Knockout Mouse Phenotyping Program (KOMP2) Highlights
The Destiny in our Bones: Density
The NIH Common Fund Knockout Mouse Phenotyping Program (KOMP2) is the flagship partner of the International Mouse Phenotyping Consortium (IMPC) to knockout (remove) and characterize all protein-coding genes in the mouse genome. 
Overall, this project helps scientists explain the genetic basis of many different types of diseases that occur in both mice and humans, including under-studied rare diseases and common chronic conditions. This collaborative effort has been a powerful resource for describing genes with previously unknown function in hearing, vision, and metabolism, for example. Now, KOMP2 researchers gained insights into the genetics of bone diseases and conditions.Osteoporosis is characterized by increased chance of fracturing bones even in the course of normal activity. Bone Mineral Density (BMD) is a measure that is often changed in a range of bone diseases and conditions, including osteoporosis. The genetic factors involved with changes in BMD, such as in osteoporosis, are not well characterized. A comprehensive and large-scale effort from the KOMP2 aims to change that, by identifying new genes involved in bone formation and health.
Phenotyping, or analyzing the characteristics of, the many different knockout mice includes skeletal exams of bone parameters: bone area (BA), bone mineral content (BMC), and the resulting calculated BMD. Using IMPC phenotyping data from 3,823 knockout mice, along with bioinformatics, and an advanced model of bone formation, researchers identified 200 genes which regulate BMD. Of these 200 genes, 141 genes were previously not known to affect BMD. This finding greatly adds to researchers’ understanding of the biology of BMD maintenance and identified novel skeletal candidate genes, including Arl4d, Ncald, and Rab3ip, for further investigation. These newly identified genes may also point to potential targets for treatments of bone disorders in humans, like osteoporosis.
Explore the phenotypic data here.
Reference:
Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density.Swan AL, Schütt C, Rozman J, Del Mar Muñiz Moreno M, Brandmaier S, Simon M, Leuchtenberger S, Griffiths M, Brommage R, Keskivali-Bond P, Grallert H, Werner T, Teperino R, Becker L, Miller G, Moshiri A, Seavitt JR, Cissell DD, Meehan TF, Acar EF, Lelliott CJ, Flenniken AM, Champy MF, Sorg T, Ayadi A, Braun RE, Cater H, Dickinson ME, Flicek P, Gallegos J, Ghirardello EJ, Heaney JD, Jacquot S, Lally C, Logan JG, Teboul L, Mason J, Spielmann N, McKerlie C, Murray SA, Nutter LMJ, Odfalk KF, Parkinson H, Prochazka J, Reynolds CL, Selloum M, Spoutil F, Svenson KL, Vales TS, Wells SE, White JK, Sedlacek R, Wurst W, Lloyd KCK, Croucher PI, Fuchs H, Williams GR, Bassett JHD, Gailus-Durner V, Herault Y, Mallon AM, Brown SDM, Mayer-Kuckuk P, Hrabe de Angelis M; IMPC Consortium. PLoS Genet. 2020 Dec 28;16(12):e1009190. doi: 10.1371/journal.pgen.1009190. PMID: 33370286; PMCID: PMC7822523.
Getting in Sync
Many human health conditions, such as sleep disorders, cardiovascular diseases, metabolic disorders, and even cancers can be the result of problems with circadian rhythm, our natural sleep-wake cycle. The circadian rhythm is one of the best-characterized mechanisms that mediates environmental signals on molecular, physiological and behavioral activities. But the process by which this rhythm gets in sync, or alignment, with regular daily light and dark cycles is not understood. Researchers from the NIH Common Fund Knockout Mouse Phenotyping Program (KOMP2) are now shedding light on how mice align their circadian rhythms to these cycles.
The NIH Common Fund Knockout Mouse Phenotyping Program (KOMP2) is part of the International Mouse Phenotyping Consortium (IMPC). This is a global effort to generate "knockout" mice for every protein coding gene in the mouse genome and then carry out a range of tests to understand each gene’s biological function. Studying the energy use of normal and different knockout mice in a well-controlled light and dark setting has now provided clues to some genetic underpinnings of circadian alignment. By collecting and studying indirect calorimetry (IC) data, a measure of energy use and activity levels, from more than 2000 normal mice, the researchers showed that onset time of peak activity and food intake rhythms are reliable parameters for screening defects of circadian alignment. Using a machine learning approach to look at the vast amount of data collected, they developed an algorithm for recognizing normal circadian parameters in mice. The algorithm was developed and validated and is available to use for future analysis of datasets. They then used this machine learning approach to look at a subset of 750 different knockout mice. They found five genes (Slc7a11, Rhbdl1, Spop, Ctc1 and Oxtr) potentially associated with altered patterns of activity or food intake, giving new insight into genes involved in circadian alignment. Because the IMPC researchers are still generating and phenotyping new knockout mice, this approach lays the foundation for a future larger and more comprehensive study of circadian behavior to uncover even more genes that help control circadian rhythm and its effects on health and disease.
Reference:
Zhang T, Xie P, Dong Y, Liu Z, Zhou F, Pan D, Huang Z, Zhai Q, Gu Y, Wu Q, Tanaka N, Obata Y, Bradley A, Lelliott CJ; Sanger Institute Mouse Genetics Project, Nutter LMJ, McKerlie C, Flenniken AM, Champy MF, Sorg T, Herault Y, Angelis MH, Durner VG, Mallon AM, Brown SDM, Meehan T, Parkinson HE, Smedley D, Lloyd KCK, Yan J, Gao X, Seong JK, Wang CL, Sedlacek R, Liu Y, Rozman J, Yang L, Xu Y. High-throughput discovery of genetic determinants of circadian misalignment. PLoS Genet. 2020 Jan 13;16(1):e1008577. doi: 10.1371/journal.pgen.1008577. PMID: 31929527; PMCID: PMC6980734.
Little Mice, Big Data
Analyzing large amounts of data can be a daunting task in any research field; this includes applying appropriate statistical methods to ensure robust conclusions. 
With many areas of biomedical research now generating massive datasets, there is a growing need for easy to use and freely available statistical tools. Increasingly, researchers are working toward making their research data and analyses follow the “FAIR” principles—findable, accessible, interoperable, and reusable.
The NIH Common Fund Knockout Mouse Phenotyping Program (KOMP2), as part of the International Mouse Phenotyping Consortium (IMPC), is leading the way in understanding different biological processes and diseases, and making their data FAIR. The researchers are part of an ambitious project to genetically silence – or “knockout” – and characterize all genes that code for proteins in the mouse genome. This effort to generate "knockout mice" for every protein-coding gene is the first step before systematically carrying out a range of tests to understand each gene’s biological function, or “phenotype.”
The IMPC has developed a software package called “OpenStats,” specifically designed for the type of high throughput data generated by large research programs like the IMPC. But, it can also be tailored for smaller scale projects. The software package has been tested and implemented by the IMPC, which is increasingly focused on reproducibility, studying both sexes, and using appropriate statistical tools and methodologies. OpenStats builds on the current IMPC statistical computing software called PhenStat . However, when compared to PhenStat, it used far less computing time and obtained consistently similar results. One important way OpenStats contributes to FAIR data is by assessing input data for completeness, redundancy, and other mismatched variables or formatting. It also provides automated ways to consistently label commonly used sex and gender terms as a single term (“sex”) to promote interoperability and reusability of data. Importantly, OpenStats is freely available (www.bioconductor.org/packages/OpenStats), allowing any researcher to reproduce and reuse analyses from others’ research while ensuring their own analysis is FAIR.
Reference:
OpenStats: A robust and scalable software package for reproducible analysis of high-throughput phenotypic data. Haselimashhadi H, Mason JC, Mallon AM, Smedley D, Meehan TF, et al. (2020) PLOS ONE 15(12): e0242933. https://doi.org/10.1371/journal.pone.0242933
Machine Learning May Aid in Understanding Pain
Pain is a complex combination of physical, emotional, and personal experiences. The Common Fund Knockout Mouse Phenotyping Program (KOMP2) is trying to better understand experiences of pain. 
The researchers are part of an ambitious project to genetically silence – or “knockout” – and characterize all genes that code for proteins in the mouse genome. This effort to generate "knockout mice" for every protein-coding gene is the first step before systematically carrying out a range of tests to understand each gene’s biological function, or “phenotype.” As part of a new effort, assays that incorporate machine learning were carried out to uncover genes involved with the experience of pain. Learning more about these genes in mice can be used to better understand how similar genes may cause or contribute to the experience of pain in humans. A better understanding of the underlying biology of pain in humans may lead to new treatments or assessments for pain, and may even help reduce our reliance on opioids.
Currently, it is hard to understand pain in pre-clinical animal model systems, like mice, and available methods often rely on studying a quick response to pain, not behavior over a long period of time. These methods are often lacking in their similarity to the human experience of pain. Because animals, like mice, can’t be asked how they feel, observation of the behavior of individual mice is often required. This approach is time consuming, labor intensive, and requires many mice. To overcome these challenges, KOMP2 researchers developed a machine learning scoring system that combines accuracy, consistency, and ease of use to provide a standard assay to study pain in mice that is also feasible for large-scale genetic studies.
During the validation of the machine learning processes the researchers analyzed 111 short videos, with a wide range of timing relative to pain experience and followed long term behaviors. They capitalized on innovations in machine learning to allow for accurate classification of specific mouse behaviors. They found they were able to easily score over 80 hours of video and find differences between mice in both response time to pain experience and breadth of behaviors. A video-based automated system is readily adoptable by other labs because the experiments are already typically recorded on video. The automated scoring feature adds an important refinement in examining behaviors indicative of pain in mice. It also improves reliability and speed with which the assay can be performed and because videos can capture a lot of behavior in individual mice, the approach can potentially even minimize the number of mice needed for a study.
Reference:
Machine learning-based automated phenotyping of inflammatory nocifensive behavior in mice. Wotton, J. M., Peterson, E., Anderson, L., Murray, S. A., Braun, R. E., Chesler, E. J., White, J. K., & Kumar, V. Molecular pain vol. 16 (2020): 1744806920958596. doi:10.1177/1744806920958596.
Learn more IMPC landing page: https://www.mousephenotype.org/understand/data-collections/pain/
A New Genetic Landscape of the Immune System Defined
The NIH Common Fund Knockout Mouse Phenotyping Program (KOMP2) collaborates with the International Mouse Phenotyping Consortium (IMPC) to knockout (remove) and characterize all protein-coding genes in the mouse genome. Overall, this project helps scientists explain the genetic basis of many different types of diseases that occur in both mice and humans, including under-studied rare diseases and common chronic diseases that affect much of the human population. This collaborative effort has been a powerful resource for describing genes with previously unknown function in hearing, embryonic development, and metabolism, for example. Now, KOMP2 researchers gained new insights on the genetics of the immune system. In addition to a standardized phenotyping of each knockout, or looking at the physical characteristics of the mice, researchers in this study carried out extra tests to more closely investigate the immune system in knockout mice. This included adding specialized tests to look at immune cell activity in the lymphatic system, the organs in the body that control the immune system, as well as testing how exposure to viral, bacterial, and parasite pathogens alters immune responses.
In this study, 25% of the 530 genes studied revealed observable differences in immune cell phenotypes. Furthermore, more than half of the genes with these immune phenotypes had no previous known link to immune system function, indicating important new discovery opportunities made possible by using these approaches. In this analysis, even well-studied genes, for example Bach2, had new phenotypes that may contribute to disease mechanisms. Collectively, these findings illustrate the value of a large-scale immune system screen to identify previously unrecognized components of immune system development and regulation, as well as uncover additional roles for known genes. Importantly, most of the mouse genes identified had a human counterpart gene that was known to be important, but not necessarily recognized to be involved in immune system regulation. This is consistent with the potential that further exploration of the genes identified will have meaningful relevance to human health.
Reference:
High-throughput phenotyping reveals expansive genetic and structural underpinnings of immune variation. Abeler-Dörner L, Laing AG, Lorenc A, Ushakov DS, Clare S, Speak AO, Duque-Correa MA, White JK, Ramirez-Solis R, Saran N, Bull KR. Nat Immunol 21, 86–100 (2020).
Age is Just a Number
The NIH Common Fund Knockout Mouse Phenotyping Program (KOMP2 is leading the way as part of the International Mouse Phenotyping Consortium (IMPC) in understanding the aging process and diseases that occur later in life. The researchers are part of an ambitious project to genetically silence – or “knockout” – and characterize all genes that code for proteins in the mouse. This effort to generate "knockout mice" for every protein-coding gene is the first step before systematically carrying out a range of tests to understand each gene’s biological function, or “phenotype.” As part of the new effort within KOMP2 to understand aging, some knockout mice that appear normal as an adolescent or young adult mice are studied over longer period, to understand disease across the lifespan. The hope is to use mice to provide more insight into human diseases that occur later in life and the human aging process.
The KOMP2 program has made significant advances in understanding genes with previously unknown function in hearing, vision, and metabolism. However, these findings are primarily from mice at adolescent to young adult life stages. Since most human diseases appear later in life, learning more about gene function at later stages is needed to reveal new phenotypes and disease relationships. To do this, the same phenotyping methods used on young mice are then repeated when the mice are older. A “middle-aged adult” mouse is between 16 and 48 weeks of age, and a “late adult” is more than 48 weeks of age (see timeframe here). The testing for the late adult starts when the mice are about a year old (52 weeks). All data for knockout mice collected at these stages so far are now on the program’s data portal. In the portal, it is possible to compare the phenotypes from the same knockout mice throughout different points of the life span. The hope is for researchers throughout the biomedical sciences to use the data to generate new hypotheses about gene function later in life, and how it can give rise to the late-appearing diseases.
Opening a 'soft window' on large datasets
Researchers from the NIH Common Fund Knockout Mouse Phenotyping Program (KOMP2) are generating a massive amount of useful data from thousands of mice. KOMP2 is part of the International Mouse Phenotyping Consortium (IMPC) effort to generate "knockout mice" for every protein coding gene in the mouse genome – which then carries out a range of tests to understand each gene’s biological function.
Experimental data from the knockout mice must be carefully compared to control data from normal mice and then appropriately analyzed to be meaningful. By nature of the high-throughput, large-scale study design, more control data are generated over time than data from each unique knockout group tested. While these ever-growing control data can help make analyses more powerful, they can also add complications because of larger variation over time with “batch” effects. Batch effects are unintended influences of variables like seasons, different personnel performing tests, and different reagent lots that can affect data. To account for this unintended variability, KOMP2 researchers developed a “soft windowing” method designed to select a time window that would include the best control data to use. The approach uses an adaptive window, meaning data from control mice measured most concurrently to the knockouts are given the strongest weight of all the control data, while data collected earlier or later had less weight. When validating their soft windowing approach, KOMP2 researchers found that the rate of false positive discovery went down. A false positive result is one that is unlikely to be biologically meaningful and most likely happened by chance. By lowering this sampling “noise,” the researchers were able to establish more associations between genes and function than with traditional methods and therefore to provide a clearer picture of the biological function of many more genes. The method is freely available in the R package SmoothWin and is intended to be generalizable and benefit large-scale human projects like the UK Biobank and All of Us.
Reference:
Soft Windowing Application to Improve Analysis of High-throughput Phenotyping Data. Haselimashhadi, H., J. C. Mason, V. Munoz-Fuentes, F. Lopez-Gomez, K. Babalola, E. F. Acar, V. Kumar, J. White, A. M. Flenniken, R. King, E. Straiton, J. R. Seavitt, A. Gaspero, A. Garza, A. E. Christianson, C. W. Hsu, C. L. Reynolds, D. G. Lanza, I. Lorenzo, J. R. Green, J. J. Gallegos, R. Bohat, R. C. Samaco, S. Veeraragavan, J. K. Kim, G. Miller, H. Fuchs, L. Garrett, L. Becker, Y. K. Kang, D. Clary, S. Y. Cho, M. Tamura, N. Tanaka, K. D. Soo, A. Bezginov, G. B. About, M. F. Champy, L. Vasseur, S. Leblanc, H. Meziane, M. Selloum, P. T. Reilly, N. Spielmann, H. Maier, V. Gailus-Durner, T. Sorg, M. Hiroshi, O. Yuichi, J. D. Heaney, M. E. Dickinson, W. Wolfgang, G. P. Tocchini-Valentini, K. C. K. Lloyd, C. McKerlie, J. K. Seong, H. Yann, M. H. de Angelis, S. D. M. Brown, D. Smedley, P. Flicek, A. M. Mallon, H. Parkinson and T. F. Meehan 2019 Oct 8;btz744. doi: 10.1093/bioinformatics/btz744. [Epub ahead of print]. PMID: 31591642.
Is this Gene 'Essential'?
Gene “essentiality” is the requirement of a gene for an organism’s survival. Understanding how “essential” a gene is can expand our understanding of diseases and problems related to when something goes wrong with those genes. Researchers from the Common Fund’s Knockout Mouse Phenotyping Program (KOMP2) , part of the International Mouse Phenotyping Consortium (IMPC), developed a new way to determine gene “essentiality.” It is designed to offer researchers, including clinical researchers, an easy-to-use method to assist in human disease gene discovery.
The IMPC is “knocking out” all protein-coding genes in the mouse genome in an attempt to understand their function. As part of this effort, they developed and validated a “Full Spectrum of Intolerance to Loss-of-function” (FUSIL) system. The system categorizes genes based on mouse phenotyping data they are generating combined with human cell data from other research efforts. The resulting system is a “gene essentiality” resource that can be used for both animals and humans. FUSIL consists of five mutually exclusive categories, ranging from those necessary for survival to those where a gene deletion has no noticeable effect. Interestingly, known human disease genes, especially disorders that start early in life, were overrepresented in FUSIL’s “developmental lethal” bin. Taking advantage of this finding, this categorization was applied to datasets from screened developmental disorder cases from three independent disease sequencing studies in humans. The researchers were then able to predict novel candidate genes for some developmental disorders in unsolved clinical cases. Overall, the new FUSIL binning system offers clinical researchers an easy-to-use method when assessing candidate disease genes for patients.
Reference:
Human and mouse essentiality screens as a resource for disease gene discovery . Cacheiro, P., V. Muñoz-Fuentes, S. A. Murray, M. E. Dickinson, M. Bucan, L. M. J. Nutter, K. A. Peterson, H. Haselimashhadi, A. M. Flenniken, H. Morgan, H. Westerberg, T. Konopka, C.-W. Hsu, A. Christiansen, D. G. Lanza, A. L. Beaudet, J. D. Heaney, H. Fuchs, V. Gailus-Durner, T. Sorg, J. Prochazka, V. Novosadova, C. J. Lelliott, H. Wardle-Jones, S. Wells, L. Teboul, H. Cater, M. Stewart, T. Hough, W. Wurst, R. Sedlacek, D. J. Adams, J. R. Seavitt, G. Tocchini-Valentini, F. Mammano, R. E. Braun, C. McKerlie, Y. Herault, M. H. de Angelis, A.-M. Mallon, K. C. K. Lloyd, S. D. M. Brown, H. Parkinson, T. F. Meehan and D. Smedley. Nat Commun 11, 655 (2020).
See Also:
Pinpointing rare disease mutations
Mouse Database Guides New Understanding of Skin and Eye Health in Humans
Researchers mined a publicly available database containing data generated and continuously updated by the International Mouse Phenotyping Consortium (IMPC) to identify mouse genes associated with eye and skin abnormities. The IMPC database is a resource not only for the scientific community, but also for clinicians who may want to find clues from mice on the genetic basis of certain human diseases. Mouse genes often are helpful for identifying and understanding equivalent genes in humans. The NIH Common Fund Knockout Mouse Phenotyping Program (KOMP2) is part of this global effort to develop this database.
There are many skin and eye disorders resulting from the same single gene mutations in both mice and humans. For example, albinism is a disorder affecting both the skin and eyes. While there are some genes linked to some forms of albinism, other cases, such as Oculocutaneous albinism, have no clear genetic cause.
The researchers used the database to search for “knockout” mice with skin, hair, or pigmentation abnormalities. They found 307 different knockout mice with skin abnormalities. Of these, 52 also had eye abnormalities. For 17 of these 52 knockout mice, there was existing literature so the researchers already knew these gene knocks would have eye or skin problems. However, 35 of the 52 knockouts revealed new genes to study with the potential to better understand albinism. These newly identified genes may also point to potential targets for gene or drug therapy in humans.
Reference:
Genome-wide screening of mouse knockouts reveals novel genes required for normal integumentary and oculocutaneous structure and function. Moore, B. A., A. M. Flenniken, D. Clary, A. S. Moshiri, L. M. J. Nutter, Z. Berberovic, C. Owen, S. Newbigging, H. Adissu, M. Eskandarian, C. McKerlie, S. Brown, S. Wells, A.-M. Mallon, A. L. Beaudet, M. H. de Angelis, N. Karp, B. Braun, Y. Herault, X. Gao, Y. Obata, P. Flicek, T. Meehan, H. Parkinson, D. Smedley, J. K. Seong, G. Tocchini-Valentini, F. Mammano, S. M. Thomasy, K. C. K. Lloyd, C. J. Murphy, A. Moshiri and International Mouse Phenotyping Consortium. Scientific Reports. Aug 1, 2019. (1):11211.
See Also:
Knockout Mice Are Guide to New Genes for Eye and Skin Disorders
Image https://www.mousephenotype.org/data/genes/MGI:2137586
Hundreds of New Genes Linked to Blindness and Other Vision Disorders
Researchers from the Knockout Mouse Phenotyping Program (KOMP2) (part of the International Mouse Phenotyping Consortium (IMPC)) have discovered new genes linked to blindness and other vision disorders in mice. Some of these genes may also be important in human eye development and vision, offering hope of increased understanding of vision disorders and ultimately new treatments for individuals with hereditary eye disease.
Understanding the genetic basis of eye diseases is a major challenge. Researchers have studied the histories of families affected by eye disorders and had previously identified numerous genes associated with a wide array of eye disease. However, this type of analysis is limited and slow, as it requires following multiple generations of people over time. Other small-scale studies with laboratory animals only investigate a single gene or handful of genes. These studies are informative, but not comprehensive. The method used by the KOMP2 researchers uses large numbers of "knockout mice" - mice that lack a single specific gene – that are carefully examined for many potential biological effects, including vision impairments. With this high throughput method, large numbers of individual genes can be investigated to establish whether the missing gene is important to eye function.
In this study, the researchers evaluated 4,364 genes. Of these genes, 347 were identified as affecting vision and 75% (261) of genes affecting vision were linked to eye function and pathology for the first time. Overall, the genes and gene families revealed in this study will serve as a powerful resource for geneticists who can now scan whole genome sequencing data for patients whose vision disorders are not linked to any of the previously known genes affecting vision. In the future, these mouse knockout models could also be used to test targeted therapies, including potential medications or even gene therapies.
Reference:
Identification of genes required for eye development by high-throughput screening of mouse knockouts. Moore B., et al. Communications Biology. Dec 21,2018. 1, 236.
Many Newly Discovered Metabolism Genes Found in Mice
Metabolism is the process of turning the food you eat into energy your body can use. Diseases that affect metabolism, including diabetes, are serious health concerns. While lifestyle choices and the environment play a role in how your metabolism operates, how many and which genes are involved in metabolism remain poorly understood. Using high-throughput mouse phenotyping, knockout mice – each lacking both copies of a specific gene – were studied for metabolic dysfunction by researchers from the Knockout Mouse Phenotyping Program (KOMP2), as part of the International Mouse Phenotyping Consortium (IMPC). With this method, they can test a single gene at a time to try to establish whether the missing gene is important to metabolism or other biological processes. Measuring things like blood glucose level, they found that 974 genes, out of 2016 tested, each had strong effects on metabolism. More importantly, almost half of those genes were newly discovered to be involved in metabolism. Furthermore, 51 of those genes had no known function until now.
This information may help researchers understand more about metabolic diseases, like diabetes, and develop better treatments. The genes identified in this study could be used, for example, as biomarkers for early diagnosis or personalized approaches for the treatment of metabolic diseases. Since this investigation only analyzed approximately 10% of all known genes, researchers will continue screening for genes associated with metabolic diseases in the coming years.
Reference:
Mice Knockouts Provide Clues to Bad Breath and Beyond
A new study has helped to uncover a gene involved in serious cases of bad breath. Though halitosis (commonly known as bad breath) is most often caused by bacteria that colonize the mouth, rarer and more serious cases have no known cause. While halitosis can be a social annoyance, rarer forms can be the result of more concerning conditions, like liver cirrhosis. An international collaboration, including UC Davis of the Knockout Mouse Phenotyping Program (KOMP2), studied both mice and humans, revealing that mutations in gene called SELENBP1, encoding a novel human enzyme called methanethiol oxidase, can be the cause of this serious form of bad breath.
Clues from patients indicated that sulfur metabolism genes likely play a role in the development of serious types of bad breath. And many of the patients had mutations in the gene SELENBP1. While this gene has been associated with some cancers, it has no known role in sulfur metabolism. Researchers then edited genes in mice to “knockout” the SELENBP1 gene. And though they didn’t directly smell the breath of the mice, they measured levels of sulfur containing compounds in the blood and urine. They found these levels increased compared to normal mice. They also confirmed biochemically that SELENBP1 does function as a sulfur metabolism enzyme and influences the concentrations of the biologically active molecules known to lead to bad breath. Given SELENBP1 association with cancer, this may also provide cancer researchers with new clues and targets for future study.
Reference:
Mutations in SELENBP1, encoding a novel human methanethiol oxidase, cause extraoral halitosis. Pol, A., Renkema, et al. Nature genetics. 2018 Jan;50(1):120-129.
New Genes to Explore in Fight Against Hearing Loss
More than 360 million people have some form of hearing impairment. We know that half of these cases are due to genetics, but the vast majority of genes responsible for many hearing loss syndromes are unknown. Now, research from the Knockout Mouse Phenotyping Program (KOMP2), part of the International Mouse Phenotyping Consortium (IMPC), shows that many more genes are involved in deafness than previously known. Because mice and humans share most genes, findings from mouse genes may tell us a lot about human hearing loss. Researchers tested over 3006 genetically modified mutant mice for hearing problems, exploring nearly 15% of the mouse genome. Hearing thresholds of the mice were measured with rising volumes of sound at different frequencies. While the study detected many genes already known to be involved in hearing loss, 52 of the genes were newly associated with hearing loss. These genes coded for many different types of proteins, from structural proteins to transcription factors, reflecting the complexity of the auditory system. Also, 41 of the 52 these genes were not even part of previously known networks of genes affecting hearing – highlighting potentially unexplored pathways of hearing loss. This information provides a large and unexplored genetic landscape that may help researchers understand more about hearing loss and develop better treatments.
Reference:
A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction. Bowl MR, Simon MM, Ingham NJ, Greenaway S, Santos L, Cater H, Taylor S, Mason J, Kurbatova N, Pearson S, Bower LR, Clary DA, Meziane H, Reilly P, Minowa O, Kelsey L, Tocchini-Valentini GP, Gao X, Bradley A, Skarnes WC, Moore M, Beaudet AL, Justice MJ, Seavitt J, Dickinson ME, Wurst W, de Angelis MH, Herault Y, Wakana S, Nutter LMJ, Flenniken AM, McKerlie C, Murray SA, Svenson KL, Braun RE, West DB, Lloyd KCK, Adams DJ, White J, Karp N, Flicek P, Smedley D, Meehan TF, Parkinson HE, Teboul LM, Wells S, Steel KP, Mallon AM, Brown SDM. Nature Communications. 2017 Oct 12;8 (886).
Mouse Study Reveals Important Differences Between Males and Females
Historically, most researchers didn’t often study both sexes in their experiments, they assumed that results from male animals would be the same as female animals. However, we now know that sex influences the frequency, progression, and severity of the majority of common diseases and disorders, including cardiovascular and autoimmune diseases. Because of this, the NIH has mandated exploring sex as a biological variable, meaning researchers must consider sex as a biological variable in the design and analysis of their animal studies.
As part of the International Mouse Phenotyping Consortium (IMPC), Knockout Mouse Phenotyping Program (KOMP2) researchers supported by the Common Fund have explored how physical characteristics, vary by sex in normal and genetically modified mice. In the largest study of its kind, they analyzed 234 different physical characteristics in more than 50,000 mice. They found that the sex of the mice influenced many traits. For example, after accounting for weight, a known sexually dimorphic variable, 9.9% of categorical traits (things that can be put into categories, such as glucose tolerance) exhibited sexual dimorphism in normal mice. For continuous traits (things that can be measured on a scale, such as cholesterol levels), a far higher proportion exhibited sexual dimorphism at 56.6%. While some traits were expected to show differences in males and females, such as glucose levels and cardiac phenotypes, others were surprising and could not have been predicted. For example, vision abnormalities from the cornea were surprisingly found more often in female mice than males.
Not only did they study normal mice, but they also measured sexual dimorphism in many different genetically modified mice. To do this, they ”knocked out” different genes and measured whether any differences in the resulting physical traits depended on the sex. Unsurprisingly, some mutations only had effects in female mice, or vice versa. For example, only males and not females with the Usp47 gene knocked out, had high cholesterol levels, which would be important to consider in studies of heart disease or other diseases in which cholesterol is involved. The results have implications for the design of future animal studies which underpin research into treatments for human diseases. This study is a major step in highlighting the impact of sex differences in biomedicine and will help in accounting for those differences in the future biomedical studies.
Reference:
Prevalence of sexual dimorphism in mammalian phenotypic traits. Karp NA, Mason J, Beaudet AL, Benjamini Y, Bower L, Braun R E, Brown S DM, Chesler EJ, Dickinson ME, Flenniken AM, Fuchs H, de Angelis MH, Gao X, Guo S, Greenaway S, Heller R, Herault Y, Justice MJ, Kurbatova N, Lelliott CJ, Lloyd KC, Mallon A, Mank JE, Masuya H, McKerlie, TF Meehan, RF Mott, SA Murray, H Parkinson, R Ramirez-Solis, Santos, JR Seavitt, D Smedley C, Sorg T, Speak A O, Steel KP, Svenson L, The International Mouse Phenotyping Consortium, Wakana S, West D, Wells S, Westerberg H, Yaacoby S, White JK . Nature Communications. 2017 June 26;8 (15475).
Researchers Use KOMP2 Mice to Learn About Genes That Help Repair Heart Tissue
The mammalian heart has the capacity to “self-renew,” or repair itself, only in very early life. Understanding more about the genes and mechanisms involved in heart repair during early life may provide clues into possible therapeutic approaches to reactivating this capacity in the adult heart. In a recent publication, Dr. James Martin and colleagues use mice generated from the Knockout Mouse Phenotyping Program (KOMP2) to study heart damage and repair. They identified a mechanism that promotes heart repair early in development through control of a gene called Pitx2. When the Pitx2 gene is activated, or “turned on,” it causes a cascade of other genes to also be activated, which limits damage and helps promote repair to the heart after an event like a heart attack. Ultimately, these researchers were able to increase expression of and activate Pitx2 in adult mice and promote some repair of heart tissue damage. These findings suggest possible mechanisms and genes to target when designing therapies to repair damaged heart tissue in humans.
Reference:
Pitx2 promotes heart repair by activating the antioxidant response after cardiac injury. Tao G, Kahr PC, Morikawa Y, Zhang M, Rahmani M, Heallen TR, Li L, Sun Z, Olson EN, Amendt BA, Martin JF. Nature. 2016 May 25;534(7605):119-23.
Illuminating Essential Gene Function in Mice
Drs. Mary Dickinson and Steve Murray and collaborators, as part of the Common Fund’s Knockout Mouse Phenotyping Program (KOMP2) and International Mouse Phenotyping Consortium (IMPC), have been using mouse models to study essential genes, or genes that are necessary for survival. In the absence of these genes, mice die as embryos, bringing up unique challenges for their analysis. However, this embryonic death also provides evidence for the critical role these essential genes play in normal growth and development in both mice and potentially humans. As part of the overall KOMP2/IMPC effort, researchers developed a strategy to more carefully study the function of these essential genes. In their strategy, they identify and describe the exact time of mouse lethality, assign phenotypes, and use a “reporter gene” to mimic the normal expression of the gene of interest in order to describe the function of these genes. This paper, High-throughput discovery of novel developmental phenotypes, is the first international, systematic effort to comprehensively characterize the functions of these genes in mice. This effort also includes 3D high-resolution imaging of embryos that are accessible on the IMPC portal. This imaging includes use of new and high level imaging that provides a level of detail not seen until now. For example, not much is currently known about disease associations with the gene Chtop. However, imaging of Chtop knockout embryos indicate abnormal eye development and neural tube defects, suggesting critical roles for this gene in normal eye and neural tube development. These results open a new line of research for scientists interested in studying development and diseases of the eye and nervous system. These new embryonic data add to the growing understanding of genetic mechanisms required for normal embryonic growth and development, while also providing insight into human developmental disorders and gene discovery for non-lethal conditions. As part of the full IMPC data, these data are contributing to this active and growing IMPC resource that will benefit the scientific community for years to come. Data are provided in real time to the entire research community, creating an “open access” environment allowing investigators to rapidly use the data to help their own research.
More information about the mice phenotyped through IMPC here.
Reference:
High-throughput discovery of novel developmental phenotypes. Dickinson ME, Ann M, Flenniken AM, Ji ,et al. Nature. 2016 Sep 14;537(7621):508-514.
IMPC Leads Coordinated Effort to Characterize Every Gene in the Mouse Genome
The International Mouse Phenotyping Consortium (IMPC) was featured in Biocentury Innovations. The article highlighted its history, organization, and exciting progress made to date. The IMPC is a confederation of international mouse phenotyping projects, including the NIH Common Fund’s Knockout Mouse Phenotyping Program (KOMP2). The goal of the IMPC is to generate knockout lines for the 21,000 known and predicted mouse genes, to ascribe functions to as many of those genes as possible through systematic phenotyping, and to distribute the data freely to the scientific community. Once complete, this will be a critical resource to researchers studying mice as model organisms and will help ascribe functions to related human genes that are currently uncharacterized. This report highlights some of the major advantages of broad-based, systemic phenotyping, including standardization of phenotyping assays and the ability to detect phenotypes in a variety of tissues for the same gene. The work of the IMPC may also inform large scale efforts to generate, coordinate, and analyze human data, such as the Precision Medicine Initiative.
More information about the mice phenotyped through IMPC here.
Reference:
Knocks Heard ‘Round The World. Tkach, K. Biocentury Innovations. 2015 September 24.
New Statistical Tools for Standardizing High Throughput Analysis in Mouse Phenotyping
Analyzing large amounts of data can be a daunting task in any research field; this also includes applying appropriate statistical analyses to ensure the most robust conclusions can be drawn. With many areas of research now generating massive data sets, there is a growing need for accessible and freely available statistical tools. One tool recently developed by Kurbatova et al., PhenStat, is a software statistical software package designed specifically for phenotyping data. The software uses the freely available R package to provide a variety of statistical methods for the identification of phenotypic associations. R is a widely available platform commonly used in bioinformatics.
The PhenStat software itself is specifically designed for the type of high throughput data generated by large research programs, but is also suitable for small and large scale users. The software package has been tested and implemented by the KOMP2 program as part of the International Mouse Phenotyping Consortium (IMPC), which aims to produce knockout mice and carry out high-throughput phenotyping of each line in order to determine the function of every gene in the mouse genome. The consortium and its researchers are increasingly focused on reproducibility, studying both sexes, and using appropriate statistical tools and methodologies. This software aims to provide the best tools to assist in these important efforts by helping researchers produce the most robust analysis. With appropriate and well documented analysis, an increase in reproducibility of results by other parties can be enhanced, which is important for all research, but particularly for in-vivo studies where limiting expensive, redundant, and unnecessary experimentation is essential.
Reference:
PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data. Kurbatova, N., Mason, J. C., Morgan, H., Meehan, T. F., & Karp, N. A. PloS one. 2014 Jul 6;.10(7), e0131274-e0131274.
NIH-Funded KOMP2 Program Leads the Way in Efforts to Ensure Reproducibility and Enhance Transparency in Research
Researchers funded by the National Institutes of Health’s Common Fund Knockout Mouse Phenotyping Program (KOMP2) are making efforts to improve methods of data collection and reporting in animal research, with the goals of making these processes more accessible and research findings more reproducible. The KOMP2 program, a part of the International Mouse Phenotyping Consortium (IMPC), aims to extensively test and generate data about mice with disrupted, or “knocked out,” genes to help better understand human biology and disease. KOMP2 researchers are examining the clinical and physical characteristics – phenotypes – of mice carrying mutations in approximately 20,000 specific genes across the genome. They hope to systematically describe each gene and its biological function.
In 2010, the United Kingdom National Centre for the Replacement, Refinement, and Reduction of Animals in Research (3R) introduced the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines 
. These guidelines were designed to address an emerging problem in biomedical animal studies -- a lack of reproducibility of research results -- and improve the overall communication of research findings. The ARRIVE guidelines consist of a checklist to be used when submitting manuscripts that include animal research. They lay out reporting requirements to ensure all the information is available to allow fully reproducible research.
To enhance and embrace reproducibility in the IMPC large-scale research data collection and analyses efforts, KOMP2-funded investigators modified the ARRIVE guidelines to apply them to the large international database housing all the program data . The investigators described the process and challenges of applying the guidelines to the IMPC database May 20, 2015, in PLoS Biology. Their efforts assessed and documented how each of the IMPC centers carried out experimental procedures; details on how the data were obtained are available for download from the IMPC web portal. Investigators also developed a new and standardized language for the IMPC consortium, allowing all phenotypic data to be described in the same way and compared across research sites.
Reference:
Applying the ARRIVE Guidelines to an In Vivo Database. Karp N, Meehan T, Morgan H, Mason J, Blake A, Kurbatova N, Smedley D, Jacobsen J, Mott R, Iyer V, Matthews P, Melvin D, Wells S, Flenniken A, Masuya H, Wakana S, White J, Lloyd KC, Reynolds C, Paylor R, West D, Svenson K, Chesler E, de Angelis M, Tocchini-Valentini G, Sorg T, Herault Y, Parkinson H, Mallon A, Brown S. PLOS Biology. 2015 May 20.
A Comprehensive New Atlas for Knockout Mice Phenotypes
Researchers from the International Mouse Phenotyping Consortium (IPMC), an international effort that includes NIH funded researchers from the Common Fund Knockout Mouse Phenotyping Program (KOMP2) have developed an atlas detailing gene expression patterns in 313 different mutant mouse lines. The Consortium as a whole is currently on track to develop 8,500 mutant mice and this manuscript represents one of the first comprehensive glimpses at early expression data coming from this group of investigators. Researchers generated the mutant mouse lines using embryonic stem cells (ESCs) in which the gene of interested is replaced with a so called “reporter gene” in such a way that the reporter mimics the normal expression of the gene of interest. A simple chemical reaction on the samples results in a blue stain where the gene is expressed. This well-known LacZ reporter system can then be used to compare various staining patterns in the mice. These staining strategies were carried out in both whole mount and on frozen sections of male and female mice and embryos. The robustness and repeatability of the lacZ staining in both 3D and in sections confirmed the feasibility of using this reporter to reveal the expression of many poorly annotated genes. The generated atlas includes information on the location and possible function of many genes that currently have unknown functions.
In this study, many large organs, such as the brain, were described in remarkable detail providing new and highly specialized information on the localization patterns of gene expression for many genes. Many organs also had complex and unique staining patterns, for example, not only was a large percentage of all reporter gene expression found in the testis, but 8% of all reporter expression was found restricted exclusively in the testis. One gene with unique expression in the testis was Jazf, which has been previously implicated in endometrial cancer, but has yet to have any known role in testicular function. Overall, the atlas provides an exceptional and comprehensive resource describing the anatomical location of gene expression in mice and provides insight into unique and unknown functions that can be targeted for further study. The full resource, to be completed by the IMPC, will provide even deeper levels of detail and data for the 8,500 knockout mouse lines that will complement this effort and give insight into the roles of thousands of genes in embryonic development, adult physiology, aging, and disease.
Reference:
A lacZ reporter gene expression atlas for 313 adult KOMP mutant mouse lines. West, D. B., R. K. Pasumarthi, B. Baridon, E. Djan, A. Trainor, S. M. Griffey, E. K. Engelhard, J. Rapp, B. Li, P. J. Jong and K. C. Lloyd. Genome Res. 2015;25(4): 598-607. PMID: 25591789.
Applying a New Method to Generate Knockout Mice
Research supported by the Common Fund’s Knockout Mouse Phenotyping Program (KOMP2) has applied a 
new way to generate conditional knockout mice, which are mice with a gene that can be selectively eliminated in specific cells or tissues at a specific point in time. Led by Dr. K.C. Kent Lloyd, researchers at the University of California Davis modified a technology known as CRISPR, or Clustered Regularly Interspaced Short Palindromic Repeat, that uses components of a bacterial immune system to precisely target genes for deletion (for more information on CRISPR, see this New York Times article). In this new study, scientists modified the CRISPR system to enhance the specificity of gene targeting while also introducing genetic changes that allow the target gene to be conditionally deleted (or “knocked out”), rather than knocked out in all cells from the beginning of development. Researchers used the new technique to generate a conditional knockout of the Isoprenoid synthase containing domain (Ispd) gene. Mutations in the human ISPD gene are associated with the neurodevelopmental disorder Walker-Warburg syndrome, a severe form of congenital muscular dystrophy affecting the muscles, brain, and eyes, that typically results in death by 3 years of age. Ispd knockout mice die at birth, limiting their effectiveness in scientific research. The conditional Ispd knockout mice may allow scientists to distinguish the effects of Ispd deletion in disease-relevant tissues at different stages of development. Beyond this important gene, however, the new technique may allow easier, faster, and more efficient generation of conditional knockout mice for many genes, both within the KOMP2 project and in labs across the world.
Reference:
Conditional targeting of Ispd using paired Cas9 nickase and a single DNA template in mice. FEBS Open Biology. Lee, AY and Lloyd, KC. July 2014; 4: 637-42. PMID: 25161872.
“Perfect Host” Developed!
Investigators at The Jackson Laboratory have developed a novel approach that enables highly efficient generation of mouse strains from Embryonic Stem (ES) cells. This advance overcomes a major limitation in mutant mouse production; namely, the uncertainty of whether the desired mutation created in ES cells is incorporated into the mouse’s reproductive cells so that it is passed along to offspring. This process has been slow, laborious, and expensive. The Perfect Host technology ensures that chimeras made by injecting ES cells into host embryos have gametes derived only from the ES cells carrying the desired mutation. Thus all offspring are paternally derived from the ES cells and will carry the mutation. This research was made possible through support from The Jackson Laboratory, the Maine Technology Institute, in addition to several NIH Institutes and Centers, including KOMP and the use of KOMP-generated ESC cell lines. This new technology will be extremely useful for the KOMP2 program, by reducing the number of mice needed for each experiment, and greatly increasing the speed and efficiency of mouse production.
Interview with KOMP2 awardee Dr. Monica Justice
Read an interview with KOMP2 awardee Dr. Monica Justice from Baylor College of Medicine, in which she discusses her career path, current work in hematopoietic cancers and genetic syndromes, and future goals for the KOMP2 project. Find out how her early years on the farm inspired a love of biology, what experiences sparked her interest in pediatric medicine, and how she enjoys spending time outside of the lab.
Read Of Mice and Men, and Medicine: an interview with Monica Justice.
Funding Opportunity Announcement to phenotype embryonic lethal knockout mice from the International Mouse Phenotyping Consortium (IMPC)!
The IMPC, a worldwide consortium that includes KOMP2 as a member, is generating an estimated 20,000 knockout mouse strains, up to 30% of which are expected to be embryonic or perinatal lethal. This funding opportunity announcement invites applications to phenotype embryonic lethal mouse strains with a long term goal of revealing important insights into normal development in addition to a variety of diseases. This funding opportunity is supported by several NIH Institutes and Centers, and is related to, but separate from, the Common Fund’s KOMP2 program.
Read the Funding Opportunity here.
Updates from KOMP2
See what KOMP2 has been doing lately! Download slides about KOMP2 history, current status, and future directions here.
KOMP2 Program Makes First Awards
Seven new projects receive NIH Common Fund support in fiscal year 2011 via the KOMP2 program. The program is creating a valuable genetic resource for revealing mammalian gene function, providing insight into genes that affect human health and disease.
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International Mouse Phenotyping Consortium (IMPC) Policies
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This page last reviewed on May 11, 2021