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BeNeLux Bioinformatics Conference – Antwerp, December 7-8 2015 Abstract ID: P Poster 10th Benelux Bioinformatics Conference bbc 2015 P60. COEXPNETVIZ: THE CONSTRUCTION AND VIZUALISATION OF CO- EXPRESSION NETWORKS Oren Tzfadia 1,2 , Tim Diels 1,2,4 , Sam De Meyer 1,2 , Klaas Vandepoele 1,2 , Yves Van de Peer 1,2,3,5,* & Asaph Aharoni 6 . Department of Plant Systems Biology, VIB, 9052 Ghent, Belgium 1 ; Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium 2 ; Genomics Research Institute (GRI), University of Pretoria, 0028 Pretoria, South Africa 3 ; Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium 4 ; Bioinformatics Institute Ghent, Ghent University, 9052 Ghent, Belgium 5 ; Department of Plant Sciences and the Environment, Weizmann Institute of Science, Rehovot 6 . INTRODUCTION Comparative transcriptomics is a common approach in functional gene discovery efforts. It allows for finding conserved co-expression patterns between orthologous genes in closely related plant species, suggesting that these genes potentially share similar function and regulation. Several efficient co-expression-based tools have been commonly used in plant research but most of these pipelines are limited to data from model systems, which greatly limit their utility. Moreover, in addition, none of the existing pipelines allow plant researchers to make use of their own unpublished gene expression data for performing a comparative co-expression analysis and generate multi-species co-expression networks. RESULTS We introduce CoExpNetViz, a computational tool that uses a set of bait genes as an input (chosen by the user) and a minimum of one pre-processed gene expression dataset. The CoExpNetViz algorithm proceeds in three main steps; (i) for every bait gene submitted, coexpression values are calculated using Pearson correlation coefficients, (ii) non-bait (or target) genes are grouped based on cross-species orthology, and (iii) output files are generated and results can be visualized as network graphs in Cytoscape. AVAILABILITY AND IMPLEMENTATION The CoExpNetViz tool is freely available both as a PHP web server (link: http://bioinformatics.psb.ugent.be/webtools/coexpr/) (implemented in C++) and as a Cytoscape plugin (implemented in Java). Both versions of the CoExpNetViz tool support LINUX and Windows platforms. 104
BeNeLux Bioinformatics Conference – Antwerp, December 7-8 2015 Abstract ID: P Poster 10th Benelux Bioinformatics Conference bbc 2015 P61. THE DETECTION OF PURIFYING SELECTION DURING TUMOUR EVOLUTION UNVEILS CANCER VULNERABILITIES Jimmy Van den Eynden 1* & Erik Larsson 1 . Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Sweden. * jimmy.van.den.eynden@gu.se Identification of somatic mutation patterns indicative of positive selection arguably has become the major goal of cancer genomics. This is motivated by a search for cancer driver genes and pathways that are recurrently activated in tumours but not normal cells, thus providing possible therapeutic windows. However, cancer cells additionally depend on a large number of basic cellular processes, and elevated sensitivity to inhibition of certain essential non-driver genes has been demonstrated in some cases. While such vulnerability genes should in theory be identifiable based on strong purifying (negative) selection in tumors, these patterns have been elusive and purifying selection remains underexplored in cancer. We established a new methodology and, using mutational data from 25 TCGA tumor types, we show for the first time that negative selection in candidate vulnerability genes can be detected. INTRODUCTION Recently it was shown that a hemizygous deletion of the well–known tumour suppressor gene TP53 creates therapeutic vulnerability in colorectal cancer due to concomitant loss of the neighbouring gene POLR2A (Liu et al., 2015). As any damaging mutation occurring in the single allele of a hemizygously deleted essential gene, like POLR2A, is expected to lead to cell death, we hypothesized that purifying selection in these genes could be unveiled by demonstrating a lower number of damaging mutations then could be expected in the absence of any selection. Therefore we used the POLR2A case as a proof-ofconcept to develop a methodology to detect purifying selection in large genome sequencing datasets. METHODS Mutation and copy number data from 25 different cancers types and 7,871 samples were downloaded from the TCGA data portal and pooled together in a large pancancer dataset. Different mutational functional impact scores were calculated using Annovar. Copy number data were analyzed using Gistic 2.0 to differentiate POLR2A copy number neutral from hemizygously deleted samples. RESULTS & DISCUSSION POLR2A was found to be hemizygously deleted in 29% of all samples. As expected, in over 99% this deletion was part of the TP53 (driving) deletion on chromosome 17. POLR2A was mutated 228 times in 2.3% of all samples. While 14 nonsense mutations and small out-of-frame insertions or deletions occurred in the copy number neutral group, none of these damaging mutations were found in the deletion group (p=0.03, fisher test), suggesting purifying selection against this type of mutations. Next to these truncating mutations, also missense mutations that have a damaging effect on the gene’s protein function are expected to be selected against. Therefore we predicted the functional impact of all mutations using different functional impact scores. The median (PolyPhen-2) functional impact score was found to significantly lower in the deletion group compared to the copy number neutral group (p=0.002, Wilcoxon test, fig.1), further confirming that purifying selection has taken place in POLR2A during tumour evolution. These preliminary findings confirm that purifying selection is detectable in vulnerability genes like POLR2A and this approach could be used to detect other, new candidate vulnerability genes. FIGURE 1. Negative selection against POLR2A high impact mutations in hemizygously deleted tumour samples. REFERENCES Liu, Y., Zhang, X., Han, C., Wan, G., Huang, X., Ivan, C., … Lu, X. (2015). TP53 loss creates therapeutic vulnerability in colorectal cancer. Nature, 520(7549), 697–701. http://doi.org/10.1038/nature14418 105
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