2014
DOI: 10.1016/j.gene.2014.08.016
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Genotype-based databases for variants causing rare diseases

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Cited by 11 publications
(7 citation statements)
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“…Missense mutations compose Ͼ85% of the known alleles, although the two most common are a splice acceptor site mutation (IVS8 -1GϾC) and a nonsense mutation (W151X) (37). As these would abolish DHCR7 expression, we selected the four most common missense mutations to study (T93M, V326L, R352W, and R352Q) (38). Despite equal transcript levels after transient expression in HEK-293 cells, protein expression was significantly reduced with all four mutations (Fig.…”
Section: Low Dhcr7 Expression In Slos Mutationsmentioning
confidence: 99%
“…Missense mutations compose Ͼ85% of the known alleles, although the two most common are a splice acceptor site mutation (IVS8 -1GϾC) and a nonsense mutation (W151X) (37). As these would abolish DHCR7 expression, we selected the four most common missense mutations to study (T93M, V326L, R352W, and R352Q) (38). Despite equal transcript levels after transient expression in HEK-293 cells, protein expression was significantly reduced with all four mutations (Fig.…”
Section: Low Dhcr7 Expression In Slos Mutationsmentioning
confidence: 99%
“…Since the early discoveries of genes such as CFTR , DMD , FMR1 , and PAH , there have been various efforts to create gene‐/disease‐specific mutation databases. These efforts started with locus‐specific databases (LSDBs) [Fokkema et al., , ; Pan et al., ; Bean et al., ; International Alport Mutation et al., ; Lanthaler et al., ] made by individual research groups for genes such as TP53 [Forbes et al., ]. In the last decade as sequencing costs dropped, new genes were rapidly discovered.…”
Section: Variant Databasesmentioning
confidence: 99%
“…This has implications in all areas of medicine and is not limited to rare diseases [Macarthur, ]. Data from large‐scale sequencing projects, such as the 1000 Genomes Project and projects focused on data aggregation, such as the ExAC database, are now freely available for use in research and diagnostic settings [Watt et al., ; Lanthaler et al., ]. These projects have made two things clear: (1) certain regions of the human genome still cannot be sequenced with adequate depth or simply have not been assigned a sequence based on their content, strand orientation, or errors in assembly; and (2) there are thousands of rare variants in the general population that are difficult to classify.…”
Section: The Burden Of Data From Large‐scale Sequencing Projectsmentioning
confidence: 99%
“…Since the early discoveries of genes such as CFTR, DMD, FMR1, and PAH, there have been various efforts to create gene/diseasespecific mutation databases. These efforts started with locus-specific databases (LSDBs) (Fokkema et al 2005;Fokkema et al 2011;Pan et al 2011;Bean et al 2013;International Alport Mutation et al 2014;Lanthaler et al 2014) made by individual research groups for genes such as TP53 (Forbes et al 2011). In the last decade as sequencing costs dropped, new genes were rapidly discovered.…”
Section: Inherited Diseasesmentioning
confidence: 99%