Characterising structural variants in patients with craniosynostosis using short-read and long-range technologies
<p><strong>Background:</strong> Structural variants (SVs) are large genomic alterations that can span from 50, to millions of base pairs, with potential clinical implications depending on their location and consequence. Characterisation and interpretation of SVs through conventiona...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2024
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| _version_ | 1826312959597477888 |
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| author | Pei, Y |
| author2 | Wilkie, A |
| author_facet | Wilkie, A Pei, Y |
| author_sort | Pei, Y |
| collection | OXFORD |
| description | <p><strong>Background:</strong> Structural variants (SVs) are large genomic alterations that can span from 50, to millions of base pairs, with potential clinical implications depending on their location and consequence. Characterisation and interpretation of SVs through conventional methods remain challenging due to both experimental and computational limitations. In contrast, emerging long-range technologies, such as Bionano Optical Genome Mapping (OGM) and Oxford Nanopore Technology (ONT), offer promise in significantly improving SV detection and interpretation.</p>
<p>Craniosynostosis (CRS) is characterised by the premature fusion of one or more cranial sutures, affecting 1 in 2000 births. Genetically, CRS is a highly heterogeneous condition, with to date 66 associated “Green” genes in the Genomics England PanelApp. This genetic complexity makes CRS an ideal candidate for genetic studies, and yet many CRS cases still lack a clear underlying molecular cause following appropriate targeted investigations.</p></br>
<p><strong>Aim:</strong> My project set out to identify clinically relevant SVs in patients with CRS lacking a genetic diagnosis, with the hypothesis that elusive pathogenic SVs may contribute to the diagnostic gap in CRS.</p></br>
<p><strong>Method and data:</strong> Three genomic approaches were employed to investigate clinically relevant SVs:</p>
<p>1. 114 CRS families were analysed by Illumina WGS as part of the 100,000 Genomes Project (100kGP);</p>
<p>2. I employed Bionano OGM to investigate 20 families to both further characterise complex SV candidates and to identify pathogenic SVs that may have been overlooked by conventional technologies;</p>
<p>3. 8 trios were analysed by ONT as part of a 100kGP pilot sequencing programme.</p></br>
<p><strong>Results:</strong> The 100kGP analysis identified several candidate SVs, with the most compelling SVs affecting the <em>HOXC</em> cluster – a group of genes previously unexplored in relation to CRS. Bionano OGM successfully identified and characterised several SVs, including a large elusive inversion affecting <em>TWIST1</em>, an ambiguous paired duplication on chr13, a chromothripsis-like event spanning over a ~3 Mb region on chr20, and an unbalanced reciprocal translocation affecting a novel disease locus near <em>KCNJ2</em>. In contrast, ONT data faced initial challenges in SV calling, while subsequent optimisation efforts yielded significant improvements, demonstrating ONT’s unique advantages in characterising insertions.</p></br>
<p><strong>Conclusion:</strong> Investigating clinically relevant SVs in CRS patients revealed compelling SVs that could explain some of the diagnostic gaps. Bionano OGM demonstrated excellent clinical utility in SV analysis, while stringent sample requirements and cost are major challenges for routine diagnostic implementation. ONT showed promise in SV analysis, but computational calling of variants needs further improvement for wider application.</p> |
| first_indexed | 2024-09-25T04:03:28Z |
| format | Thesis |
| id | oxford-uuid:5cdb1ac2-e294-4390-8704-c788b484389b |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:03:28Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | oxford-uuid:5cdb1ac2-e294-4390-8704-c788b484389b2024-05-17T09:06:47ZCharacterising structural variants in patients with craniosynostosis using short-read and long-range technologiesThesishttp://purl.org/coar/resource_type/c_db06uuid:5cdb1ac2-e294-4390-8704-c788b484389bGeneticsGenomicsMedical geneticsBioinformaticsClinical GeneticsEnglishHyrax Deposit2024Pei, YWilkie, ATwigg, SGibbons, RTaylor, JBeggs, A<p><strong>Background:</strong> Structural variants (SVs) are large genomic alterations that can span from 50, to millions of base pairs, with potential clinical implications depending on their location and consequence. Characterisation and interpretation of SVs through conventional methods remain challenging due to both experimental and computational limitations. In contrast, emerging long-range technologies, such as Bionano Optical Genome Mapping (OGM) and Oxford Nanopore Technology (ONT), offer promise in significantly improving SV detection and interpretation.</p> <p>Craniosynostosis (CRS) is characterised by the premature fusion of one or more cranial sutures, affecting 1 in 2000 births. Genetically, CRS is a highly heterogeneous condition, with to date 66 associated “Green” genes in the Genomics England PanelApp. This genetic complexity makes CRS an ideal candidate for genetic studies, and yet many CRS cases still lack a clear underlying molecular cause following appropriate targeted investigations.</p></br> <p><strong>Aim:</strong> My project set out to identify clinically relevant SVs in patients with CRS lacking a genetic diagnosis, with the hypothesis that elusive pathogenic SVs may contribute to the diagnostic gap in CRS.</p></br> <p><strong>Method and data:</strong> Three genomic approaches were employed to investigate clinically relevant SVs:</p> <p>1. 114 CRS families were analysed by Illumina WGS as part of the 100,000 Genomes Project (100kGP);</p> <p>2. I employed Bionano OGM to investigate 20 families to both further characterise complex SV candidates and to identify pathogenic SVs that may have been overlooked by conventional technologies;</p> <p>3. 8 trios were analysed by ONT as part of a 100kGP pilot sequencing programme.</p></br> <p><strong>Results:</strong> The 100kGP analysis identified several candidate SVs, with the most compelling SVs affecting the <em>HOXC</em> cluster – a group of genes previously unexplored in relation to CRS. Bionano OGM successfully identified and characterised several SVs, including a large elusive inversion affecting <em>TWIST1</em>, an ambiguous paired duplication on chr13, a chromothripsis-like event spanning over a ~3 Mb region on chr20, and an unbalanced reciprocal translocation affecting a novel disease locus near <em>KCNJ2</em>. In contrast, ONT data faced initial challenges in SV calling, while subsequent optimisation efforts yielded significant improvements, demonstrating ONT’s unique advantages in characterising insertions.</p></br> <p><strong>Conclusion:</strong> Investigating clinically relevant SVs in CRS patients revealed compelling SVs that could explain some of the diagnostic gaps. Bionano OGM demonstrated excellent clinical utility in SV analysis, while stringent sample requirements and cost are major challenges for routine diagnostic implementation. ONT showed promise in SV analysis, but computational calling of variants needs further improvement for wider application.</p> |
| spellingShingle | Genetics Genomics Medical genetics Bioinformatics Clinical Genetics Pei, Y Characterising structural variants in patients with craniosynostosis using short-read and long-range technologies |
| title | Characterising structural variants in patients with craniosynostosis using short-read and long-range technologies |
| title_full | Characterising structural variants in patients with craniosynostosis using short-read and long-range technologies |
| title_fullStr | Characterising structural variants in patients with craniosynostosis using short-read and long-range technologies |
| title_full_unstemmed | Characterising structural variants in patients with craniosynostosis using short-read and long-range technologies |
| title_short | Characterising structural variants in patients with craniosynostosis using short-read and long-range technologies |
| title_sort | characterising structural variants in patients with craniosynostosis using short read and long range technologies |
| topic | Genetics Genomics Medical genetics Bioinformatics Clinical Genetics |
| work_keys_str_mv | AT peiy characterisingstructuralvariantsinpatientswithcraniosynostosisusingshortreadandlongrangetechnologies |