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22 results on '"Haeussler, Maximilian"'

1. Spatial epigenome-transcriptome co-profiling of mammalian tissues

Author

Zhang, Di, Deng, Yanxiang, Kukanja, Petra, Agirre, Eneritz, Bartosovic, Marek, Dong, Mingze, Ma, Cong, Ma, Sai, Su, Graham, Bao, Shuozhen, Liu, Yang, Xiao, Yang, Rosoklija, Gorazd B, Dwork, Andrew J, Mann, J John, Leong, Kam W, Boldrini, Maura, Wang, Liya, Haeussler, Maximilian, Raphael, Benjamin J, Kluger, Yuval, Castelo-Branco, Gonçalo, and Fan, Rong

Subjects
Mammals, Epigenomics, Aging, General Science & Technology, Gene Expression Profiling, 1.1 Normal biological development and functioning, Human Genome, Brain, Chromatin, Histones, Mice, Epigenome, Rare Diseases, Gene Expression Regulation, Genetic, Organ Specificity, Underpinning research, Genetics, Animals, Humans, Generic health relevance, Single-Cell Analysis, Transcriptome, Epigenesis, Biotechnology
Abstract

Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context1-5. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.

Published
2023

2. Single-cell genomics identifies cell type-specific molecular changes in autism

Author

Velmeshev, Dmitry, Schirmer, Lucas, Jung, Diane, Haeussler, Maximilian, Perez, Yonatan, Mayer, Simone, Bhaduri, Aparna, Goyal, Nitasha, Rowitch, David H, Kriegstein, Arnold R, Velmeshev, Dmitry [0000-0002-7440-8805], Schirmer, Lucas [0000-0001-7142-4116], Haeussler, Maximilian [0000-0001-8721-8253], Mayer, Simone [0000-0002-6381-2474], Bhaduri, Aparna [0000-0003-4625-6899], Rowitch, David H [0000-0002-0079-0060], Kriegstein, Arnold R [0000-0001-5742-2990], and Apollo - University of Cambridge Repository

Subjects
Cell Nucleus, Male, Neurons, Adolescent, Sequence Analysis, RNA, Gene Expression Profiling, Neocortex, Genomics, behavioral disciplines and activities, Young Adult, nervous system, Gene Expression Regulation, Child, Preschool, mental disorders, Humans, Female, Microglia, Autistic Disorder, Single-Cell Analysis, Child
Abstract

Despite the clinical and genetic heterogeneity of autism, bulk gene expression studies show that changes in the neocortex of autism patients converge on common genes and pathways. However, direct assessment of specific cell types in the brain affected by autism has not been feasible until recently. We used single-nucleus RNA sequencing of cortical tissue from patients with autism to identify autism-associated transcriptomic changes in specific cell types. We found that synaptic signaling of upper-layer excitatory neurons and the molecular state of microglia are preferentially affected in autism. Moreover, our results show that dysregulation of specific groups of genes in cortico-cortical projection neurons correlates with clinical severity of autism. These findings suggest that molecular changes in upper-layer cortical circuits are linked to behavioral manifestations of autism.

Published
2019
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3. The UCSC Genome Browser database: 2017 update

Author

Tyner, Cath, Barber, Galt P., Casper, Jonathan, Clawson, Hiram, Diekhans, Mark, Eisenhart, Christopher, Fischer, Clayton M., Gibson, David, Gonzalez, Jairo Navarro, Guruvadoo, Luvina, Haeussler, Maximilian, Heitner, Steve, Hinrichs, Angie S., Karolchik, Donna, Lee, Brian T., Lee, Christopher M., Nejad, Parisa, Raney, Brian J., Rosenbloom, Kate R., Speir, Matthew L., Villarreal, Chris, Vivian, John, Zweig, Ann S., Haussler, David, Kuhn, Robert M., and Kent, W. James

Subjects
Genome, Human Genome, Computational Biology, Molecular Sequence Annotation, Genomics, Biological Sciences, Web Browser, Search Engine, Databases, Genetic, Information and Computing Sciences, Databases, Genetic, Genetics, Database Issue, Animals, Humans, natural sciences, Environmental Sciences, Software, Developmental Biology
Abstract

Since its 2001 debut, the University of California, Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu/) team has provided continuous support to the international genomics and biomedical communities through a web-based, open source platform designed for the fast, scalable display of sequence alignments and annotations landscaped against a vast collection of quality reference genome assemblies. The browser's publicly accessible databases are the backbone of a rich, integrated bioinformatics tool suite that includes a graphical interface for data queries and downloads, alignment programs, command-line utilities and more. This year's highlights include newly designed home and gateway pages; a new 'multi-region' track display configuration for exon-only, gene-only and custom regions visualization; new genome browsers for three species (brown kiwi, crab-eating macaque and Malayan flying lemur); eight updated genome assemblies; extended support for new data types such as CRAM, RNA-seq expression data and long-range chromatin interaction pairs; and the unveiling of a new supported mirror site in Japan.

Published
2016

4. Single-cell genomics identifies cell type-specific molecular changes in autism

Author

Velmeshev, Dmitry, Schirmer, Lucas, Jung, Diane, Haeussler, Maximilian, Perez, Yonatan, Mayer, Simone, Bhaduri, Aparna, Goyal, Nitasha, Rowitch, David H, and Kriegstein, Arnold R

Subjects
Male, Adolescent, General Science & Technology, Autism, Intellectual and Developmental Disabilities (IDD), Neocortex, Young Adult, Behavioral and Social Science, Genetics, Humans, 2.1 Biological and endogenous factors, Autistic Disorder, Aetiology, Child, Preschool, Neurons, Cell Nucleus, Pediatric, Gene Expression Profiling, Human Genome, Neurosciences, Genomics, Brain Disorders, Mental Health, Gene Expression Regulation, Neurological, RNA, Female, Microglia, Single-Cell Analysis, Sequence Analysis, Biotechnology
Abstract

Despite the clinical and genetic heterogeneity of autism, bulk gene expression studies show that changes in the neocortex of autism patients converge on common genes and pathways. However, direct assessment of specific cell types in the brain affected by autism has not been feasible until recently. We used single-nucleus RNA sequencing of cortical tissue from patients with autism to identify autism-associated transcriptomic changes in specific cell types. We found that synaptic signaling of upper-layer excitatory neurons and the molecular state of microglia are preferentially affected in autism. Moreover, our results show that dysregulation of specific groups of genes in cortico-cortical projection neurons correlates with clinical severity of autism. These findings suggest that molecular changes in upper-layer cortical circuits are linked to behavioral manifestations of autism.

Published
2019

5. Publisher Correction: Federated discovery and sharing of genomic data using Beacons

Author

Fiume, Marc, Cupak, Miroslav, Keenan, Stephen, Rambla, Jordi, de la Torre, Sabela, Dyke, Stephanie OM, Brookes, Anthony J, Carey, Knox, Lloyd, David, Goodhand, Peter, Haeussler, Maximilian, Baudis, Michael, Stockinger, Heinz, Dolman, Lena, Lappalainen, Ilkka, Törnroos, Juha, Linden, Mikael, Spalding, J Dylan, Ur-Rehman, Saif, Page, Angela, Flicek, Paul, Sherry, Stephen, Haussler, David, Varma, Susheel, Saunders, Gary, and Scollen, Serena

Abstract

In the version of this article initially published, Lena Dolman's second affiliation was given as Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK. The correct second affiliation is Ontario Institute for Cancer Research, Toronto, Ontario, Canada. The error has been corrected in the HTML and PDF versions of the article.

Published
2019

6. Dynamic landscape and regulation of RNA editing in mammals

Author

Tan, Meng How, Qin, Li, Shanmugam, Raghuvaran, Piskol, Robert, Kohler, Jennefer, Young, Amy N., Liu, Kaiwen Ivy, Zhang, Rui, Ramaswami, Gokul, Ariyoshi, Kentaro, Gupte, Ankita, Keegan, Liam P., George, Cyril X., Ramu, Avinash, Huang, Ni, Pollina, Elizabeth A., Leeman, Dena S., Rustighi, Alessandra, Goh, Y. P. Sharon, Aguet, François, Ardlie, Kristin G., Cummings, Beryl B., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Karczewski, Konrad J., Lek, Monkol, Xiao, Li, Macarthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segrè, Ayellet V., Trowbridge, Casandra A., Tukiainen, Taru, Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Castel, Stephane E., Chen, Lin S., Chiang, Colby, Conrad, Donald F., Cox, Nancy J., Damani, Farhan N., Davis, Joe R., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frésard, Laure, Gamazon, Eric R., Garrido-Martín, Diego, Gewirtz, Ariel D. H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, Yuan, He, Hormozdiari, Farhad, Howald, Cedric, Hae Kyung, Im, Brian, Jo, Kang, Eun Yong, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Gen, Li, Xin, Li, Liu, Boxiang, Mangul, Serghei, Mccarthy, Mark I., Mcdowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muñoz-Aguirre, Manuel, Ndungu, Anne W., Nicolae, Dan L., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolaos, Papasaikas, Panagiotis, Park, Yoson, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J., Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Strober, Benjamin J., Sul, Jae Hoon, Tsang, Emily K., Urbut, Sarah, Van De Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Hualin S., Xi, Yeger-Lotem, Esti, Zappala, Zachary, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manolis, Kibriya, Muhammad G., Lee, Kristen, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nicholas, Fan, Wu, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., Mcdonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., Mclean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Liqun, Qi, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Ki Sung, Um, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thomas, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. James, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, Zhu, Jingchun, Chawla, Ajay, Del Sal, Giannino, Peltz, Gary, Brunet, Anne, Samuel, Charles E., O'Connell, Mary A., Walkley, Carl R., Nishikura, Kazuko, Jin Billy, Li, Tan, Meng How, Li, Qin, Shanmugam, Raghuvaran, Piskol, Robert, Kohler, Jennefer, Young, Amy N., Liu, Kaiwen Ivy, Zhang, Rui, Ramaswami, Gokul, Ariyoshi, Kentaro, Gupte, Ankita, Keegan, Liam P., George, Cyril X., Ramu, Avinash, Huang, Ni, Pollina, Elizabeth A., Leeman, Dena S., Rustighi, Alessandra, Goh, Y. P. Sharon, Aguet, Françoi, Ardlie, Kristin G., Cummings, Beryl B., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Karczewski, Konrad J., Lek, Monkol, Li, Xiao, Macarthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segrè, Ayellet V., Trowbridge, Casandra A., Tukiainen, Taru, Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexi, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Castel, Stephane E., Chen, Lin S., Chiang, Colby, Conrad, Donald F., Cox, Nancy J., Damani, Farhan N., Davis, Joe R., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frésard, Laure, Gamazon, Eric R., Garrido-Martín, Diego, Gewirtz, Ariel D. H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Im, Hae Kyung, Jo, Brian, Kang, Eun Yong, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, Mccarthy, Mark I., Mcdowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muñoz-Aguirre, Manuel, Ndungu, Anne W., Nicolae, Dan L., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolao, Papasaikas, Panagioti, Park, Yoson, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashi, Sammeth, Michael, Scott, Alexandra J., Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Strober, Benjamin J., Sul, Jae Hoon, Tsang, Emily K., Urbut, Sarah, Van De Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Xi, Hualin S., Yeger-Lotem, Esti, Zappala, Zachary, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manoli, Kibriya, Muhammad G., Lee, Kristen, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nichola, Wu, Fan, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcu, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., Mcdonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., Mclean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Qi, Liqun, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Um, Ki Sung, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thoma, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. Jame, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, Zhu, Jingchun, Chawla, Ajay, Del Sal, Giannino, Peltz, Gary, Brunet, Anne, Samuel, Charles E., O'Connell, Mary A., Walkley, Carl R., Nishikura, Kazuko, Li, Jin Billy, Brown, Andrew Anand, Dermitzakis, Emmanouil, and Howald, Cédric

Subjects
0301 basic medicine, Male, Primates, Genotype, Adenosine Deaminase, RNA-binding protein, Computational biology, RNA-Binding Protein, Biology, Article, Animals, Female, HEK293 Cells, Humans, Mice, Muscles, Nuclear Proteins, Organ Specificity, Proteolysis, RNA Editing, Spatio-Temporal Analysis, Species Specificity, Transcriptome, RNA-Binding Proteins, Multidisciplinary, 03 medical and health sciences, HEK293 Cell, Coding region, ddc:576.5, Proteolysi, Gene, Nuclear Protein, Regulation of gene expression, Genetics, Animal, Primate, RNA, 030104 developmental biology, RNA editing, ADAR, Muscle, Spatio-Temporal Analysi, Human
Abstract

Adenosine-to-inosine (A-to-I) RNA editing is a conserved post-transcriptional mechanism mediated by ADAR enzymes that diversifies the transcriptome by altering selected nucleotides in RNA molecules1. Although many editing sites have recently been discovered2,3,4,5,6,7, the extent to which most sites are edited and how the editing is regulated in different biological contexts are not fully understood8,9,10. Here we report dynamic spatiotemporal patterns and new regulators of RNA editing, discovered through an extensive profiling of A-to-I RNA editing in 8,551 human samples (representing 53 body sites from 552 individuals) from the Genotype-Tissue Expression (GTEx) project and in hundreds of other primate and mouse samples. We show that editing levels in non-repetitive coding regions vary more between tissues than editing levels in repetitive regions. Globally, ADAR1 is the primary editor of repetitive sites and ADAR2 is the primary editor of non-repetitive coding sites, whereas the catalytically inactive ADAR3 predominantly acts as an inhibitor of editing. Cross-species analysis of RNA editing in several tissues revealed that species, rather than tissue type, is the primary determinant of editing levels, suggesting stronger cis-directed regulation of RNA editing for most sites, although the small set of conserved coding sites is under stronger trans-regulation. In addition, we curated an extensive set of ADAR1 and ADAR2 targets and showed that many editing sites display distinct tissue-specific regulation by the ADAR enzymes in vivo. Further analysis of the GTEx data revealed several potential regulators of editing, such as AIMP2, which reduces editing in muscles by enhancing the degradation of the ADAR proteins. Collectively, our work provides insights into the complex cis- and trans-regulation of A-to-I editing.

Published
2017

7. Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex

Author

Nowakowski, Tomasz J, Bhaduri, Aparna, Pollen, Alex A, Alvarado, Beatriz, Mostajo-Radji, Mohammed A, Di Lullo, Elizabeth, Haeussler, Maximilian, Sandoval-Espinosa, Carmen, Liu, Siyuan John, Velmeshev, Dmitry, Ounadjela, Johain Ryad, Shuga, Joe, Wang, Xiaohui, Lim, Daniel A, West, Jay A, Leyrat, Anne A, Kent, W James, and Kriegstein, Arnold R

Subjects
Telencephalon, Cerebral Cortex, Neurons, Pediatric, General Science & Technology, Neurogenesis, 1.1 Normal biological development and functioning, Neurosciences, Stem Cell Research, Gene Expression Regulation, Underpinning research, Genetics, Humans, Developmental, Stem Cell Research - Nonembryonic - Non-Human, Neuroglia
Abstract

Systematic analyses of spatiotemporal gene expression trajectories during organogenesis have been challenging because diverse cell types at different stages of maturation and differentiation coexist in the emerging tissues. We identified discrete cell types as well as temporally and spatially restricted trajectories of radial glia maturation and neurogenesis in developing human telencephalon. These lineage-specific trajectories reveal the expression of neurogenic transcription factors in early radial glia and enriched activation of mammalian target of rapamycin signaling in outer radial glia. Across cortical areas, modest transcriptional differences among radial glia cascade into robust typological distinctions among maturing neurons. Together, our results support a mixed model of topographical, typological, and temporal hierarchies governing cell-type diversity in the developing human telencephalon, including distinct excitatory lineages emerging in rostral and caudal cerebral cortex.

Published
2017

8. ANISEED 2017: extending the integrated ascidian database to the exploration and evolutionary comparison of genome-scale datasets

Author

Brozovic, Matija, Dantec, Christelle, Dardaillon, Justine, Dauga, Delphine, Faure, Emmanuel, Gineste, Mathieu, Louis, Alexandra, Naville, Magali, Nitta, Kazuhiro R, Piette, Jacques, Reeves, Wendy, Scornavacca, Céline, Simion, Paul, Vincentelli, Renaud, Bellec, Maelle, Aicha, Sameh Ben, Fagotto, Marie, Guéroult-Bellone, Marion, Haeussler, Maximilian, Jacox, Edwin, Lowe, Elijah K, Mendez, Mickael, Roberge, Alexis, Stolfi, Alberto, Yokomori, Rui, Brown, CTitus, Cambillau, Christian, Christiaen, Lionel, Delsuc, Frédéric, Douzery, Emmanuel, Dumollard, Rémi, Kusakabe, Takehiro, Nakai, Kenta, Nishida, Hiroki, Satou, Yutaka, Swalla, Billie, Veeman, Michael, Volff, Jean-Nicolas, Lemaire, Patrick, Centre de recherche en Biologie Cellulaire (CRBM), Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Bioself Communication [Marseille], Institut de Biologie Computationnelle (IBC), Institut National de la Recherche Agronomique (INRA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Visual Objects from Reality To Expression (VORTEX), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Institut de biologie de l'ENS Paris (UMR 8197/1024) (IBENS), Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de Génomique Fonctionnelle de Lyon (IGFL), École normale supérieure - Lyon (ENS Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Institut de Biologie du Développement de Marseille (IBDM), Aix Marseille Université (AMU)-Collège de France (CdF)-Centre National de la Recherche Scientifique (CNRS), Kansas State University, Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS), Architecture et fonction des macromolécules biologiques (AFMB), Institut National de la Recherche Agronomique (INRA)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Université de Montpellier (UM), Laboratoire de Biologie du Développement de Villefranche sur mer (LBDV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Santa Cruz Genomics Institute, University of California [Santa Cruz] (UCSC), University of California-University of California, Michigan State University [East Lansing], Michigan State University System, School of Biology [Atlanta], Georgia Institute of Technology [Atlanta], The University of Tokyo, New York University [New York] (NYU), NYU System (NYU), Konan University [Kobe, Japan], Osaka University [Osaka], Kyoto University [Kyoto], Institut de Génomique Fonctionnelle (IGF), Université de Montpellier (UM)-Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS), Centre de recherche en Biologie cellulaire de Montpellier (CRBM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Real Expression Artificial Life (IRIT-REVA), Université Toulouse Capitole (UT Capitole), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse Capitole (UT Capitole), Institut de biologie de l'ENS Paris (IBENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS), University of California [Santa Cruz] (UC Santa Cruz), University of California (UC)-University of California (UC), The University of Tokyo (UTokyo), Kyoto University, Godin, Christophe, Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-École normale supérieure - Lyon (ENS Lyon), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UR226, Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut National de la Recherche Agronomique (INRA), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), École normale supérieure de Lyon (ENS de Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), ANR-16-CE92-0019,EVOBOOSTER,Impact des éléments transposables sur les réseaux de régulation génique : application aux voies biologiques à évolution rapide chez les poissons(2016), and Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université Montpellier 1 (UM1)

Subjects
Transcription, Genetic, Evolution, Datasets as Topic, Gene Expression, Bioengineering, Web Browser, Evolution, Molecular, Databases, Genetic, Species Specificity, Information and Computing Sciences, Databases, Genetic, Genetics, Animals, Data Mining, Database Issue, natural sciences, Urochordata, Phylogeny, Internet, Genome, Human Genome, Molecular, Molecular Sequence Annotation, DNA, Biological Sciences, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Biological Evolution, Ciona intestinalis, Gene Ontology, Vertebrates, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, Transcription, Environmental Sciences, Biotechnology, Developmental Biology, Protein Binding, Transcription Factors
Abstract

International audience; ANISEED (www.aniseed.cnrs.fr) is the main model organism database for tunicates, the sister-group of vertebrates. This release gives access to annotated genomes, gene expression patterns, and anatomical descriptions for nine ascidian species. It provides increased integration with external molecular and taxonomy databases, better support for epigenomics datasets, in particular RNA-seq, ChIP-seq and SELEX-seq, and features novel interactive interfaces for existing and novel datatypes. In particular, the cross-species navigation and comparison is enhanced through a novel taxonomy section describing each represented species and through the implementation of interactive phylogenetic gene trees for 60% of tunicate genes. The gene expression section displays the results of RNA-seq experiments for the three major model species of solitary ascidians. Gene expression is controlled by the binding of transcription factors to cis-regulatory sequences. A high-resolution description of the DNA-binding specificity for 131 Ciona robusta (formerly C. intestinalis type A) transcription factors by SELEX-seq is provided and used to map candidate binding sites across the Ciona robusta and Phallusia mammillata genomes. Finally, use of a WashU Epigenome browser enhances genome navigation, while a Genomicus server was set up to explore microsynteny relationships within tunicates and with vertebrates, Amphioxus, echinoderms and hemichordates.

Published
2017

9. Genetic effects on gene expression across human tissues

Author

Haugen, Eric, He, Yuan, Chen, Lin S., Dermitzakis, Emmanouil T., Branton, Philip A., Nobel, Andrew B., Park, YoSon, McLean, Jeffrey A., Neri, Fidencio J., Tabor, David E., Saha, Ashis, Sobin, Leslie, Doherty, Jennifer A., Rosenbloom, Kate R., Quan, Jie, Strober, Benjamin J., Liu, Yaping, Valley, Dana, Basha, Omer, Barshir, Ruth, Trowbridge, Casandra A., Segrè, Ayellet V., Skol, Andrew, Karasik, Ellen, Bridge, Jason, Kent, W. James, Chiang, Colby, Damani, Farhan N., Karczewski, Konrad J., Barcus, Mary E., Oliva, Meritxell, Papasaikas, Panagiotis, Nelson, Jemma, Linke, Caroline, Paten, Benedict, Gelfand, Ellen T., Zhu, Jingchun, Wright, Fred A., Smith, Kevin S., Halow, Jessica, Kim-Hellmuth, Sarah, Salvatore, Michael, Hunter, Steven, Noble, Michael S., Goldman, Mary, Nguyen, Duyen Y., Singh, Shilpi, Rohrer, Daniel C., Cox, Nancy J., Hickey, Peter F., Battle, Alexis, Claussnitzer, Melina, Molinie, Benoit, Aguet, François, Balliu, Brunilda, Thomas, Jeffrey A., Hormozdiari, Farhad, Hou, Lei, Kaul, Rajinder, Peterson, Christine B., Lin, Jessica, Barker, Laura K., Brown, Christopher D., Guan, Ping, Lee, Kristen, Gloudemans, Michael J., Ripke, Stephan, Moser, Michael T., Muñoz-Aguirre, Manuel, Haeussler, Maximilian, Vatanian, Negin, Gewirtz, Ariel D.H., Castel, Stephane E., Monlong, Jean, Scott, Alexandra J., Stamatoyannopoulos, John, Ruffier, Magali, Zappala, Zachary, Li, Xiao, Ferreira, Pedro G., Nierras, Concepcion R., Yeger-Lotem, Esti, Wen, Xiaoquan, Struewing, Jeffery P., Delaneau, Olivier, Tukiainen, Taru, Tomaszewski, Maria M., Jo, Brian, Park, Yongjin, Martin, Casey, Bogu, Gireesh K., Pierce, Brandon L., Zhou, Yi-Hui, Eskin, Eleazar, Reverter, Ferran, Guigó, Roderic, Teran, Nicole A., Lek, Monkol, Leinweber, William F., Ardlie, Kristin G., Kopen, Gene, Ongen, Halit, Lonsdale, John T., Hall, Ira M., Bustamante, Carlos D., Quon, Gerald, Han, Buhm, Mohammadi, Pejman, Nicolae, Dan L., Kellis, Manolis, Vivian, John, Robinson, Karna L., Davis, David A., Washington, Michael, Montroy, Robert G., Craft, Brian, Wang, Gao, Garrido-Martín, Diego, Taylor, Kieron, Linder, Sandra, Hadley, Kane, Addington, Anjene M., Davis, Joe R., Siminoff, Laura A., Miklos, Mark, Tsang, Emily K., Diegel, Morgan, Mash, Deborah C., McDowell, Ian C., Lockhart, Nicole C., Payne, Anthony J., Abell, Nathan S., Cummings, Beryl B., Wheeler, Joseph, Matose, Takunda, Demanelis, Kathryn, Gliner, Genna, Stephens, Matthew, McDonald, Alisa, Rao, Abhi, Foster, Barbara A., Frésard, Laure, Brown, Andrew A., Zhang, Rui, Rinaldi, Nicola J., Gillard, Bryan M., Zerbino, Daniel R., Sabatti, Chiara, Moore, Helen M., Hasz, Richard, Brigham, Lori E., Zaugg, Judith B., Jian, Ruiqi, Conrad, Donald F., Snyder, Michael P., Im, Hae Kyung, Wu, Fan, MacArthur, Daniel G., Liu, Boxiang, Gamazon, Eric R., Jiang, Lihua, Sammeth, Michael, Johns, Christopher, Maurano, Matthew T., Hansen, Kasper D., Kang, Eun Yong, Myer, Kevin, Tang, Hua, Johnson, Mark, Fernando, Marian S., Smith, Anna M., Urbut, Sarah, Gould, Sarah E., Van Wittenberghe, Nicholas, Lee, Christopher M., Engelhardt, Barbara E., Panousis, Nikolaos, Palowitch, John J., Kibriya, Muhammad G., Sheppard, Dan, McCarthy, Mark I., Ndungu, Anne W., Valentino, Kimberly M., Sodaei, Reza, Sandstrom, Richard, Parsana, Princy, Kim, Yungil, Kumar, Rachna, Chan, Joanne, Little, A. Roger, Shimko, Tyler C., Volpi, Simona, Li, Qin, Akey, Joshua M., Walters, Gary, Roe, Bryan, Undale, Anita H., Van De Bunt, Martijn, Getz, Gad, Li, Jin Billy, Mangul, Serghei, Feinberg, Andrew P., Sul, Jae Hoon, Rizzardi, Lindsay F., Nguyen, Duyen T., Stranger, Barbara E., Um, Ki Sung, Flicek, Paul, Trevanion, Stephen J., Vaught, Jimmie B., Lockart, Nicole C., Nedzel, Jared L., Handsaker, Robert E., Hunter, Marcus, Xi, Hualin S., Bates, Daniel, Howald, Cedric, Roche, Nancy V., Koester, Susan, Huang, Katherine H., Sullivan, Timothy J., Wang, Meng, Shabalin, Andrey A., Shad, Saboor, Hariharan, Pushpa, He, Amy Z., Qi, Liqun, Lappalainen, Tuuli, Li, Xin, Carithers, Latarsha J., Mestichelli, Bernadette, Kashin, Seva, Li, Gen, Jasmine, Farzana, Juettemann, Thomas, Montgomery, Stephen B., Zhang, Hailei, Traino, Heather M., Mosavel, Maghboeba, Koester, Susan E., Lin, Shin, Jewell, Scott D., Johnson, Audra, and Wang, Li

Abstract

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

Published
2017
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10. Additional file 7: Figure S3. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Subjects
sense organs, skin and connective tissue diseases
Abstract

MIT specificity scores calculated by the CRISPOR website for 28 guide sequences calculated based on predicted off-targets with up to four, five, and six mismatches. Only one label is shown for identical guide sequences from two different studies. A change from four to five allowed mismatches used in the scoring results in a change of the specificity scores but only in minor changes of the ranking of the guide sequences by specificity score. (PDF 23 kb)

Published
2016
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11. Additional file 13: Figure S5. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Extended version of Fig. 4 . This figure includes the datasets not shown in Fig. 4. Shown are: Wang 2015 data, both human and mouse data from Doench 2014, Doench 2016, both cell lines tested by Chari et al., Housden score and Housden dataset, Liu dataset and the score-like efficiency heuristics from Ren et al. and Farboud et al. Labeling is similar to Fig. 4: datasets are indicated along the y-axis and scores for predicting guide actvity along the x-axis. Data points where the training data of the algorithm has been processed with the algorithm, so likely affected by over-fitting, are shown in grey. (PDF 22 kb)

Published
2016
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12. Additional file 9: Figure S4. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Similar to Fig. 3 but using off-target predictions by the CRISPR Design website ( http://crispr.mit.edu/ ). a For the 28 tested guide sequences, MIT guide specificity scores as calculated by the MIT website (x-axis), number of off-targets (y-axis), and sum of off-target modification frequencies (circle size). b The specificity of the 28 tested guide sequences (blue) versus the specificity scores of all unique 20mers in human coding regions (green). The specificity score histogram was calculated by running 1000 randomly selected guide sequences from human coding regions through the CRISPR Design website ( http://crispr.mit.edu/ ). (PDF 40 kb)

Published
2016
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13. Additional file 16: Figure S6. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Precision/recall curves for the large-scale datasets. The precision/recall plot for the Wong score on the Chari dataset looks different to that in the Wong et al. article as our study is analyzing only full datasets and Wong et al. used cross-fold data. The datasets by Hart, Doench 2016, Koike-Yusa, or Wang/Xu give the best impression of the Wong score on independent data that was not used for training by Wong et al. (PDF 87 kb)

Published
2016
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14. Additional file 6: Figure S2. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Ratio of off-target to on-target cleavage for validated guide sequences. The two guides RAG1B and RAG1A are not shown on this plot as their on-target cleavage was not determined in the study by Frock et al. [28]. Studies in the legend are referenced by the first author’s name; in the case of Kim et al., the cell type is also indicated. For each guide, the sum of all off-target modification frequencies was divided by the on-target modification frequency, e.g., a ratio of 2 indicates that cleavage is twice as frequent on all off-targets taken together than on the target. To better show the two outliers, a portion of the x-axis and y-axis was cut out. The CRISPOR website and Genome Browser tracks show a warning message for guide sequences with a GC content >75 %. (PDF 66 kb)

Published
2016
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15. Additional file 7: Figure S3. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Subjects
sense organs, skin and connective tissue diseases
Abstract

MIT specificity scores calculated by the CRISPOR website for 28 guide sequences calculated based on predicted off-targets with up to four, five, and six mismatches. Only one label is shown for identical guide sequences from two different studies. A change from four to five allowed mismatches used in the scoring results in a change of the specificity scores but only in minor changes of the ranking of the guide sequences by specificity score. (PDF 23 kb)

Published
2016
Full Text
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16. Additional file 9: Figure S4. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Similar to Fig. 3 but using off-target predictions by the CRISPR Design website ( http://crispr.mit.edu/ ). a For the 28 tested guide sequences, MIT guide specificity scores as calculated by the MIT website (x-axis), number of off-targets (y-axis), and sum of off-target modification frequencies (circle size). b The specificity of the 28 tested guide sequences (blue) versus the specificity scores of all unique 20mers in human coding regions (green). The specificity score histogram was calculated by running 1000 randomly selected guide sequences from human coding regions through the CRISPR Design website ( http://crispr.mit.edu/ ). (PDF 40 kb)

Published
2016
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17. Additional file 3: Figure S1. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Overlap of off-target detection for the EMX1 and VEGFA guides tested by different assays. Off-targets are only shown if they were detected by at least a single study and with a frequency of 0.1 %. See Additional file 1: Tables S1 and Additional file 4: Table S2 for the modification frequencies and additional details on the off-targets for the guides EMX1 and VEGFA, respectively. Additional file 4: Table S2 also includes the data by Hsu et al. [7], who quantified cleavage at putative off-target loci predicted by the CRISPR Design website ( http://crispr.mit.edu/ ) with targeted deep sequencing, Tsai et al. [3], who isolated double-strand breaks with modified oligonucleotides followed by sequencing, Frock et al. [28], who detected translocations, and Kim et al. [33] and Kim et al. [27], who performed whole-genome sequencing to find CRISPR-induced modifications. For details on the different studies, see Additional file 1: Table S1. (PDF 17 kb)

Published
2016
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18. Additional file 3: Figure S1. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Overlap of off-target detection for the EMX1 and VEGFA guides tested by different assays. Off-targets are only shown if they were detected by at least a single study and with a frequency of 0.1 %. See Additional file 1: Tables S1 and Additional file 4: Table S2 for the modification frequencies and additional details on the off-targets for the guides EMX1 and VEGFA, respectively. Additional file 4: Table S2 also includes the data by Hsu et al. [7], who quantified cleavage at putative off-target loci predicted by the CRISPR Design website ( http://crispr.mit.edu/ ) with targeted deep sequencing, Tsai et al. [3], who isolated double-strand breaks with modified oligonucleotides followed by sequencing, Frock et al. [28], who detected translocations, and Kim et al. [33] and Kim et al. [27], who performed whole-genome sequencing to find CRISPR-induced modifications. For details on the different studies, see Additional file 1: Table S1. (PDF 17 kb)

Published
2016
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19. Additional file 17: Figure S7. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Precision/recall for the top quartile against the top quartile of the predictions. Positives are the top 25 % of each assay. Precision is defined as the ratio True positives/(True positives + False positives) or intuitively the ability of a score not to label as positive a sample that is negative. The recall is the ratio True positives/(True positives + False negatives) or intuitively the ability of a score to find all the positive samples. When the cost of the assay is high and there are many candidate guide sequences, e.g., for a long exon in rats, the priority may be on precision or, conversely, it may be on recall for a short exon in Drosophila. Data are separated into three parts: (1) U6-base data, (2) T7 in vitro data, (3) data from this study. The rules by Ren and Farboud are already binary; all other scores were considered a positive if the rank-percent of the score exceeded 75 %. The 75 rank-percent cutoffs were: Housden, 6.8; Wang, 78; Chari, 53; Doench, 32; Moreno-Mateos, 60; Xu, 42; Fusi, 62; Wong, 0. The 75 % cutoff for the Wong score is indeed 0 as most values of this score are 0. The Wong score has a good precision on the large U6-based datasets but a relatively low recall. Among the heuristics, the -GG rule from Farboud et al. has high precision for T7 in vitro transcription datasets, except for the Farboud dataset where some guides have been designed to fulfill the rule, so it is not unbiased. In U6-based datasets, most scores show a similar precision, but the Fusi et al. score has generally higher recall. (PDF 147 kb)

Published
2016
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20. Additional file 6: Figure S2. of Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR

Author

Haeussler, Maximilian, Schönig, Kai, Eckert, Hélène, Eschstruth, Alexis, Mianné, Joffrey, Jean-Baptiste Renaud, Schneider-Maunoury, Sylvie, Shkumatava, Alena, Teboul, Lydia, Kent, Jim, Jean-Stephane Joly, and Concordet, Jean-Paul

Abstract

Ratio of off-target to on-target cleavage for validated guide sequences. The two guides RAG1B and RAG1A are not shown on this plot as their on-target cleavage was not determined in the study by Frock et al. [28]. Studies in the legend are referenced by the first author’s name; in the case of Kim et al., the cell type is also indicated. For each guide, the sum of all off-target modification frequencies was divided by the on-target modification frequency, e.g., a ratio of 2 indicates that cleavage is twice as frequent on all off-targets taken together than on the target. To better show the two outliers, a portion of the x-axis and y-axis was cut out. The CRISPOR website and Genome Browser tracks show a warning message for guide sequences with a GC content >75 %. (PDF 66 kb)

Published
2016
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21. A dual origin of the pituitary primordium in the ascidian

Author

Kano, Shungo, Satou, Y., Deschet, K., Martin, P., Haeussler, Maximilian, Joly, Jean-Stephane, USC CNRS jeune équipe Développement, Evolution et Plasticité du Système Nerveux (DEPSN), Institut National de la Recherche Agronomique (INRA), Society for Integrative and Comparative Biology (SICB). USA., and ProdInra, Migration

Subjects
[SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio], embryonic structures, [INFO]Computer Science [cs], [INFO] Computer Science [cs]
Abstract

The pituitary is an essential endocrine organ in the vertebrates. While the urochordate possesses no distinct pituitary organ, it has been long proposed that the ascidian neural complex (NC) composes homologous organs to the brain and the pituitary. Recent molecular data suggests that the ciliated funnel (CF), one of the NC components, is the most probable candidate as several placodal genes including CiPitx are expressed at the ectodermal stomodaeum and the CF, respectively, in embryonic and the adult stages (Boorman and Shimeld, 2002; Christiaen et al., 2002). To reinforce this hypothesis with insights from the developmental process, we conducted lineage analyses mainly using a photo-convertible fluorescent protein Kaede driven with promoters recapitulating endogenous expressions of CiPitx and CiNut (the neural tube marker). We validated that a part of the ectodermal stomodeaum invaginates, separates from the major part and gives rise to the distal tip of the CF. Furthermore, we revealed that the proximal domain of the CF, which is adjacent to the distal tip, is derived from the neuroectodermal "dorsal duct". Thus, the ascidian CF has a dual origin and its organogenesis resembles the vertebrate pituitary. We then investigated whether the ectodermal CF expresses genes relevant to an endocrine activity like the vertebrate pituitary. However, we could not confirm it. It is likely that a pituitary primordium is present in the ascidian, but that the endocrine activity of the pituitary is a vertebrate innovation presumably with evolutions of adenohypophyseal transcription factors which terminally differentiate hormone-secreting cells.

Published
2010

22. Registered access: authorizing data access

Author

Dyke, Stephanie O.M., Linden, Mikael, Lappalainen, Ilkka, De Argila, Jordi R., Carey, Knox, Lloyd, David, Spalding, J.D., Cabili, Moran N., Kerry, Giselle, Foreman, Julia, Cutts, Tim, Shabani, Mahsa, Rodriguez, Laura L., Haeussler, Maximilian, Walsh, Brian, Jiang, Xiaoqian, Wang, Shuang, Perrett, Daniel, Boughtwood, Tiffany, Matern, Andreas, Brookes, Anthony J., Cupak, Miro, Fiume, Marc, Pandya, Ravi, Tulchinsky, Ilia, Scollen, Serena, Törnroos, Juha, Das, Samir, Evans, Alan C., Malin, Bradley A., Beck, Stephan, Brenner, Steven E., Nyrönen, Tommi, Blomberg, Niklas, Firth, Helen V., Hurles, Matthew, Philippakis, Anthony A., Rätsch, Gunnar, Brudno, Michael, Boycott, Kym M., Rehm, Heidi L., Baudis, Michael, Sherry, Stephen T., Kato, Kazuto, Knoppers, Bartha M., Baker, Dixie, and Flicek, Paul

Subjects
3. Good health
Abstract

The Global Alliance for Genomics and Health (GA4GH) proposes a data access policy model—“registered access”—to increase and improve access to data requiring an agreement to basic terms and conditions, such as the use of DNA sequence and health data in research. A registered access policy would enable a range of categories of users to gain access, starting with researchers and clinical care professionals. It would also facilitate general use and reuse of data but within the bounds of consent restrictions and other ethical obligations. In piloting registered access with the Scientific Demonstration data sharing projects of GA4GH, we provide additional ethics, policy and technical guidance to facilitate the implementation of this access model in an international setting., European Journal of Human Genetics, 26 (12), ISSN:1476-5438, ISSN:1018-4813

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