Application of genomic technologies for molecular diagnosis of genetic diseases
<p>Methods for sequencing deoxyribonucleic acid (DNA) have improved rapidly in the past decade. Recent methods, termed "next-generation sequencing" (NGS), have made sequencing large quantities of DNA economically viable in molecular diagnostics of genetic diseases. This thesis descri...
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| Format: | Thesis |
| Language: | English |
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2015
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| _version_ | 1797090026129981440 |
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| author | Hudspith, K |
| author2 | Neméth, A |
| author_facet | Neméth, A Hudspith, K |
| author_sort | Hudspith, K |
| collection | OXFORD |
| description | <p>Methods for sequencing deoxyribonucleic acid (DNA) have improved rapidly in the past decade. Recent methods, termed "next-generation sequencing" (NGS), have made sequencing large quantities of DNA economically viable in molecular diagnostics of genetic diseases. This thesis describes some of the first investigations to use NGS for such a purpose.</p> <p>Several different NGS platforms, each of which differs substantially in terms of sample preparation, chemistry, and sequencing methodology, were tested, in addition to several sequence capture and enrichment technologies that allow sequencing to be targeted, and these combinations were compared to Sanger sequencing. They were each found to have different strengths and weaknesses, which affect their accuracy, reliability, time taken to results, financial cost, and ease of use, but all showed high accuracy and dramatically increased throughput over Sanger sequencing.</p> <p>NGS was used to identify pathogenic mutations in two groups of patients who had either inherited retinal dystrophies (IRD), or severe early onset epilepsies. NGS was able to identify pathogenic variants, demonstrating the ability of the technology to provide medically useful information for genetically heterogeneous conditions. NGS combined with a novel data analysis pipeline was able to make a secure molecular diagnosis in 25% of a cohort of IRD patients who previously did not have a genetic diagnosis.</p> <p>The greatest challenge presented by NGS was found to be filtering the vast amounts of data produced to identify potential pathogenic variants. In silico pathogenicity prediction programs were used, but none were 100% accurate. Other methods were also employed to provide further evidence of pathogenicity. These included family based DNA testing for cosegregation of variants with phenotype, and transcript based analysis. In some patients, despite extensive genetic testing, a secure molecular diagnosis could not be made using DNA sequencing technologies, illustrating that challenges still remain in the field of genetic diagnostics.</p> |
| first_indexed | 2024-03-07T03:12:33Z |
| format | Thesis |
| id | oxford-uuid:b4addaed-e9f9-4762-846a-87eb73f77235 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T03:12:33Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | oxford-uuid:b4addaed-e9f9-4762-846a-87eb73f772352022-03-27T04:28:02ZApplication of genomic technologies for molecular diagnosis of genetic diseasesThesishttp://purl.org/coar/resource_type/c_db06uuid:b4addaed-e9f9-4762-846a-87eb73f77235Human geneticsEnglishORA Deposit2015Hudspith, KNeméth, AHalford, SDownes, S<p>Methods for sequencing deoxyribonucleic acid (DNA) have improved rapidly in the past decade. Recent methods, termed "next-generation sequencing" (NGS), have made sequencing large quantities of DNA economically viable in molecular diagnostics of genetic diseases. This thesis describes some of the first investigations to use NGS for such a purpose.</p> <p>Several different NGS platforms, each of which differs substantially in terms of sample preparation, chemistry, and sequencing methodology, were tested, in addition to several sequence capture and enrichment technologies that allow sequencing to be targeted, and these combinations were compared to Sanger sequencing. They were each found to have different strengths and weaknesses, which affect their accuracy, reliability, time taken to results, financial cost, and ease of use, but all showed high accuracy and dramatically increased throughput over Sanger sequencing.</p> <p>NGS was used to identify pathogenic mutations in two groups of patients who had either inherited retinal dystrophies (IRD), or severe early onset epilepsies. NGS was able to identify pathogenic variants, demonstrating the ability of the technology to provide medically useful information for genetically heterogeneous conditions. NGS combined with a novel data analysis pipeline was able to make a secure molecular diagnosis in 25% of a cohort of IRD patients who previously did not have a genetic diagnosis.</p> <p>The greatest challenge presented by NGS was found to be filtering the vast amounts of data produced to identify potential pathogenic variants. In silico pathogenicity prediction programs were used, but none were 100% accurate. Other methods were also employed to provide further evidence of pathogenicity. These included family based DNA testing for cosegregation of variants with phenotype, and transcript based analysis. In some patients, despite extensive genetic testing, a secure molecular diagnosis could not be made using DNA sequencing technologies, illustrating that challenges still remain in the field of genetic diagnostics.</p> |
| spellingShingle | Human genetics Hudspith, K Application of genomic technologies for molecular diagnosis of genetic diseases |
| title | Application of genomic technologies for molecular diagnosis of genetic diseases |
| title_full | Application of genomic technologies for molecular diagnosis of genetic diseases |
| title_fullStr | Application of genomic technologies for molecular diagnosis of genetic diseases |
| title_full_unstemmed | Application of genomic technologies for molecular diagnosis of genetic diseases |
| title_short | Application of genomic technologies for molecular diagnosis of genetic diseases |
| title_sort | application of genomic technologies for molecular diagnosis of genetic diseases |
| topic | Human genetics |
| work_keys_str_mv | AT hudspithk applicationofgenomictechnologiesformoleculardiagnosisofgeneticdiseases |