Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the population
Background Large genomic databases enable genetic evaluation in terms of haploinsufficiency and prevalence of missense and synonymous variants. We explored these parameters in ocular tumour-associated genes.Methods A curated list of ocular tumour-associated genes was assessed using the genomic datab...
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BMJ Publishing Group
2024-04-01
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| Series: | BMJ Open Ophthalmology |
| Online Access: | https://bmjophth.bmj.com/content/9/1/e001565.full |
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| author | Jose S Pulido Mandeep S Sagoo Omar A Mahroo Alexander Tanner |
| author_facet | Jose S Pulido Mandeep S Sagoo Omar A Mahroo Alexander Tanner |
| author_sort | Jose S Pulido |
| collection | DOAJ |
| description | Background Large genomic databases enable genetic evaluation in terms of haploinsufficiency and prevalence of missense and synonymous variants. We explored these parameters in ocular tumour-associated genes.Methods A curated list of ocular tumour-associated genes was assessed using the genomic databases Genome Aggregation Database (gnomAD) and DatabasE of genomiC varIation and Phenotype in Humans using Ensembl Resources (DECIPHER) and compared with breast and lung cancer-associated gene lists. Haploinsufficiency was determined based on specific criteria: probability of loss of function index ≥0.9 in gnomAD, upper CI O/E limit <0.35 for loss of function variants in gnomAD and/or a DECIPHER pHaplo ≥0.86. UniProt was used for further gene characterisation, and gene ontology Protein Analysis THrough Evolutionary Relationships was explored for common biological pathways. In addition, we identified genes with under-representation/over-representation of missense/synonymous variants.Results Fifty-seven genes were identified in association with ocular and extraocular tumours.Regarding haploinsufficiency, 41% of genes met the criteria for negative selection, with 57% categorised as tumour-suppressing and 39% as oncogenic. Most genes were involved in regulatory processes. Regarding triplosensitivity, 33% of genes reached significance and 83% of these were haploinsufficient. Analysis of variants revealed under-representation of missense variants in 23% of genes and over-representation of synonymous variants in 5% of genes. Ocular tumour-associated genes exhibited higher scores for haploinsufficiency and triplosensitivity compared with breast and lung cancer-associated genes. Pathway analysis revealed significant enrichment in cellular proliferation, differentiation and division. Encoded proteins of ocular tumour-associated genes were generally longer than the median of the UniProt database.Conclusion Our findings highlight the importance of negative selection in ocular tumour genes, supporting cranial gene conservation. This study provides insights into ocular tumourigenesis and future research avenues. |
| format | Article |
| id | doaj-art-0aad19f4d25d4946acfc7631e75c858b |
| institution | Kabale University |
| issn | 2397-3269 |
| language | English |
| publishDate | 2024-04-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open Ophthalmology |
| spelling | doaj-art-0aad19f4d25d4946acfc7631e75c858b2025-02-06T08:25:11ZengBMJ Publishing GroupBMJ Open Ophthalmology2397-32692024-04-019110.1136/bmjophth-2023-001565Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the populationJose S Pulido0Mandeep S Sagoo1Omar A Mahroo2Alexander Tanner3Retinal Genetics Service, Moorfields Eye Hospital NHS Foundation Trust, London, UKInstitute of Ophthalmology, University College London, London, UKOphthalmology, Moorfields Eye Hospital NHS Foundation Trust, London, UK2 University Hospitals Sussex NHS Foundation Trust, Brighton, UKBackground Large genomic databases enable genetic evaluation in terms of haploinsufficiency and prevalence of missense and synonymous variants. We explored these parameters in ocular tumour-associated genes.Methods A curated list of ocular tumour-associated genes was assessed using the genomic databases Genome Aggregation Database (gnomAD) and DatabasE of genomiC varIation and Phenotype in Humans using Ensembl Resources (DECIPHER) and compared with breast and lung cancer-associated gene lists. Haploinsufficiency was determined based on specific criteria: probability of loss of function index ≥0.9 in gnomAD, upper CI O/E limit <0.35 for loss of function variants in gnomAD and/or a DECIPHER pHaplo ≥0.86. UniProt was used for further gene characterisation, and gene ontology Protein Analysis THrough Evolutionary Relationships was explored for common biological pathways. In addition, we identified genes with under-representation/over-representation of missense/synonymous variants.Results Fifty-seven genes were identified in association with ocular and extraocular tumours.Regarding haploinsufficiency, 41% of genes met the criteria for negative selection, with 57% categorised as tumour-suppressing and 39% as oncogenic. Most genes were involved in regulatory processes. Regarding triplosensitivity, 33% of genes reached significance and 83% of these were haploinsufficient. Analysis of variants revealed under-representation of missense variants in 23% of genes and over-representation of synonymous variants in 5% of genes. Ocular tumour-associated genes exhibited higher scores for haploinsufficiency and triplosensitivity compared with breast and lung cancer-associated genes. Pathway analysis revealed significant enrichment in cellular proliferation, differentiation and division. Encoded proteins of ocular tumour-associated genes were generally longer than the median of the UniProt database.Conclusion Our findings highlight the importance of negative selection in ocular tumour genes, supporting cranial gene conservation. This study provides insights into ocular tumourigenesis and future research avenues.https://bmjophth.bmj.com/content/9/1/e001565.full |
| spellingShingle | Jose S Pulido Mandeep S Sagoo Omar A Mahroo Alexander Tanner Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the population BMJ Open Ophthalmology |
| title | Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the population |
| title_full | Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the population |
| title_fullStr | Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the population |
| title_full_unstemmed | Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the population |
| title_short | Genetic analysis of ocular tumour-associated genes using large genomic datasets: insights into selection constraints and variant representation in the population |
| title_sort | genetic analysis of ocular tumour associated genes using large genomic datasets insights into selection constraints and variant representation in the population |
| url | https://bmjophth.bmj.com/content/9/1/e001565.full |
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