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Plasma membrane regulates Ras signaling networks

Cellular logistics 2016年第4期5卷 e1136374页

作者： Tanmay Sanjeev Chavan Serena Muratcioglu Richard Marszalek Hyunbum Jang Ozlem Keskin Attila Gursoy Ruth Nussinov Vadim Gaponenko Department of Medicinal Chemistry University of Illinois at Chicago Chicago IL USA. Center for Computational Biology and Bioinformatics Koc University Istanbul Turkey. Department of Biochemistry and Molecular Genetics Cancer and Inflammation Program Basic Science Program Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research National Cancer Institute at Frederick Frederick MD USA. Frederick MD USA Sackler Institute of Molecular Medicine Department of Human Genetics and Molecular Medicine Sackler School of Medicine Tel Aviv University Tel Aviv Israel.

Ras GTPases activate more than 20 signaling pathways, regulating such essential cellular functions as proliferation, survival, and migration. How Ras proteins control their signaling diversity is still a mystery. Several pieces of evidence suggest that the plasma membrane plays a critical role. Among these are: (1) selective recruitment of Ras and its effectors to particular localities allowing access to Ras regulators and effectors; (2) specific membrane-induced conformational changes promoting Ras functional diversity; and (3) oligomerization of membrane-anchored Ras to recruit and activate Raf. Taken together, the membrane does not only attract and retain Ras but also is a key regulator of Ras signaling. This can already be gleaned from the large variability in the sequences of Ras membrane targeting domains, suggesting that localization, environment and orientation are important factors in optimizing the function of Ras isoforms.

关键词： Ras GTPases Ras oligomerization Ras signaling lipid rafts membrane microdomains plasma membrane

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Author Correction: Federated learning enables big data for rare cancer boundary detection

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Nature communications 2023年第1期14卷 436页

作者： Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI

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Admixture mapping analysis in the context of GWAS with GAW18 data

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BMC proceedings 2014年第SUPPL 1期8卷 S3页

作者： Mengjie Chen Can Yang Cong Li Lin Hou Xiaowei Chen Hongyu Zhao Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Biostatistics Yale School of Public Health Yale University New Haven CT 06520 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA

Admixture mapping is a disease-mapping strategy to identify disease susceptibility variants in an admixed population that is a result of mating between 2 historically separated populations differing in allele frequencies and disease prevalence. With the increasing availability of high-density genotyping data generated in genome-wide association studies, it is of interest to investigate how to apply admixture mapping in the context of the genome-wide association studies and how to adjust for admixture in association tests. In this study, we first evaluated 3 different local ancestry inference methods, LAMP, LAMP-LD, and MULTIMIX. Then we applied admixture mapping analysis based on estimated local ancestry. Finally, we performed association tests with adjustment for local ancestry.

关键词： Reference Panel Admixture Mapping Local Ancestry Native American Ancestry Human Genome Diversity Project

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28 GBshape: a genome browser database for DNA shape annotations

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Journal of Biomolecular Structure and Dynamics 2015年第SUPP 1期33卷 16页

作者： Tsu-Pei Chiu[a][*] Lin Yang[a] Tianyin Zhou[a] Bradley J. Main[a] Stephen C.J. Parker[b] Sergey V. Nuzhdin[a] Thomas D. Tullius[c] Remo Rohs[a] [a] Molecular and Computational Biology Program Department of Biological Sciences University of Southern California Los Angeles CA 90089 USA[b] Departments of Computational Medicine and Bioinformatics and Human Genetics University of Michigan Ann Arbor MI 48109 USA[c] Department of Chemistry and Program in Bioinformatics Boston University Boston MA 02215 USA

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Publisher Correction: Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

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Nature communications 2018年第1期9卷 3493页

作者： Seyedeh M Zekavat Sanni Ruotsalainen Robert E Handsaker Maris Alver Jonathan Bloom Timothy Poterba Cotton Seed Jason Ernst Mark Chaffin Jesse Engreitz Gina M Peloso Ani Manichaikul Chaojie Yang Kathleen A Ryan Mao Fu W Craig Johnson Michael Tsai Matthew Budoff Ramachandran S Vasan L Adrienne Cupples Jerome I Rotter Stephen S Rich Wendy Post Braxton D Mitchell Adolfo Correa Andres Metspalu James G Wilson Veikko Salomaa Manolis Kellis Mark J Daly Benjamin M Neale Steven McCarroll Ida Surakka Tonu Esko Andrea Ganna Samuli Ripatti Sekar Kathiresan Pradeep Natarajan Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA 02142 USA. Yale School of Medicine New Haven CT 06510 USA. Department of Computational Biology & Bioinformatics Yale University New Haven CT 06510 USA. Institute for Molecular Medicine University of Helsinki Helsinki Finland. Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA 02142 USA. Department of Genetics Harvard Medical School Boston MA 02115 USA. Department of Biotechnology Institute of Molecular and Cell Biology University of Tartu Tartu Estonia. Estonian Genome Center Tallinn Estonia. Analytic and Translational Genetics Unit Boston MA 02142 USA. Department of Biological Chemistry University of California Los Angeles Los Angeles CA 90095 USA. Department of Biostatistics Boston University School of Public Health Boston MA 02118 USA. Center for Public Health Genomics University of Virginia Charlottesville VA 22904 USA. Program in Personalized and Genomic Medicine Division of Endocrinology Diabetes & Nutrition Department of Medicine University of Maryland School of Medicine Baltimore MD 21201 USA. Department of Biostatistics School of Public Health and Community Medicine University of Washington Seattle WA 98195 USA. Department of Laboratory Medicine and Pathology University of Minnesota Minneapolis MN 55455 USA. Division of Cardiology Harbor-UCLA Medical Center Los Angeles Biomedical Research Institute Los Angeles CA 90509 USA. NHLBI Framingham Heart Study Framingham MA 20892 USA. Sections of Preventive medicine and Epidemiology and cardiovascular medicine Departments of Medicine and Epidemiology Boston university Schools of Medicine and Public health Boston MA 02118 USA. Departments of Pediatrics and Medicine The Institute for Translational Genomics and Population Sciences Los Angeles Biomedical Research Institute Harbor-UCLA Medical Center Torrance CA 90509 USA. Division of Cardiology

The original version of this article contained an error in the name of the author Ramachandran S. Vasan, which was incorrectly given as Vasan S. Ramachandran. This has now been corrected in both the PDF and HTML versi...

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Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 765, 2017)

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NATURE GENETICS 2018年第5期50卷 765-766页

作者： Turcot, Valerie Lu, Yingchang Highland, Heather M. Schurmann, Claudia Justice, Anne E. Fine, Rebecca S. Bradfield, Jonathan P. Esko, Tonu Giri, Ayush Graff, Mariaelisa Guo, Xiuqing Hendricks, Audrey E. Karaderi, Tugce Lempradl, Adelheid Locke, Adam E. Mahajan, Anubha Marouli, Eirini Sivapalaratnam, Suthesh Young, Kristin L. Alfred, Tamuno Feitosa, Mary F. Masca, Nicholas G. D. Manning, Alisa K. Medina-Gomez, Carolina Mudgal, Poorva Ng, Maggie C. Y. Reiner, Alex P. Vedantam, Sailaja Willems, Sara M. Winkler, Thomas W. Abecasis, Goncalo Aben, Katja K. Alam, Dewan S. Alharthi, Sameer E. Allison, Matthew Amouyel, Philippe Asselbergs, Folkert W. Auer, Paul L. Balkau, Beverley Bang, Lia E. Barroso, Ines Bastarache, Lisa Benn, Marianne Bergmann, Sven Bielak, Lawrence F. Bluher, Matthias Boehnke, Michael Boeing, Heiner Boerwinkle, Eric Boger, Carsten A. Bork-Jensen, Jette Bots, Michiel L. Bottinger, Erwin P. Bowden, Donald W. Brandslund, Ivan Breen, Gerome Brilliant, Murray H. Broer, Linda Brumat, Marco Burt, Amber A. Butterworth, Adam S. Campbell, Peter T. Cappellani, Stefania Carey, David J. Catamo, Eulalia Caulfield, Mark J. Chambers, John C. Chasman, Daniel I. Chen, Yii-Der I. Chowdhury, Rajiv Christensen, Cramer Chu, Audrey Y. Cocca, Massimiliano Collins, Francis S. Cook, James P. Corley, Janie Galbany, Jordi Corominas Cox, Amanda J. Crosslin, David S. Cuellar-Partida, Gabriel D'Eustacchio, Angela Danesh, John Davies, Gail Bakker, Paul I. W. Groot, Mark C. H. Mutsert, Renee Deary, Ian J. Dedoussis, George Demerath, Ellen W. Heijer, Martin Hollander, Anneke I. Ruijter, Hester M. Dennis, Joe G. Denny, Josh C. Angelantonio, Emanuele Drenos, Fotios Du, Mengmeng Dube, Marie-Pierre Dunning, Alison M. Easton, Douglas F. Edwards, Todd L. Ellinghaus, David Ellinor, Patrick T. Elliott, Paul Evangelou, Evangelos Farmaki, Aliki-Eleni Farooqi, I. Sadaf Faul, Jessica D. Fauser, Sascha Feng, Shuang Ferrannini, Ele Ferrieres, Jean Florez, Jose C. Ford, Ian Fornage, Myriam Franco, Oscar H. Franke, Andre Franks, Paul W. Friedrich, Ne Montreal Heart Institute Université de Montréal Montreal Quebec Canada Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University School of Medicine Nashville TN USA Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA Genetics of Obesity and Related Metabolic Traits Program Icahn School of Medicine at Mount Sinai New York NY USA Department of Epidemiology University of North Carolina Chapel Hill NC USA Human Genetics Center University of Texas School of Public Health University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences University of Texas Health Science Center at Houston Houston TX USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Genetics Harvard Medical School Boston MA USA Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children’s Hospital Boston MA USA Center for Applied Genomics Division of Human Genetics Children’s Hospital of Philadelphia Philadelphia PA USA Quantinuum Research LLC San Diego CA USA Estonian Genome Center University of Tartu Tartu Estonia Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Nashville TN USA Institute for Translational Genomics and Population Sciences LABioMed at Harbor-UCLA Medical Center Torrance CA USA Wellcome Trust Sanger Institute Hinxton UK Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK Department of Biological Sciences Faculty of Arts and Sciences Eastern Mediterranean University Famagusta Cyprus Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (***35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

关键词： Genome-wide association studies Obesity

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Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

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Nature genetics 2019年第7期51卷 1191-1192页

作者： Valérie Turcot Yingchang Lu Heather M Highland Claudia Schurmann Anne E Justice Rebecca S Fine Jonathan P Bradfield Tõnu Esko Ayush Giri Mariaelisa Graff Xiuqing Guo Audrey E Hendricks Tugce Karaderi Adelheid Lempradl Adam E Locke Anubha Mahajan Eirini Marouli Suthesh Sivapalaratnam Kristin L Young Tamuno Alfred Mary F Feitosa Nicholas G D Masca Alisa K Manning Carolina Medina-Gomez Poorva Mudgal Maggie C Y Ng Alex P Reiner Sailaja Vedantam Sara M Willems Thomas W Winkler Gonçalo Abecasis Katja K Aben Dewan S Alam Sameer E Alharthi Matthew Allison Philippe Amouyel Folkert W Asselbergs Paul L Auer Beverley Balkau Lia E Bang Inês Barroso Lisa Bastarache Marianne Benn Sven Bergmann Lawrence F Bielak Matthias Blüher Michael Boehnke Heiner Boeing Eric Boerwinkle Carsten A Böger Jette Bork-Jensen Michiel L Bots Erwin P Bottinger Donald W Bowden Ivan Brandslund Gerome Breen Murray H Brilliant Linda Broer Marco Brumat Amber A Burt Adam S Butterworth Peter T Campbell Stefania Cappellani David J Carey Eulalia Catamo Mark J Caulfield John C Chambers Daniel I Chasman Yii-Der I Chen Rajiv Chowdhury Cramer Christensen Audrey Y Chu Massimiliano Cocca Francis S Collins James P Cook Janie Corley Jordi Corominas Galbany Amanda J Cox David S Crosslin Gabriel Cuellar-Partida Angela D'Eustacchio John Danesh Gail Davies Paul I W Bakker Mark C H Groot Renée Mutsert Ian J Deary George Dedoussis Ellen W Demerath Martin Heijer Anneke I Hollander Hester M Ruijter Joe G Dennis Josh C Denny Emanuele Di Angelantonio Fotios Drenos Mengmeng Du Marie-Pierre Dubé Alison M Dunning Douglas F Easton Todd L Edwards David Ellinghaus Patrick T Ellinor Paul Elliott Evangelos Evangelou Aliki-Eleni Farmaki I Sadaf Farooqi Jessica D Faul Sascha Fauser Shuang Feng Ele Ferrannini Jean Ferrieres Jose C Florez Ian Ford Myriam Fornage Oscar H Franco Andre Franke Paul W Franks Nele Friedrich Ruth Frikke-Schmidt Tessel E Galesloot Wei Gan Ilaria Gandin Paolo Gasparini Jane Gibson Vilmantas Giedraitis Anette P Gjesing Penny Gordon-Larsen Mathias Gorski Hans-Jörgen Montreal Heart Institute Université de Montréal Montreal Quebec Canada. Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University School of Medicine Nashville TN USA. Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA. Genetics of Obesity and Related Metabolic Traits Program Icahn School of Medicine at Mount Sinai New York NY USA. Department of Epidemiology University of North Carolina Chapel Hill NC USA. Human Genetics Center University of Texas School of Public Health University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences University of Texas Health Science Center at Houston Houston TX USA. Broad Institute of MIT and Harvard Cambridge MA USA. Department of Genetics Harvard Medical School Boston MA USA. Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children's Hospital Boston MA USA. Center for Applied Genomics Division of Human Genetics Children's Hospital of Philadelphia Philadelphia PA USA. Quantinuum Research LLC San Diego CA USA. Estonian Genome Center University of Tartu Tartu Estonia. Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Nashville TN USA. Institute for Translational Genomics and Population Sciences LABioMed at Harbor-UCLA Medical Center Torrance CA USA. Wellcome Trust Sanger Institute Hinxton UK. Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA. Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK. Department of Biological Sciences Faculty of Arts and Sciences Eastern Mediterranean University Famagusta Cyprus. Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany. Department of Biostatistics and Center for Statistical Genetics University of M

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Adjustment of familial relatedness in association test for rare variants

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BMC proceedings 2014年第SUPPL 1 GENETIC ANALYSIS WORKSHOP 18VANESSA OLMO期8卷 S39页

作者： Cong Li Can Yang Mengjie Chen Xiaowei Chen Lin Hou Hongyu Zhao Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Biostatistics Yale School of Public Health 60 College Street New Haven CT 06520 USA.

High-throughput sequencing technology allows researchers to test associations between phenotypes and all the variants identified throughout the genome, and is especially useful for analyzing rare variants. However, the statistical power to identify phenotype-associated rare variants is very low with typical genome-wide association studies because of their low allele frequencies among unrelated individuals. In contrast, a family-based design may have more power because rare variants are more likely to be enriched in families than among unrelated individuals. Regardless, an analysis of family-based association studies needs to account appropriately for relatedness between family members. We analyzed the observed quantitative trait systolic blood pressure as well as the simulated Q1 data in the Genetic Analysis Workshop 18 data set using 4 tests: (a) a single-variant test, (b) a collapsing test, (c) a single-variant test where familial relatedness was accounted for, and (d) a collapsing test where familial relatedness was accounted for. We then compared the results of the 4 methods and observed that adjusting for familial relatedness could appropriately control the false-positive rate while maintaining reasonable power to detect several strongly associated variants/genes.

关键词： Linear Mixed Model Rare Variant Genetic Analysis Workshop Familial Relatedness Genetic Similarity Matrix

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Flor Revisited(Again):eQTL and Mutational Analysis of NB-LRR Mediated Immunity to Powdery Mildew in Barley

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Journal of Integrative Agriculture 2014年第2期13卷 237-243页

作者： Roger Wise Priyanka Surana Greg Fuerst Ruo Xu Divya Mistry Julie Dickerson Dan Nettleton Corn Insects and Crop Genetics Research Unit U.S.Department of Agriculture-Agricultural Research ServiceIowa State UniversityAmesIowa 50011USA Department of Plant Pathology & Microbiology Center for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIowa 50011USA Department of Statistics Iowa State UniversityAmesIowa 50011USA Department of Electrical and Computer Engineering Iowa State UniversityAmesIowa 50011USA

Genes encoding early signaling events in pathogen defense often are identified only by their phenotype. Such genes involved in barley-powdery mildew interactions include Mla, specifying race-specific resistance; Rarl （Required for Mla12-specified resistance1）, and Roml （Restoration of Mla-specified resistancel）. The HSP90-SGT1-RAR1 complex appears to function as chaperone in MLA-specified resistance, however, much remains to be discovered regarding the precise signaling underlying plant immunity. Genetic analyses of fast-neutron mutants derived from CI 16151 （Mla6） uncovered a novel locus, designated Rar3 （R_equired for Mla6-specified resitance3）. Rar3 segregates independent of Mla6 and Rarl, and rar3 mutants are susceptible to Blumeria graminis f. sp. hordei （Bgh） isolate 5874 （A VRar）, whereas, wild-type progenitor plants are resistant. Comparative expression analyses of the rar3 mutant vs. its wild-type progenitor were conducted via Barleyl GeneChip and GAIIx paired-end RNA-Seq. Whereas Rarl affects transcription of relatively few genes; Rar3 appears to influence thousands, notably in genes controlling ATP binding, catalytic activity, transcription, and phosphorylation; possibly membrane bound or in the nucleus, eQTL analysis of a segregating doubled haploid population identified over two-thousand genes as being regulated by Mla （q value/FDR=0.00001）, a subset of which are significant in Rar3 interactions. The intersection of datasets derived from mla-loss-of-function mutants, Mla-associated eQTL, and rar3-mediated transcriptome reprogramming are narrowing the focus on essential genes required for Mla-specified immunity.

关键词： eQTL transcript profiling immunity resistance signaling barley Blumeria graminis

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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

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JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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