Gonzalez-Perez A.,University Pompeu Fabra |
Mustonen V.,Wellcome Trust Sanger Institute |
Reva B.,Sloan Kettering Cancer Center |
Ritchie G.R.S.,Wellcome Trust Sanger Institute |
And 30 more authors.
The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. © 2013 Nature America, Inc. All rights reserved. Source
Heriche J.-K.,Cell Biology & Biophysics Unit |
Lees J.G.,University College London |
Morilla I.,University of Malaga |
Morilla I.,Swiss Institute of Bioinformatics |
And 15 more authors.
Molecular Biology of the Cell
The advent of genome-wide RNA interference (RNAi)-based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function - mitotic chromosome condensation - and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest. © 2014 Hériché et al. Source
Kulis M.,University of Barcelona |
Queiros A.C.,University of Barcelona |
Castellano G.,University of Barcelona |
Beekman R.,University of Barcelona |
And 31 more authors.
We analyzed the DNA methylome of ten subpopulations spanning the entire B cell differentiation program by whole-genome bisulfite sequencing and high-density microarrays. We observed that non-CpG methylation disappeared upon B cell commitment, whereas CpG methylation changed extensively during B cell maturation, showing an accumulative pattern and affecting around 30% of all measured CpG sites. Early differentiation stages mainly displayed enhancer demethylation, which was associated with upregulation of key B cell transcription factors and affected multiple genes involved in B cell biology. Late differentiation stages, in contrast, showed extensive demethylation of heterochromatin and methylation gain at Polycomb-repressed areas, and genes with apparent functional impact in B cells were not affected. This signature, which has previously been linked to aging and cancer, was particularly widespread in mature cells with an extended lifespan. Comparing B cell neoplasms with their normal counterparts, we determined that they frequently acquire methylation changes in regions already undergoing dynamic methylation during normal B cell differentiation. © 2015 Nature America, Inc. All rights reserved. Source
Bibikova M.,Illumina |
Queiros A.C.,University of Barcelona |
Martinez-Trillos A.,University of Barcelona |
Barberan-Soler S.,University Pompeu Fabra |
And 17 more authors.
We have extensively characterized the DNA methylomes of 139 patients with chronic lymphocytic leukemia (CLL) with mutated or unmutated IGHV and of several mature B-cell subpopulations through the use of whole-genome bisulfite sequencing and high-density microarrays. The two molecular subtypes of CLL have differing DNA methylomes that seem to represent epigenetic imprints from distinct normal B-cell subpopulations. DNA hypomethylation in the gene body, targeting mostly enhancer sites, was the most frequent difference between naive and memory B cells and between the two molecular subtypes of CLL and normal B cells. Although DNA methylation and gene expression were poorly correlated, we identified gene-body CpG dinucleotides whose methylation was positively or negatively associated with expression. We have also recognized a DNA methylation signature that distinguishes new clinico-biological subtypes of CLL. We propose an epigenomic scenario in which differential methylation in the gene body may have functional and clinical implications in leukemogenesis. © 2012 Nature America, Inc. All rights reserved. Source
Puente X.S.,University of Oviedo |
Bea S.,Institute dinvestigacions Biomediques August Pi i Sunyer IDIBAPS |
Valdes-Mas R.,University of Oviedo |
Villamor N.,University of Barcelona |
And 48 more authors.
Chronic lymphocytic leukaemia (CLL) is a frequent disease in which the genetic alterations determining the clinicobiological behaviour are not fully understood. Here we describe a comprehensive evaluation of the genomic landscape of 452 CLL cases and 54 patients with monoclonal B-lymphocytosis, a precursor disorder. We extend the number of CLL driver alterations, including changes in ZNF292, ZMYM3, ARID1A and PTPN11. We also identify novel recurrent mutations in non-coding regions, including the 3′ region of NOTCH1, which cause aberrant splicing events, increase NOTCH1 activity and result in a more aggressive disease. In addition, mutations in an enhancer located on chromosome 9p13 result in reduced expression of the B-cell-specific transcription factor PAX5. The accumulative number of driver alterations (0 to ≥ 4) discriminated between patients with differences in clinical behaviour. This study provides an integrated portrait of the CLL genomic landscape, identifies new recurrent driver mutations of the disease, and suggests clinical interventions that may improve the management of this neoplasia. © 2015 Macmillan Publishers Limited. All rights reserved. Source