Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Analysis of schizophrenia susceptibility variants identified by GWAS : a bioinformatics and molecular genetics approach
Thesis (MSc)--Stellenbosch University, 2014.
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | en_ZA |
| Published: |
Stellenbosch : Stellenbosch University
2015
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867614066452725760 |
|---|---|
| access_status_str | Open Access |
| author | Coffee, Michelle |
| author2 | Warnich, L.
|
| author_browse | Coffee, Michelle Warnich, L. |
| author_facet | Warnich, L.
Coffee, Michelle |
| author_sort | Coffee, Michelle |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2014. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/95790 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:46:07.073Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/95790 Analysis of schizophrenia susceptibility variants identified by GWAS : a bioinformatics and molecular genetics approach Coffee, Michelle Warnich, L. Niehaus, D. J. H. Stellenbosch University. Faculty of AgriSciences. Dept. of Genetics. Schizophrenia Genome wide association studies (GWAS) Bioinformatics Molecular genetics UCTD Thesis (MSc)--Stellenbosch University, 2014. ENGLISH ABSTRACT: Described as one of the costliest and most debilitating disorders, schizophrenia has proven to be among the greatest challenges for medical researchers. The disorder poses difficulties on all levels: from genotype to phenotype. Even though it is known that there is a substantial genetic contribution to schizophrenia susceptibility (~80%), it is unknown whether this is due to common variants, rare variants, epigenetic factors, polymorphisms in regulatory regions of the genome or a combination of all these factors. Over the past few decades, many approaches have been employed to elucidate the genetic architecture of schizophrenia, with the latest and most promising being genome wide association studies (GWAS). However, nearly a decade after the first GWAS, the limitations are increasingly being recognised and new avenues need to be explored. Studies have recently started to focus on the analysis of non-coding regions of the genome since these regions harbour the majority of variants identified in GWAS thus far. This study aimed to use recently developed programs that utilize data from large scale studies such as previous GWAS, the Encyclopaedia of DNA Elements (ENCODE), 1000 Genomes, HapMap and Functional Annotation of the Mammalian Genome (FANTOM) to establish a simple, yet effective bioinformatics pipeline for the identification and assessment of variants in regulatory regions. Using the established workflow, 149 single nucleotide polymorphisms (SNPs) in regulatory regions were implicated in schizophrenia susceptibility, with the most significant SNP being rs200981. Pathway and network analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and GeneMANIA respectively indicated that the most frequently affected genes were involved in immune responses or neurodevelopmental processes, which support previous findings. Yet, novel findings of this study implicated processes crucial for DNA packaging (from DNA level to chromatin level). The second part of the study used restriction fragment length polymorphism analysis of polymerase chain reaction-amplified fragments (PCR-RFLP) to genotype ten of the most significant SNPs (identified by bioinformatic analyses in the first part of the study) in a South African Xhosa cohort of 100 cases and 100 controls, while bi-directional Sanger sequencing was used to confirm the presence of these SNPs. Statistical analyses revealed two haplotypes of regulatory variants, rs200483-rs200485-rs2517611 (p = 0.0385; OR = 1.71; 95% CI = 1.01-2.91) and rs200981-rs2517611-rs3129701 (p = 0.041; OR = 0.51; 95% CI = 0.27-0.98) associated with schizophrenia susceptibility. Bioinformatic analysis indicated that these haplotypes affect DNA packaging, which supported the findings of the first part of the study and could implicate epigenetic processes. The findings of this study support the importance of regulatory variants in schizophrenia susceptibility. This study also showed the importance of combining GWAS data with additional analyses in order to better understand complex diseases. It is hoped that these findings could fuel future research, specifically in genetically unique populations. AFRIKAANSE OPSOMMING: Skisofrenie kan beskryf word as een van die duurste en mees ernstige siektes en bly steeds een van die grootste uitdagings vir mediese navorsers. Hierdie versteuring behels probleme op alle vlakke: van genotipe tot fenotipe. Alhoewel dit bekend is dat daar 'n aansienlike genetiese bydrae tot skisofrenie vatbaarheid is (~ 80%), is dit onbekend of dit is as gevolg van algemene variasies, skaars variasies, epigenetiese faktore, variasies in regulerende gebiede van die genoom of 'n kombinasie van al hierdie faktore. Oor die afgelope paar dekades is verskeie benaderings gebruik om die genetiese samestelling van skisofrenie te bestudeer, met die nuutste en mees belowende synde genoom-wye assosiasie studies (GWAS). Byna 'n dekade na die eerste GWAS, word die beperkinge egter toenemend erken en nuwe navorsingstrategieë moet gebruik word. Studies het onlangs begin om meer te fokus op die analise van nie-koderende areas van die genoom aangesien hierdie areas die meerderheid van die variasies behels wat tot dusver in GWAS geïdentifiseer is. Hierdie studie het gepoog om onlangs ontwikkelde programme, wat gebruik maak van die data van grootskaalse studies soos vorige GWAS, die “Encyclopaedia of DNA Elements” (ENCODE), “1000 Genomes”, “HapMap” en “Functional Annotation of the Mammalian Genome” (FANTOM), te implementeer om sodoende 'n eenvoudige, maar doeltreffende bioinformatika pyplyn vir die identifisering en evaluering van variante in regulerende gebiede, te vestig. Deur die gebruik van die gevestigde bioinformatika pyplyn, is 149 enkel nukleotied polimorfismes (SNPs) in regulerende gebiede in skisofrenie vatbaarheid betrek, met rs200981 wat die mees betekenisvol was. Pad- en netwerk-analise met die onderskeidelike hulp van die “Database for Annotation, Visualization and Integrated Discovery” (DAVID) en “GeneMANIA”, het aangedui dat die gene wat die meeste geaffekteer was, betrokke is by immuunreaksies en neuro-ontwikkeling. Hierdie bevindinge ondersteun vorige studies. Tog het nuwe bevindinge van hierdie studie prosesse geïmpliseer wat uiters noodsaaklik is vir DNS verpakking (van DNS- tot chromatien-vlak). Die tweede deel van die studie het restriksie fragment lengte polimorfisme analise van polimerase ketting reaksie geamplifiseerde fragmente (PKR-RFLP) gebruik om tien van die belangrikste SNPs (wat geïdentifiseer is deur bioinformatiese ontledings in die eerste deel van die studie) in `n Suid-Afrikaanse Xhosa studiegroep van 100 skisofrenie gevalle en 100 kontroles te genotipeer, terwyl tweerigting Sanger volgordebepaling gebruik is om die teenwoordigheid van hierdie SNPs te bevestig. Statistiese analise het aangedui dat twee National Research Foundation (DAAD-NRF) Masters 2015-01-13T11:46:59Z 2015-06-30T03:00:13Z 2014-12 Thesis http://hdl.handle.net/10019.1/95790 en_ZA Stellenbosch University 156 pages : illustrations application/pdf application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Schizophrenia Genome wide association studies (GWAS) Bioinformatics Molecular genetics UCTD Coffee, Michelle Analysis of schizophrenia susceptibility variants identified by GWAS : a bioinformatics and molecular genetics approach |
| title | Analysis of schizophrenia susceptibility variants identified by GWAS : a bioinformatics and molecular genetics approach |
| title_full | Analysis of schizophrenia susceptibility variants identified by GWAS : a bioinformatics and molecular genetics approach |
| title_fullStr | Analysis of schizophrenia susceptibility variants identified by GWAS : a bioinformatics and molecular genetics approach |
| title_full_unstemmed | Analysis of schizophrenia susceptibility variants identified by GWAS : a bioinformatics and molecular genetics approach |
| title_short | Analysis of schizophrenia susceptibility variants identified by GWAS : a bioinformatics and molecular genetics approach |
| title_sort | analysis of schizophrenia susceptibility variants identified by gwas a bioinformatics and molecular genetics approach |
| topic | Schizophrenia Genome wide association studies (GWAS) Bioinformatics Molecular genetics UCTD |
| url | http://hdl.handle.net/10019.1/95790 |
| work_keys_str_mv | AT coffeemichelle analysisofschizophreniasusceptibilityvariantsidentifiedbygwasabioinformaticsandmoleculargeneticsapproach |