Analysis of the mitochondrial DNA of Schizophrenia patients by next generation sequencing

Mitochondrial DNA (mtDNA), a maternally inherited 16.6-Kb molecule crucial for energy production, is implicated in numerous human traits and disorders. It has been hypothesized that the presence of mutations in the mtDNA may contribute to the complex genetic basis of schizophreniadisease, due to the evidence of maternal inheritance and the presence of schizophrenia symptoms in patients affected of a mitochondrial disorder related to a mtDNA mutation. The present project aims to study the association of variants of mitochondrial DNA (mtDNA), and an increased risk of schizophrenia in a cohort of patients and controls from the same population. The entire mtDNA of 55 schizophrenia patients with an apparent maternal transmission of the disease and 38 controls was sequenced by Next Generation Sequencing (Ion Torrent PGM, Life Technologies) and compared to the reference sequence. The current method for establishing mtDNA haplotypes is Sanger sequencing, which is laborious, timeconsuming, and expensive. With the emergence of Next Generation Sequencing technologies, this sequencing process can be much more quickly and cost-efficiently. We have identified 14 variants that have not been previously reported. Two of them were missense variants: MTATP6 p.V113M and MTND5 p.F334L ,and also three variants encoding rRNA and one variant encoding tRNA. Not significant differences have been found in the number of variants between the two groups. We found that the sequence alignment algorithm employed to align NGS reads played a significant role in the analysis of the data and the resulting mtDNA haplotypes. Further development of the bioinformatics analysis and annotation step would be desirable to facilitate the application of NGS in mtDNA analysis.

miR-143 Interferes with ERK5 Signaling, and Abrogates Prostate Cancer Progression in Mice

Abstract Background: Micro RNAs are small, non-coding, single-stranded RNAs that negatively regulate gene expression at the post-transcriptional level. Since miR-143 was found to be down-regulated in prostate cancer cells, we wanted to analyze its expression in human prostate cancer, and test the ability of miR-43 to arrest prostate cancer cell growth in vitro and in vivo. Results: Expression of miR-143 was analyzed in human prostate cancers by quantitative PCR, and by in situ hybridization. miR-143 was introduced in cancer cells in vivo by electroporation. Bioinformatics analysis and luciferase-based assays were used to determine miR-143 targets. We show in this study that miR-143 levels are inversely correlated with advanced stages of prostate cancer. Rescue of miR-143 expression in cancer cells results in the arrest of cell proliferation and the abrogation of tumor growth in mice. Furthermore, we show that the effects of miR-143 are mediated, at least in part by the inhibition of extracellular signal-regulated kinase-5 (ERK5) activity. We show here that ERK5 is a miR-143 target in prostate cancer. Conclusions: miR-143 is as a new target for prostate cancer treatment.

Bioinformatics: making large-scale science happen

Bionformatics is a rapidly evolving research field dedicated toanalyzing and managing biological data with computational resources. This paperaims to overview some of the processes and applications currently implementedat CCiT-UB¿s Bioinformatics Unit, focusing mainly on the areas of Genomics,Transcriptomics and Proteomics

Integrative analysis of the Regulatory Region of the FGFR3 Oncogene

The study of transcriptional regulation often needs the integration of diverse yet independent data. In the present work, sequence conservation, predic-tion of transcription factor binding sites (TFBS) and gene expression analysis have been applied to the detection of putative transcription factor (TF) modules in the regulatory region of the FGFR3 oncogene. Several TFs with conserved binding sites in the FGFR3 regulatory region have shown high positive or negative corre-lation with FGFR3 expression both in urothelial carcinoma and in benign nevi. By means of conserved TF cluster analysis, two different TF modules have been iden-tified in the promoter and first intron of FGFR3 gene. These modules contain acti-vating AP2, E2F, E47 and SP1 binding sites plus motifs for EGR with possible repressor function.

An integrative computational analysis provides evidence for FBN1-associated network deregulation in trisomy 21

Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.

DnaSP v5: A software for comprehensive analysis of DNA polymorphism data

DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.

An integrative computational analysis provides evidence for FBN1-associated network deregulation in trisomy 21

Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.