chris A. Morris, AgResearch, Ruakura Research Centre, P.B. 3123, Hamilton, 3240 New Zealand Paul J. Fisher, AgResearch, Invermay Agricultural Centre, P.B. 50034, Mosgiel, 9053 New Zealand Wayne S. Pitchford, School of Animal & Veterinary Sciences, University of Adelaide, Roseworthy Campus, Roseworthy, SA 5371, Australia Cynthia D. K. Bottema, School of Animal & Veterinary Sciences, University of Adelaide, Roseworthy Campus, Roseworthy, SA 5371, Australia Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description:    Individual variation in sensitivity to acute ethanol (EtOH) challenge is associated with alcohol drinking and is a predictor of alcohol abuse. Previous studies have shown that the C57BL/6J (B6) and 129S1/SvImJ (S1) inbred mouse strains differ in responses on certain measures of acute EtOH intoxication. To gain insight into genetic factors contributing to these differences, we performed quantitative trait locus (QTL) analysis of measures of EtOH-induced ataxia (accelerating rotarod), hypothermia, and loss of righting reflex (LORR) duration in a B6 × S1 F2 population. We confirmed that S1 showed greater EtOH-induced hypothermia (specifically at a high dose) and longer LORR compared to B6. QTL analysis revealed several additive and interacting loci for various phenotypes, as well as examples of genotype interactions with sex. QTLs for different EtOH phenotypes were largely non-overlapping, suggesting separable genetic influences on these behaviors. The most compelling main-effect QTLs were for hypothermia on chromosome 16 and for LORR on chromosomes 4 and 6. Several QTLs overlapped with loci repeatedly linked to EtOH drinking in previous mouse studies. The architecture of the traits we examined was complex but clearly amenable to dissection in future studies. Using integrative genomics strategies, plausible functional and positional candidates may be found. Uncovering candidate genes associated with variation in these phenotypes in this population could ultimately shed light on genetic factors underlying sensitivity to EtOH intoxication and risk for alcoholism in humans. Content Type Journal Article Pages 1-17 DOI 10.1007/s00335-012-9394-2 Authors Elissa J. Chesler, The Jackson Laboratory, 600 Main St, Bar Harbor, ME 04609, USA Aaron Plitt, Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse (NIAAA), NIH, Bethesda, MD, USA Daniel Fisher, Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse (NIAAA), NIH, Bethesda, MD, USA Benita Hurd, Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse (NIAAA), NIH, Bethesda, MD, USA Lauren Lederle, Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse (NIAAA), NIH, Bethesda, MD, USA Jason A. Bubier, The Jackson Laboratory, 600 Main St, Bar Harbor, ME 04609, USA Carly Kiselycznyk, Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse (NIAAA), NIH, Bethesda, MD, USA Andrew Holmes, Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse (NIAAA), NIH, Bethesda, MD, USA Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990

Description:    Red blood cells are essential for oxygen transport and other physiologic processes. Red cell characteristics are typically determined by complete blood counts which measure parameters such as hemoglobin levels and mean corpuscular volumes; these parameters reflect the quality and quantity of red cells in the circulation at any particular moment. To identify the genetic determinants of red cell parameters, we performed genome-wide association analysis on LG/J × SM/J F 2 and F 34 advanced intercross lines using single nucleotide polymorphism genotyping and a novel algorithm for mapping in the combined populations. We identified significant quantitative trait loci for red cell parameters on chromosomes 6, 7, 8, 10, 12, and 17; our use of advanced intercross lines reduced the quantitative trait loci interval width from 1.6- to 9.4-fold. Using the genomic sequences of LG/J and SM/J mice, we identified nonsynonymous coding single nucleotide polymorphisms in candidate genes residing within quantitative trait loci and performed sequence alignments and molecular modeling to gauge the potential impact of amino acid substitutions. These results should aid in the identification of genes critical for red cell physiology and metabolism and demonstrate the utility of advanced intercross lines in uncovering genetic determinants of inherited traits. Content Type Journal Article Pages 1-11 DOI 10.1007/s00335-012-9393-3 Authors Thomas B. Bartnikas, Department of Pathology, Children’s Hospital, Enders 1110, 300 Longwood Avenue, Boston, MA 02115, USA Clarissa C. Parker, Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA Riyan Cheng, Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA Dean R. Campagna, Department of Pathology, Children’s Hospital, Enders 1110, 300 Longwood Avenue, Boston, MA 02115, USA Jackie E. Lim, Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27708, USA Abraham A. Palmer, Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA Mark D. Fleming, Department of Pathology, Children’s Hospital, Enders 1110, 300 Longwood Avenue, Boston, MA 02115, USA Journal Mammalian Genome Online ISSN 1432-1777 Print ISSN 0938-8990