gene panels
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Cancers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 404
Author(s):  
Yuri Belotti ◽  
Elaine Hsuen Lim ◽  
Chwee Teck Lim

Ovarian cancer is the eighth global leading cause of cancer-related death among women. The most common form is the high-grade serous ovarian carcinoma (HGSOC). No further improvements in the 5-year overall survival have been seen over the last 40 years since the adoption of platinum- and taxane-based chemotherapy. Hence, a better understanding of the mechanisms governing this aggressive phenotype would help identify better therapeutic strategies. Recent research linked onset, progression, and response to treatment with dysregulated components of the tumor microenvironment (TME) in many types of cancer. In this study, using bioinformatic approaches, we identified a 19-gene TME-related HGSOC prognostic genetic panel (19 prognostic genes (PLXNB2, HMCN2, NDNF, NTN1, TGFBI, CHAD, CLEC5A, PLXNA1, CST9, LOXL4, MMP17, PI3, PRSS1, SERPINA10, TLL1, CBLN2, IL26, NRG4, and WNT9A) by assessing the RNA sequencing data of 342 tumors available in the TCGA database. Using machine learning, we found that specific patterns of infiltrating immune cells characterized each risk group. Furthermore, we demonstrated the predictive potential of our risk score across different platforms and its improved prognostic performance compared with other gene panels.


Author(s):  
Fiana Ní Ghrálaigh ◽  
Ellen McCarthy ◽  
Daniel N. Murphy ◽  
Louise Gallagher ◽  
Lorna M. Lopez

AbstractAutism is a prevalent neurodevelopmental condition, highly heterogenous in both genotype and phenotype. This communication adds to existing discussion of the heterogeneity of clinical sequencing tests, “gene panels”, marketed for application in autism. We evaluate the clinical utility of available gene panels based on existing genetic evidence. We determine that diagnostic yields of these gene panels range from 0.22% to 10.02% and gene selection for the panels is variable in relevance, here measured as percentage overlap with SFARI Gene and ranging from 15.15% to 100%. We conclude that gene panels marketed for use in autism are currently of limited clinical utility, and that sequencing with greater coverage may be more appropriate.


2021 ◽  
Author(s):  
Damianos Melidis ◽  
Christian Landgraf ◽  
Anja Schoener-Heinisch ◽  
Gunnar Schmidt ◽  
Sandra von Hardenberg ◽  
...  

Since next-generation sequencing (NGS) has become widely available, large gene panels containing up to several hundred genes can be sequenced cost-efficiently. However, the interpretation of the often large numbers of sequence variants detected when using NGS is laborious, prone to errors and often not comparable across laboratories. To overcome this challenge, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) introduced standards and guidelines for the interpretation of sequencing variants. Further gene- and disease-specific refinements regarding hereditary hearing loss have been developed since then. With more than 200 genes associated with hearing disorders, the manual inspection of possible causative variants is especially difficult and time consuming. We developed an open-source bioinformatics tool GenOtoScope, which automates all ACMG/AMP criteria that can be assessed without further individual patient information or human curator investigation, including the refined loss of function criterion (“PVS1”). Two types of interfaces are provided: (i) a command line application to classify sequence variants in batches for a set of patients and (ii) a user-friendly website to classify single variants. We compared the performance of our tool with two other variant classification tools using two hearing loss data sets, which were manually annotated either by the ClinGen Hearing Loss Gene Curation Expert Panel or the diagnostics unit of our human genetics department. GenOtoScope achieved the best average accuracy and precision for both data sets. Compared to the second-best tool, GenOtoScope improved accuracy metric by 25.75% and 4.57% and precision metric by 52.11% and 12.13% on the two data sets respectively. The web interface is freely accessible. The command line application along with all source code, documentation and example outputs can be found via the project GitHub page.


2021 ◽  
Vol 19 (1) ◽  
pp. 60-78
Author(s):  
GEORGIOS N. TSAOUSIS ◽  
EIRINI PAPADOPOULOU ◽  
KONSTANTINOS AGIANNITOPOULOS ◽  
GEORGIA PEPE ◽  
NIKOLAOS TSOULOS ◽  
...  

2021 ◽  
Author(s):  
Eric de Bony ◽  
Fien Gysens ◽  
Nurten Yigit ◽  
Jasper Anckaert ◽  
Celine Everaert ◽  
...  

AbstractMolecular phenotyping through shallow 3’-end RNA-sequencing workflows is increasingly applied in the context of large-scale chemical or genetic perturbation screens to study disease biology or support drug discovery. While these workflows enable accurate quantification of the most abundant genes, they are less effective for applications that require expression profiling of low abundant transcripts, like long non-coding RNAs (lncRNAs), or selected gene panels. To tackle these issues, we describe a workflow combining 3’-end library preparation with 3’-end hybrid capture probes and shallow RNA-sequencing for cost-effective, targeted quantification of subsets of (low abundant) genes across hundreds to thousands of samples. To assess the performance of the method, we designed a capture probe set for more than 100 mRNA and lncRNA target genes and applied the workflow to a cohort of 360 samples. When compared to standard 3’-end RNA-sequencing, 3’-end capture sequencing resulted in a more than 100-fold enrichment of target gene abundance while conserving relative inter-gene and inter-sample abundances. 3’-end RNA capture sequencing enables accurate targeted gene expression profiling at extremely shallow sequencing depth.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Alsu Missarova ◽  
Jaison Jain ◽  
Andrew Butler ◽  
Shila Ghazanfar ◽  
Tim Stuart ◽  
...  

AbstractscRNA-seq datasets are increasingly used to identify gene panels that can be probed using alternative technologies, such as spatial transcriptomics, where choosing the best subset of genes is vital. Existing methods are limited by a reliance on pre-existing cell type labels or by difficulties in identifying markers of rare cells. We introduce an iterative approach, geneBasis, for selecting an optimal gene panel, where each newly added gene captures the maximum distance between the true manifold and the manifold constructed using the currently selected gene panel. Our approach outperforms existing strategies and can resolve cell types and subtle cell state differences.


2021 ◽  
Vol 12 ◽  
Author(s):  
Krista Heliö ◽  
Mikko I. Mäyränpää ◽  
Inka Saarinen ◽  
Saija Ahonen ◽  
Heidi Junnila ◽  
...  

Background: Familial dilated cardiomyopathy (DCM) is a monogenic disorder typically inherited in an autosomal dominant pattern. We have identified two Finnish families with familial cardiomyopathy that is not explained by a variant in any previously known cardiomyopathy gene. We describe the cardiac phenotype related to homozygous truncating GCOM1 variants.Methods and Results: This study included two probands and their relatives. All the participants are of Finnish ethnicity. Whole-exome sequencing was used to test the probands; bi-directional Sanger sequencing was used to identify the GCOM1 variants in probands’ family members. Clinical evaluation was performed, medical records and death certificates were obtained. Immunohistochemical analysis of myocardial samples was conducted. A homozygous GCOM1 variant was identified altogether in six individuals, all considered to be affected. None of the nine heterozygous family members fulfilled any cardiomyopathy criteria. Heart failure was the leading clinical feature, and the patients may have had a tendency for atrial arrhythmias.Conclusions: This study demonstrates the significance of GCOM1 variants as a cause of human cardiomyopathy and highlights the importance of searching for new candidate genes when targeted gene panels do not yield a positive outcome.


Genes ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1824
Author(s):  
Cristina Villanueva-Mendoza ◽  
Miquel Tuson ◽  
David Apam-Garduño ◽  
Marta de Castro-Miró ◽  
Raul Tonda ◽  
...  

In this work, we aimed to provide the genetic diagnosis of a large cohort of patients affected with inherited retinal dystrophies (IRDs) from Mexico. Our data add valuable information to the genetic portrait in rare ocular diseases of Mesoamerican populations, which are mostly under-represented in genetic studies. A cohort of 144 unrelated probands with a clinical diagnosis of IRD were analyzed by next-generation sequencing using target gene panels (overall including 346 genes and 65 intronic sequences). Four unsolved cases were analyzed by whole-exome sequencing (WES). The pathogenicity of new variants was assessed by in silico prediction algorithms and classified following the American College of Medical Genetics and Genomics (ACMG) guidelines. Pathogenic or likely pathogenic variants were identified in 105 probands, with a final diagnostic yield of 72.9%; 17 cases (11.8%) were partially solved. Eighteen patients were clinically reclassified after a genetic diagnostic test (17.1%). In our Mexican cohort, mutations in 48 genes were found, with ABCA4, CRB1, RPGR and USH2A as the major contributors. Notably, over 50 new putatively pathogenic variants were identified. Our data highlight cases with relevant clinical and genetic features due to mutations in the RAB28 and CWC27 genes, enrich the novel mutation repertoire and expand the IRD landscape of the Mexican population.


2021 ◽  
pp. 1-11
Author(s):  
Montse Pauta ◽  
Berta Campos ◽  
Maria Segura-Puimedon ◽  
Gemma Arca ◽  
Alfons Nadal ◽  
...  

<b><i>Objective:</i></b> The aim of the study was to assess the diagnostic yield of 2 different next-generation sequencing (NGS) approaches: gene panel and “solo” clinical exome sequencing (solo-CES), in fetuses with structural anomalies and normal chromosomal microarray analysis (CMA), in the absence of a known familial mutation. <b><i>Methodology:</i></b> Gene panels encompassing from 2 to 140 genes, were applied mainly in persistent nuchal fold/fetal hydrops and in large hyperechogenic kidneys. Solo-CES, which entails sequencing the fetus alone and only interpreting the Online Mendelian Inheritance in Man genes, was performed in multisystem or recurrent structural anomalies. <b><i>Results:</i></b> During the study period (2015–2020), 153 NGS studies were performed in 148 structurally abnormal fetuses with a normal CMA. The overall diagnostic yield accounted for 35% (53/153) of samples and 36% (53/148) of the fetuses. Diagnostic yield with the gene panels was 31% (15/49), similar to 37% (38/104) in solo-CES. <b><i>Conclusions:</i></b> A monogenic disease was established as the underlying cause in 35% of selected fetal structural anomalies by gene panels and solo-CES.


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