Using XHMM Software to Detect Copy Number Variation in Whole-Exome Sequencing Data

Current protocols in human genetics / editorial board, Jonathan L. Haines ... [et al.] 04/2014; 81(7):7.23.1-7.23.21. DOI: 10.1002/0471142905.hg0723s81
Source: PubMed


Copy number variation (CNV) has emerged as an important genetic component in human diseases, which are increasingly being studied for large numbers of samples by sequencing the coding regions of the genome, i.e., exome sequencing. Nonetheless, detecting this variation from such targeted sequencing data is a difficult task, involving sorting out signal from noise, for which we have recently developed a set of statistical and computational tools called XHMM. In this unit, we give detailed instructions on how to run XHMM and how to use the resulting CNV calls in biological analyses. Curr. Protoc. Hum. Genet. 81:7.23.1-7.23.21. © 2014 by John Wiley & Sons, Inc.

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    ABSTRACT: Whole-exome sequencing (WES) is becoming a standard tool for detecting nucleotide changes, and determining whether WES data can be used for the detection of copy-number variations (CNVs) is of interest. To date, several algorithms have been developed for such analyses, although verification is needed to establish if they fit well for the appropriate purpose, depending on the characteristics of each algorithm. Here, we performed WES CNV analysis using the eXome Hidden Markov Model (XHMM). We validated its performance using 27 rare CNVs previously identified by microarray as positive controls, finding that the detection rate was 59%, or higher (89%) with three or more targets. XHMM can be effectively used, especially for the detection of >200 kb CNVs. XHMM may be useful for deletion breakpoint detection. Next, we applied XHMM to genetically unsolved patients, demonstrating successful identification of pathogenic CNVs: 1.5-1.9-Mb deletions involving NSD1 in patients with unknown overgrowth syndrome leading to the diagnosis of Sotos syndrome, and 6.4-Mb duplication involving MECP2 in affected brothers with late-onset spasm and progressive cerebral/cerebellar atrophy confirming the clinical suspect of MECP2 duplication syndrome. The possibility of an 'exome-first' approach for clinical genetic investigation may be considered to save the cost of multiple investigations.Journal of Human Genetics advance online publication, 22 January 2015; doi:10.1038/jhg.2014.124.
    Journal of Human Genetics 01/2015; 60(4). DOI:10.1038/jhg.2014.124 · 2.46 Impact Factor
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    ABSTRACT: Interpreting the genomic and phenotypic consequences of copy-number variation (CNV) is essential to understanding the etiology of genetic disorders. Whereas deletion CNVs lead obviously to haploinsufficiency, duplications might cause disease through triplosensitivity, gene disruption, or gene fusion at breakpoints. The mutational spectrum of duplications has been studied at certain loci, and in some cases these copy-number gains are complex chromosome rearrangements involving triplications and/or inversions. However, the organization of clinically relevant duplications throughout the genome has yet to be investigated on a large scale. Here we fine-mapped 184 germline duplications (14.7 kb-25.3 Mb; median 532 kb) ascertained from individuals referred for diagnostic cytogenetics testing. We performed next-generation sequencing (NGS) and whole-genome sequencing (WGS) to sequence 130 breakpoints from 112 subjects with 119 CNVs and found that most (83%) were tandem duplications in direct orientation. The remainder were triplications embedded within duplications (8.4%), adjacent duplications (4.2%), insertional translocations (2.5%), or other complex rearrangements (1.7%). Moreover, we predicted six in-frame fusion genes at sequenced duplication breakpoints; four gene fusions were formed by tandem duplications, one by two interconnected duplications, and one by duplication inserted at another locus. These unique fusion genes could be related to clinical phenotypes and warrant further study. Although most duplications are positioned head-to-tail adjacent to the original locus, those that are inverted, triplicated, or inserted can disrupt or fuse genes in a manner that might not be predicted by conventional copy-number assays. Therefore, interpreting the genetic consequences of duplication CNVs requires breakpoint-level analysis. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
    The American Journal of Human Genetics 01/2015; 96(2). DOI:10.1016/j.ajhg.2014.12.017 · 10.93 Impact Factor
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    ABSTRACT: Adrenal insufficiency is a rare, but potentially fatal medical condition. In children, the cause is most commonly congenital and in recent years a growing number of causative gene mutations have been identified resulting in a myriad of syndromes that share adrenal insufficiency as one of the main characteristics. The evolution of adrenal insufficiency is dependent on the variant and the particular gene affected, meaning that rapid and accurate diagnosis is imperative for effective treatment of the patient. Common practice is for candidate genes to be sequenced individually, which is a time-consuming process and complicated by overlapping clinical phenotypes. However, with the availability, and increasing cost effectiveness of whole-exome sequencing, there is the potential for this to become a powerful diagnostic tool. Here, we report the results of whole-exome sequencing of 43 patients referred to us with a diagnosis of familial glucocorticoid deficiency (FGD) who were mutation negative for MC2R, MRAP, and STAR the most commonly mutated genes in FGD. WES provided a rapid genetic diagnosis in 17/43 sequenced patients, for the remaining 60% the gene defect may be within intronic/regulatory regions not covered by WES or may be in gene(s) representing novel etiologies. The diagnosis of isolated or familial glucocorticoid deficiency was only confirmed in 3 of the 17 patients, other genetic diagnoses were adrenal hypo- and hyperplasia, Triple A, and autoimmune polyendocrinopathy syndrome type I, emphasizing both the difficulty of phenotypically distinguishing between disorders of PAI and the utility of WES as a tool to achieve this.
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