@article {816, title = {Spectrum of genetic variants in moderate to severe sporadic hearing loss in Pakistan.}, journal = {Sci Rep}, volume = {10}, year = {2020}, month = {2020 07 17}, pages = {11902}, abstract = {

Hearing loss affects 380 million people worldwide due to environmental or genetic causes. Determining the cause of deafness in individuals without previous family history of hearing loss is challenging and has been relatively unexplored in Pakistan. We investigated the spectrum of genetic variants in hearing loss in a cohort of singleton affected individuals born to consanguineous parents. Twenty-one individuals with moderate to severe hearing loss were recruited. We performed whole-exome sequencing on DNA samples from the participants, which identified seventeen variants in ten known deafness genes and one novel candidate gene. All identified variants were homozygous except for two. Eleven of the variants were novel, including one multi-exonic homozygous deletion in OTOA. A missense variant in ESRRB was implicated for recessively inherited moderate to severe hearing loss. Two individuals were heterozygous for variants in MYO7A and CHD7, respectively, consistent with de novo variants or dominant inheritance with incomplete penetrance as the reason for their hearing loss. Our results indicate that similar to familial cases of deafness, variants in a large number of genes are responsible for moderate to severe hearing loss in sporadic individuals born to consanguineous couples.

}, keywords = {Adolescent, Amino Acid Sequence, Audiometry, Pure-Tone, Child, Child, Preschool, Deafness, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Hearing Loss, Heterozygote, Homozygote, Humans, Mutation, Missense, Pakistan, Phenotype, Whole Exome Sequencing, Young Adult}, issn = {2045-2322}, doi = {10.1038/s41598-020-68779-5}, author = {Ramzan, Memoona and Bashir, Rasheeda and Salman, Midhat and Mujtaba, Ghulam and Sobreira, Nara and Witmer, P Dane and Naz, Sadaf} } @article {139, title = {GeneMatcher: a matching tool for connecting investigators with an interest in the same gene.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Oct}, pages = {928-30}, abstract = {

Here, we describe an overview and update on GeneMatcher (http://www.genematcher.org), a freely accessible Web-based tool developed as part of the Baylor-Hopkins Center for Mendelian Genomics. We created GeneMatcher with the goal of identifying additional individuals with rare phenotypes who had variants in the same candidate disease gene. We also wanted to facilitate connections to basic scientists working on orthologous genes in model systems with the goal of connecting their work to human Mendelian phenotypes. Meeting these goals will enhance the identification of novel Mendelian genes. Launched in September, 2013, GeneMatcher now has 2,178 candidate genes from 486 submitters spread across 38 countries entered in the database (June 1, 2015). GeneMatcher is also part of the Matchmaker Exchange (http://matchmakerexchange.org/) with an Application Programing Interface enabling submitters to query other databases of genetic variants and phenotypes without having to create accounts and data entries in multiple systems.

}, keywords = {Computational Biology, Databases, Genetic, Genetic Predisposition to Disease, Genetic Variation, Humans, Information Dissemination, Phenotype, Rare Diseases, Software, User-Computer Interface, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22844}, author = {Sobreira, Nara and Schiettecatte, Fran{\c c}ois and Valle, David and Hamosh, Ada} } @article {193, title = {New tools for Mendelian disease gene identification: PhenoDB variant analysis module; and GeneMatcher, a web-based tool for linking investigators with an interest in the same gene.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Apr}, pages = {425-31}, abstract = {

Identifying the causative variant from among the thousands identified by whole-exome sequencing or whole-genome sequencing is a formidable challenge. To make this process as efficient and flexible as possible, we have developed a Variant Analysis Module coupled to our previously described Web-based phenotype intake tool, PhenoDB (http://researchphenodb.net and http://phenodb.org). When a small number of candidate-causative variants have been identified in a study of a particular patient or family, a second, more difficult challenge becomes proof of causality for any given variant. One approach to this problem is to find other cases with a similar phenotype and mutations in the same candidate gene. Alternatively, it may be possible to develop biological evidence for causality, an approach that is assisted by making connections to basic scientists studying the gene of interest, often in the setting of a model organism. Both of these strategies benefit from an open access, online site where individual clinicians and investigators could post genes of interest. To this end, we developed GeneMatcher (http://genematcher.org), a freely accessible Website that enables connections between clinicians and researchers across the world who share an interest in the same gene(s).

}, keywords = {Computational Biology, Databases, Genetic, Genetic Association Studies, Genetic Diseases, Inborn, Genetic Variation, Genomics, Internet, Phenotype, Software, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22769}, author = {Sobreira, Nara and Schiettecatte, Fran{\c c}ois and Boehm, Corinne and Valle, David and Hamosh, Ada} } @article {277, title = {DIAMUND: direct comparison of genomes to detect mutations.}, journal = {Hum Mutat}, volume = {35}, year = {2014}, month = {2014 Mar}, pages = {283-8}, abstract = {

DNA sequencing has become a powerful method to discover the genetic basis of disease. Standard, widely used protocols for analysis usually begin by comparing each individual to the human reference genome. When applied to a set of related individuals, this approach reveals millions of differences, most of which are shared among the individuals and unrelated to the disease being investigated. We have developed a novel algorithm for variant detection, one that compares DNA sequences directly to one another, without aligning them to the reference genome. When used to find de novo mutations in exome sequences from family trios, or to compare normal and diseased samples from the same individual, the new method, direct alignment for mutation discovery (DIAMUND), produces a dramatically smaller list of candidate mutations than previous methods, without losing sensitivity to detect the true cause of a genetic disease. We demonstrate our results on several example cases, including two family trios in which it correctly found the disease-causing variant while excluding thousands of harmless variants that standard methods had identified.

}, keywords = {Algorithms, Computational Biology, Exome, Genetic Loci, Genetic Variation, Genome, Human, Humans, Mutation, Sequence Alignment, Sequence Analysis, DNA, Software}, issn = {1098-1004}, doi = {10.1002/humu.22503}, author = {Salzberg, Steven L and Pertea, Mihaela and Fahrner, Jill A and Sobreira, Nara} }