Publication:
Unmasking Retinitis Pigmentosa complex cases by a whole genome sequencing algorithm based on open-access tools: hidden recessive inheritance and potential oligogenic variants.

dc.contributor.authorGonzález-Del Pozo, María
dc.contributor.authorFernández-Suárez, Elena
dc.contributor.authorMartín-Sánchez, Marta
dc.contributor.authorBravo-Gil, Nereida
dc.contributor.authorMéndez-Vidal, Cristina
dc.contributor.authorRodríguez-de la Rúa, Enrique
dc.contributor.authorBorrego, Salud
dc.contributor.authorAntiñolo, Guillermo
dc.date.accessioned2023-02-08T14:41:10Z
dc.date.available2023-02-08T14:41:10Z
dc.date.issued2020-02-12
dc.description.abstractRetinitis Pigmentosa (RP) is a clinically and genetically heterogeneous disorder that results in inherited blindness. Despite the large number of genes identified, only ~ 60% of cases receive a genetic diagnosis using targeted-sequencing. The aim of this study was to design a whole genome sequencing (WGS) based approach to increase the diagnostic yield of complex Retinitis Pigmentosa cases. WGS was conducted in three family members, belonging to one large apparent autosomal dominant RP family that remained unsolved by previous studies, using Illumina TruSeq library preparation kit and Illumina HiSeq X platform. Variant annotation, filtering and prioritization were performed using a number of open-access tools and public databases. Sanger sequencing of candidate variants was conducted in the extended family members. We have developed and optimized an algorithm, based on the combination of different open-access tools, for variant prioritization of WGS data which allowed us to reduce significantly the number of likely causative variants pending to be manually assessed and segregated. Following this algorithm, four heterozygous variants in one autosomal recessive gene (USH2A) were identified, segregating in pairs in the affected members. Additionally, two pathogenic alleles in ADGRV1 and PDZD7 could be contributing to the phenotype in one patient. The optimization of a diagnostic algorithm for WGS data analysis, accompanied by a hypothesis-free approach, have allowed us to unmask the genetic cause of the disease in one large RP family, as well as to reassign its inheritance pattern which implies differences in the clinical management of these cases. These results contribute to increasing the number of cases with apparently dominant inheritance that carry causal mutations in recessive genes, as well as the possible involvement of various genes in the pathogenesis of RP in one patient. Moreover, our WGS-analysis approach, based on open-access tools, can easily be implemented by other researchers and clinicians to improve the diagnostic yield of additional patients with inherited retinal dystrophies.
dc.identifier.doi10.1186/s12967-020-02258-3
dc.identifier.essn1479-5876
dc.identifier.pmcPMC7014749
dc.identifier.pmid32050993
dc.identifier.pubmedURLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014749/pdf
dc.identifier.unpaywallURLhttps://doi.org/10.1186/s12967-020-02258-3
dc.identifier.urihttp://hdl.handle.net/10668/15096
dc.issue.number1
dc.journal.titleJournal of translational medicine
dc.journal.titleabbreviationJ Transl Med
dc.language.isoen
dc.organizationIBIS
dc.page.number73
dc.pubmedtypeJournal Article
dc.pubmedtypeResearch Support, Non-U.S. Gov't
dc.rightsAttribution 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectADGRV1
dc.subjectInherited retinal dystrophies
dc.subjectNGS
dc.subjectPDZD7
dc.subjectRetinitis Pigmentosa
dc.subjectUSH2A
dc.subjectWGS
dc.subject.meshAlgorithms
dc.subject.meshDNA Mutational Analysis
dc.subject.meshHumans
dc.subject.meshMutation
dc.subject.meshPedigree
dc.subject.meshRetinitis Pigmentosa
dc.subject.meshWhole Genome Sequencing
dc.titleUnmasking Retinitis Pigmentosa complex cases by a whole genome sequencing algorithm based on open-access tools: hidden recessive inheritance and potential oligogenic variants.
dc.typeresearch article
dc.type.hasVersionVoR
dc.volume.number18
dspace.entity.typePublication

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
PMC7014749.pdf
Size:
1.91 MB
Format:
Adobe Portable Document Format