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Optimising a clinical whole exome sequencing pipeline: diagnosing South African patients with osteogenesis imperfecta
Thesis (MSc)--Stellenbosch University, 2022.
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| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2022
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| _version_ | 1867613925306007552 |
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| access_status_str | Open Access |
| author | Coetzer, Kimberly Christine |
| author2 | Moosa, Shahida |
| author_browse | Coetzer, Kimberly Christine Moosa, Shahida |
| author_facet | Moosa, Shahida Coetzer, Kimberly Christine |
| author_sort | Coetzer, Kimberly Christine |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2022. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/126289 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:43:53.285Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/126289 Optimising a clinical whole exome sequencing pipeline: diagnosing South African patients with osteogenesis imperfecta Coetzer, Kimberly Christine Moosa, Shahida Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Biomedical Sciences. Molecular Biology and Human Genetics. Rare diseases Osteogenesis imperfecta Exomes UCTD Thesis (MSc)--Stellenbosch University, 2022. ENGLISH ABSTRACT: Compared to communicable diseases, rare disease research, diagnosis, and treatment have been disproportionately disadvantaged in Africa. Conventional testing methods that do not take into account a patient's genetic makeup, result in a diagnostic odyssey. This project aimed to change that for a subset of patients with a rare disease called osteogenesis imperfecta. Osteogenesis imperfecta (OI) is a clinically heterogeneous skeletal disorder characterized by osteopenia and an increased fracture incidence. It occurs in approximately one in every 15-20 000 births and is known to vary considerably in its severity. This MSc project is incorporated into the Undiagnosed Disease Programme (UDP) in South Africa and aimed to use next-generation sequencing (NGS) technology to identify disease genes and causal variants in patients with clinico-radiological features of OI using an optimized clinical genomics bioinformatics pipeline. A total of 48 patients with suspected OI were recruited at Tygerberg Hospital’s Genetics Clinic. Patients were selected for an Invitae gene panel test (n=35), a single variant test (n=1) or whole-exome sequencing (WES) (n=12, 10 affected), depending on funding eligibility. Using open-source software and tools, an in-house genomic bioinformatics pipeline was created. This pipeline started with automated variant calling using bcbio followed by four variant prioritization pipelines. The first employed snpEff to extract OI-causing genes. The remaining three pipelines employed Exomiser with and/or without the use of a gene panel and phenotype filter. The resulting variants were further prioritized and analysed using an extended variant prioritization pipeline. Additionally, a manual variant calling pipeline (GATK) was employed to be used as a control. The resulting variants were classified using online tools and also manually classified using ACMG/AMP for training purposes. All ten WES patients were successfully definitively diagnosed with OI using the optimized inhouse pipeline. A causal variant in COL1A1 or COL1A2 was identified in 92% of this patient cohort (90% of WES patients, 94% of Invitae patients), which is in line with previous studies. This pipeline identified two novel causal variants in COL1A1 and COL1A2. Exomiser was able to accurately rank 10/10 (100%) of the OI patient’s causal variants in the top two when a gene panel and phenotype filter were used. Using the multi-gene OI panel, a recurrent variant in COL1A2: c.1892G>T, p.Gly631Val was identified in 23 patients from four unrelated families of mixed ancestry. Additionally, two patients were diagnosed with the same common homozygous variant in FKBP10: c.831dupC. This is the first report of a South African patient of mixed ancestry with an FKBP10 variant, suggesting that the current practice of testing only Black South Africans for this variant should be re-evaluated. These patients’ results served as a variant database for OI in our population. This research resulted in a highly accurate, optimized in-house pipeline, capable of diagnosing OI patients. This work demonstrated that using this pipeline greatly decreases the workload for variant prioritization and interpretation, especially for disorders with well-described phenotypes. The present study has therefore demonstrated that patients with undiagnosed rare diseases benefit from state-of-the-art NGS technologies, which provide them with an accurate molecular diagnosis, bringing an end to their diagnostic odysseys. Future research will concentrate on further improving the in-house pipeline so that it can be tested on other rare monogenic disorders. AFRIKAANSE OPSOMMING: In vergelyking met oordraagbare siektes, is navorsing oor seldsame siektes, diagnose en behandeling buitensporig benadeel in Afrika. Konvensionele toetsmetodes wat nie 'n pasiënt se genetiese samestelling in ag neem nie, lei tot 'n diagnostiese odyssee. Hiedie projek is daarop gemik om dit te verander vir a substel pasiënt met a selsame siekte, genaamd osteogenesis imperfecta (OI). OI is 'n klinies heterogene afwyking wat gekenmerk word deur osteopenie en 'n verhoogde fraktuurvoorkoms. Dit kom by ongeveer een uit elke 15-20 000 geboortes voor en dit is bekend dat dit aansienlik verskil in die erns daarvan. Hierdie MScprojek is geïnkorporeer by die Ongediagnoseerde Siekte-program (UDP) in Suid-Afrika en het ten doel om volgende-generasie volgordebepaling (NGS) tegnologie te gebruik om siektegene en oorsaaklike variante in pasiënte met klinies-radiologiese kenmerke van OI te identifiseer deur gebruik te maak van 'n geoptimaliseerde kliniese genomika bioinformatika pyplyn. Altesaam 48 pasiënte met vermoedelike OI is by Tygerberg-hospitaal se Genetika-kliniek gewerf. Pasiënte is geselekteer vir 'n Invitae-geenpaneeltoets (n=35), 'n enkelvarianttoets (n=1) of heeleksoomvolgordebepaling (WES) (n=12, 10 aangetas), afhangende van die geskiktheid vir befondsing. Met behulp van oopbronsagteware en hulpmiddels is 'n interne genomiese bioinformatika-pyplyn geskep. Hierdie pyplyn het begin met outomatiese variantoproepe wat bcbio gebruik, gevolg deur vier variant-prioritiseringspyplyne. Die eerste het snpEff gebruik om OI-veroorsakende gene te onttrek. Die oorblywende drie pyplyne het Exomiser gebruik met en/of sonder die gebruik van 'n geenpaneel en fenotipe filter. Die gevolglike variante is verder geprioritiseer en geanaliseer deur gebruik te maak van 'n uitgebreide variant prioritiseringspyplyn. Daarbenewens is 'n handmatige variantoproeppyplyn (GATK) gebruik om as 'n kontrole te gebruik. Die gevolglike variante is met die hand geklassifiseer deur ACMG/AMP vir opleidingsdoeleindes te gebruik. Al tien WES-pasiënte is suksesvol met OI gediagnoseer deur gebruik te maak van die geoptimaliseerde interne pyplyn. 'n Oorsaaklike variant in COL1A1 of COL1A2 is geïdentifiseer in 92% van hierdie pasiëntkohort (90% van WES-pasiënte, 94% van Invitaepasiënte) wat in lyn is met vorige studies. Hierdie pyplyn het twee nuwe oorsaaklike variante in COL1A1 en COL1A2 geïdentifiseer. Exomiser was in staat om 10/10 (100%) van die OIpasiënt se oorsaaklike variante akkuraat in die top twee te rangskik wanneer 'n geenpaneel en fenotipe filter gebruik is. 'n Herhalende variant in COL1A2: c.1892G>T, p.Gly631Val was geïdentifiseer in 23 pasiënte uit vier onverwante families van gemengde afkoms. Twee verdere pasiënte is gediagnoseer met dieselfde algemene homosigotiese variant in FKBP10:c.831dupC. Dit is die eerste verslag van 'n Suid-Afrikaanse pasiënt van gemengde afkoms, wat daarop dui dat die huidige praktyk om slegs Swart Suid-Afrikaners vir hierdie variant te toets, herevalueer moet word. Hierdie pasiënte se resultate het gedien as 'n variant databasis vir OI in ons bevolking. Ten slotte, hierdie navorsing het gelei tot 'n hoogs akkurate, geoptimaliseerde interne pyplyn wat in staat is om OI-pasiënte te diagnoseer. Hierdie werk het getoon dat die gebruik van hierdie pyplyn die werkslading vir variantprioritisering en interpretasie aansienlik verminder, veral vir versteurings met goed beskryfde fenotipes. Die huidige studie het dus getoon dat pasiënte met ongediagnoseerde seldsame siektes baat vind by die nuutste NGS-tegnologieë, wat hulle van 'n akkurate molekulêre diagnose voorsien, wat 'n einde bring aan hul diagnostiese odyssee. Toekomstige navorsing sal daarop konsentreer om die interne pyplyn verder te verbeter sodat dit op ander seldsame monogene afwykings getoets kan word. Masters 2022-10-25T13:28:14Z 2023-01-23T06:50:37Z 2022-10-25T13:28:14Z 2022-10 Thesis http://hdl.handle.net/10019.1/126289 en_ZA Stellenbosch University xvi, 129 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Rare diseases Osteogenesis imperfecta Exomes UCTD Coetzer, Kimberly Christine Optimising a clinical whole exome sequencing pipeline: diagnosing South African patients with osteogenesis imperfecta |
| title | Optimising a clinical whole exome sequencing pipeline: diagnosing South African patients with osteogenesis imperfecta |
| title_full | Optimising a clinical whole exome sequencing pipeline: diagnosing South African patients with osteogenesis imperfecta |
| title_fullStr | Optimising a clinical whole exome sequencing pipeline: diagnosing South African patients with osteogenesis imperfecta |
| title_full_unstemmed | Optimising a clinical whole exome sequencing pipeline: diagnosing South African patients with osteogenesis imperfecta |
| title_short | Optimising a clinical whole exome sequencing pipeline: diagnosing South African patients with osteogenesis imperfecta |
| title_sort | optimising a clinical whole exome sequencing pipeline diagnosing south african patients with osteogenesis imperfecta |
| topic | Rare diseases Osteogenesis imperfecta Exomes UCTD |
| url | http://hdl.handle.net/10019.1/126289 |
| work_keys_str_mv | AT coetzerkimberlychristine optimisingaclinicalwholeexomesequencingpipelinediagnosingsouthafricanpatientswithosteogenesisimperfecta |