Baldassi C.,Polytechnic University of Turin |
Zamparo M.,Polytechnic University of Turin |
Feinauer C.,Polytechnic University of Turin |
Procaccini A.,Human Genetics Foundation Turin |
And 4 more authors.
PLoS ONE | Year: 2014
In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code. © 2014 Baldassi et al. Source
Pardini B.,Human Genetics Foundation Turin |
Rosa F.,Human Genetics Foundation Turin |
Barone E.,University of Pisa |
Di Gaetano C.,Human Genetics Foundation Turin |
And 15 more authors.
Clinical Cancer Research | Year: 2013
Purpose: Colorectal cancer is routinely treated with a 5-fluorouracil (5-FU)-based chemotherapy. 5-FU incorporates into DNA, and the base excision repair (BER) pathway specifically recognizes such damage. We investigated the association of single-nucleotide polymorphisms (SNP) in the 30-untranslated regions (UTR) of BER genes, and potentially affecting the microRNA (miRNA) binding, on the risk of colorectal cancer, its progression, and prognosis. SNPs in miRNA-binding sites may modulate the posttranscriptional regulation of gene expression operated by miRNAs and explain interindividual variability in BER capacity and response to 5-FU. Experimental Design: We tested 12 SNPs in the 30-UTRs of five BER genes for colorectal cancer susceptibility in a case-control study (1,098 cases and 1,459 healthy controls). Subsequently, we analyzed the role of these SNPs on clinical outcomes of patients (866 in the Training set and 232 in the Replication set). Results: SNPs in theSMUG1and NEIL2 genes were associated with overall survival. In particular,SMUG1 rs2233921 TT carriers showed increased survival compared with those with GT/GG genotypes [HR, 0.54; 95% confidence interval (CI), 0.36-0.81; P = 0.003] in the Training set and after pooling results from the Replication set. The association was more significant following stratification for 5-FU-based chemotherapy (P=5.6 × 10-5). A reduced expression of the reporter gene for the T allele of rs2233921 was observed when compared with the common G allele by in vitro assay. None of the genotyped BER polymorphisms were associated with colorectal cancer risk. Conclusions:Weprovidethe first evidence thatvariations inmiRNA-bindingsites inBERgenes30-UTRmay modulate colorectal cancer prognosis and therapy response. © 2013 American Association for Cancer Research. Source
Singmann P.,Helmholtz Center for Environmental Research |
Shem-Tov D.,Tel Aviv University |
Wahl S.,Helmholtz Center for Environmental Research |
Wahl S.,German Center for Diabetes Research |
And 34 more authors.
Epigenetics and Chromatin | Year: 2015
Background: Disease risk and incidence between males and females reveal differences, and sex is an important component of any investigation of the determinants of phenotypes or disease etiology. Further striking differences between men and women are known, for instance, at the metabolic level. The extent to which men and women vary at the level of the epigenome, however, is not well documented. DNA methylation is the best known epigenetic mechanism to date. Results: In order to shed light on epigenetic differences, we compared autosomal DNA methylation levels between men and women in blood in a large prospective European cohort of 1799 subjects, and replicated our findings in three independent European cohorts. We identified and validated 1184 CpG sites to be differentially methylated between men and women and observed that these CpG sites were distributed across all autosomes. We showed that some of the differentially methylated loci also exhibit differential gene expression between men and women. Finally, we found that the differentially methylated loci are enriched among imprinted genes, and that their genomic location in the genome is concentrated in CpG island shores. Conclusion: Our epigenome-wide association study indicates that differences between men and women are so substantial that they should be considered in design and analyses of future studies. © 2015 Singmann et al. Source