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. 2018 Mar 1;27(5):853-859.
doi: 10.1093/hmg/ddy005.

Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes

Affiliations

Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes

Xingyi Guo et al. Hum Mol Genet. .

Abstract

Functional disruptions of susceptibility genes by large genomic structure variant (SV) deletions in germlines are known to be associated with cancer risk. However, few studies have been conducted to systematically search for SV deletions in breast cancer susceptibility genes. We analysed deep (> 30x) whole-genome sequencing (WGS) data generated in blood samples from 128 breast cancer patients of Asian and European descent with either a strong family history of breast cancer or early cancer onset disease. To identify SV deletions in known or suspected breast cancer susceptibility genes, we used multiple SV calling tools including Genome STRiP, Delly, Manta, BreakDancer and Pindel. SV deletions were detected by at least three of these bioinformatics tools in five genes. Specifically, we identified heterozygous deletions covering a fraction of the coding regions of BRCA1 (with approximately 80kb in two patients), and TP53 genes (with ∼1.6 kb in two patients), and of intronic regions (∼1 kb) of the PALB2 (one patient), PTEN (three patients) and RAD51C genes (one patient). We confirmed the presence of these deletions using real-time quantitative PCR (qPCR). Our study identified novel SV deletions in breast cancer susceptibility genes and the identification of such SV deletions may improve clinical testing.

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Figures

Figure 1.
Figure 1.
SV deletions in the coding regions of BRCA1 and qPCR validation. (A) SV deletions in the coding regions of BRCA1 were identified by multiple tools, including GenomeSTRiP, Delly, and Manta. The black track indicates the two patients carrying the SV deletion, which can be observed through the reduction of the read densities to half in the deleted regions, compared with the flanking undeleted regions (indicated by the dashed lines). (B) Results from qPCR validation. Deletions were observed among two patients predicted to carry the deletions based on the WGS data but not in 10 control samples (predicted to not be carrying the deletions based on WGS data or 1000 Genomes). Technique replications of qPCR result for each sample are represented by each dot.
Figure 2.
Figure 2.
SV deletion in the TP53 and qPCR validation. (A) An SV deletion in the last exon of the TP53 isoform was identified in two patients. (B) Results from qPCR validation for these two cases and 26 control samples.
Figure 3.
Figure 3.
SV deletions in the intronic regions of PTEN, PALB2 and RAD51C and qPCR validation. (A–C) SV deletions in the intronic regions of PALB2, PTEN, and RAD51C. At the top of each panel: epigenetic landscape of SV deletion. From top to bottom, RefSeq genes; layered H3K4Me1, H3K4Me3, and H3K27Ac histone modifications; DNase clusters; clustered ChIP-seq binding sites; The signals of different layered histone modifications from the same ENCODE cell line are shown in the same color. (D) qPCR results for the deletion in PTEN. (E) qPCR results for the deletion in RAD51C.

References

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