Title |
Prevalence of sexual dimorphism in mammalian phenotypic traits
|
---|---|
Published in |
Nature Communications, June 2017
|
DOI | 10.1038/ncomms15475 |
Pubmed ID | |
Authors |
Natasha A. Karp, Jeremy Mason, Arthur L. Beaudet, Yoav Benjamini, Lynette Bower, Robert E. Braun, Steve D.M. Brown, Elissa J. Chesler, Mary E. Dickinson, Ann M. Flenniken, Helmut Fuchs, Martin Hrabe de Angelis, Xiang Gao, Shiying Guo, Simon Greenaway, Ruth Heller, Yann Herault, Monica J. Justice, Natalja Kurbatova, Christopher J. Lelliott, K.C. Kent Lloyd, Ann-Marie Mallon, Judith E. Mank, Hiroshi Masuya, Colin McKerlie, Terrence F. Meehan, Richard F. Mott, Stephen A. Murray, Helen Parkinson, Ramiro Ramirez-Solis, Luis Santos, John R. Seavitt, Damian Smedley, Tania Sorg, Anneliese O. Speak, Karen P. Steel, Karen L. Svenson, Shigeharu Wakana, David West, Sara Wells, Henrik Westerberg, Shay Yaacoby, Jacqueline K. White |
Abstract |
The role of sex in biomedical studies has often been overlooked, despite evidence of sexually dimorphic effects in some biological studies. Here, we used high-throughput phenotype data from 14,250 wildtype and 40,192 mutant mice (representing 2,186 knockout lines), analysed for up to 234 traits, and found a large proportion of mammalian traits both in wildtype and mutants are influenced by sex. This result has implications for interpreting disease phenotypes in animal models and humans. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 16 | 19% |
United Kingdom | 14 | 16% |
Germany | 4 | 5% |
Spain | 4 | 5% |
Canada | 2 | 2% |
France | 2 | 2% |
Australia | 2 | 2% |
Japan | 1 | 1% |
Switzerland | 1 | 1% |
Other | 1 | 1% |
Unknown | 38 | 45% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 52 | 61% |
Scientists | 30 | 35% |
Practitioners (doctors, other healthcare professionals) | 2 | 2% |
Science communicators (journalists, bloggers, editors) | 1 | 1% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
Unknown | 257 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 56 | 22% |
Researcher | 54 | 21% |
Student > Master | 25 | 10% |
Student > Bachelor | 25 | 10% |
Professor | 14 | 5% |
Other | 40 | 16% |
Unknown | 44 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 60 | 23% |
Biochemistry, Genetics and Molecular Biology | 47 | 18% |
Neuroscience | 21 | 8% |
Medicine and Dentistry | 19 | 7% |
Immunology and Microbiology | 12 | 5% |
Other | 43 | 17% |
Unknown | 56 | 22% |