Gross Chromosomal Rearrangements (GCRs) play an important role in human diseases, including cancer. Although most of the nonessential Genome Instability Suppressing (GIS) genes in Saccharomyces cerevisiae are known, the essential genes in which mutations can cause increased GCR rates are not well understood. Here 2 S. cerevisiae GCR assays were used to screen a targeted collection of temperature-sensitive mutants to identify mutations that caused increased GCR rates. This identified 94 essential GIS (eGIS) genes in which mutations cause increased GCR rates and 38 candidate eGIS genes that encode eGIS1 protein-interacting or family member proteins. Analysis of TCGA data using the human genes predicted to encode the proteins and protein complexes implicated by the S. cerevisiae eGIS genes revealed a significant enrichment of mutations affecting predicted human eGIS genes in 10 of the 16 cancers analyzed.

It is estimated that 10 to 20% of all genes in the human genome encode cell surface proteins and due to their subcellular localization these proteins represent excellent targets for cancer diagnosis and therapeutics. Therefore, a precise characterization of the surfaceome set in different types of tumor is needed. Using TCGA data from 15 different tumor types and a new method to identify cancer genes, the S-score, we identified several potential therapeutic targets within the surfaceome set. This allowed us to expand a previous analysis from us and provided a clear characterization of the human surfaceome in the tumor landscape. Moreover, we present evidence that a three-gene set—WNT5A, CNGA2, and IGSF9B—can be used as a signature associated with shorter survival in breast cancer patients. The data made available here will help the community to develop more efficient diagnostic and therapeutic tools for a variety of tumor types.

BackgroundDifferences in gene expression have a significant role in the diversity of phenotypes in humans. Here we integrated human public data from ENCODE, 1000 Genomes and Geuvadis to explore the populational landscape of INDELs affecting transcription factor-binding sites (TFBS). A significant fraction of TFBS close to the transcription start site of known genes is affected by INDELs with a consequent effect at the expression of the associated gene.ResultsHundreds of TFBS-affecting INDELs (TFBS-ID) show a differential frequency between human populations, suggesting a role of natural selection in the spread of such variant INDELs. A comparison with a dataset of known human genomic regions under natural selection allowed us to identify several cases of TFBS-ID likely involved in populational adaptations. Ontology analyses on the differential TFBS-ID further indicated several biological processes under natural selection in different populations.ConclusionTogether, our results strongly suggest that INDELs have an important role in modulating gene expression patterns in humans. The dataset we make available, together with other data reporting variability at both regulatory and coding regions of genes, represent a powerful tool for studies aiming to better understand the evolution of gene regulatory networks in humans.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1744-5) contains supplementary material, which is available to authorized users.