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Genes essential to life found in mouse mutants are related to many human disease genes

September 16, 2016
Perelman School of Medicine at the University of Pennsylvania
Mutant traits have, for the first time, been identified in the mouse for 52 human disease genes. This significantly contributes to the understanding of the genetic bases for some human diseases.

About one-third of all genes in the mammalian genome are essential for life. An international, multi-institutional research collaboration identified, for the first time, mutant traits in the mouse for 52 human disease genes, which significantly contributes to the understanding of the genetic bases for some human diseases, including cardiovascular defects, spina bifida, and metabolic disorders, among many others. The study was published this week in Nature.

The group's work is part of the International Mouse Phenotyping Consortium (IMPC), which is generating and assessing the physiological characteristics (phenotyping) of mutations for all of the protein-coding genes in the mouse genome. The Consortium aims to discover new functions for the roughly 20,000 genes mice share with humans and makes all of these mouse strains available to provide a platform for better understanding the mechanisms of human disease. The research team includes investigators from the Perelman School of Medicine at the University of Pennsylvania, The Jackson Laboratory, the Baylor College of Medicine, the University of Toronto, and the MRC Harwell Institute, United Kingdom.

The Nature study reports the results of the first 1,700-plus genes characterized by the IMPC, which includes 410 genes, that when mutated on both the maternal and paternal copy, are lethal to the mice and an additional 198 for which fewer than half of the expected number of mutants was identified.

This study is set apart by its use of high-throughput imaging with automated analysis to identify novel features that would have easily been missed using older technology. Employing a new, standardized phenotyping pipeline and mouse strains of a single specific genetic background called C57BL/6N, the researchers established both the time of embryo death and the nature of the lethal phenotypes for these lines, discovering many novel phenotypes that shed light on the function of these genes. Incorporation of the high-resolution, three-dimensional imaging and automated, computational analysis of the images allowed the team to rapidly gather detailed data, enabling the discovery of new phenotypes at an unprecedented scale.

The Penn team contributed to the bioinformatics analysis of essential genes in humans and showed their relevance to human disease. "The sheer amount of new data reported in this paper is impressive," said co-author Maja Bucan, PhD, a professor of Genetics. "For years, a phenotype for just one knockout mouse would form the basis of a single paper, and this paper includes analysis of 410 knockouts. We compared the genes analyzed in this paper with a list of known human disease genes, which made it possible to identify for the first time the mutant phenotypes in the mouse for 52 human disease genes." Mouse knockouts are genetically modified animals in which an existing gene has been inactivated for the purposes of studying the functions of sequenced genes.

"When looking across the seven or eight embryos generated for each of the 410 knockouts, we found variations in phenotype at a surprising frequency," said co-author Steve Murray, PhD, senior research scientist at the Jackson Lab. "We expect diversity when we look across different genetic backgrounds, but this is the first large-scale documentation of mice with the same mutation, and otherwise same genetic makeup, that have different individual phenotypes."

In addition, in collaboration with the Exome Aggregation Consortium, another large, international DNA-sequencing initiative, the IMPC showed that human versions of mouse essential genes are significantly depleted for harmful mutations in humans. "As a result, we surmise that these essential genes are strong candidates for undiagnosed and rare diseases," said co-first author Xiao Ji, a doctoral student in the Bucan lab.

The IMPC calculated that only a small percentage of genes are studied by the broad research community. From this, the systematic approach to phenotyping and unrestricted access to data and mouse models provided by the IMPC promises to fill this large gap in understanding mammalian gene function. All data and images generated by the project are available to researchers, disseminated via an open-source web portal. The mouse models generated are also available to other researchers who may be investigating particular pathways or disease phenotypes.

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Materials provided by Perelman School of Medicine at the University of Pennsylvania. Note: Content may be edited for style and length.

Journal Reference:

  1. Mary E. Dickinson, Ann M. Flenniken, Xiao Ji, Lydia Teboul, Michael D. Wong, Jacqueline K. White, Terrence F. Meehan, Wolfgang J. Weninger, Henrik Westerberg, Hibret Adissu, Candice N. Baker, Lynette Bower, James M. Brown, L. Brianna Caddle, Francesco Chiani, Dave Clary, James Cleak, Mark J. Daly, James M. Denegre, Brendan Doe, Mary E. Dolan, Sarah M. Edie, Helmut Fuchs, Valerie Gailus-Durner, Antonella Galli, Alessia Gambadoro, Juan Gallegos, Shiying Guo, Neil R. Horner, Chih-Wei Hsu, Sara J. Johnson, Sowmya Kalaga, Lance C. Keith, Louise Lanoue, Thomas N. Lawson, Monkol Lek, Manuel Mark, Susan Marschall, Jeremy Mason, Melissa L. McElwee, Susan Newbigging, Lauryl M. J. Nutter, Kevin A. Peterson, Ramiro Ramirez-Solis, Douglas J. Rowland, Edward Ryder, Kaitlin E. Samocha, John R. Seavitt, Mohammed Selloum, Zsombor Szoke-Kovacs, Masaru Tamura, Amanda G. Trainor, Ilinca Tudose, Shigeharu Wakana, Jonathan Warren, Olivia Wendling, David B. West, Leeyean Wong, Atsushi Yoshiki, Matthew McKay, Barbara Urban, Caroline Lund, Erin Froeter, Taylor LaCasse, Adrienne Mehalow, Emily Gordon, Leah Rae Donahue, Robert Taft, Peter Kutney, Stephanie Dion, Leslie Goodwin, Susan Kales, Rachel Urban, Kristina Palmer, Fabien Pertuy, Deborah Bitz, Bruno Weber, Patrice Goetz-Reiner, Hughes Jacobs, Elise Le Marchand, Amal El Amri, Leila El Fertak, Hamid Ennah, Dalila Ali-Hadji, Abdel Ayadi, Marie Wattenhofer-Donze, Sylvie Jacquot, Philippe André, Marie-Christine Birling, Guillaume Pavlovic, Tania Sorg, Iva Morse, Frank Benso, Michelle E. Stewart, Carol Copley, Jackie Harrison, Samantha Joynson, Ruolin Guo, Dawei Qu, Shoshana Spring, Lisa Yu, Jacob Ellegood, Lily Morikawa, Xueyuan Shang, Pat Feugas, Amie Creighton, Patricia Castellanos Penton, Ozge Danisment, Nicola Griggs, Catherine L. Tudor, Angela L. Green, Cecilia Icoresi Mazzeo, Emma Siragher, Charlotte Lillistone, Elizabeth Tuck, Diane Gleeson, Debarati Sethi, Tanya Bayzetinova, Jonathan Burvill, Bishoy Habib, Lauren Weavers, Ryea Maswood, Evelina Miklejewska, Michael Woods, Evelyn Grau, Stuart Newman, Caroline Sinclair, Ellen Brown, Shinya Ayabe, Mizuho Iwama, Ayumi Murakami, Daniel G. MacArthur, Glauco P. Tocchini-Valentini, Xiang Gao, Paul Flicek, Allan Bradley, William C. Skarnes, Monica J. Justice, Helen E. Parkinson, Mark Moore, Sara Wells, Robert E. Braun, Karen L. Svenson, Martin Hrabe de Angelis, Yann Herault, Tim Mohun, Ann-Marie Mallon, R. Mark Henkelman, Steve D. M. Brown, David J. Adams, K. C. Kent Lloyd, Colin McKerlie, Arthur L. Beaudet, Maja Bućan, Stephen A. Murray. High-throughput discovery of novel developmental phenotypes. Nature, 2016; DOI: 10.1038/nature19356

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Perelman School of Medicine at the University of Pennsylvania. "Genes essential to life found in mouse mutants are related to many human disease genes." ScienceDaily. ScienceDaily, 16 September 2016. <>.
Perelman School of Medicine at the University of Pennsylvania. (2016, September 16). Genes essential to life found in mouse mutants are related to many human disease genes. ScienceDaily. Retrieved March 3, 2024 from
Perelman School of Medicine at the University of Pennsylvania. "Genes essential to life found in mouse mutants are related to many human disease genes." ScienceDaily. (accessed March 3, 2024).

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