CEQer: A Graphical Tool for Copy Number and Allelic Imbalance Detection from Whole-Exome Sequencing Data

<div><p>Copy number alterations (CNA) are common events occurring in leukaemias and solid tumors. Comparative Genome Hybridization (CGH) is actually the gold standard technique to analyze CNAs; however, CGH analysis requires dedicated instruments and is able to perform only low resolution Loss of Heterozygosity (LOH) analyses. Here we present CEQer (Comparative Exome Quantification analyzer), a new graphical, event-driven tool for CNA/allelic-imbalance (AI) coupled analysis of exome sequencing data. By using case-control matched exome data, CEQer performs a comparative digital exonic quantification to generate CNA data and couples this information with exome-wide LOH and allelic imbalance detection. This data is used to build mixed statistical/heuristic models allowing the identification of CNA/AI events. To test our tool, we initially used in silico generated data, then we performed whole-exome sequencing from 20 leukemic specimens and corresponding matched controls and we analyzed the results using CEQer. Taken globally, these analyses showed that the combined use of comparative digital exon quantification and LOH/AI allows generating very accurate CNA data. Therefore, we propose CEQer as an efficient, robust and user-friendly graphical tool for the identification of CNA/AI in the context of whole-exome sequencing data.</p></div

Summary of the main characteristics of 6 copy number analysis tools.

<p>L/W/M: Linux/Windows/MacOS.</p>1<p>L/W/M for processing. W is required for visualization and real-time filtering.</p>2<p>The Java Runtime is required.</p>3<p>The. NET framework Runtime is required. If not present in the system, it is automatically installed during CEQer setup.</p

CNA analysis of sample CML002BC.

<p>a) Genome view of patient CML002BC. Coverage data are represented as Normalized Log2 Ratios. Individual colors represent specific chromosomes from 1 (left) to Y (right). b) Individual views of chromosome 9 and chromosome 22 (c). Dark-yellow dots indicate copy neutral exons, red dots copy gain CNA regions. Thick red horizontal bars identify copy gain regions. Boxed panels represent magnified views of the CNA boundaries: individual genes/exons delimiting the copy gain CNA region (s) are indicated.</p

Whole-genome view of CML-CP (a, CML-CP-001 to 009) and aCML samples (b, aCML-001 to 008).

<p>The two black arrows point to a deletion occurring in patient CML-CP-003; the red arrow points to an amplification of the whole chromosome 11 in patient aCML-002.</p

CNA analysis of sample aCML-002 and CML-CP-003.

<p>Whole-exome view of patients aCML-002 (a) and CML-CP-003 (b). Coverage data are indicated as Normalized Log2 Ratios. Individual colors represent specific chromosomes from 1 (left) to Y (right). Red and black arrows indicate CNA areas in patient aCML-002 and CML-CP-003, respectively. c, d) Individual views of chromosome 9 (c) and 22 (d) of patient CML-CP-003. Dark-yellow dots indicate copy neutral exons, green dots copy loss CNA exons. Thick green horizontal bars identify copy loss regions. e) Detailed view of the boundaries delimiting the CNA regions in chromosome 9 (upper panel) and 22 (lower panel). Individual genes/exons delimiting the copy loss CNA region (s) are shown. Blue boxed rectangles highlight the candidate LOH positions, marked as green circles. f) Proposed model of derivative chromosome 9 partial deletion: the boxed regions represent the deleted genomic loci as identified by CEQer. The relative position of the two regions in the derivative chromosome 9 is shown in the bottom part of the panel. g) Dual color <i>BCR/ABL1</i> FISH analysis of patient CML-CP-003 at onset of the disease. h) Sanger sequencing at onset of the disease and upon cytogenetic remission of 6 heterozygous single nucleotide polymorphism sites shown in panel e, identified by CEQer as putative LOH loci. The blue boxes indicate the heterozygous nucleotides; the black arrows point to the corresponding chromatogram peaks.</p

CNA analysis of sample CML001BC and CML004BC.

<p>a) Genome view of patient CML001BC analyzed by CEQer and (b) corresponding CGH analysis. c) Genome view of patient CML004BC and (d) corresponding CGH analysis. Genome views of coverage data are represented as Normalized Log2 Ratios. Individual colors represent specific chromosomes from 1 (left) to X (right). e) Individual views of CML001BC-chromosome 9 and of CML004BC-chromosome 17. Dark-yellow dots indicate copy neutral exons; green dots copy loss and red dots copy gain CNA regions. Thick red and green horizontal bars identify copy gain and loss regions, respectively. Large gray circles indicate heterozygous positions in the control dataset whose heterozygosity is conserved in the case. Large green, blue and dark-red circles indicate copy loss, +1 copy gain and +2 copy gain LOH/AI events, respectively. The position of LOH/AI markers on the y axis indicates the corresponding allelic ratio.</p

Whole-exome sequencing identification of non-synonymous SNP variants of 10 CHI patients.

*<p>Mutation reported in Human Genome Mutation Database( HGMD).</p><p>PolyPhen/SIFT: (−) benign or tolerated; (+) possibly damaging/DAMAGING Low confidence;</p><p>(++) probably damaging/DAMAGING.</p><p>In bold known causative genes.</p

Functional annotation of novel variants.

<p>Functional annotation of novel variants.</p

Genome-wide screening of copy number alterations and LOH events in renal cell carcinomas and integration with gene expression profile-0

<p><b>Copyright information:</b></p><p>Taken from "Genome-wide screening of copy number alterations and LOH events in renal cell carcinomas and integration with gene expression profile"</p><p>http://www.molecular-cancer.com/content/7/1/6</p><p>Molecular Cancer 2008;7():6-6.</p><p>Published online 14 Jan 2008</p><p>PMCID:PMC2253555.</p><p></p>d blue blocks). Each tumor sample was compared to its matched normal blood sample, and regions of DNA copy number gain (red lines) and copy number loss (green lines) were plotted along each chromosome. Datasets from only GeneChip50K Hind arrays were used