Loading...
5 results
Search Results
Now showing 1 - 5 of 5
- The complexity of identification of pathogenic variantsPublication . Fino, Joana; David, DezsoIntroduction: Natural occurring genomic variant, from single nucleotide to balanced, unbalanced and complex rearrangements, spanning large chromosomal regions, has been reported to cause human pathologies. As such, we present cases with neurodevelopmental disorder, infertility, and recurrent miscarriage, which reflect the complexity of the identification of pathogenic variants, considering the variation spectrum, the underlying pathogenic mechanisms, and the heterogeneous clinical presentations. Methods: Long and small insert genomic sequencing (GS) was applied to four cases. Variants were identified from GS data mapped against the reference human genome and confirmed through Sanger sequencing. Results were interpreted using SVInterpreter, Exomiser, genotype-phenotype correlation and convergent genomic data analysis. Results: Although the first case is a carrier of a t(17;19)(p13.1;p13.3)mat, disrupting GSG1L2, and of a presumably paternally inherited dup(2)(q14.3q21.1), encompassing the autosomal dominant (AD) phenotype-associated PROC and HS6ST1 genes, the identified novel frameshift c.4442del, p.(Gly1481Valfs*21) variant of CHD4, was considered the disease-causing variant, since the proband’s phenotype fits the CHD4-associated Sifrim-Hitz-Weiss syndrome (Da Silva et al., 2022). Cases 2 and 3 were both reported with infertility, and carriers of t(5;9)(q31.3;p13) and t(4;21)(p14;q21.3), respectively. Our study revealed that the phenotype most plausibly resulted from a chromosomal position effect over YIPF5 and SPATC1L. The last case, presented intellectual disability and recurrent miscarriage, associated to t(7;22)(p13;q13.1). The 7p13 breakpoint disrupts the brain specific CAMK2B, causing AD mental retardation 54 (OMIM #617799), whereas increased meiotic segregation of der(22), during gametogenesis, most likely explain the reported miscarriage (David et al., 2023). Conclusions: These cases highlight the intricacy of pathogenic mechanisms leading to human disorders, the necessity for identification and evaluation of the “full” spectrum of genomic and genetic variants, of comparative reverse phenotyping, including patients with pathogenic variants affecting the same genes. Finally, highlight the need of introducing a more precise genomic medicine in clinical practice. This research was supported by FCT—Fundação para a Ciência e a Tecnologia, Research Grant HMSP-ICT/0016/2013 of the Harvard Medical School—Portugal Program.
- SVInterpreter: A Comprehensive Topologically Associated Domain-Based Clinical Outcome Prediction Tool for Balanced and Unbalanced Structural VariantsPublication . Fino, Joana; Marques, Barbara; Dong, Zirui; David, DezsoWith the advent of genomic sequencing, a number of balanced and unbalanced structural variants (SVs) can be detected per individual. Mainly due to incompleteness and the scattered nature of the available annotation data of the human genome, manual interpretation of the SV’s clinical significance is laborious and cumbersome. Since bioinformatic tools developed for this task are limited, a comprehensive tool to assist clinical outcome prediction of SVs is warranted. Herein, we present SVInterpreter, a free Web application, which analyzes both balanced and unbalanced SVs using topologically associated domains (TADs) as genome units. Among others, gene-associated data (as function and dosage sensitivity), phenotype similarity scores, and copy number variants (CNVs) scoring metrics are retrieved for an informed SV interpretation. For evaluation, we retrospectively applied SVInterpreter to 97 balanced (translocations and inversions) and 125 unbalanced (deletions, duplications, and insertions) previously published SVs, and 145 SVs identified from 20 clinical samples. Our results showed the ability of SVInterpreter to support the evaluation of SVs by (1) confirming more than half of the predictions of the original studies, (2) decreasing 40% of the variants of uncertain significance, and (3) indicating several potential position effect events. To our knowledge, SVInterpreter is the most comprehensive TAD-based tool to identify the possible disease-causing candidate genes and to assist prediction of the clinical outcome of SVs. SVInterpreter is available at http://dgrctools-insa.min-saude.pt/cgi-bin/SVInterpreter.py.
- TAD-GConTool and CNV-ConTool to assist prediction of phenotypic outcome of chromosomal rearrangementsPublication . Fino, Joana; David, DezsoWith the advance of genome sequencing technologies, it is currently possible to identify a large number of chromosomal or genomic structural variants in a single individual. Therefore, the validation and manual assessment of structural variants clinical significance becomes unpractical and time consuming when performed with previous methodologies. In order to assist the validation process, we developed two clinically inspired bioinformatics tools - TADGConTool and CNV-ConTool. They were developed in python with a Common Gateway Interface that allows easy and user-friendly access through any standards compliant web browser (available at: http://dgrctools.insa.min- saude.pt/). TAD-GConTool collects genomic information of breakpoint regions, using topological associated domains (TADs) as reference. It then accesses public databases to retrieve elements found inside TADs, and the associated clinical phenotypes, highlighting those causing dominant disorders. CNV-ConTool searches for overlaps between patient-specific breakpoints and CNVs, and those reported in several public databases. These tools were already successfully applied to about 40 cases studied under the project “Next-gen cytogenetics enters clinical care and annotates the human genome” (HMSPICT/0016/2013) and are now being made available to the broader scientific community. These tools allowed a faster and more informed evaluation of the genomic structural variants, helping select potential pathogenic variants, either by identifying phenotype- associated genes, or by overlapping deletions and duplications with already described benign or pathogenic CNVs. As genome sequencing is becoming more and more a routine method for identification of chromosomal and genomic structural variants, such clinically oriented bioinformatics tools are crucial and represent the first level of analysis toward personalized genomic medicine. This research was supported by national funds through FCT - Fundação para a Ciência e a Tecnologia, Research Grant HMSP-ICT/0016/2013.
- SVInterpreter: a web-based tool for structural variants inspection and identification of possible disease-causing candidate genesPublication . Fino, Joana; Marques, Barbara; Dong, Zirui; David, DezsoIntroduction: With the advent of genomic sequencing, the identification of structural variants (SVs) is no longer a challenge, being possible to detect an average of 5 K SVs by individual. Contrarily, the annotation of the genome is incomplete, and the data is scattered along different databases, making SV manual evaluation complicated and time-consuming. Also, the available tools are limited on their scope. Thus, to address the need of a comprehensive application to assist evaluation of clinical outcome of SVs, we developed Structural Variant Interpreter (SVInterpreter). Methods: SVInterpreter is a free Python-CGI developed Web application able to analyze SVs using Topologically Associated Domains as genome units, within which genome browsers data, medically actionable genes, virtual gene panels and HPO similarity results, among other information, is retrieved. Results: We started by re-analysing 220 published SVs, of which about 50% were previously classified as VUS. SVInterpreter corroborated the previous classification in about 84% of the SVs. In about 5% of the SVs, SVInterpreter gave indication of possible position effect, through phenotype similarity, disrupted chromatin loops or genome wide association studies. Then, we show the applicability of SVInterpreter on the clinical setting, by inspecting 15 cases analysed by chromosomal microarray or genome sequencing. Conclusions: To our knowledge, SVInterpreter is the most comprehensive TAD based tool to assist prediction of clinical outcome of SVs. Based on gathered information, identification of possible disease-causing candidate genes and SVs is easily achievable. SVInterpreter is available at http://dgrctools-insa.min-saude.pt/cgi-bin/SVInterpreter.py
- Projeto Doenças Genómicas e Rearranjos Cromossómicos: dificuldades diagnósticas e o impacto para a famíliaPublication . David, DezsoStructural chromosomal rearrangements (SCRs) have long been recognized as a major source of human developmental anomalies, including, among others, congenital anomalies, and neurodevelopmental, intellectual and cognitive disabilities. Indeed, causal relationship between congenital anomalies and related SCRs are expected to occur in up to 40% of the affected subjects. Approaches used for detection of such SCRs evolved significantly from classical and molecular cytogenetic technologies, such as FISH and microarrays, to whole genome sequencing (WGS) with high physical and low sequence coverage, also known as large-insert WGS.