Genome-wide associations reveal human-mouse genetic convergence and modifiers of myogenesis, CPNE1 and STC2
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A. Skol | M. Abney | R. Cheng | A. Palmer | J. Gregory | C. Parker | A. Douglas | D. Vandenbergh | G. Sokoloff | A. Lionikas | A. H. Hernández Cordero | Natalia M. Gonzales | A. I. H. Cordero
[1] Daniel L. Koller,et al. Disentangling the genetics of lean mass. , 2019, The American journal of clinical nutrition.
[2] Gregory M. Cooper,et al. CADD: predicting the deleteriousness of variants throughout the human genome , 2018, Nucleic Acids Res..
[3] Margaret G. Distler,et al. Genome wide association analysis in a mouse advanced intercross line , 2018, Nature Communications.
[4] Benjamin B. Sun,et al. New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries. , 2018, Nature Genetics.
[5] P. Donnelly,et al. The UK Biobank resource with deep phenotyping and genomic data , 2018, Nature.
[6] Arcadi Navarro,et al. Replicability and Prediction: Lessons and Challenges from GWAS. , 2018, Trends in genetics : TIG.
[7] Po-Ru Loh,et al. Mixed-model association for biobank-scale datasets , 2018, Nature Genetics.
[8] Samuel E. Jones,et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry , 2018, bioRxiv.
[9] Luke R. Lloyd-Jones,et al. Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio , 2018, Genetics.
[10] P. Carbonetto,et al. Replication and discovery of musculoskeletal QTLs in LG/J and SM/J advanced intercross lines , 2018, Physiological reports.
[11] Astrid Gall,et al. Ensembl 2018 , 2017, Nucleic Acids Res..
[12] Erdogan Taskesen,et al. Functional mapping and annotation of genetic associations with FUMA , 2017, Nature Communications.
[13] P. Donnelly,et al. Genome-wide genetic data on ~500,000 UK Biobank participants , 2017, bioRxiv.
[14] Stephen C. J. Parker,et al. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass , 2017, Nature Communications.
[15] M. Narici,et al. Structure and function of human muscle fibres and muscle proteome in physically active older men , 2017, The Journal of physiology.
[16] S. Fiering,et al. Fine-mapping of genes determining extrafusal fiber properties in murine soleus muscle. , 2017, Physiological genomics.
[17] Buhm Han,et al. Comparison of Two Meta-Analysis Methods: Inverse-Variance-Weighted Average and Weighted Sum of Z-Scores , 2016, Genomics & informatics.
[18] Lang Li,et al. Charcot-Marie-Tooth gene, SBF2, associated with taxane-induced peripheral neuropathy in African Americans , 2016, Oncotarget.
[19] Trevor Hastie,et al. REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants. , 2016, American journal of human genetics.
[20] Peter Carbonetto,et al. Genome-wide association study of behavioral, physiological and gene expression traits in commercially available outbred CFW mice , 2016, Nature Genetics.
[21] Steve D. M. Brown,et al. Genome-wide association of multiple complex traits in outbred mice by ultra low-coverage sequencing , 2016, Nature Genetics.
[22] T. Spector,et al. Contribution of Heritability and Epigenetic Factors to Skeletal Muscle Mass Variation in United Kingdom Twins , 2016, The Journal of clinical endocrinology and metabolism.
[23] Brian L Browning,et al. Genotype Imputation with Millions of Reference Samples. , 2016, American journal of human genetics.
[24] Ellen T. Gelfand,et al. A Novel Approach to High-Quality Postmortem Tissue Procurement: The GTEx Project , 2015, Biopreservation and biobanking.
[25] Gabor T. Marth,et al. A global reference for human genetic variation , 2015, Nature.
[26] D. Conrad,et al. Using whole-genome sequences of the LG/J and SM/J inbred mouse strains to prioritize quantitative trait genes and nucleotides , 2015, BMC Genomics.
[27] S. Inoue,et al. Recent genetic discoveries in osteoporosis, sarcopenia and obesity. , 2015, Endocrine journal.
[28] N. Wray,et al. Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance components analysis , 2015, Nature Genetics.
[29] P. Elliott,et al. UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.
[30] D. Balding,et al. Relatedness in the post-genomic era: is it still useful? , 2014, Nature Reviews Genetics.
[31] Carson C Chow,et al. Second-generation PLINK: rising to the challenge of larger and richer datasets , 2014, GigaScience.
[32] B. Berger,et al. Efficient Bayesian mixed model analysis increases association power in large cohorts , 2014, Nature Genetics.
[33] M. Daly,et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies , 2014, Nature Genetics.
[34] E. Füchtbauer,et al. Stanniocalcin-2 Inhibits Mammalian Growth by Proteolytic Inhibition of the Insulin-like Growth Factor Axis* , 2014, The Journal of Biological Chemistry.
[35] Ross M. Fraser,et al. Defining the role of common variation in the genomic and biological architecture of adult human height , 2014, Nature Genetics.
[36] P. Carbonetto,et al. High-Resolution Genetic Mapping of Complex Traits from a Combined Analysis of F2 and Advanced Intercross Mice , 2014, Genetics.
[37] P. Carbonetto,et al. Discovery and refinement of muscle weight QTLs in B6 × D2 advanced intercross mice. , 2014, Physiological genomics.
[38] D. Guertin,et al. Adipocytes arise from multiple lineages that are heterogeneously and dynamically distributed , 2014, Nature Communications.
[39] Y. Ouchi,et al. Large-scale analysis reveals a functional single-nucleotide polymorphism in the 5′-flanking region of PRDM16 gene associated with lean body mass , 2014, Aging cell.
[40] H. Deng,et al. Genome-Wide Association Study Identified Copy Number Variants Important for Appendicular Lean Mass , 2014, PloS one.
[41] M. Yamada,et al. Age‐dependent changes in skeletal muscle mass and visceral fat area in Japanese adults from 40 to 79 years‐of‐age , 2014, Geriatrics & gerontology international.
[42] P. Visscher,et al. Advantages and pitfalls in the application of mixed-model association methods , 2014, Nature Genetics.
[43] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[44] Y. Tüzün,et al. Basic histological structure and functions of facial skin. , 2014, Clinics in dermatology.
[45] Kathleen Marchal,et al. A network-based approach to identify substrate classes of bacterial glycosyltransferases , 2014, BMC Genomics.
[46] J. Cheverud,et al. The effect of dietary fat intake on hepatic gene expression in LG/J AND SM/J mice , 2014, BMC Genomics.
[47] K. Gundersen,et al. A cellular memory mechanism aids overload hypertrophy in muscle long after an episodic exposure to anabolic steroids , 2013, The Journal of physiology.
[48] M. Abney,et al. Practical Considerations Regarding the Use of Genotype and Pedigree Data to Model Relatedness in the Context of Genome-Wide Association Studies , 2013, G3: Genes, Genomes, Genetics.
[49] R. Cheng,et al. A Simulation Study of Permutation, Bootstrap, and Gene Dropping for Assessing Statistical Significance in the Case of Unequal Relatedness , 2013, Genetics.
[50] H. Deng,et al. Suggestion of GLYAT gene underlying variation of bone size and body lean mass as revealed by a bivariate genome-wide association study , 2013, Human Genetics.
[51] J. Derry,et al. Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses , 2012, BMC Genomics.
[52] Johannes E. Schindelin,et al. Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.
[53] M. Stephens,et al. Genome-wide Efficient Mixed Model Analysis for Association Studies , 2012, Nature Genetics.
[54] P. Visscher,et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits , 2012, Nature Genetics.
[55] Hui Shen,et al. Genome-wide association study of copy number variation identified gremlin1 as a candidate gene for lean body mass , 2011, Journal of Human Genetics.
[56] A. Palmer,et al. QTL Analysis of Type I and Type IIA Fibers in Soleus Muscle in a Cross between LG/J and SM/J Mouse Strains , 2011, Front. Gene..
[57] J. Marchini,et al. Genotype Imputation with Thousands of Genomes , 2011, G3: Genes | Genomes | Genetics.
[58] S. Blair,et al. Longitudinal changes in body composition associated with healthy ageing: men, aged 20–96 years , 2011, British Journal of Nutrition.
[59] D. Zaykin,et al. Optimally weighted Z‐test is a powerful method for combining probabilities in meta‐analysis , 2011, Journal of evolutionary biology.
[60] Arrate Muñoz-Barrutia,et al. 3D reconstruction of histological sections: Application to mammary gland tissue , 2010, Microscopy research and technique.
[61] S. Ellard,et al. Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations. , 2010, Genetic testing and molecular biomarkers.
[62] R. Cheng,et al. Fine-mapping of muscle weight QTL in LG/J and SM/J intercrosses. , 2010, Physiological genomics.
[63] Mark Abney,et al. Genome-Wide Association Studies and the Problem of Relatedness Among Advanced Intercross Lines and Other Highly Recombinant Populations , 2010, Genetics.
[64] Alkes L. Price,et al. New approaches to population stratification in genome-wide association studies , 2010, Nature Reviews Genetics.
[65] P. Bork,et al. A method and server for predicting damaging missense mutations , 2010, Nature Methods.
[66] A. J. Zweers,et al. Measuring shoot length of submerged aquatic plants using graph analysis , 2010 .
[67] William J. Astle,et al. Population Structure and Cryptic Relatedness in Genetic Association Studies , 2009, 1010.4681.
[68] E. Birney,et al. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt , 2009, Nature Protocols.
[69] S. Levy,et al. Genome-wide association and replication studies identified TRHR as an important gene for lean body mass. , 2009, American journal of human genetics.
[70] M. Daly,et al. Estimation of the multiple testing burden for genomewide association studies of nearly all common variants , 2008, Genetic epidemiology.
[71] D. Heckerman,et al. Efficient Control of Population Structure in Model Organism Association Mapping , 2008, Genetics.
[72] J. Faulkner,et al. AGE‐RELATED CHANGES IN THE STRUCTURE AND FUNCTION OF SKELETAL MUSCLES , 2007, Clinical and experimental pharmacology & physiology.
[73] Amanda B. Hepler,et al. Genetic relatedness analysis: modern data and new challenges , 2006, Nature Reviews Genetics.
[74] Karl W. Broman,et al. Poor Performance of Bootstrap Confidence Intervals for the Location of a Quantitative Trait Locus , 2006, Genetics.
[75] M. McMullen,et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness , 2006, Nature Genetics.
[76] M. Whitlock. Combining probability from independent tests: the weighted Z‐method is superior to Fisher's approach , 2005, Journal of evolutionary biology.
[77] Bart De Moor,et al. BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis , 2005, Bioinform..
[78] M. Olivier. A haplotype map of the human genome , 2003, Nature.
[79] Feng Li,et al. An Introduction to Metaanalysis , 2005 .
[80] G. F. Wagner,et al. Human stanniocalcin-2 exhibits potent growth-suppressive properties in transgenic mice independently of growth hormone and IGFs. , 2005, American journal of physiology. Endocrinology and metabolism.
[81] Ronenn Roubenoff,et al. The Healthcare Costs of Sarcopenia in the United States , 2004, Journal of the American Geriatrics Society.
[82] Luigi Ferrucci,et al. Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia. , 2003, Journal of applied physiology.
[83] Steven Henikoff,et al. SIFT: predicting amino acid changes that affect protein function , 2003, Nucleic Acids Res..
[84] Hao Wu,et al. R/qtl: QTL Mapping in Experimental Crosses , 2003, Bioinform..
[85] M. Brent,et al. Comparison of mouse and human genomes followed by experimental verification yields an estimated 1,019 additional genes , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[86] J. L. Tomsig,et al. Copines: a ubiquitous family of Ca2+-dependent phospholipid-binding proteins , 2002, Cellular and Molecular Life Sciences CMLS.
[87] S. Heymsfield,et al. Total-body skeletal muscle mass: estimation by a new dual-energy X-ray absorptiometry method. , 2002, The American journal of clinical nutrition.
[88] M. Pfaffl,et al. A new mathematical model for relative quantification in real-time RT-PCR. , 2001, Nucleic acids research.
[89] J. Cheverud,et al. Genetic architecture of adiposity in the cross of LG/J and SM/J inbred mice , 2001, Mammalian Genome.
[90] R. Ross,et al. Skeletal muscle mass and distribution in 468 men and women aged 18-88 yr. , 2000, Journal of applied physiology.
[91] D Siegmund,et al. Statistical methods for mapping quantitative trait loci from a dense set of markers. , 1999, Genetics.
[92] J. Fleg,et al. Muscle quality. I. Age-associated differences between arm and leg muscle groups. , 1999, Journal of applied physiology.
[93] S. Sasaki,et al. Molecular cloning of a second human stanniocalcin homologue (STC2). , 1998, Biochemical and biophysical research communications.
[94] R. Casaburi,et al. Testosterone replacement increases fat-free mass and muscle size in hypogonadal men. , 1997, The Journal of clinical endocrinology and metabolism.
[95] J. Cheverud,et al. Quantitative trait loci for murine growth. , 1996, Genetics.
[96] M. Soller,et al. Advanced intercross lines, an experimental population for fine genetic mapping. , 1995, Genetics.
[97] R. Doerge,et al. Empirical threshold values for quantitative trait mapping. , 1994, Genetics.
[98] J. Tobin,et al. The role of muscle loss in the age-related decline of grip strength: cross-sectional and longitudinal perspectives. , 1990, Journal of gerontology.
[99] J. W. Macarthur. Genetics of Body Size and Related Characters. II. Satellite Characters Associated with Body Size in Mice , 1944, The American Naturalist.
[100] J. W. Macarthur. Genetics of Body Size and Related Characters. I. Selecting Small and Large Races of the Laboratory Mouse , 1944, The American Naturalist.
[101] H. D. Goodale. A STUDY OF THE INHERITANCE OF BODY WEIGHT IN THE ALBINO MOUSE BY SELECTION , 1938 .