scholarly journals RefCNV: Identification of Gene-Based Copy Number Variants Using Whole Exome Sequencing

2016 ◽  
Vol 15 ◽  
pp. CIN.S36612 ◽  
Author(s):  
Lun-Ching Chang ◽  
Biswajit Das ◽  
Chih-Jian Lih ◽  
Han Si ◽  
Corinne E. Camalier ◽  
...  

With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that the processing steps had an impact on the coverage distribution. For each exon, we compared the observed coverage with the expected normal coverage. Thresholds for determining CNVs were selected to control the false-positive error rate. RefCNV prediction correlated significantly ( r = 0.96–0.86) with CNV measured by digital polymerase chain reaction for MET (7q31), EGFR (7p12), or ERBB2 (17q12) in 13 tumor cell lines. The genome-wide CNV analysis showed a good overall correlation (Spearman's coefficient = 0.82) between RefCNV estimation and publicly available CNV data in Cancer Cell Line Encyclopedia. RefCNV also showed better performance than three other CNV estimation methods in genome-wide CNV analysis.

2021 ◽  
Vol 14 ◽  
Author(s):  
Tiejia Jiang ◽  
Jia Gao ◽  
Lihua Jiang ◽  
Lu Xu ◽  
Congying Zhao ◽  
...  

Epilepsy is one of the most common neurological disorders in pediatric patients with other underlying neurological defects. Identifying the underlying etiology is crucial for better management of the disorder. We performed trio-whole exome sequencing in 221 pediatric patients with epilepsy. Probands were divided into seizures with developmental delay/intellectual disability (DD/ID) and seizures without DD/ID groups. Pathogenic (P) or likely pathogenic (LP) variants were identified in 71/110 (64.5%) patients in the seizures with DD/ID group and 21/111 (18.9%) patients in the seizures without DD/ID group (P < 0.001). Eighty-seven distinct P/LP single nucleotide variants (SNVs)/insertion deletions (Indels) were detected, with 55.2% (48/87) of them being novel. All aneuploidy and P/LP copy number variants (CNVs) larger than 100 Kb were identifiable by both whole-exome sequencing and copy number variation sequencing (CNVseq) in 123 of individuals (41 pedigrees). Ten of P/LP CNVs in nine patients and one aneuploidy variant in one patient (Patient #56, #47, XXY) were identified by CNVseq. Herein, we identified seven genes (NCL, SEPHS2, PA2G4, SLC35G2, MYO1C, GPR158, and POU3F1) with de novo variants but unknown pathogenicity that were not previously associated with epilepsy. Potential effective treatment options were available for 32 patients with a P/LP variant, based on the molecular diagnosis. Genetic testing may help identify the molecular etiology of early onset epilepsy and DD/ID and further aid to choose the appropriate treatment strategy for patients.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 228-228
Author(s):  
Joachim Kunz ◽  
Tobias Rausch ◽  
Obul R Bandapalli ◽  
Martina U. Muckenthaler ◽  
Adrian M Stuetz ◽  
...  

Abstract Acute precursor T-lymphoblastic leukemia (T-ALL) remains a serious challenge in pediatric oncology, because relapses carry a particularly poor prognosis with high rates of induction failure and death despite generally excellent treatment responses of the initial disease. It is critical, therefore, to understand the molecular evolution of pediatric T-ALL and to elucidate the mechanisms leading to T-ALL relapse and to understand the differences in treatment response between the two phases of the disease. We have thus subjected DNA from bone marrow samples obtained at the time of initial diagnosis, remission and relapse of 14 patients to whole exome sequencing (WES). Eleven patients suffered from early relapse (duration of remission 6-19 months) and 3 patients from late relapse (duration of remission 29-46 months).The Agilent SureSelect Target Enrichment Kit was used to capture human exons for deep sequencing. The captured fragments were sequenced as 100 bp paired reads using an Illumina HiSeq2000 sequencing instrument. All sequenced DNA reads were preprocessed using Trimmomatic (Lohse et al., Nucl. Acids Res., 2012) to clip adapter contaminations and to trim reads for low quality bases. The remaining reads greater than 36bp were mapped to build hg19 of the human reference genome with Stampy (Lunter & Goodson, Genome Res. 2011), using default parameters. Following such preprocessing, the number of mapped reads was >95% for all samples. Single-nucleotide variants (SNVs) were called using SAMtools mpileup (Li et al., Bioinformatics, 2009). The number of exonic SNVs varied between 23,741 and 31,418 per sample. To facilitate a fast classification and identification of candidate driver mutations, all identified coding SNVs were comprehensively annotated using the ANNOVAR framework (Wang et al., Nat. Rev. Genet., 2010). To identify possible somatic driver mutations, candidate SNVs were filtered for non-synonymous, stopgain or stoploss SNVs, requiring an SNV quality greater or equal to 50, and requiring absence of segmental duplications. Leukemia-specific mutations were identified by filtering against the corresponding remission sample and validated by Sanger sequencing of the genomic DNA following PCR amplification. We identified on average 9.3 somatic single nucleotide variants (SNV) and 0.6 insertions and deletions (indels) per patient sample at the time of initial diagnosis and 21.7 SNVs and 0.3 indels in relapse. On average, 6.3 SNVs were detected both at the time of initial diagnosis and in relapse. These SNVs were thus defined as leukemia specific. Further to SNVs, we have also estimated the frequency of copy number variations (CNV) at low resolution. Apart from the deletions resulting from T-cell receptor rearrangement, we identified on average for each patient 0.7 copy number gains and 2.2 copy number losses at the time of initial diagnosis and 0.5 copy number gains and 2.4 copy number losses in relapse. We detected 24/27 copy number alterations both in initial diagnosis and in relapse. The most common CNV detected was the CDKN2A/B deletion on chromosome 9p. Nine genes were recurrently mutated in 2 or more patients thus indicating the functional leukemogenic potential of these SNVs in T-ALL. These recurrent mutations included known oncogenes (Notch1), tumor suppressor genes (FBXW7, PHF6, WT1) and genes conferring drug resistance (NT5C2). In several patients one gene (such as Notch 1, PHF6, WT1) carried different mutations either at the time of initial diagnosis and or in relapse, indicating that the major leukemic clone had been eradicated by primary treatment, but that a minor clone had persisted and expanded during relapse. The types of mutations did not differ significantly between mutations that were either already present at diagnosis or those that were newly acquired in relapse, indicating that the treatment did not cause specific genomic damage. We will further characterize the clonal evolution of T-ALL into relapse by targeted re-sequencing at high depth of genes with either relapse specific or initial-disease specific mutations. In conclusion, T-ALL relapse differs from primary disease by a higher number of leukemogenic SNVs without gross genomic instability resulting in large CNVs. Disclosures: No relevant conflicts of interest to declare.


2020 ◽  
Vol 22 (8) ◽  
pp. 1041-1049
Author(s):  
Évelin A. Zanardo ◽  
Fabíola P. Monteiro ◽  
Samar N. Chehimi ◽  
Yanca G. Oliveira ◽  
Alexandre T. Dias ◽  
...  

2013 ◽  
Vol 34 (10) ◽  
pp. 1439-1448 ◽  
Author(s):  
Joep de Ligt ◽  
Philip M. Boone ◽  
Rolph Pfundt ◽  
Lisenka E.L.M. Vissers ◽  
Todd Richmond ◽  
...  

2014 ◽  
Vol 42 (12) ◽  
pp. e97-e97 ◽  
Author(s):  
Daniel Backenroth ◽  
Jason Homsy ◽  
Laura R. Murillo ◽  
Joe Glessner ◽  
Edwin Lin ◽  
...  

Genomics Data ◽  
2014 ◽  
Vol 2 ◽  
pp. 144-146 ◽  
Author(s):  
Joep de Ligt ◽  
Philip M. Boone ◽  
Rolph Pfundt ◽  
Lisenka E.L.M. Vissers ◽  
Nicole de Leeuw ◽  
...  

2013 ◽  
Vol 132 (7) ◽  
pp. 825-841 ◽  
Author(s):  
Carl Friedrich Classen ◽  
Vera Riehmer ◽  
Christina Landwehr ◽  
Anne Kosfeld ◽  
Stefanie Heilmann ◽  
...  

2013 ◽  
Vol 14 (10) ◽  
pp. R120 ◽  
Author(s):  
Alberto Magi ◽  
Lorenzo Tattini ◽  
Ingrid Cifola ◽  
Romina D’Aurizio ◽  
Matteo Benelli ◽  
...  

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