Gaitatzes, Athanasios

AbstractCopy number variation (CNV) is a common form of structural variation detected in human genomes, occurring as both constitutional and somatic events. Cytogenetic techniques like chromosomal microarray (CMA) are widely used in analyzing CNVs. However, CMA techniques cannot resolve the full nature of these structural variations (i.e. the orientation and location of associated breakpoint junctions) and must be combined with other cytogenetic techniques, such as karyotyping or FISH, to do so. This makes the development of a next‐generation sequencing (NGS) approach capable of resolving both CNVs and breakpoint junctions desirable. Mate‐pair sequencing (MPseq) is a NGS technology designed to find large structural rearrangements across the entire genome. Here we present an algorithm capable of performing copy number analysis from mate‐pair sequencing data. The algorithm uses a step‐wise procedure involving normalization, segmentation, and classification of the sequencing data. The segmentation technique combines both read depth and discordant mate‐pair reads to increase the sensitivity and resolution of CNV calls. The method is particularly suited to MPseq, which is designed to detect breakpoint junctions at high resolution. This allows for the classification step to accurately calculate copy number levels at the relatively low read depth of MPseq. Here we compare results for a series of hematological cancer samples that were tested with CMA and MPseq. We demonstrate comparable sensitivity to the state‐of‐the‐art CMA technology, with the benefit of improved breakpoint resolution. The algorithm provides a powerful analytical tool for the analysis of MPseq results in cancer.

Abstract Motivation The ability to produce and analyze whole genome sequencing (WGS) data from samples with structural variations (SV) generated the need to visualize such abnormalities in simplified plots. Conventional two-dimensional representations of WGS data frequently use either circular or linear layouts. There are several diverse advantages regarding both these representations, but their major disadvantage is that they do not use the two-dimensional space very efficiently. We propose a layout, termed the Genome U-Plot, which spreads the chromosomes on a two-dimensional surface and essentially quadruples the spatial resolution. We present the Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities. We compare conventional visualization schemas with the Genome U-Plot using visualization metrics such as number of line crossings and crossing angle resolution measures. Based on our metrics, we improve the readability of the resulting graph by at least 2-fold, making apparent important features and making it easy to identify important genomic changes. Results A whole genome visualization tool with high spatial resolution and improved aesthetic qualities. Availability and implementation An implementation and documentation of the Genome U-Plot is publicly available at https://github.com/gaitat/GenomeUPlot. Supplementary information Supplementary data are available at Bioinformatics online.

Abstract TMPRSS2-ERG gene fusions occur in over 50% of prostate cancers, but their impact on clinical outcomes is not well understood. Retention of interstitial genes between TMPRSS2 and ERG has been reported to influence tumor progression in an animal model. In this study, we analyzed the status of TMPRSS2-ERG fusion genes and interstitial genes in tumors from a large cohort of men treated surgically for prostate cancer, associating alterations with biochemical progression. Through whole-genome mate pair sequencing, we mapped and classified rearrangements driving ETS family gene fusions in 133 cases of very low-, low-, intermediate-, and high-risk prostate cancer from radical prostatectomy specimens. TMPRSS2-ERG gene fusions were observed in 44% of cases, and over 90% of these fusions occurred in ERG exons 3 or 4. ERG fusions retaining interstitial sequences occurred more frequently in very low-risk tumors. These tumors also frequently displayed ERG gene fusions involving alternative 5′-partners to TMPRSS2, specifically SLC45A3 and NDRG1 and other ETS family genes, which retained interstitial TMPRSS2/ERG sequences. Lastly, tumors displaying TMPRSS2-ERG fusions that retained interstitial genes were less likely to be associated with biochemical recurrence (P = 0.028). Our results point to more favorable clinical outcomes in patients with ETS family fusion-positive prostate cancers, which retain potential tumor-suppressor genes in the interstitial regions between TMPRSS2 and ERG. Identifying these patients at biopsy might improve patient management, particularly with regard to active surveillance. Cancer Res; 77(22); 6157–67. ©2017 AACR.