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Identification of novel candidate disease genes from de novo exonic copy number variants.


ABSTRACT: BACKGROUND:Exon-targeted microarrays can detect small (<1000 bp) intragenic copy number variants (CNVs), including those that affect only a single exon. This genome-wide high-sensitivity approach increases the molecular diagnosis for conditions with known disease-associated genes, enables better genotype-phenotype correlations, and facilitates variant allele detection allowing novel disease gene discovery. METHODS:We retrospectively analyzed data from 63,127 patients referred for clinical chromosomal microarray analysis (CMA) at Baylor Genetics laboratories, including 46,755 individuals tested using exon-targeted arrays, from 2007 to 2017. Small CNVs harboring a single gene or two to five non-disease-associated genes were identified; the genes involved were evaluated for a potential disease association. RESULTS:In this clinical population, among rare CNVs involving any single gene reported in 7200 patients (11%), we identified 145 de novo autosomal CNVs (117 losses and 28 intragenic gains), 257 X-linked deletion CNVs in males, and 1049 inherited autosomal CNVs (878 losses and 171 intragenic gains); 111 known disease genes were potentially disrupted by de novo autosomal or X-linked (in males) single-gene CNVs. Ninety-one genes, either recently proposed as candidate disease genes or not yet associated with diseases, were disrupted by 147 single-gene CNVs, including 37 de novo deletions and ten de novo intragenic duplications on autosomes and 100 X-linked CNVs in males. Clinical features in individuals with de novo or X-linked CNVs encompassing at most five genes (224 bp to 1.6 Mb in size) were compared to those in individuals with larger-sized deletions (up to 5 Mb in size) in the internal CMA database or loss-of-function single nucleotide variants (SNVs) detected by clinical or research whole-exome sequencing (WES). This enabled the identification of recently published genes (BPTF, NONO, PSMD12, TANGO2, and TRIP12), novel candidate disease genes (ARGLU1 and STK3), and further confirmation of disease association for two recently proposed disease genes (MEIS2 and PTCHD1). Notably, exon-targeted CMA detected several pathogenic single-exon CNVs missed by clinical WES analyses. CONCLUSIONS:Together, these data document the efficacy of exon-targeted CMA for detection of genic and exonic CNVs, complementing and extending WES in clinical diagnostics, and the potential for discovery of novel disease genes by genome-wide assay.

SUBMITTER: Gambin T 

PROVIDER: S-EPMC5607840 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Identification of novel candidate disease genes from de novo exonic copy number variants.

Gambin Tomasz T   Yuan Bo B   Bi Weimin W   Liu Pengfei P   Rosenfeld Jill A JA   Coban-Akdemir Zeynep Z   Pursley Amber N AN   Nagamani Sandesh C S SCS   Marom Ronit R   Golla Sailaja S   Dengle Lauren L   Petrie Heather G HG   Matalon Reuben R   Emrick Lisa L   Proud Monica B MB   Treadwell-Deering Diane D   Chao Hsiao-Tuan HT   Koillinen Hannele H   Brown Chester C   Urraca Nora N   Mostafavi Roya R   Bernes Saunder S   Roeder Elizabeth R ER   Nugent Kimberly M KM   Bader Patricia I PI   Bellus Gary G   Cummings Michael M   Northrup Hope H   Ashfaq Myla M   Westman Rachel R   Wildin Robert R   Beck Anita E AE   Immken LaDonna L   Elton Lindsay L   Varghese Shaun S   Buchanan Edward E   Faivre Laurence L   Lefebvre Mathilde M   Schaaf Christian P CP   Walkiewicz Magdalena M   Yang Yaping Y   Kang Sung-Hae L SL   Lalani Seema R SR   Bacino Carlos A CA   Beaudet Arthur L AL   Breman Amy M AM   Smith Janice L JL   Cheung Sau Wai SW   Lupski James R JR   Patel Ankita A   Shaw Chad A CA   Stankiewicz Paweł P  

Genome medicine 20170921 1


<h4>Background</h4>Exon-targeted microarrays can detect small (<1000 bp) intragenic copy number variants (CNVs), including those that affect only a single exon. This genome-wide high-sensitivity approach increases the molecular diagnosis for conditions with known disease-associated genes, enables better genotype-phenotype correlations, and facilitates variant allele detection allowing novel disease gene discovery.<h4>Methods</h4>We retrospectively analyzed data from 63,127 patients referred for  ...[more]

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