Genome-Wide Association Study Identifies Genetic Susceptibility Loci
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Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
A Yeast Phenomic Model for the Gene Interaction Network Modulating
Louie et al. Genome Medicine 2012, 4:103 http://genomemedicine.com/content/4/12/103 RESEARCH Open Access A yeast phenomic model for the gene interaction network modulating CFTR-ΔF508 protein biogenesis Raymond J Louie3†, Jingyu Guo1,2†, John W Rodgers1, Rick White4, Najaf A Shah1, Silvere Pagant3, Peter Kim3, Michael Livstone5, Kara Dolinski5, Brett A McKinney6, Jeong Hong2, Eric J Sorscher2, Jennifer Bryan4, Elizabeth A Miller3* and John L Hartman IV1,2* Abstract Background: The overall influence of gene interaction in human disease is unknown. In cystic fibrosis (CF) a single allele of the cystic fibrosis transmembrane conductance regulator (CFTR-ΔF508) accounts for most of the disease. In cell models, CFTR-ΔF508 exhibits defective protein biogenesis and degradation rather than proper trafficking to the plasma membrane where CFTR normally functions. Numerous genes function in the biogenesis of CFTR and influence the fate of CFTR-ΔF508. However it is not known whether genetic variation in such genes contributes to disease severity in patients. Nor is there an easy way to study how numerous gene interactions involving CFTR-ΔF would manifest phenotypically. Methods: To gain insight into the function and evolutionary conservation of a gene interaction network that regulates biogenesis of a misfolded ABC transporter, we employed yeast genetics to develop a ‘phenomic’ model, in which the CFTR-ΔF508-equivalent residue of a yeast homolog is mutated (Yor1-ΔF670), and where the genome is scanned quantitatively for interaction. We first confirmed that Yor1-ΔF undergoes protein misfolding and has reduced half-life, analogous to CFTR-ΔF. Gene interaction was then assessed quantitatively by growth curves for approximately 5,000 double mutants, based on alteration in the dose response to growth inhibition by oligomycin, a toxin extruded from the cell at the plasma membrane by Yor1. -
Whole Genome Sequencing Identifies Novel Structural Variant in a Large Indian Family Affected with X - Linked Agammaglobulinemia
medRxiv preprint doi: https://doi.org/10.1101/2020.10.05.20200949; this version posted October 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license . Whole Genome Sequencing identifies novel structural variant in a large Indian family affected with X - linked agammaglobulinemia 1,2,# 3,5,#,$ 3,4 3 Abhinav Jain , Geeta Madathil Govindaraj , Athulya Edavazhippurath , Nabeel Faisal , Rahul C 1 1,2 6 3 1 1 Bhoyar , Vishu Gupta , Ramya Uppuluri , Shiny Padinjare Manakkad , Atul Kashyap , Anoop Kumar , 1,2 1,2 7 7 3 Mohit Kumar Divakar , Mohamed Imran , Sneha Sawant , Aparna Dalvi , Krishnan Chakyar , 7 6 1,2,$ 1,2,$ Manisha Madkaikar , Revathi Raj , Sridhar Sivasubbu , Vinod Scaria 1 CSIR-Institute of Genomics and Integrative Biology, Mathura Road, New Delhi, Delhi, India 2 Academy of Scientific and Innovative Research (AcSIR), Mathura Road, New Delhi, Delhi, India 3 Department of Pediatrics, Government Medical College Kozhikode, Kozhikode, Kerala, India 4 Multidisciplinary Research Unit, Government College Kozhikode, Kozhikode, Kerala, India 5 FPID Regional Diagnostic Centre, Government Medical College Kozhikode, Kozhikode, Kerala India 6 Department of Pediatric Hematology, Oncology, Blood and Marrow Transplantation, Apollo Hospitals, 320, Padma complex, Anna salai, Teynampet, Chennai, Tamil Nadu, India 7 Department of Pediatric Immunology and Leukocyte Biology, ICMR-National Institute of Immunohaematology, KEM Hospital, Parel, Mumbai, Maharashtra, India. # Joint first authors $ Corresponding author Vinod Scaria: [email protected] Sridhar Sivasubbu: [email protected] Geeta Madathil Govindaraj: [email protected] NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. -
Exome Sequencing and Functional Validation in Zebrafish Identify
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector REPORT Exome Sequencing and Functional Validation in Zebrafish Identify GTDC2 Mutations as a Cause of Walker-Warburg Syndrome M. Chiara Manzini,1,2 Dimira E. Tambunan,1,2 R. Sean Hill,1,2 Tim W. Yu,1,2 Thomas M. Maynard,3 Erin L. Heinzen,4 Kevin V. Shianna,4 Christine R. Stevens,5 Jennifer N. Partlow,1,2 Brenda J. Barry,1,2 Jacqueline Rodriguez,1,2 Vandana A. Gupta,1,6 Abdel-Karim Al-Qudah,7 Wafaa M. Eyaid,8 Jan M. Friedman,9,10 Mustafa A. Salih,11 Robin Clark,12 Isabella Moroni,13 Marina Mora,14 Alan H. Beggs,1,6 Stacey B. Gabriel,5 and Christopher A. Walsh1,2,5,* Whole-exome sequencing (WES), which analyzes the coding sequence of most annotated genes in the human genome, is an ideal approach to studying fully penetrant autosomal-recessive diseases, and it has been very powerful in identifying disease-causing muta- tions even when enrollment of affected individuals is limited by reduced survival. In this study, we combined WES with homozygosity analysis of consanguineous pedigrees, which are informative even when a single affected individual is available, to identify genetic mutations responsible for Walker-Warburg syndrome (WWS), a genetically heterogeneous autosomal-recessive disorder that severely affects the development of the brain, eyes, and muscle. Mutations in seven genes are known to cause WWS and explain 50%–60% of cases, but multiple additional genes are expected to be mutated because unexplained cases show suggestive linkage to diverse loci. -
Genomic Approaches for Understanding the Genetics of Complex Disease
Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Perspective Genomic approaches for understanding the genetics of complex disease William L. Lowe Jr.1 and Timothy E. Reddy2,3 1Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA; 2Department of Biostatistics and Bioinformatics, Duke University Medical School, Durham, North Carolina 27708, USA; 3Center for Genomic and Computational Biology, Duke University Medical School, Durham, North Carolina 27708, USA There are thousands of known associations between genetic variants and complex human phenotypes, and the rate of novel discoveries is rapidly increasing. Translating those associations into knowledge of disease mechanisms remains a fundamental challenge because the associated variants are overwhelmingly in noncoding regions of the genome where we have few guiding principles to predict their function. Intersecting the compendium of identified genetic associations with maps of regulatory activity across the human genome has revealed that phenotype-associated variants are highly enriched in candidate regula- tory elements. Allele-specific analyses of gene regulation can further prioritize variants that likely have a functional effect on disease mechanisms; and emerging high-throughput assays to quantify the activity of candidate regulatory elements are a promising next step in that direction. Together, these technologies have created the ability to systematically and empirically test hypotheses about the function of noncoding variants and haplotypes at the scale needed for comprehensive and system- atic follow-up of genetic association studies. Major coordinated efforts to quantify regulatory mechanisms across genetically diverse populations in increasingly realistic cell models would be highly beneficial to realize that potential. -
WO 2012/174282 A2 20 December 2012 (20.12.2012) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2012/174282 A2 20 December 2012 (20.12.2012) P O P C T (51) International Patent Classification: David [US/US]; 13539 N . 95th Way, Scottsdale, AZ C12Q 1/68 (2006.01) 85260 (US). (21) International Application Number: (74) Agent: AKHAVAN, Ramin; Caris Science, Inc., 6655 N . PCT/US20 12/0425 19 Macarthur Blvd., Irving, TX 75039 (US). (22) International Filing Date: (81) Designated States (unless otherwise indicated, for every 14 June 2012 (14.06.2012) kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, English (25) Filing Language: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, Publication Language: English DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, KR, (30) Priority Data: KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, 61/497,895 16 June 201 1 (16.06.201 1) US MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, 61/499,138 20 June 201 1 (20.06.201 1) US OM, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SC, SD, 61/501,680 27 June 201 1 (27.06.201 1) u s SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, 61/506,019 8 July 201 1(08.07.201 1) u s TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. -
QTL Analysis Reveals Genomic Variants Linked to High-Temperature
Wang et al. Biotechnol Biofuels (2019) 12:59 https://doi.org/10.1186/s13068-019-1398-7 Biotechnology for Biofuels RESEARCH Open Access QTL analysis reveals genomic variants linked to high-temperature fermentation performance in the industrial yeast Zhen Wang1,2†, Qi Qi1,2†, Yuping Lin1*, Yufeng Guo1, Yanfang Liu1,2 and Qinhong Wang1* Abstract Background: High-temperature fermentation is desirable for the industrial production of ethanol, which requires thermotolerant yeast strains. However, yeast thermotolerance is a complicated quantitative trait. The understanding of genetic basis behind high-temperature fermentation performance is still limited. Quantitative trait locus (QTL) map- ping by pooled-segregant whole genome sequencing has been proved to be a powerful and reliable approach to identify the loci, genes and single nucleotide polymorphism (SNP) variants linked to quantitative traits of yeast. Results: One superior thermotolerant industrial strain and one inferior thermosensitive natural strain with distinct high-temperature fermentation performances were screened from 124 Saccharomyces cerevisiae strains as parent strains for crossing and segregant isolation. Based on QTL mapping by pooled-segregant whole genome sequencing as well as the subsequent reciprocal hemizygosity analysis (RHA) and allele replacement analysis, we identifed and validated total eight causative genes in four QTLs that linked to high-temperature fermentation of yeast. Interestingly, loss of heterozygosity in fve of the eight causative genes including RXT2, ECM24, CSC1, IRA2 and AVO1 exhibited posi- tive efects on high-temperature fermentation. Principal component analysis (PCA) of high-temperature fermentation data from all the RHA and allele replacement strains of those eight genes distinguished three superior parent alleles including VPS34, VID24 and DAP1 to be greatly benefcial to high-temperature fermentation in contrast to their inferior parent alleles. -
Supplementary Material Contents
Supplementary Material Contents Immune modulating proteins identified from exosomal samples.....................................................................2 Figure S1: Overlap between exosomal and soluble proteomes.................................................................................... 4 Bacterial strains:..............................................................................................................................................4 Figure S2: Variability between subjects of effects of exosomes on BL21-lux growth.................................................... 5 Figure S3: Early effects of exosomes on growth of BL21 E. coli .................................................................................... 5 Figure S4: Exosomal Lysis............................................................................................................................................ 6 Figure S5: Effect of pH on exosomal action.................................................................................................................. 7 Figure S6: Effect of exosomes on growth of UPEC (pH = 6.5) suspended in exosome-depleted urine supernatant ....... 8 Effective exosomal concentration....................................................................................................................8 Figure S7: Sample constitution for luminometry experiments..................................................................................... 8 Figure S8: Determining effective concentration ......................................................................................................... -
Genetic Identification of Brain Cell Types Underlying Schizophrenia
bioRxiv preprint doi: https://doi.org/10.1101/145466; this version posted June 2, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Genetic identification of brain cell types underlying schizophrenia Nathan G. Skene 1 †, Julien Bryois 2 †, Trygve E. Bakken3, Gerome Breen 4,5, James J Crowley 6, Héléna A Gaspar 4,5, Paola Giusti-Rodriguez 6, Rebecca D Hodge3, Jeremy A. Miller 3, Ana Muñoz-Manchado 1, Michael C O’Donovan 7, Michael J Owen 7, Antonio F Pardiñas 7, Jesper Ryge 8, James T R Walters 8, Sten Linnarsson 1, Ed S. Lein 3, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Patrick F Sullivan 2,6 *, Jens Hjerling- Leffler 1 * Affiliations: 1 Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-17177 Stockholm, Sweden. 2 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, SE-17177 Stockholm, Sweden. 3 Allen Institute for Brain Science, Seattle, Washington 98109, USA. 4 King’s College London, Institute of Psychiatry, Psychology and Neuroscience, MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, London, UK. 5 National Institute for Health Research Biomedical Research Centre, South London and Maudsley National Health Service Trust, London, UK. 6 Departments of Genetics, University of North Carolina, Chapel Hill, NC, 27599-7264, USA. 7 MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK. -
A Comprehensive Database of Putative Human Microrna Target Site
bioRxiv preprint doi: https://doi.org/10.1101/554485; this version posted May 26, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. dbMTS: a comprehensive database of putative human microRNA target site SNVs and their functional predictions Chang Li1,2, Michael D. Swartz3, Bing Yu1, Yongsheng Bai4, Xiaoming Liu1,2* 1Human Genetics Center and Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 2USF Genomics, College of Public Health, University of South Florida, Tampa, FL 3Department of Biostatistics, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 4Department of Internal Medicine, University of Michigan, Ann Arbor, MI *Correspondence: Xiaoming Liu, [email protected] Funding information: This work is supported partially by NIH funding 1UM1HG008898 and partially by the startup funding for XL from the University of South Florida. bioRxiv preprint doi: https://doi.org/10.1101/554485; this version posted May 26, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract microRNAs (miRNAs) are short non-coding RNAs that can repress the expression of protein coding messenger RNAs (mRNAs) by binding to the 3’UTR of the target. -
Interleukin 10 Mutant Zebrafish Have an Enhanced Interferon
www.nature.com/scientificreports OPEN Interleukin 10 mutant zebrafsh have an enhanced interferon gamma response and improved Received: 22 August 2017 Accepted: 20 June 2018 survival against a Mycobacterium Published: xx xx xxxx marinum infection Sanna-Kaisa E. Harjula1, Markus J. T. Ojanen1,2, Sinja Taavitsainen3, Matti Nykter3 & Mika Rämet1,4,5,6 Tuberculosis ranks as one of the world’s deadliest infectious diseases causing more than a million casualties annually. IL10 inhibits the function of Th1 type cells, and IL10 defciency has been associated with an improved resistance against Mycobacterium tuberculosis infection in a mouse model. Here, we utilized M. marinum infection in the zebrafsh (Danio rerio) as a model for studying Il10 in the host response against mycobacteria. Unchallenged, nonsense il10e46/e46 mutant zebrafsh were fertile and phenotypically normal. Following a chronic mycobacterial infection, il10e46/e46 mutants showed enhanced survival compared to the controls. This was associated with an increased expression of the Th cell marker cd4-1 and a shift towards a Th1 type immune response, which was demonstrated by the upregulated expression of tbx21 and ifng1, as well as the down-regulation of gata3. In addition, at 8 weeks post infection il10e46/e46 mutant zebrafsh had reduced expression levels of proinfammatory cytokines tnf and il1b, presumably indicating slower progress of the infection. Altogether, our data show that Il10 can weaken the immune defense against M. marinum infection in zebrafsh by restricting ifng1 response. Importantly, our fndings support the relevance of M. marinum infection in zebrafsh as a model for tuberculosis. Annually more than 10 million new tuberculosis cases are estimated to emerge, leading to over a million casualties1. -
Comparison of Structural and Short Variants Detectedby Linked-Read
cancers Article Comparison of Structural and Short Variants Detected by Linked-Read and Whole-Exome Sequencing in Multiple Myeloma Ashwini Kumar 1,2 , Sadiksha Adhikari 1,2, Matti Kankainen 2,3,4,5 and Caroline A. Heckman 1,2,* 1 Institute for Molecular Medicine Finland-FIMM, HiLIFE-Helsinki Institute of Life Science, iCAN Digital Cancer Medicine Flagship, University of Helsinki, Tukholmankatu 8, 00290 Helsinki, Finland; ashwini.kumar@helsinki.fi (A.K.); sadiksha.adhikari@helsinki.fi (S.A.) 2 iCAN Digital Precision Cancer Medicine, University of Helsinki, 00014 Helsinki, Finland; matti.kankainen@helsinki.fi 3 Medical and Clinical Genetics, University of Helsinki, Helsinki University Hospital, 00029 Helsinki, Finland 4 Translational Immunology Research Program and Department of Clinical Chemistry, University of Helsinki, 00290 Helsinki, Finland 5 Hematology Research Unit Helsinki, Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, 00290 Helsinki, Finland * Correspondence: caroline.heckman@helsinki.fi; Tel.: +358-29-412-5769 Simple Summary: The wide variety of next-generation sequencing technologies requires thorough evaluation and understanding of their advantages and shortcomings of these different approaches prior to their implementation in a precision medicine setting. Here, we compared the performance of two DNA sequencing methods, whole-exome and linked-read exome sequencing, to detect large Citation: Kumar, A.; Adhikari, S.; structural variants (SVs) and short variants in eight multiple myeloma (MM) patient cases. For three Kankainen, M.; Heckman, C.A. patient cases, matched tumor-normal samples were sequenced with both methods to compare somatic Comparison of Structural and Short SVs and short variants. The methods’ clinical relevance was also evaluated, and their sensitivity Variants Detected by Linked-Read and specificity to detect MM-specific cytogenetic alterations and other short variants were measured.