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419 results on '"Mallon, Ann-Marie"'

1. Impact of essential genes on the success of genome editing experiments generating 3313 new genetically engineered mouse lines

Author

Elrick, Hillary, Peterson, Kevin A, Willis, Brandon J, Lanza, Denise G, Acar, Elif F, Ryder, Edward J, Teboul, Lydia, Kasparek, Petr, Birling, Marie-Christine, Adams, David J, Bradley, Allan, Braun, Robert E, Brown, Steve D, Caulder, Adam, Codner, Gemma F, DeMayo, Francesco J, Dickinson, Mary E, Doe, Brendan, Duddy, Graham, Gertsenstein, Marina, Goodwin, Leslie O, Hérault, Yann, Lintott, Lauri G, Lloyd, KC Kent, Lorenzo, Isabel, Mackenzie, Matthew, Mallon, Ann-Marie, McKerlie, Colin, Parkinson, Helen, Ramirez-Solis, Ramiro, Seavitt, John R, Sedlacek, Radislav, Skarnes, William C, Smedley, Damien, Wells, Sara, White, Jacqueline K, Wood, Joshua A, Murray, Stephen A, Heaney, Jason D, and Nutter, Lauryl MJ

Subjects
Biological Sciences, Genetics, Biotechnology, 1.1 Normal biological development and functioning, Animals, Genes, Essential, Mice, Gene Editing, Mice, Knockout, CRISPR-Cas Systems, Alleles, Mice, Inbred C57BL, Male, Female, Genetic Engineering, Phenotype, Cas9, Genome editing, Mouse, Knockout, International Mouse Phenotyping Consortium
Abstract

The International Mouse Phenotyping Consortium (IMPC) systematically produces and phenotypes mouse lines with presumptive null mutations to provide insight into gene function. The IMPC now uses the programmable RNA-guided nuclease Cas9 for its increased capacity and flexibility to efficiently generate null alleles in the C57BL/6N strain. In addition to being a valuable novel and accessible research resource, the production of 3313 knockout mouse lines using comparable protocols provides a rich dataset to analyze experimental and biological variables affecting in vivo gene engineering with Cas9. Mouse line production has two critical steps - generation of founders with the desired allele and germline transmission (GLT) of that allele from founders to offspring. A systematic evaluation of the variables impacting success rates identified gene essentiality as the primary factor influencing successful production of null alleles. Collectively, our findings provide best practice recommendations for using Cas9 to generate alleles in mouse essential genes, many of which are orthologs of genes linked to human disease.

Published
2024

2. Identifying genetic determinants of inflammatory pain in mice using a large-scale gene-targeted screen

Author

Wotton, Janine M, Peterson, Emma, Flenniken, Ann M, Bains, Rasneer S, Veeraragavan, Surabi, Bower, Lynette R, Bubier, Jason A, Parisien, Marc, Bezginov, Alexandr, Haselimashhadi, Hamed, Mason, Jeremy, Moore, Michayla A, Stewart, Michelle E, Clary, Dave A, Delbarre, Daniel J, Anderson, Laura C, D'Souza, Abigail, Goodwin, Leslie O, Harrison, Mark E, Huang, Ziyue, Mckay, Matthew, Qu, Dawei, Santos, Luis, Srinivasan, Subhiksha, Urban, Rachel, Vukobradovic, Igor, Ward, Christopher S, Willett, Amelia M, Consortium, The International Mouse Phenotyping, Braun, Robert E, Brown, Steve DM, Dickinson, Mary E, Heaney, Jason D, Kumar, Vivek, Lloyd, KC Kent, Mallon, Ann-Marie, McKerlie, Colin, Murray, Stephen A, Nutter, Lauryl MJ, Parkinson, Helen, Seavitt, John R, Wells, Sara, Samaco, Rodney C, Chesler, Elissa J, Smedley, Damian, Diatchenko, Luda, Baumbauer, Kyle M, Young, Erin E, Bonin, Robert P, Mandillo, Silvia, and White, Jacqueline K

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Basic Behavioral and Social Science, Genetics, Pain Research, Chronic Pain, Behavioral and Social Science, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Animals, Freund's Adjuvant, Mice, Mice, Knockout, Nociception, Pain, Pain Measurement, Nocifensive behavior, Sensitization, Formalin, Hargreaves, von Frey, Complete Freund's adjuvant, Single-gene knockout mouse, Screen, IMPC, Comorbidity, Autism, International Mouse Phenotyping Consortium, Medical and Health Sciences, Psychology and Cognitive Sciences, Anesthesiology, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

AbstractIdentifying the genetic determinants of pain is a scientific imperative given the magnitude of the global health burden that pain causes. Here, we report a genetic screen for nociception, performed under the auspices of the International Mouse Phenotyping Consortium. A biased set of 110 single-gene knockout mouse strains was screened for 1 or more nociception and hypersensitivity assays, including chemical nociception (formalin) and mechanical and thermal nociception (von Frey filaments and Hargreaves tests, respectively), with or without an inflammatory agent (complete Freund's adjuvant). We identified 13 single-gene knockout strains with altered nocifensive behavior in 1 or more assays. All these novel mouse models are openly available to the scientific community to study gene function. Two of the 13 genes (Gria1 and Htr3a) have been previously reported with nociception-related phenotypes in genetically engineered mouse strains and represent useful benchmarking standards. One of the 13 genes (Cnrip1) is known from human studies to play a role in pain modulation and the knockout mouse reported herein can be used to explore this function further. The remaining 10 genes (Abhd13, Alg6, BC048562, Cgnl1, Cp, Mmp16, Oxa1l, Tecpr2, Trim14, and Trim2) reveal novel pathways involved in nociception and may provide new knowledge to better understand genetic mechanisms of inflammatory pain and to serve as models for therapeutic target validation and drug development.

Published
2022

3. Interoperability of statistical models in pandemic preparedness: principles and reality

Author

Nicholson, George, Blangiardo, Marta, Briers, Mark, Diggle, Peter J., Fjelde, Tor Erlend, Ge, Hong, Goudie, Robert J. B., Jersakova, Radka, King, Ruairidh E., Lehmann, Brieuc C. L., Mallon, Ann-Marie, Padellini, Tullia, Teh, Yee Whye, Holmes, Chris, and Richardson, Sylvia

Subjects
Statistics - Methodology, Statistics - Applications, 62P10
Abstract

We present "interoperability" as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving pandemic response. Interoperability provides an important set of principles for future pandemic preparedness, through the joint design and deployment of adaptable systems of statistical models for disease surveillance using probabilistic reasoning. We illustrate this through case studies for inferring spatial-temporal coronavirus disease 2019 (COVID-19) prevalence and reproduction numbers in England., Comment: 26 pages, 10 figures, for associated mpeg file Movie 1 please see https://www.dropbox.com/s/kn9y1v6zvivfla1/Interoperability_of_models_Movie_1.mp4?dl=0

Published
2021

4. A framework for longitudinal latent factor modelling of treatment response in clinical trials with applications to Psoriatic Arthritis and Rheumatoid Arthritis

Author

Falck, Fabian, Zhu, Xuan, Ghalebikesabi, Sahra, Kormaksson, Matthias, Vandemeulebroecke, Marc, Zhang, Cong, Martin, Ruvie, Gardiner, Stephen, Kwok, Chun Hei, West, Dominique M., Santos, Luis, Tian, Chengeng, Pang, Yu, Readie, Aimee, Ligozio, Gregory, Gandhi, Kunal K., Nichols, Thomas E., Mallon, Ann-Marie, Kelly, Luke, Ohlssen, David, and Nicholson, George

Published
2024
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5. Mendelian gene identification through mouse embryo viability screening

Author

Cacheiro, Pilar, Westerberg, Carl Henrik, Mager, Jesse, Dickinson, Mary E, Nutter, Lauryl MJ, Muñoz-Fuentes, Violeta, Hsu, Chih-Wei, Van den Veyver, Ignatia B, Flenniken, Ann M, McKerlie, Colin, Murray, Stephen A, Teboul, Lydia, Heaney, Jason D, Lloyd, KC Kent, Lanoue, Louise, Braun, Robert E, White, Jacqueline K, Creighton, Amie K, Laurin, Valerie, Guo, Ruolin, Qu, Dawei, Wells, Sara, Cleak, James, Bunton-Stasyshyn, Rosie, Stewart, Michelle, Harrisson, Jackie, Mason, Jeremy, Haseli Mashhadi, Hamed, Parkinson, Helen, Mallon, Ann-Marie, and Smedley, Damian

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Biotechnology, Human Genome, Rare Diseases, Genetics, 2.1 Biological and endogenous factors, Animals, Embryo, Mammalian, Female, Genes, Lethal, Homozygote, Humans, Mice, Mice, Knockout, Phenotype, Pregnancy, International Mouse Phenotyping Consortium, Genomics England Research Consortium, Clinical Sciences
Abstract

BackgroundThe diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property.MethodsHere we further dissected this spectrum by assessing the embryonic stage at which homozygous loss-of-function results in lethality in mice from the International Mouse Phenotyping Consortium, classifying the set of lethal genes into one of three windows of lethality: early, mid, or late gestation lethal. We studied the correlation between these windows of lethality and various gene features including expression across development, paralogy and constraint metrics together with human disease phenotypes. We explored a gene similarity approach for novel gene discovery and investigated unsolved cases from the 100,000 Genomes Project.ResultsWe found that genes in the early gestation lethal category have distinct characteristics and are enriched for genes linked with recessive forms of inherited metabolic disease. We identified several genes sharing multiple features with known biallelic forms of inborn errors of the metabolism and found signs of enrichment of biallelic predicted pathogenic variants among early gestation lethal genes in patients recruited under this disease category. We highlight two novel gene candidates with phenotypic overlap between the patients and the mouse knockouts.ConclusionsInformation on the developmental period at which embryonic lethality occurs in the knockout mouse may be used for novel disease gene discovery that helps to prioritise variants in unsolved rare disease cases.

Published
2022

6. Comprehensive ECG reference intervals in C57BL/6N substrains provide a generalizable guide for cardiac electrophysiology studies in mice

Author

Oestereicher, Manuela A., Wotton, Janine M., Ayabe, Shinya, Bou About, Ghina, Cheng, Tsz Kwan, Choi, Jae-Hoon, Clary, Dave, Dew, Emily M., Elfertak, Lahcen, Guimond, Alain, Haseli Mashhadi, Hamed, Heaney, Jason D., Kelsey, Lois, Keskivali-Bond, Piia, Lopez Gomez, Federico, Marschall, Susan, McFarland, Michael, Meziane , Hamid, Munoz Fuentes, Violeta, Nam , Ki-Hoan, Nichtová, Zuzana, Pimm, Dale, Bower, Lynette, Prochazka, Jan, Rozman, Jan, Santos, Luis, Stewart, Michelle, Tanaka, Nobuhiko, Ward, Christopher S., Willett, Amelia M. E., Wilson, Robert, Braun, Robert E., Dickinson, Mary E., Flenniken, Ann M., Herault, Yann, Lloyd, K. C. Kent, Mallon, Ann-Marie, McKerlie, Colin, Murray, Stephen A., Nutter, Lauryl M. J., Sedlacek, Radislav, Seong, Je Kyung, Sorg, Tania, Tamura, Masaru, Wells, Sara, Schneltzer, Elida, Fuchs, Helmut, Gailus-Durner, Valerie, Hrabe de Angelis, Martin, White, Jacqueline K., and Spielmann, Nadine

Published
2023
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8. A resource of targeted mutant mouse lines for 5,061 genes

Author

Birling, Marie-Christine, Yoshiki, Atsushi, Adams, David J, Ayabe, Shinya, Beaudet, Arthur L, Bottomley, Joanna, Bradley, Allan, Brown, Steve DM, Bürger, Antje, Bushell, Wendy, Chiani, Francesco, Chin, Hsian-Jean Genie, Christou, Skevoulla, Codner, Gemma F, DeMayo, Francesco J, Dickinson, Mary E, Doe, Brendan, Donahue, Leah Rae, Fray, Martin D, Gambadoro, Alessia, Gao, Xiang, Gertsenstein, Marina, Gomez-Segura, Alba, Goodwin, Leslie O, Heaney, Jason D, Hérault, Yann, de Angelis, Martin Hrabe, Jiang, Si-Tse, Justice, Monica J, Kasparek, Petr, King, Ruairidh E, Kühn, Ralf, Lee, Ho, Lee, Young Jae, Liu, Zhiwei, Lloyd, KC Kent, Lorenzo, Isabel, Mallon, Ann-Marie, McKerlie, Colin, Meehan, Terrence F, Fuentes, Violeta Munoz, Newman, Stuart, Nutter, Lauryl MJ, Oh, Goo Taeg, Pavlovic, Guillaume, Ramirez-Solis, Ramiro, Rosen, Barry, Ryder, Edward J, Santos, Luis A, Schick, Joel, Seavitt, John R, Sedlacek, Radislav, Seisenberger, Claudia, Seong, Je Kyung, Skarnes, William C, Sorg, Tania, Steel, Karen P, Tamura, Masaru, Tocchini-Valentini, Glauco P, Wang, Chi-Kuang Leo, Wardle-Jones, Hannah, Wattenhofer-Donzé, Marie, Wells, Sara, Wiles, Michael V, Willis, Brandon J, Wood, Joshua A, Wurst, Wolfgang, Xu, Ying, Teboul, Lydia, and Murray, Stephen A

Subjects
Biological Sciences, Genetics, Infectious Diseases, Biotechnology, 2.1 Biological and endogenous factors, Animals, Gene Deletion, Genetic Association Studies, Genome, Genotype, Information Dissemination, International Cooperation, Internet, Mice, Mice, Knockout, Mouse Embryonic Stem Cells, Mutagenesis, Phenotype, International Mouse Phenotyping Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

The International Mouse Phenotyping Consortium reports the generation of new mouse mutant strains for over 5,000 genes, including 2,850 novel null, 2,987 novel conditional- ready, and 4,433 novel reporter alleles.

Published
2021

9. The Deep Genome Project

Author

Lloyd, KC Kent, Adams, David J, Baynam, Gareth, Beaudet, Arthur L, Bosch, Fatima, Boycott, Kym M, Braun, Robert E, Caulfield, Mark, Cohn, Ronald, Dickinson, Mary E, Dobbie, Michael S, Flenniken, Ann M, Flicek, Paul, Galande, Sanjeev, Gao, Xiang, Grobler, Anne, Heaney, Jason D, Herault, Yann, de Angelis, Martin Hrabě, Lupski, James R, Lyonnet, Stanislas, Mallon, Ann-Marie, Mammano, Fabio, MacRae, Calum A, McInnes, Roderick, McKerlie, Colin, Meehan, Terrence F, Murray, Stephen A, Nutter, Lauryl MJ, Obata, Yuichi, Parkinson, Helen, Pepper, Michael S, Sedlacek, Radislav, Seong, Je Kyung, Shiroishi, Toshihiko, Smedley, Damian, Tocchini-Valentini, Glauco, Valle, David, Wang, Chi-Kuang Leo, Wells, Sara, White, Jacqueline, Wurst, Wolfgang, Xu, Ying, and Brown, Steve DM

Subjects
Animals, Genes, Genome, Humans, Mice, Mutation, Phenotype, Proteins, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Published
2020

10. Soft windowing application to improve analysis of high-throughput phenotyping data

Author

Haselimashhadi, Hamed, Mason, Jeremy C, Munoz-Fuentes, Violeta, López-Gómez, Federico, Babalola, Kolawole, Acar, Elif F, Kumar, Vivek, White, Jacqui, Flenniken, Ann M, King, Ruairidh, Straiton, Ewan, Seavitt, John Richard, Gaspero, Angelina, Garza, Arturo, Christianson, Audrey E, Hsu, Chih-Wei, Reynolds, Corey L, Lanza, Denise G, Lorenzo, Isabel, Green, Jennie R, Gallegos, Juan J, Bohat, Ritu, Samaco, Rodney C, Veeraragavan, Surabi, Kim, Jong Kyoung, Miller, Gregor, Fuchs, Helmult, Garrett, Lillian, Becker, Lore, Kang, Yeon Kyung, Clary, David, Cho, Soo Young, Tamura, Masaru, Tanaka, Nobuhiko, Soo, Kyung Dong, Bezginov, Alexandr, About, Ghina Bou, Champy, Marie-France, Vasseur, Laurent, Leblanc, Sophie, Meziane, Hamid, Selloum, Mohammed, Reilly, Patrick T, Spielmann, Nadine, Maier, Holger, Gailus-Durner, Valerie, Sorg, Tania, Hiroshi, Masuya, Yuichi, Obata, Heaney, Jason D, Dickinson, Mary E, Wolfgang, Wurst, Tocchini-Valentini, Glauco P, Lloyd, Kevin C Kent, McKerlie, Colin, Seong, Je Kyung, Yann, Herault, de Angelis, Martin Hrabé, Brown, Steve DM, Smedley, Damian, Flicek, Paul, Mallon, Ann-Marie, Parkinson, Helen, and Meehan, Terrence F

Subjects
Biological Sciences, Genetics, Animals, Genetic Association Studies, Humans, Mice, Phenotype, Population Health, Software, Mathematical Sciences, Information and Computing Sciences, Bioinformatics, Biological sciences, Information and computing sciences, Mathematical sciences
Abstract

MotivationHigh-throughput phenomic projects generate complex data from small treatment and large control groups that increase the power of the analyses but introduce variation over time. A method is needed to utlize a set of temporally local controls that maximizes analytic power while minimizing noise from unspecified environmental factors.ResultsHere we introduce 'soft windowing', a methodological approach that selects a window of time that includes the most appropriate controls for analysis. Using phenotype data from the International Mouse Phenotyping Consortium (IMPC), adaptive windows were applied such that control data collected proximally to mutants were assigned the maximal weight, while data collected earlier or later had less weight. We applied this method to IMPC data and compared the results with those obtained from a standard non-windowed approach. Validation was performed using a resampling approach in which we demonstrate a 10% reduction of false positives from 2.5 million analyses. We applied the method to our production analysis pipeline that establishes genotype-phenotype associations by comparing mutant versus control data. We report an increase of 30% in significant P-values, as well as linkage to 106 versus 99 disease models via phenotype overlap with the soft-windowed and non-windowed approaches, respectively, from a set of 2082 mutant mouse lines. Our method is generalizable and can benefit large-scale human phenomic projects such as the UK Biobank and the All of Us resources.Availability and implementationThe method is freely available in the R package SmoothWin, available on CRAN http://CRAN.R-project.org/package=SmoothWin.Supplementary informationSupplementary data are available at Bioinformatics online.

Published
2020

11. High-throughput discovery of genetic determinants of circadian misalignment

Author

Zhang, Tao, Xie, Pancheng, Dong, Yingying, Liu, Zhiwei, Zhou, Fei, Pan, Dejing, Huang, Zhengyun, Zhai, Qiaocheng, Gu, Yue, Wu, Qingyu, Tanaka, Nobuhiko, Obata, Yuichi, Bradley, Allan, Lelliott, Christopher J, Nutter, Lauryl MJ, McKerlie, Colin, Flenniken, Ann M, Champy, Marie-France, Sorg, Tania, Herault, Yann, De Angelis, Martin Hrabe, Durner, Valerie Gailus, Mallon, Ann-Marie, Brown, Steve DM, Meehan, Terry, Parkinson, Helen E, Smedley, Damian, Lloyd, KC Kent, Yan, Jun, Gao, Xiang, Seong, Je Kyung, Wang, Chi-Kuang Leo, Sedlacek, Radislav, Liu, Yi, Rozman, Jan, Yang, Ling, and Xu, Ying

Subjects
Biochemistry and Cell Biology, Biological Sciences, Genetics, Neurosciences, Sleep Research, Amino Acid Transport System y+, Animals, Circadian Rhythm, Machine Learning, Male, Mice, Mice, Inbred C57BL, Mutation, Receptors, Oxytocin, Repressor Proteins, Serine Endopeptidases, Telomere-Binding Proteins, Ubiquitin-Protein Ligase Complexes, Sanger Institute Mouse Genetics Project, Developmental Biology
Abstract

Circadian systems provide a fitness advantage to organisms by allowing them to adapt to daily changes of environmental cues, such as light/dark cycles. The molecular mechanism underlying the circadian clock has been well characterized. However, how internal circadian clocks are entrained with regular daily light/dark cycles remains unclear. By collecting and analyzing indirect calorimetry (IC) data from more than 2000 wild-type mice available from the International Mouse Phenotyping Consortium (IMPC), we show that the onset time and peak phase of activity and food intake rhythms are reliable parameters for screening defects of circadian misalignment. We developed a machine learning algorithm to quantify these two parameters in our misalignment screen (SyncScreener) with existing datasets and used it to screen 750 mutant mouse lines from five IMPC phenotyping centres. Mutants of five genes (Slc7a11, Rhbdl1, Spop, Ctc1 and Oxtr) were found to be associated with altered patterns of activity or food intake. By further studying the Slc7a11tm1a/tm1a mice, we confirmed its advanced activity phase phenotype in response to a simulated jetlag and skeleton photoperiod stimuli. Disruption of Slc7a11 affected the intercellular communication in the suprachiasmatic nucleus, suggesting a defect in synchronization of clock neurons. Our study has established a systematic phenotype analysis approach that can be used to uncover the mechanism of circadian entrainment in mice.

Published
2020

12. Human and mouse essentiality screens as a resource for disease gene discovery

Author

Cacheiro, Pilar, Muñoz-Fuentes, Violeta, Murray, Stephen A, Dickinson, Mary E, Bucan, Maja, Nutter, Lauryl MJ, Peterson, Kevin A, Haselimashhadi, Hamed, Flenniken, Ann M, Morgan, Hugh, Westerberg, Henrik, Konopka, Tomasz, Hsu, Chih-Wei, Christiansen, Audrey, Lanza, Denise G, Beaudet, Arthur L, Heaney, Jason D, Fuchs, Helmut, Gailus-Durner, Valerie, Sorg, Tania, Prochazka, Jan, Novosadova, Vendula, Lelliott, Christopher J, Wardle-Jones, Hannah, Wells, Sara, Teboul, Lydia, Cater, Heather, Stewart, Michelle, Hough, Tertius, Wurst, Wolfgang, Sedlacek, Radislav, Adams, David J, Seavitt, John R, Tocchini-Valentini, Glauco, Mammano, Fabio, Braun, Robert E, McKerlie, Colin, Herault, Yann, de Angelis, Martin Hrabě, Mallon, Ann-Marie, Lloyd, KC Kent, Brown, Steve DM, Parkinson, Helen, Meehan, Terrence F, and Smedley, Damian

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Biomedical and Clinical Sciences, Genetics, Biotechnology, Human Genome, Prevention, 2.1 Biological and endogenous factors, Aetiology, Generic health relevance, Good Health and Well Being, Animals, Disease, Genes, Essential, Genetic Association Studies, Genomics, Humans, Mice, Mice, Knockout, Genomics England Research Consortium, International Mouse Phenotyping Consortium
Abstract

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery.

Published
2020

13. Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density

Author

Swan, Anna L, Schütt, Christine, Rozman, Jan, del Mar Muñiz Moreno, Maria, Brandmaier, Stefan, Simon, Michelle, Leuchtenberger, Stefanie, Griffiths, Mark, Brommage, Robert, Keskivali-Bond, Piia, Grallert, Harald, Werner, Thomas, Teperino, Raffaele, Becker, Lore, Miller, Gregor, Moshiri, Ala, Seavitt, John R, Cissell, Derek D, Meehan, Terrence F, Acar, Elif F, Lelliott, Christopher J, Flenniken, Ann M, Champy, Marie-France, Sorg, Tania, Ayadi, Abdel, Braun, Robert E, Cater, Heather, Dickinson, Mary E, Flicek, Paul, Gallegos, Juan, Ghirardello, Elena J, Heaney, Jason D, Jacquot, Sylvie, Lally, Connor, Logan, John G, Teboul, Lydia, Mason, Jeremy, Spielmann, Nadine, McKerlie, Colin, Murray, Stephen A, Nutter, Lauryl MJ, Odfalk, Kristian F, Parkinson, Helen, Prochazka, Jan, Reynolds, Corey L, Selloum, Mohammed, Spoutil, Frantisek, Svenson, Karen L, Vales, Taylor S, Wells, Sara E, White, Jacqueline K, Sedlacek, Radislav, Wurst, Wolfgang, Lloyd, KC Kent, Croucher, Peter I, Fuchs, Helmut, Williams, Graham R, Bassett, JH Duncan, Gailus-Durner, Valerie, Herault, Yann, Mallon, Ann-Marie, Brown, Steve DM, Mayer-Kuckuk, Philipp, and Hrabe de Angelis, Martin

Subjects
Biological Sciences, Genetics, Osteoporosis, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Aetiology, Underpinning research, Musculoskeletal, Animals, Bone Density, Female, Gene Expression Regulation, Gene Ontology, Genetic Pleiotropy, Genome-Wide Association Study, Genotype, Male, Mice, Mice, Transgenic, Mutation, Osteoblasts, Osteoclasts, Phenotype, Promoter Regions, Genetic, Protein Interaction Maps, Sex Characteristics, Transcriptome, IMPC Consortium, Developmental Biology
Abstract

The genetic landscape of diseases associated with changes in bone mineral density (BMD), such as osteoporosis, is only partially understood. Here, we explored data from 3,823 mutant mouse strains for BMD, a measure that is frequently altered in a range of bone pathologies, including osteoporosis. A total of 200 genes were found to significantly affect BMD. This pool of BMD genes comprised 141 genes with previously unknown functions in bone biology and was complementary to pools derived from recent human studies. Nineteen of the 141 genes also caused skeletal abnormalities. Examination of the BMD genes in osteoclasts and osteoblasts underscored BMD pathways, including vesicle transport, in these cells and together with in silico bone turnover studies resulted in the prioritization of candidate genes for further investigation. Overall, the results add novel pathophysiological and molecular insight into bone health and disease.

Published
2020

14. Author Correction: Identification of genes required for eye development by high-throughput screening of mouse knockouts

Author

Moore, Bret A, Leonard, Brian C, Sebbag, Lionel, Edwards, Sydney G, Cooper, Ann, Imai, Denise M, Straiton, Ewan, Santos, Luis, Reilly, Christopher, Griffey, Stephen M, Bower, Lynette, Clary, David, Mason, Jeremy, Roux, Michel J, Meziane, Hamid, Herault, Yann, McKerlie, Colin, Flenniken, Ann M, Nutter, Lauryl MJ, Berberovic, Zorana, Owen, Celeste, Newbigging, Susan, Adissu, Hibret, Eskandarian, Mohammed, Hsu, Chih-Wei, Kalaga, Sowmya, Udensi, Uchechukwu, Asomugha, Chinwe, Bohat, Ritu, Gallegos, Juan J, Seavitt, John R, Heaney, Jason D, Beaudet, Arthur L, Dickinson, Mary E, Justice, Monica J, Philip, Vivek, Kumar, Vivek, Svenson, Karen L, Braun, Robert E, Wells, Sara, Cater, Heather, Stewart, Michelle, Clementson-Mobbs, Sharon, Joynson, Russell, Gao, Xiang, Suzuki, Tomohiro, Wakana, Shigeharu, Smedley, Damian, Seong, JK, Tocchini-Valentini, Glauco, Moore, Mark, Fletcher, Colin, Karp, Natasha, Ramirez-Solis, Ramiro, White, Jacqueline K, de Angelis, Martin Hrabe, Wurst, Wolfgang, Thomasy, Sara M, Flicek, Paul, Parkinson, Helen, Brown, Steve DM, Meehan, Terrence F, Nishina, Patsy M, Murray, Stephen A, Krebs, Mark P, Mallon, Ann-Marie, Kent Lloyd, KC, Murphy, Christopher J, and Moshiri, Ala

Subjects
Biomedical and Clinical Sciences, Genetics, International Mouse Phenotyping Consortium, Biological sciences, Biomedical and clinical sciences
Abstract

[This corrects the article DOI: 10.1038/s42003-018-0226-0.].

Published
2019

15. Erratum: Author Correction: Identification of genes required for eye development by high-throughput screening of mouse knockouts.

Author

Moore, Bret A, Leonard, Brian C, Sebbag, Lionel, Edwards, Sydney G, Cooper, Ann, Imai, Denise M, Straiton, Ewan, Santos, Luis, Reilly, Christopher, Griffey, Stephen M, Bower, Lynette, Clary, David, Mason, Jeremy, Roux, Michel J, Meziane, Hamid, Herault, Yann, International Mouse Phenotyping Consortium, McKerlie, Colin, Flenniken, Ann M, Nutter, Lauryl MJ, Berberovic, Zorana, Owen, Celeste, Newbigging, Susan, Adissu, Hibret, Eskandarian, Mohammed, Hsu, Chih-Wei, Kalaga, Sowmya, Udensi, Uchechukwu, Asomugha, Chinwe, Bohat, Ritu, Gallegos, Juan J, Seavitt, John R, Heaney, Jason D, Beaudet, Arthur L, Dickinson, Mary E, Justice, Monica J, Philip, Vivek, Kumar, Vivek, Svenson, Karen L, Braun, Robert E, Wells, Sara, Cater, Heather, Stewart, Michelle, Clementson-Mobbs, Sharon, Joynson, Russell, Gao, Xiang, Suzuki, Tomohiro, Wakana, Shigeharu, Smedley, Damian, Seong, JK, Tocchini-Valentini, Glauco, Moore, Mark, Fletcher, Colin, Karp, Natasha, Ramirez-Solis, Ramiro, White, Jacqueline K, de Angelis, Martin Hrabe, Wurst, Wolfgang, Thomasy, Sara M, Flicek, Paul, Parkinson, Helen, Brown, Steve DM, Meehan, Terrence F, Nishina, Patsy M, Murray, Stephen A, Krebs, Mark P, Mallon, Ann-Marie, Kent Lloyd, KC, Murphy, Christopher J, and Moshiri, Ala

Subjects
International Mouse Phenotyping Consortium, Genetics
Abstract

[This corrects the article DOI: 10.1038/s42003-018-0226-0.].

Published
2019

18. Extensive identification of genes involved in congenital and structural heart disorders and cardiomyopathy

Author

Spielmann, Nadine, Miller, Gregor, Oprea, Tudor I., Hsu, Chih-Wei, Fobo, Gisela, Frishman, Goar, Montrone, Corinna, Haseli Mashhadi, Hamed, Mason, Jeremy, Munoz Fuentes, Violeta, Leuchtenberger, Stefanie, Ruepp, Andreas, Wagner, Matias, Westphal, Dominik S., Wolf, Cordula, Görlach, Agnes, Sanz-Moreno, Adrián, Cho, Yi-Li, Teperino, Raffaele, Brandmaier, Stefan, Sharma, Sapna, Galter, Isabella Rikarda, Östereicher, Manuela A., Zapf, Lilly, Mayer-Kuckuk, Philipp, Rozman, Jan, Teboul, Lydia, Bunton-Stasyshyn, Rosie K. A., Cater, Heather, Stewart, Michelle, Christou, Skevoulla, Westerberg, Henrik, Willett, Amelia M., Wotton, Janine M., Roper, Willson B., Christiansen, Audrey E., Ward, Christopher S., Heaney, Jason D., Reynolds, Corey L., Prochazka, Jan, Bower, Lynette, Clary, David, Selloum, Mohammed, Bou About, Ghina, Wendling, Olivia, Jacobs, Hugues, Leblanc, Sophie, Meziane, Hamid, Sorg, Tania, Audain, Enrique, Gilly, Arthur, Rayner, Nigel W., Hitz, Marc-Phillip, Zeggini, Eleftheria, Wolf, Eckhard, Sedlacek, Radislav, Murray, Steven A., Svenson, Karen L., Braun, Robert E., White, Jaqueline K., Kelsey, Lois, Gao, Xiang, Shiroishi, Toshihiko, Xu, Ying, Seong, Je Kyung, Mammano, Fabio, Tocchini-Valentini, Glauco P., Beaudet, Arthur L., Meehan, Terrence F., Parkinson, Helen, Smedley, Damian, Mallon, Ann-Marie, Wells, Sara E., Grallert, Harald, Wurst, Wolfgang, Marschall, Susan, Fuchs, Helmut, Brown, Steve D. M., Flenniken, Ann M., Nutter, Lauryl M. J., McKerlie, Colin, Herault, Yann, Lloyd, K. C. Kent, Dickinson, Mary E., Gailus-Durner, Valerie, and Hrabe de Angelis, Martin

Published
2022
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20. The International Mouse Phenotyping Consortium (IMPC): a functional catalogue of the mammalian genome that informs conservation

Author

Muñoz-Fuentes, Violeta, Cacheiro, Pilar, Meehan, Terrence F, Aguilar-Pimentel, Juan Antonio, Brown, Steve DM, Flenniken, Ann M, Flicek, Paul, Galli, Antonella, Mashhadi, Hamed Haseli, Hrabě de Angelis, Martin, Kim, Jong Kyoung, Lloyd, KC Kent, McKerlie, Colin, Morgan, Hugh, Murray, Stephen A, Nutter, Lauryl MJ, Reilly, Patrick T, Seavitt, John R, Seong, Je Kyung, Simon, Michelle, Wardle-Jones, Hannah, Mallon, Ann-Marie, Smedley, Damian, Parkinson, Helen E, and the IMPC consortium

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Generic health relevance, Life on Land, Cheetah, Endangered species, Loss-of-function, Non-model species, Panda, Polar bear, Phenotype, Wolf, Essential genes, IMPC, Knockout, Mouse, IMPC consortium, Environmental Sciences, Evolutionary Biology, Biological sciences, Environmental sciences
Abstract

The International Mouse Phenotyping Consortium (IMPC) is building a catalogue of mammalian gene function by producing and phenotyping a knockout mouse line for every protein-coding gene. To date, the IMPC has generated and characterised 5186 mutant lines. One-third of the lines have been found to be non-viable and over 300 new mouse models of human disease have been identified thus far. While current bioinformatics efforts are focused on translating results to better understand human disease processes, IMPC data also aids understanding genetic function and processes in other species. Here we show, using gorilla genomic data, how genes essential to development in mice can be used to help assess the potentially deleterious impact of gene variants in other species. This type of analyses could be used to select optimal breeders in endangered species to maintain or increase fitness and avoid variants associated to impaired-health phenotypes or loss-of-function mutations in genes of critical importance. We also show, using selected examples from various mammal species, how IMPC data can aid in the identification of candidate genes for studying a condition of interest, deliver information about the mechanisms involved, or support predictions for the function of genes that may play a role in adaptation. With genotyping costs decreasing and the continued improvements of bioinformatics tools, the analyses we demonstrate can be routinely applied.

Published
2018

21. Identification of genetic elements in metabolism by high-throughput mouse phenotyping

Author

Rozman, Jan, Rathkolb, Birgit, Oestereicher, Manuela A, Schütt, Christine, Ravindranath, Aakash Chavan, Leuchtenberger, Stefanie, Sharma, Sapna, Kistler, Martin, Willershäuser, Monja, Brommage, Robert, Meehan, Terrence F, Mason, Jeremy, Haselimashhadi, Hamed, IMPC Consortium, Hough, Tertius, Mallon, Ann-Marie, Wells, Sara, Santos, Luis, Lelliott, Christopher J, White, Jacqueline K, Sorg, Tania, Champy, Marie-France, Bower, Lynette R, Reynolds, Corey L, Flenniken, Ann M, Murray, Stephen A, Nutter, Lauryl MJ, Svenson, Karen L, West, David, Tocchini-Valentini, Glauco P, Beaudet, Arthur L, Bosch, Fatima, Braun, Robert B, Dobbie, Michael S, Gao, Xiang, Herault, Yann, Moshiri, Ala, Moore, Bret A, Kent Lloyd, KC, McKerlie, Colin, Masuya, Hiroshi, Tanaka, Nobuhiko, Flicek, Paul, Parkinson, Helen E, Sedlacek, Radislav, Seong, Je Kyung, Wang, Chi-Kuang Leo, Moore, Mark, Brown, Steve D, Tschöp, Matthias H, Wurst, Wolfgang, Klingenspor, Martin, Wolf, Eckhard, Beckers, Johannes, Machicao, Fausto, Peter, Andreas, Staiger, Harald, Häring, Hans-Ulrich, Grallert, Harald, Campillos, Monica, Maier, Holger, Fuchs, Helmut, Gailus-Durner, Valerie, Werner, Thomas, and Hrabe de Angelis, Martin

Subjects
Biochemistry and Cell Biology, Bioinformatics and Computational Biology, Genetics, Biological Sciences, Human Genome, Nutrition, 2.1 Biological and endogenous factors, Generic health relevance, Animals, Area Under Curve, Basal Metabolism, Blood Glucose, Body Weight, Diabetes Mellitus, Type 2, Gene Regulatory Networks, Genome-Wide Association Study, High-Throughput Screening Assays, Humans, Metabolic Diseases, Mice, Mice, Knockout, Obesity, Oxygen Consumption, Phenotype, Triglycerides, IMPC Consortium
Abstract

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome.

Published
2018

22. Identification of genes required for eye development by high-throughput screening of mouse knockouts

Author

Moore, Bret A, Leonard, Brian C, Sebbag, Lionel, Edwards, Sydney G, Cooper, Ann, Imai, Denise M, Straiton, Ewan, Santos, Luis, Reilly, Christopher, Griffey, Stephen M, Bower, Lynette, Clary, David, Mason, Jeremy, Roux, Michel J, Meziane, Hamid, Herault, Yann, McKerlie, Colin, Flenniken, Ann M, Nutter, Lauryl MJ, Berberovic, Zorana, Owen, Celeste, Newbigging, Susan, Adissu, Hibret, Eskandarian, Mohammed, Hsu, Chih-Wei, Kalaga, Sowmya, Udensi, Uchechukwu, Asomugha, Chinwe, Bohat, Ritu, Gallegos, Juan J, Seavitt, John R, Heaney, Jason D, Beaudet, Arthur L, Dickinson, Mary E, Justice, Monica J, Philip, Vivek, Kumar, Vivek, Svenson, Karen L, Braun, Robert E, Wells, Sara, Cater, Heather, Stewart, Michelle, Clementson-Mobbs, Sharon, Joynson, Russell, Gao, Xiang, Suzuki, Tomohiro, Wakana, Shigeharu, Smedley, Damian, Seong, JK, Tocchini-Valentini, Glauco, Moore, Mark, Fletcher, Colin, Karp, Natasha, Ramirez-Solis, Ramiro, White, Jacqueline K, de Angelis, Martin Hrabe, Wurst, Wolfgang, Thomasy, Sara M, Flicek, Paul, Parkinson, Helen, Brown, Steve DM, Meehan, Terrence F, Nishina, Patsy M, Murray, Stephen A, Krebs, Mark P, Mallon, Ann-Marie, Lloyd, KC Kent, Murphy, Christopher J, and Moshiri, Ala

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Biomedical and Clinical Sciences, Genetics, Ophthalmology and Optometry, Human Genome, Biotechnology, Eye Disease and Disorders of Vision, Aetiology, 2.1 Biological and endogenous factors, Eye, International Mouse Phenotyping Consortium, Biological sciences, Biomedical and clinical sciences
Abstract

Despite advances in next generation sequencing technologies, determining the genetic basis of ocular disease remains a major challenge due to the limited access and prohibitive cost of human forward genetics. Thus, less than 4,000 genes currently have available phenotype information for any organ system. Here we report the ophthalmic findings from the International Mouse Phenotyping Consortium, a large-scale functional genetic screen with the goal of generating and phenotyping a null mutant for every mouse gene. Of 4364 genes evaluated, 347 were identified to influence ocular phenotypes, 75% of which are entirely novel in ocular pathology. This discovery greatly increases the current number of genes known to contribute to ophthalmic disease, and it is likely that many of the genes will subsequently prove to be important in human ocular development and disease.

Published
2018

24. Publisher Correction: Extensive identification of genes involved in congenital and structural heart disorders and cardiomyopathy

Author

Spielmann, Nadine, Miller, Gregor, Oprea, Tudor I., Hsu, Chih-Wei, Fobo, Gisela, Frishman, Goar, Montrone, Corinna, Haseli Mashhadi, Hamed, Mason, Jeremy, Munoz Fuentes, Violeta, Leuchtenberger, Stefanie, Ruepp, Andreas, Wagner, Matias, Westphal, Dominik S., Wolf, Cordula, Görlach, Agnes, Sanz-Moreno, Adrián, Cho, Yi-Li, Teperino, Raffaele, Brandmaier, Stefan, Sharma, Sapna, Galter, Isabella Rikarda, Östereicher, Manuela A., Zapf, Lilly, Mayer-Kuckuk, Philipp, Rozman, Jan, Teboul, Lydia, Bunton-Stasyshyn, Rosie K. A., Cater, Heather, Stewart, Michelle, Christou, Skevoulla, Westerberg, Henrik, Willett, Amelia M., Wotton, Janine M., Roper, Willson B., Christiansen, Audrey E., Ward, Christopher S., Heaney, Jason D., Reynolds, Corey L., Prochazka, Jan, Bower, Lynette, Clary, David, Selloum, Mohammed, Bou About, Ghina, Wendling, Olivia, Jacobs, Hugues, Leblanc, Sophie, Meziane, Hamid, Sorg, Tania, Audain, Enrique, Gilly, Arthur, Rayner, Nigel W., Hitz, Marc-Phillip, Zeggini, Eleftheria, Wolf, Eckhard, Sedlacek, Radislav, Murray, Steven A., Svenson, Karen L., Braun, Robert E., White, Jaqueline K., Kelsey, Lois, Gao, Xiang, Shiroishi, Toshihiko, Xu, Ying, Seong, Je Kyung, Mammano, Fabio, Tocchini-Valentini, Glauco P., Beaudet, Arthur L., Meehan, Terrence F., Parkinson, Helen, Smedley, Damian, Mallon, Ann-Marie, Wells, Sara E., Grallert, Harald, Wurst, Wolfgang, Marschall, Susan, Fuchs, Helmut, Brown, Steve D. M., Flenniken, Ann M., Nutter, Lauryl M. J., McKerlie, Colin, Herault, Yann, Lloyd, K. C. Kent, Dickinson, Mary E., Gailus-Durner, Valerie, and Hrabe de Angelis, Martin

Published
2022
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25. Correction: Corrigendum: High-throughput discovery of novel developmental phenotypes

Author

Dickinson, Mary E, Flenniken, Ann M, Ji, Xiao, Teboul, Lydia, Wong, Michael D, White, Jacqueline K, Meehan, Terrence F, Weninger, Wolfgang J, Westerberg, Henrik, Adissu, Hibret, Baker, Candice N, Bower, Lynette, Brown, James M, Caddle, L Brianna, Chiani, Francesco, Clary, Dave, Cleak, James, Daly, Mark J, Denegre, James M, Doe, Brendan, Dolan, Mary E, Edie Helmut Fuchs, Sarah M, Gailus-Durner, Valerie, Galli, Antonella, Gambadoro, Alessia, Gallegos, Juan, Guo, Shiying, Horner, Neil R, Hsu, Chih-Wei, Johnson, Sara J, Kalaga, Sowmya, Keith, Lance C, Lanoue, Louise, Lawson, Thomas N, Lek, Monkol, Mark, Manuel, Marschall, Susan, Mason, Jeremy, McElwee, Melissa L, Nutter, Susan Newbigging Lauryl MJ, Peterson, Kevin A, Ramirez-Solis, Ramiro, Rowland, Douglas J, Ryder, Edward, Samocha, Kaitlin E, Seavitt, John R, Selloum, Mohammed, Szoke-Kovacs, Zsombor, Tamura, Masaru, Trainor, Amanda G, Tudose, Ilinca, Wakana, Shigeharu, Warren, Jonathan, Wendling, Olivia, West, David B, Wong, Leeyean, Yoshiki, Atsushi, Wurst, Wolfgang, MacArthur, Daniel G, Tocchini-Valentini, Glauco P, Gao, Xiang, Flicek, Paul, Bradley, Allan, Skarnes, William C, Justice, Monica J, Parkinson, Helen E, Moore, Mark, Wells, Sara, Braun, Robert E, Svenson, Karen L, de Angelis, Martin Hrabe, Herault, Yann, Mohun, Tim, Mallon, Ann-Marie, Henkelman, R Mark, Brown, Steve DM, Adams, David J, Lloyd, KC Kent, McKerlie, Colin, Beaudet, Arthur L, and Murray, Maja Bućan Stephen A

Subjects
International Mouse Phenotyping Consortium, General Science & Technology
Abstract

This corrects the article DOI: 10.1038/nature19356.

Published
2017

26. Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium.

Author

Meehan, Terrence F, Conte, Nathalie, West, David B, Jacobsen, Julius O, Mason, Jeremy, Warren, Jonathan, Chen, Chao-Kung, Tudose, Ilinca, Relac, Mike, Matthews, Peter, Karp, Natasha, Santos, Luis, Fiegel, Tanja, Ring, Natalie, Westerberg, Henrik, Greenaway, Simon, Sneddon, Duncan, Morgan, Hugh, Codner, Gemma F, Stewart, Michelle E, Brown, James, Horner, Neil, International Mouse Phenotyping Consortium, Haendel, Melissa, Washington, Nicole, Mungall, Christopher J, Reynolds, Corey L, Gallegos, Juan, Gailus-Durner, Valerie, Sorg, Tania, Pavlovic, Guillaume, Bower, Lynette R, Moore, Mark, Morse, Iva, Gao, Xiang, Tocchini-Valentini, Glauco P, Obata, Yuichi, Cho, Soo Young, Seong, Je Kyung, Seavitt, John, Beaudet, Arthur L, Dickinson, Mary E, Herault, Yann, Wurst, Wolfgang, de Angelis, Martin Hrabe, Lloyd, KC Kent, Flenniken, Ann M, Nutter, Lauryl MJ, Newbigging, Susan, McKerlie, Colin, Justice, Monica J, Murray, Stephen A, Svenson, Karen L, Braun, Robert E, White, Jacqueline K, Bradley, Allan, Flicek, Paul, Wells, Sara, Skarnes, William C, Adams, David J, Parkinson, Helen, Mallon, Ann-Marie, Brown, Steve DM, and Smedley, Damian

Subjects
International Mouse Phenotyping Consortium, Animals, Mice, Knockout, Humans, Mice, Genetic Diseases, Inborn, Disease Models, Animal, Genetic Predisposition to Disease, Phenotype, Female, Male, Gene Knockout Techniques, Knockout, Genetic Diseases, Inborn, Disease Models, Animal, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

Although next-generation sequencing has revolutionized the ability to associate variants with human diseases, diagnostic rates and development of new therapies are still limited by a lack of knowledge of the functions and pathobiological mechanisms of most genes. To address this challenge, the International Mouse Phenotyping Consortium is creating a genome- and phenome-wide catalog of gene function by characterizing new knockout-mouse strains across diverse biological systems through a broad set of standardized phenotyping tests. All mice will be readily available to the biomedical community. Analyzing the first 3,328 genes identified models for 360 diseases, including the first models, to our knowledge, for type C Bernard-Soulier, Bardet-Biedl-5 and Gordon Holmes syndromes. 90% of our phenotype annotations were novel, providing functional evidence for 1,092 genes and candidates in genetically uncharacterized diseases including arrhythmogenic right ventricular dysplasia 3. Finally, we describe our role in variant functional validation with The 100,000 Genomes Project and others.

Published
2017

27. A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction

Author

Bowl, Michael R, Simon, Michelle M, Ingham, Neil J, Greenaway, Simon, Santos, Luis, Cater, Heather, Taylor, Sarah, Mason, Jeremy, Kurbatova, Natalja, Pearson, Selina, Bower, Lynette R, Clary, Dave A, Meziane, Hamid, Reilly, Patrick, Minowa, Osamu, Kelsey, Lois, The International Mouse Phenotyping Consortium, Tocchini-Valentini, Glauco P, Gao, Xiang, Bradley, Allan, Skarnes, William C, Moore, Mark, Beaudet, Arthur L, Justice, Monica J, Seavitt, John, Dickinson, Mary E, Wurst, Wolfgang, de Angelis, Martin Hrabe, Herault, Yann, Wakana, Shigeharu, Nutter, Lauryl MJ, Flenniken, Ann M, McKerlie, Colin, Murray, Stephen A, Svenson, Karen L, Braun, Robert E, West, David B, Lloyd, KC Kent, Adams, David J, White, Jacqui, Karp, Natasha, Flicek, Paul, Smedley, Damian, Meehan, Terrence F, Parkinson, Helen E, Teboul, Lydia M, Wells, Sara, Steel, Karen P, Mallon, Ann-Marie, and Brown, Steve DM

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Allied Health and Rehabilitation Science, Clinical Sciences, Health Sciences, Clinical Research, Hearing Loss, Human Genome, Neurosciences, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Neurological, Ear, Animals, Datasets as Topic, Genetic Testing, Hearing Tests, Mice, Mice, Knockout, Phenotype, Protein Interaction Maps, International Mouse Phenotyping Consortium
Abstract

The developmental and physiological complexity of the auditory system is likely reflected in the underlying set of genes involved in auditory function. In humans, over 150 non-syndromic loci have been identified, and there are more than 400 human genetic syndromes with a hearing loss component. Over 100 non-syndromic hearing loss genes have been identified in mouse and human, but we remain ignorant of the full extent of the genetic landscape involved in auditory dysfunction. As part of the International Mouse Phenotyping Consortium, we undertook a hearing loss screen in a cohort of 3006 mouse knockout strains. In total, we identify 67 candidate hearing loss genes. We detect known hearing loss genes, but the vast majority, 52, of the candidate genes were novel. Our analysis reveals a large and unexplored genetic landscape involved with auditory function.The full extent of the genetic basis for hearing impairment is unknown. Here, as part of the International Mouse Phenotyping Consortium, the authors perform a hearing loss screen in 3006 mouse knockout strains and identify 52 new candidate genes for genetic hearing loss.

Published
2017

28. Prevalence of sexual dimorphism in mammalian phenotypic traits

Author

Karp, Natasha A, Mason, Jeremy, Beaudet, Arthur L, Benjamini, Yoav, Bower, Lynette, Braun, Robert E, Brown, Steve DM, Chesler, Elissa J, Dickinson, Mary E, Flenniken, Ann M, Fuchs, Helmut, Angelis, Martin Hrabe de, Gao, Xiang, Guo, Shiying, Greenaway, Simon, Heller, Ruth, Herault, Yann, Justice, Monica J, Kurbatova, Natalja, Lelliott, Christopher J, Lloyd, KC Kent, Mallon, Ann-Marie, Mank, Judith E, Masuya, Hiroshi, McKerlie, Colin, Meehan, Terrence F, Mott, Richard F, Murray, Stephen A, Parkinson, Helen, Ramirez-Solis, Ramiro, Santos, Luis, Seavitt, John R, Smedley, Damian, Sorg, Tania, Speak, Anneliese O, Steel, Karen P, Svenson, Karen L, Wakana, Shigeharu, West, David, Wells, Sara, Westerberg, Henrik, Yaacoby, Shay, and White, Jacqueline K

Subjects
Biological Psychology, Biological Sciences, Biomedical and Clinical Sciences, Psychology, Genetics, Animals, Body Weight, Female, Genes, Modifier, Genotype, Mammals, Mice, Phenotype, Quantitative Trait, Heritable, Sex Characteristics, International Mouse Phenotyping Consortium
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.

Published
2017

30. High-throughput discovery of novel developmental phenotypes.

Author

Dickinson, Mary E, Flenniken, Ann M, Ji, Xiao, Teboul, Lydia, Wong, Michael D, White, Jacqueline K, Meehan, Terrence F, Weninger, Wolfgang J, Westerberg, Henrik, Adissu, Hibret, Baker, Candice N, Bower, Lynette, Brown, James M, Caddle, L Brianna, Chiani, Francesco, Clary, Dave, Cleak, James, Daly, Mark J, Denegre, James M, Doe, Brendan, Dolan, Mary E, Edie, Sarah M, Fuchs, Helmut, Gailus-Durner, Valerie, Galli, Antonella, Gambadoro, Alessia, Gallegos, Juan, Guo, Shiying, Horner, Neil R, Hsu, Chih-Wei, Johnson, Sara J, Kalaga, Sowmya, Keith, Lance C, Lanoue, Louise, Lawson, Thomas N, Lek, Monkol, Mark, Manuel, Marschall, Susan, Mason, Jeremy, McElwee, Melissa L, Newbigging, Susan, Nutter, Lauryl MJ, Peterson, Kevin A, Ramirez-Solis, Ramiro, Rowland, Douglas J, Ryder, Edward, Samocha, Kaitlin E, Seavitt, John R, Selloum, Mohammed, Szoke-Kovacs, Zsombor, Tamura, Masaru, Trainor, Amanda G, Tudose, Ilinca, Wakana, Shigeharu, Warren, Jonathan, Wendling, Olivia, West, David B, Wong, Leeyean, Yoshiki, Atsushi, International Mouse Phenotyping Consortium, Jackson Laboratory, Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS), Charles River Laboratories, MRC Harwell, Toronto Centre for Phenogenomics, Wellcome Trust Sanger Institute, RIKEN BioResource Center, MacArthur, Daniel G, Tocchini-Valentini, Glauco P, Gao, Xiang, Flicek, Paul, Bradley, Allan, Skarnes, William C, Justice, Monica J, Parkinson, Helen E, Moore, Mark, Wells, Sara, Braun, Robert E, Svenson, Karen L, de Angelis, Martin Hrabe, Herault, Yann, Mohun, Tim, Mallon, Ann-Marie, Henkelman, R Mark, Brown, Steve DM, Adams, David J, Lloyd, KC Kent, McKerlie, Colin, Beaudet, Arthur L, Bućan, Maja, and Murray, Stephen A

Subjects
International Mouse Phenotyping Consortium, Jackson Laboratory, Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris, Charles River Laboratories, MRC Harwell, Toronto Centre for Phenogenomics, Wellcome Trust Sanger Institute, RIKEN BioResource Center, Animals, Mice, Inbred C57BL, Mice, Knockout, Humans, Mice, Disease, Imaging, Three-Dimensional, Conserved Sequence, Sequence Homology, Phenotype, Penetrance, Mutation, Polymorphism, Single Nucleotide, Genes, Essential, Genes, Lethal, Embryo, Mammalian, Genome-Wide Association Study, High-Throughput Screening Assays, Biotechnology, Human Genome, Pediatric, Congenital Structural Anomalies, Genetics, 2.1 Biological and endogenous factors, General Science & Technology
Abstract

Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.

Published
2016

31. Applying the ARRIVE Guidelines to an In Vivo Database.

Author

Karp, Natasha A, Meehan, Terry F, Morgan, Hugh, Mason, Jeremy C, Blake, Andrew, Kurbatova, Natalja, Smedley, Damian, Jacobsen, Julius, Mott, Richard F, Iyer, Vivek, Matthews, Peter, Melvin, David G, Wells, Sara, Flenniken, Ann M, Masuya, Hiroshi, Wakana, Shigeharu, White, Jacqueline K, Lloyd, KC Kent, Reynolds, Corey L, Paylor, Richard, West, David B, Svenson, Karen L, Chesler, Elissa J, de Angelis, Martin Hrabě, Tocchini-Valentini, Glauco P, Sorg, Tania, Herault, Yann, Parkinson, Helen, Mallon, Ann-Marie, and Brown, Steve DM

Subjects
Animals, Mice, Animal Experimentation, Phenotype, Guidelines as Topic, Databases as Topic, Developmental Biology, Biological Sciences, Agricultural and Veterinary Sciences, Medical and Health Sciences
Abstract

The Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines were developed to address the lack of reproducibility in biomedical animal studies and improve the communication of research findings. While intended to guide the preparation of peer-reviewed manuscripts, the principles of transparent reporting are also fundamental for in vivo databases. Here, we describe the benefits and challenges of applying the guidelines for the International Mouse Phenotyping Consortium (IMPC), whose goal is to produce and phenotype 20,000 knockout mouse strains in a reproducible manner across ten research centres. In addition to ensuring the transparency and reproducibility of the IMPC, the solutions to the challenges of applying the ARRIVE guidelines in the context of IMPC will provide a resource to help guide similar initiatives in the future.

Published
2015

32. Advancing data science in drug development through an innovative computational framework for data sharing and statistical analysis

Author

Mallon, Ann-Marie, Häring, Dieter A., Dahlke, Frank, Aarden, Piet, Afyouni, Soroosh, Delbarre, Daniel, El Emam, Khaled, Ganjgahi, Habib, Gardiner, Stephen, Kwok, Chun Hei, West, Dominique M., Straiton, Ewan, Haemmerle, Sibylle, Huffman, Adam, Hofmann, Tom, Kelly, Luke J., Krusche, Peter, Laramee, Marie-Claude, Lheritier, Karine, Ligozio, Greg, Readie, Aimee, Santos, Luis, Nichols, Thomas E., Branson, Janice, and Holmes, Chris

Published
2021
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33. Response to anti-IL17 therapy in inflammatory disease is not strongly impacted by genetic background

Author

Zhang, Cong, primary, Shestopaloff, Konstantin, additional, Hollis, Benjamin, additional, Kwok, Chun Hei, additional, Hon, Claudia, additional, Hartmann, Nicole, additional, Tian, Chengeng, additional, Wozniak, Magdalena, additional, Santos, Luis, additional, West, Dominique, additional, Gardiner, Stephen, additional, Mallon, Ann-Marie, additional, Readie, Aimee, additional, Martin, Ruvie, additional, Nichols, Thomas, additional, Beste, Michael T., additional, Zierer, Jonas, additional, Ferrero, Enrico, additional, Vandemeulebroecke, Marc, additional, and Jostins-Dean, Luke, additional

Published
2023
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37. The Regulatory Factor ZFHX3 Modifies Circadian Function in SCN via an AT Motif-Driven Axis

Author

Parsons, Michael J., Brancaccio, Marco, Sethi, Siddharth, Maywood, Elizabeth S., Satija, Rahul, Edwards, Jessica K., Jagannath, Aarti, Couch, Yvonne, Finelli, Mattéa J., Smyllie, Nicola J., Esapa, Christopher, Butler, Rachel, Barnard, Alun R., Chesham, Johanna E., Saito, Shoko, Joynson, Greg, Wells, Sara, Foster, Russell G., Oliver, Peter L., Simon, Michelle M., Mallon, Ann-Marie, Hastings, Michael H., and Nolan, Patrick M.

Published
2015
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38. Precision medicine: Look to the mice

Author

Lloyd, K. C. Kent, Meehan, Terry, Beaudet, Arthur, Murray, Steve, Svenson, Karen, McKerlie, Colin, West, David, Morse, Iva, Parkinson, Helen, Brown, Steve, Mallon, Ann-Marie, and Moore, Mark

Published
2015

39. The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease

Author

Groza, Tudor, primary, Gomez, Federico Lopez, additional, Mashhadi, Hamed Haseli, additional, Muñoz-Fuentes, Violeta, additional, Gunes, Osman, additional, Wilson, Robert, additional, Cacheiro, Pilar, additional, Frost, Anthony, additional, Keskivali-Bond, Piia, additional, Vardal, Bora, additional, McCoy, Aaron, additional, Cheng, Tsz Kwan, additional, Santos, Luis, additional, Wells, Sara, additional, Smedley, Damian, additional, Mallon, Ann-Marie, additional, and Parkinson, Helen, additional

Published
2022
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42. Interoperability of Statistical Models in Pandemic Preparedness:Principles and Reality

Author

Nicholson, George, Blangiardo, Marta, Briers, Mark, Diggle, Peter J., Fjelde, Tor Erlend, Ge, Hong, Goudie, Robert J. B., Jersakova, Radka, King, Ruairidh E., Lehmann, Brieuc C. L., Mallon, Ann-Marie, Padellini, Tullia, Teh, Yee Whye, Holmes, Chris, Richardson, Sylvia, Nicholson, George, Blangiardo, Marta, Briers, Mark, Diggle, Peter J., Fjelde, Tor Erlend, Ge, Hong, Goudie, Robert J. B., Jersakova, Radka, King, Ruairidh E., Lehmann, Brieuc C. L., Mallon, Ann-Marie, Padellini, Tullia, Teh, Yee Whye, Holmes, Chris, and Richardson, Sylvia

Abstract

We present interoperability as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving pandemic response. Interoperability provides an important set of principles for future pandemic preparedness, through the joint design and deployment of adaptable systems of statistical models for disease surveillance using probabilistic reasoning. We illustrate this through case studies for inferring and characterising spatial-temporal prevalence and reproduction numbers of SARS-CoV-2 infections in England.

Published
2022

43. Time varying association between deprivation, ethnicity and SARS-CoV-2 infections in England:A population-based ecological study

Author

Padellini, Tullia, Jersakova, Radka, Diggle, Peter J, Holmes, Chris, King, Ruairidh E, Lehmann, Brieuc C L, Mallon, Ann-Marie, Nicholson, George, Richardson, Sylvia, Blangiardo, Marta, Padellini, Tullia, Jersakova, Radka, Diggle, Peter J, Holmes, Chris, King, Ruairidh E, Lehmann, Brieuc C L, Mallon, Ann-Marie, Nicholson, George, Richardson, Sylvia, and Blangiardo, Marta

Abstract

Ethnically diverse and socio-economically deprived communities have been differentially affected by the COVID-19 pandemic in the UK. Using a multilevel regression model we assessed the time-varying association between SARS-CoV-2 infections and areal level deprivation and ethnicity from 1st of June 2020 to the 19th of September 2021. We separately considered weekly test positivity rate and estimated debiased prevalence at the Lower Tier Local Authority (LTLA) level, adjusting for confounders and spatio-temporal correlation structure. Comparing the least deprived and predominantly White areas with most deprived and predominantly non-White areas over the whole study period, the weekly positivity rate increases from 2·977% (95% CrI 2.913%-3.029%) to 3·347% (95% CrI 3.300%-3.402%). Similarly, prevalence increases from 0·369% (95% CrI 0.361%-0.375%) to 0·405% (95% CrI 0.399%-0.412%). Deprivation has a stronger effect until October 2020, while the effect of ethnicity becomes more pronounced at the peak of the second wave and then again in May-June 2021. In the second wave of the pandemic, LTLAs with large South Asian populations were the most affected, whereas areas with large Black populations did not show increased values for either outcome during the entire period under analysis. Deprivation and proportion of non-White populations are both associated with an increased COVID-19 burden in terms of disease spread and monitoring, but the strength of association varies over the course of the pandemic and for different ethnic subgroups. The consistency of results across the two outcomes suggests that deprivation and ethnicity have a differential impact on disease exposure or susceptibility rather than testing access and habits.

Published
2022

44. Corrigendum: High-throughput discovery of novel developmental phenotypes

Author

Dickinson, Mary E., Flenniken, Ann M., Ji, Xiao, Teboul, Lydia, Wong, Michael D., White, Jacqueline K., Meehan, Terrence F., Weninger, Wolfgang J., Westerberg, Henrik, Adissu, Hibret, Baker, Candice N., Bower, Lynette, Brown, James M., Caddle, Brianna L., Chiani, Francesco, Clary, Dave, Cleak, James, Daly, Mark J., Denegre, James M., Doe, Brendan, Dolan, Mary E., Helmut Fuchs, Sarah M. Edie, Gailus-Durner, Valerie, Galli, Antonella, Gambadoro, Alessia, Gallegos, Juan, Guo, Shiying, Horner, Neil R., Hsu, Chih-Wei, Johnson, Sara J., Kalaga, Sowmya, Keith, Lance C., Lanoue, Louise, Lawson, Thomas N., Lek, Monkol, Mark, Manuel, Marschall, Susan, Mason, Jeremy, McElwee, Melissa L., Nutter, Susan Newbigging Lauryl M. J., Peterson, Kevin A., Ramirez-Solis, Ramiro, Rowland, Douglas J., Ryder, Edward, Samocha, Kaitlin E., Seavitt, John R., Selloum, Mohammed, Szoke-Kovacs, Zsombor, Tamura, Masaru, Trainor, Amanda G., Tudose, Ilinca, Wakana, Shigeharu, Warren, Jonathan, Wendling, Olivia, West, David B., Wong, Leeyean, Yoshiki, Atsushi, Wurst, Wolfgang, MacArthur, Daniel G., Tocchini-Valentini, Glauco P., Gao, Xiang, Flicek, Paul, Bradley, Allan, Skarnes, William C., Justice, Monica J., Parkinson, Helen E., Moore, Mark, Wells, Sara, Braun, Robert E., Svenson, Karen L., de Angelis, Martin Hrabe, Herault, Yann, Mohun, Tim, Mallon, Ann-Marie, Henkelman, Mark R., Brown, Steve D. M., Adams, David J., Lloyd, Kent K.C., McKerlie, Colin, Beaudet, Arthur L., and Murray, Maja Bućan Stephen A.

Published
2017
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46. A mouse informatics platform for phenotypic and translational discovery

Author

Ring, Natalie, Meehan, Terrence F., Blake, Andrew, Brown, James, Chen, Chao-Kung, Conte, Nathalie, Di Fenza, Armida, Fiegel, Tanja, Horner, Neil, Jacobsen, Julius O. B., Karp, Natasha, Lawson, Thomas, Mason, Jeremy C., Matthews, Peter, Morgan, Hugh, Relac, Mike, Santos, Luis, Smedley, Damian, Sneddon, Duncan, Pengelly, Alice, Tudose, Ilinca, Warren, Jonathan W. G., Westerberg, Henrik, Yaikhom, Gagarine, Parkinson, Helen, and Mallon, Ann-Marie

Published
2015
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47. Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics

Author

Hrabě de Angelis, Martin, Nicholson, George, Selloum, Mohammed, White, Jacqueline K, Morgan, Hugh, Ramirez-Solis, Ramiro, Sorg, Tania, Wells, Sara, Fuchs, Helmut, Fray, Martin, Adams, David J, Adams, Niels C, Adler, Thure, Aguilar-Pimentel, Antonio, Ali-Hadji, Dalila, Amann, Gregory, André, Philippe, Atkins, Sarah, Auburtin, Aurelie, Ayadi, Abdel, Becker, Julien, Becker, Lore, Bedu, Elodie, Bekeredjian, Raffi, Birling, Marie-Christine, Blake, Andrew, Bottomley, Joanna, Bowl, Michael R, Brault, Véronique, Busch, Dirk H, Bussell, James N, Calzada-Wack, Julia, Cater, Heather, Champy, Marie-France, Charles, Philippe, Chevalier, Claire, Chiani, Francesco, Codner, Gemma F, Combe, Roy, Cox, Roger, Dalloneau, Emilie, Dierich, André, Di Fenza, Armida, Doe, Brendan, Duchon, Arnaud, Eickelberg, Oliver, Esapa, Chris T, Fertak, Lahcen El, Feigel, Tanja, Emelyanova, Irina, Estabel, Jeanne, Favor, Jack, Flenniken, Ann, Gambadoro, Alessia, Garrett, Lilian, Gates, Hilary, Gerdin, Anna-Karin, Gkoutos, George, Greenaway, Simon, Glasl, Lisa, Goetz, Patrice, Da Cruz, Isabelle Goncalves, Götz, Alexander, Graw, Jochen, Guimond, Alain, Hans, Wolfgang, Hicks, Geoff, Hölter, Sabine M, Höfler, Heinz, Hancock, John M, Hoehndorf, Robert, Hough, Tertius, Houghton, Richard, Hurt, Anja, Ivandic, Boris, Jacobs, Hughes, Jacquot, Sylvie, Jones, Nora, Karp, Natasha A, Katus, Hugo A, Kitchen, Sharon, Klein-Rodewald, Tanja, Klingenspor, Martin, Klopstock, Thomas, Lalanne, Valerie, Leblanc, Sophie, Lengger, Christoph, le Marchand, Elise, Ludwig, Tonia, Lux, Aline, McKerlie, Colin, Maier, Holger, Mandel, Jean-Louis, Marschall, Susan, Mark, Manuel, Melvin, David G, Meziane, Hamid, Micklich, Kateryna, Mittelhauser, Christophe, Monassier, Laurent, Moulaert, David, Muller, Stéphanie, Naton, Beatrix, Neff, Frauke, Nolan, Patrick M, Nutter, Lauryl M J, Ollert, Markus, Pavlovic, Guillaume, Pellegata, Natalia S, Peter, Emilie, Petit-Demoulière, Benoit, Pickard, Amanda, Podrini, Christine, Potter, Paul, Pouilly, Laurent, Puk, Oliver, Richardson, David, Rousseau, Stephane, Quintanilla-Fend, Leticia, Quwailid, Mohamed M, Racz, Ildiko, Rathkolb, Birgit, Riet, Fabrice, Rossant, Janet, Roux, Michel, Rozman, Jan, Ryder, Edward, Salisbury, Jennifer, Santos, Luis, Schäble, Karl-Heinz, Schiller, Evelyn, Schrewe, Anja, Schulz, Holger, Steinkamp, Ralf, Simon, Michelle, Stewart, Michelle, Stöger, Claudia, Stöger, Tobias, Sun, Minxuan, Sunter, David, Teboul, Lydia, Tilly, Isabelle, Tocchini-Valentini, Glauco P, Tost, Monica, Treise, Irina, Vasseur, Laurent, Velot, Emilie, Vogt-Weisenhorn, Daniela, Wagner, Christelle, Walling, Alison, Wattenhofer-Donze, Marie, Weber, Bruno, Wendling, Olivia, Westerberg, Henrik, Willershäuser, Monja, Wolf, Eckhard, Wolter, Anne, Wood, Joe, Wurst, Wolfgang, Yildirim, Ali Önder, Zeh, Ramona, Zimmer, Andreas, Zimprich, Annemarie, Holmes, Chris, Steel, Karen P, Herault, Yann, Gailus-Durner, Valérie, Mallon, Ann-Marie, and Brown, Steve D M

Published
2015
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48. Interoperability of Statistical Models in Pandemic Preparedness: Principles and Reality

Author

Nicholson, George, primary, Blangiardo, Marta, additional, Briers, Mark, additional, Diggle, Peter J., additional, Fjelde, Tor Erlend, additional, Ge, Hong, additional, Goudie, Robert J. B., additional, Jersakova, Radka, additional, King, Ruairidh E., additional, Lehmann, Brieuc C. L., additional, Mallon, Ann-Marie, additional, Padellini, Tullia, additional, Teh, Yee Whye, additional, Holmes, Chris, additional, and Richardson, Sylvia, additional

Published
2022
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49. Additional file 2 of Mendelian gene identification through mouse embryo viability screening

Author

Cacheiro, Pilar, Westerberg, Carl Henrik, Mager, Jesse, Dickinson, Mary E., Nutter, Lauryl M. J., Muñoz-Fuentes, Violeta, Hsu, Chih-Wei, Van den Veyver, Ignatia B., Flenniken, Ann M., McKerlie, Colin, Murray, Stephen A., Teboul, Lydia, Heaney, Jason D., Lloyd, K. C. Kent, Lanoue, Louise, Braun, Robert E., White, Jacqueline K., Creighton, Amie K., Laurin, Valerie, Guo, Ruolin, Qu, Dawei, Wells, Sara, Cleak, James, Bunton-Stasyshyn, Rosie, Stewart, Michelle, Harrisson, Jackie, Mason, Jeremy, Haseli Mashhadi, Hamed, Parkinson, Helen, Mallon, Ann-Marie, and Smedley, Damian

Abstract

Additional file 2: Fig. S1. WoL and cell essentiality scores. Fig. S2. WoL and cell essentiality categorisation. Fig. S3. WoL and additional gene features. Fig. S4. WoL and paralogues features. Fig. S5. WoL and additional disease features. Fig. S6. Prediction of early lethal genes. Fig. S7. Enrichment analysis of genes sharing attributes with a BIEM gene among the EL category.

Published
2022
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50. Supplementary Material from Modelling the genetic aetiology of complex disease: human���mouse conservation of noncoding features and disease-associated loci

Author

Powell, George, Long, Helen, Zolkiewski, Lousia, Dumbell, Rebecca, Mallon, Ann-Marie, Lindgren, Cecilia M., and Simon, Michelle M.

Abstract

Supplementary PDF containing detailed methodology, supplementary figure 1, and supplementary tables 1 to 8 as referred to in the main manuscript.

Published
2022
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