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1. Whole genome analysis for 163 gRNAs in Cas9-edited mice reveals minimal off-target activity

Author

Peterson, Kevin A, Khalouei, Sam, Hanafi, Nour, Wood, Joshua A, Lanza, Denise G, Lintott, Lauri G, Willis, Brandon J, Seavitt, John R, Braun, Robert E, Dickinson, Mary E, White, Jacqueline K, Lloyd, KC Kent, Heaney, Jason D, Murray, Stephen A, Ramani, Arun, and Nutter, Lauryl MJ

Subjects
Gene Editing, Mice, Genome, Mutagenesis, Mutation, Human Genome, Genetics, Animals, 2.1 Biological and endogenous factors, CRISPR-Cas Systems, Aetiology, Biotechnology
Abstract

Genome editing with CRISPR-associated (Cas) proteins holds exceptional promise for "correcting" variants causing genetic disease. To realize this promise, off-target genomic changes cannot occur during the editing process. Here, we use whole genome sequencing to compare the genomes of 50 Cas9-edited founder mice to 28 untreated control mice to assess the occurrence of S. pyogenes Cas9-induced off-target mutagenesis. Computational analysis of whole-genome sequencing data detects 26 unique sequence variants at 23 predicted off-target sites for 18/163 guides used. While computationally detected variants are identified in 30% (15/50) of Cas9 gene-edited founder animals, only 38% (10/26) of the variants in 8/15 founders validate by Sanger sequencing. In vitro assays for Cas9 off-target activity identify only two unpredicted off-target sites present in genome sequencing data. In total, only 4.9% (8/163) of guides tested have detectable off-target activity, a rate of 0.2 Cas9 off-target mutations per founder analyzed. In comparison, we observe ~1,100 unique variants in each mouse regardless of genome exposure to Cas9 indicating off-target variants comprise a small fraction of genetic heterogeneity in Cas9-edited mice. These findings will inform future design and use of Cas9-edited animal models as well as provide context for evaluating off-target potential in genetically diverse patient populations.

Published
2023

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

Author

Cacheiro, Pilar, Muñoz-Fuentes, Violeta, Westerberg, Henrik, Scott, R. H., Siddiq, A., Sieghart, A., Smith, K. R., Sosinsky, A., Spooner, W., Stevens, H. E., Stuckey, A., Sultana, R., Thomas, E. R. A., Konopka, Tomasz, Thompson, S. R., Tregidgo, C., Tucci, A., Walsh, E., Watters, S. A., Welland, M. J., Williams, E., Witkowska, K., Wood, S. M., Zarowiecki, M., Hsu, Chih-Wei, Marschall, Susan, Lengger, Christoph, Maier, Holger, Seisenberger, Claudia, Bürger, Antje, Kühn, Ralf, Schick, Joel, Hörlein, Andreas, Oritz, Oskar, Giesert, Florian, Christiansen, Audrey, Beig, Joachim, Kenyon, Janet, Codner, Gemma, Fray, Martin, Johnson, Sara J, Cleak, James, Szoke-Kovacs, Zsombor, Lafont, David, Vancollie, Valerie E, McLaren, Robbie S B, Lanza, Denise G, Hughes-Hallett, Lena, Rowley, Christine, Sanderson, Emma, Galli, Antonella, Tuck, Elizabeth, Green, Angela, Tudor, Catherine, Siragher, Emma, Dabrowska, Monika, Mazzeo, Cecilia Icoresi, Beaudet, Arthur L, Griffiths, Mark, Gannon, David, Doe, Brendan, Cockle, Nicola, Kirton, Andrea, Bottomley, Joanna, Ingle, Catherine, Ryder, Edward, Gleeson, Diane, Ramirez-Solis, Ramiro, Heaney, Jason D, Birling, Marie-Christine, Pavlovic, Guillaume, Ayadi, Abdel, Hamid, Meziane, About, Ghina Bou, Champy, Marie-France, Jacobs, Hugues, Wendling, Olivia, Leblanc, Sophie, Vasseur, Laurent, Fuchs, Helmut, Chesler, Elissa J, Kumar, Vivek, White, Jacqueline K, Svenson, Karen L, Wiegand, Jean-Paul, Anderson, Laura L, Wilcox, Troy, Clark, James, Ryan, Jennifer, Denegre, James, Gailus-Durner, Valerie, Stearns, Tim, Philip, Vivek, Witmeyer, Catherine, Bates, Lindsay, Seavey, Zachary, Stanley, Pamela, Willet, Amelia, Roper, Willson, Creed, Julie, Moore, Michayla, Sorg, Tania, Dorr, Alex, Fraungruber, Pamelia, Presby, Rose, Mckay, Matthew, Nguyen-Bresinsky, Dong, Goodwin, Leslie, Urban, Rachel, Kane, Coleen, Murray, Stephen A, Prochazka, Jan, Novosadova, Vendula, Lelliott, Christopher J, Wardle-Jones, Hannah, Wells, Sara, Teboul, Lydia, Cater, Heather, Stewart, Michelle, Hough, Tertius, Wurst, Wolfgang, Dickinson, Mary E, 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, Bucan, Maja, Lloyd, K C Kent, Brown, Steve D M, Parkinson, Helen, Meehan, Terrence F, Smedley, Damian, Consortium, Genomics England Research, Consortium, International Mouse Phenotyping, Ambrose, J. C., Arumugam, P., Baple, E. L., Nutter, Lauryl M J, Bleda, M., Boardman-Pretty, F., Boissiere, J. M., Boustred, C. R., Brittain, H., Caulfield, M. J., Chan, G. C., Craig, C. E. H., Daugherty, L. C., de Burca, A., Peterson, Kevin A, Devereau, A., Elgar, G., Foulger, R. E., Fowler, T., Furió-Tarí, P., Hackett, J. M., Halai, D., Hamblin, A., Henderson, S., Holman, J. E., Haselimashhadi, Hamed, Hubbard, T. J. P., Ibáñez, K., Jackson, R., Jones, L. J., Kasperaviciute, D., Kayikci, M., Lahnstein, L., Lawson, K., Leigh, S. E. A., Leong, I. U. S., Flenniken, Ann M, Lopez, F. J., Maleady-Crowe, F., Mason, J., McDonagh, E. M., Moutsianas, L., Mueller, M., Murugaesu, N., Need, A. C., Odhams, C. A., Patch, C., Morgan, Hugh, Perez-Gil, D., Polychronopoulos, D., Pullinger, J., Rahim, T., Rendon, A., Riesgo-Ferreiro, P., Rogers, T., Ryten, M., Savage, K., Sawant, K., Cacheiro, Pilar [0000-0002-6335-8208], Muñoz-Fuentes, Violeta [0000-0003-3574-546X], Nutter, Lauryl MJ [0000-0001-9619-146X], Peterson, Kevin A [0000-0001-8353-3694], Haselimashhadi, Hamed [0000-0001-7334-2421], Konopka, Tomasz [0000-0003-3042-4712], Hsu, Chih-Wei [0000-0002-9591-9567], Lanza, Denise G [0000-0001-8750-6933], Heaney, Jason D [0000-0001-8475-8828], Fuchs, Helmut [0000-0002-5143-2677], Gailus-Durner, Valerie [0000-0002-6076-0111], Lelliott, Christopher J [0000-0001-8087-4530], Adams, David J [0000-0001-9490-0306], Mammano, Fabio [0000-0003-3751-1691], McKerlie, Colin [0000-0002-2232-0967], Herault, Yann [0000-0001-7049-6900], de Angelis, Martin Hrabě [0000-0002-7898-2353], Lloyd, KC Kent [0000-0002-5318-4144], Smedley, Damian [0000-0002-5836-9850], Apollo - University of Cambridge Repository, Queen Mary University of London (QMUL), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, The Jackson Laboratory [Bar Harbor] (JAX), Baylor College of Medicine (BCM), Baylor University, University of Pennsylvania, The Hospital for sick children [Toronto] (SickKids), Mount Sinai Hospital [Toronto, Canada] (MSH), MRC Harwell Institute [UK], Helmholtz Zentrum München = German Research Center for Environmental Health, Institut Clinique de la Souris (ICS), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), French National Infrastructure for Mouse Phenogenomics (PHENOMIN), Institute of Molecular Genetics of the Czech Academy of Sciences (IMG / CAS), Czech Academy of Sciences [Prague] (CAS), The Wellcome Trust Sanger Institute [Cambridge], Technische Universität München = Technical University of Munich (TUM), Ludwig-Maximilians-Universität München (LMU), CNR - Italian National Research Council (CNR), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), German Center for Diabetes Research - Deutsches Zentrum für Diabetesforschung [Neuherberg] (DZD), University of California [Davis] (UC Davis), University of California (UC), J C Ambrose, P Arumugam, E L Baple, M Bleda, F Boardman-Pretty, J M Boissiere, C R Boustred, H Brittain, M J Caulfield, G C Chan, C E H Craig, L C Daugherty, A de Burca, A Devereau, G Elgar, R E Foulger, T Fowler, P Furió-Tarí, J M Hackett, D Halai, A Hamblin, S Henderson, J E Holman, T J P Hubbard, K Ibáñez, R Jackson, L J Jones, D Kasperaviciute, M Kayikci, L Lahnstein, K Lawson, S E A Leigh, I U S Leong, F J Lopez, F Maleady-Crowe, J Mason, E M McDonagh, L Moutsianas, M Mueller, N Murugaesu, A C Need, C A Odhams, C Patch, D Perez-Gil, D Polychronopoulos, J Pullinger, T Rahim, A Rendon, P Riesgo-Ferreiro, T Rogers, M Ryten, K Savage, K Sawant, R H Scott, A Siddiq, A Sieghart, K R Smith, A Sosinsky, W Spooner, H E Stevens, A Stuckey, R Sultana, E R A Thomas, S R Thompson, C Tregidgo, A Tucci, E Walsh, S A Watters, M J Welland, E Williams, K Witkowska, S M Wood, M Zarowiecki, Susan Marschall, Christoph Lengger, Holger Maier, Claudia Seisenberger, Antje Bürger, Ralf Kühn, Joel Schick, Andreas Hörlein, Oskar Oritz, Florian Giesert, Joachim Beig, Janet Kenyon, Gemma Codner, Martin Fray, Sara J Johnson, James Cleak, Zsombor Szoke-Kovacs, David Lafont, Valerie E Vancollie, Robbie S B McLaren, Lena Hughes-Hallett, Christine Rowley, Emma Sanderson, Antonella Galli, Elizabeth Tuck, Angela Green, Catherine Tudor, Emma Siragher, Monika Dabrowska, Cecilia Icoresi Mazzeo, Mark Griffiths, David Gannon, Brendan Doe, Nicola Cockle, Andrea Kirton, Joanna Bottomley, Catherine Ingle, Edward Ryder, Diane Gleeson, Ramiro Ramirez-Solis, Marie-Christine Birling, Guillaume Pavlovic, Abdel Ayadi, Meziane Hamid, Ghina Bou About, Marie-France Champy, Hugues Jacobs, Olivia Wendling, Sophie Leblanc, Laurent Vasseur, Elissa J Chesler, Vivek Kumar, Jacqueline K White, Karen L Svenson, Jean-Paul Wiegand, Laura L Anderson, Troy Wilcox, James Clark, Jennifer Ryan, James Denegre, Tim Stearns, Vivek Philip, Catherine Witmeyer, Lindsay Bates, Zachary Seavey, Pamela Stanley, Amelia Willet, Willson Roper, Julie Creed, Michayla Moore, Alex Dorr, Pamelia Fraungruber, Rose Presby, Matthew Mckay, Dong Nguyen-Bresinsky, Leslie Goodwin, Rachel Urban, Coleen Kane, Herault, Yann, and Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)

Subjects
0301 basic medicine, Mutation rate, Cancer Research, [SDV]Life Sciences [q-bio], General Physics and Astronomy, methods [Genetic Association Studies], Disease, VARIANTS, Mice, Essential, 0302 clinical medicine, IMPC, Genetics research, Lethal allele, 2.1 Biological and endogenous factors, Aetiology, lcsh:Science, Organism, ComputingMilieux_MISCELLANEOUS, Disease gene, Mice, Knockout, 0303 health sciences, Multidisciplinary, Genes, Essential, genetics [Disease], Genomics, R/BIOCONDUCTOR PACKAGE, DATABASE, UPDATE, GENOME, [SDV] Life Sciences [q-bio], Knockout mouse, Identification (biology), ddc:500, International Mouse Phenotyping Consortium, Technology Platforms, Biotechnology, Knockout, Science, Computational biology, Biology, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Genetics, medicine, Animals, Humans, Genetic variation, Clinical genetics, Gene, Genetic Association Studies, 030304 developmental biology, Disease model, Prevention, Human Genome, General Chemistry, medicine.disease, Developmental disorder, Good Health and Well Being, 030104 developmental biology, Genomics England Research Consortium, Genes, lcsh:Q, Generic health relevance, 030217 neurology & neurosurgery, Rare disease
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., Discovery of causal variants for monogenic disorders has been facilitated by whole exome and genome sequencing, but does not provide a diagnosis for all patients. Here, the authors propose a Full Spectrum of Intolerance to Loss-of-Function (FUSIL) categorization that integrates gene essentiality information to aid disease gene discovery.

Published
2020
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3. Characterization of a RAD51C-silenced high-grade serous ovarian cancer model during development of PARP inhibitor resistance

Author

Hurley, Rachel M, McGehee, Cordelia D, Nesic, Ksenija, Correia, Cristina, Weiskittel, Taylor M, Kelly, Rebecca L, Venkatachalam, Annapoorna, Hou, Xiaonan, Pathoulas, Nicholas M, Meng, X Wei, Kondrashova, Olga, Radke, Marc R, Schneider, Paula A, Flatten, Karen S, Peterson, Kevin L, Becker, Marc A, Wong, Ee Ming, Southey, Melissa S, Dobrovic, Alexander, Lin, Kevin K, Harding, Thomas C, McNeish, Iain, Ross, Christian A, Wagner, Jill M, Wakefield, Matthew J, Scott, Clare L, Haluska, Paul, Hendrickson, Andrea E Wahner, Karnitz, Larry M, Swisher, Elizabeth M, Li, Hu, Weroha, S John, and Kaufmann, Scott H

Subjects
Uncategorized
Abstract

Acquired PARP inhibitor (PARPi) resistance in BRCA1- or BRCA2-mutant ovarian cancer often results from secondary mutations that restore expression of functional protein. RAD51C is a less commonly studied ovarian cancer susceptibility gene whose promoter is sometimes methylated, leading to homologous recombination (HR) deficiency and PARPi sensitivity. For this study, the PARPi-sensitive patient-derived ovarian cancer xenograft PH039, which lacks HR gene mutations but harbors RAD51C promoter methylation, was selected for PARPi resistance by cyclical niraparib treatment in vivo. PH039 acquired PARPi resistance by the third treatment cycle and grew through subsequent treatment with either niraparib or rucaparib. Transcriptional profiling throughout the course of resistance development showed widespread pathway level changes along with a marked increase in RAD51C mRNA, which reflected loss of RAD51C promoter methylation. Analysis of ovarian cancer samples from the ARIEL2 Part 1 clinical trial of rucaparib monotherapy likewise indicated an association between loss of RAD51C methylation prior to on-study biopsy and limited response. Interestingly, the PARPi resistant PH039 model remained platinum sensitive. Collectively, these results not only indicate that PARPi treatment pressure can reverse RAD51C methylation and restore RAD51C expression, but also provide a model for studying the clinical observation that PARPi and platinum sensitivity are sometimes dissociated.

Published
2021
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4. A microRNA cluster in the Fragile-X region expressed during spermatogenesis targets FMR1

Author

Ramaiah, Madhuvanthi, Tan, Kun, Plank, Terra-Dawn M, Song, Hye-Won, Chousal, Jennifer N, Jones, Samantha, Shum, Eleen Y, Sheridan, Steven D, Peterson, Kevin J, Gromoll, Jörg, Haggarty, Stephen J, Cook-Andersen, Heidi, and Wilkinson, Miles F

Subjects
Male, congenital, hereditary, and neonatal diseases and abnormalities, Intellectual and Developmental Disabilities (IDD), Messenger, translation, testis, Mice, Fragile X Mental Retardation Protein, Rare Diseases, evolution, Genetics, Animals, Humans, Spermatogenesis, 3' Untranslated Regions, FMR1, Pediatric, microRNA, nervous system diseases, Brain Disorders, MicroRNAs, Gene Expression Regulation, Multigene Family, Fragile X Syndrome, RNA, RNA Interference, Biochemistry and Cell Biology, Biotechnology, Developmental Biology
Abstract

Testis-expressed X-linked genes typically evolve rapidly. Here, we report on a testis-expressed X-linked microRNA (miRNA) cluster that despite rapid alterations in sequence has retained its position in the Fragile-X region of the X chromosome in placental mammals. Surprisingly, the miRNAs encoded by this cluster (Fx-mir) have a predilection for targeting the immediately adjacent gene, Fmr1, an unexpected finding given that miRNAs usually act in trans, not in cis Robust repression of Fmr1 is conferred by combinations of Fx-mir miRNAs induced in Sertoli cells (SCs) during postnatal development when they terminate proliferation. Physiological significance is suggested by the finding that FMRP, the protein product of Fmr1, is downregulated when Fx-mir miRNAs are induced, and that FMRP loss causes SC hyperproliferation and spermatogenic defects. Fx-mir miRNAs not only regulate the expression of FMRP, but also regulate the expression of eIF4E and CYFIP1, which together with FMRP form a translational regulatory complex. Our results support a model in which Fx-mir family members act cooperatively to regulate the translation of batteries of mRNAs in a developmentally regulated manner in SCs.

Published
2019

5. 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, International Mouse Phenotyping Consortium, 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
General Science & Technology, International Mouse Phenotyping Consortium
Abstract

This corrects the article DOI: 10.1038/nature19356.

Published
2017

6. 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, Laboratory, Jackson, Infrastructure Nationale PHENOMIN, Institut Clinique De La Souris (ICS), Laboratories, Charles River, 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, Murray, Stephen A, Bradley, Allan [0000-0002-2349-8839], and Apollo - University of Cambridge Repository

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

7. The D2Refine Platform for the Standardization of Clinical Research Study Data Dictionaries: Usability Study

Author

Sharma, Deepak Kumar, Peterson, Kevin Jerrold, Hong, Na, and Jiang, Guoqian

Subjects
0301 basic medicine, Standardization, Computer science, media_common.quotation_subject, Interoperability, interoperability, Health Informatics, Human Factors and Ergonomics, Task (project management), 03 medical and health sciences, 0302 clinical medicine, usability study, usability framework, 030212 general & internal medicine, Function (engineering), media_common, standardization, Original Paper, Information retrieval, business.industry, metadata, Usability, Data dictionary, Metadata, electronic health records, 030104 developmental biology, Task analysis, data dictionary, business
Abstract

Background: D2Refine provides a Web-based environment to create clinical research study data dictionaries and enables standardization and harmonization of its variable definitions with controlled terminology resources. Objective: To assess the usability of the functions D2Refine offers, a usability study was designed and executed. Methods: We employed the TURF (task, user, representation, and function) Usability Framework of electronic health record usability to design, configure, and execute the usability study and performed quantitative analyses. D2Refine was compared for its usability metrics against two other comparable solutions, OntoMaton and RightField, which have very similar functionalities for creating, managing, and standardizing data dictionaries. We first conducted the function analysis by conducting one-on-one interviews armed with questionnaires to catalog expected functionality. The enrolled participants carried out the steps for selected tasks to accomplish specific goals and their feedback was captured to conduct the task analysis. Results: We enrolled a group (n=27) of study developers, managers, and software professionals to execute steps of analysis as specified by the TURF framework. For the within-model domain function saturation, D2Refine had 96% saturation, which was 4 percentage points better than OntoMaton and 28 percentage points better than RightField. The manual examination and statistical analysis of the data were conducted for task analysis, and the results demonstrated a significant difference for favorability toward D2Refine (P

Published
2018

8. A Long-Duration Propulsive Lunar Landing Testbed

Author

Shankar, Krishna, Peterson, Kevin, Jones, Heather, and Whittaker, William

Subjects
FOS: Computer and information sciences, 80101 Adaptive Agents and Intelligent Robotics
Abstract

Affordable test articles for descent and landing are crucial for developing commercial lunar landing capability. To ensure successful lunar landing, flight software must be tested over mission-length durations on hardware exhibiting dynamics analogous to those of true flight articles. Energetic and structural constraints typically preclude affordable long-duration lander tests.

Published
2011
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9. Planning-based Prediction for Pedestrians

Author

Ziebart, Brian, Ratliff, Nathan, Garratt Gallagher, Peterson, Kevin, J. Andrew Bagnell, Hebert, Martial, Anind K. Dey, and Siddhartha Srinivasa

Subjects
FOS: Computer and information sciences, 80101 Adaptive Agents and Intelligent Robotics
Abstract

In this paper, we describe a novel uncertaintybased technique for predicting the future motions of a moving person. Our model assumes that people behave purposefully – efficiently acting to reach intended destinations. We employ the Markov decision process framework and the principle of maximum entropy to obtain a probabilistic, approximately optimal model of human behavior that admits efficient inference and learning algorithms. The method learns a cost function of features of the environment that explains previously observed behavior. This enables generalization to physical changes in the environment, and entirely different environments. Our approach enables robots to plan paths that balance time-togoal and pedestrian disruption. We quantitatively show the improvement provided by our approach.

Published
2009
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10. Inverse Optimal Heuristic Control for Imitation Learning

Author

Ratliff, Nathan, Ziebart, Brian, Peterson, Kevin, J. Andrew Bagnell, Hebert, Martial, Anind K. Dey, and Siddhartha Srinivasa

Subjects
FOS: Computer and information sciences, 80101 Adaptive Agents and Intelligent Robotics
Abstract

mitation learning is an increasingly important tool for both developing automatic decision making systems as well as for learning to predict decision-making and behavior by observation. Two basic approaches are common: the first, which we here term \emph{behavioral cloning} (BC)\cite{BehavioralCloning,ALVINN,DAVE}, treats the imitation learning problem as a straightforward one of supervised learning (e.g. classification) where the goal is to map observations to controls. Secondly, the notion of\emph{inverse optimal control} (IOC) \cite{BoydIOC,ng00irl,Abbeel04c,mmp06} for modeling such decision making behavior has gained prominence as it allows for learned decision-making that reasons sequentially and over a long horizon. Unfortunately, such inverse optimal control methods rely upon the ability to efficiently solve a planning problem and suffer from the usual ``curse of dimensionality'' when the state space gets large. This paper presents a novel approach to imitation learning that we call \emph{Inverse Optimal Heuristic Control }(IOHC) which capitalizes on the strengths of both paradigms by allowing long-horizon, planning style reasoning in a low dimensional space, while enabling a high dimensional additional set of features to guide overall action selection. We frame this combined problem as one of optimization, and although the resulting objective function is actually non-convex, we are able to provide convex upper and lower bounds to optimize as surrogates. Further, these bounds, as well as our empirical results, show that the objective function is nearly convex and leads to improved performance on a set of imitation learning problems including turn prediction of drivers as well as predicting the likely paths taken by pedestrians in an office environment.

Published
2009
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