TaccLab

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Professor Cristian Taccioli Laboratory

Bioinformatics Laboratory

CRISTIAN TACCIOLIUniversity of Padova

Not living physical systems are simple, and naturally contain little information, whereas life on earth is extremely complex. However, the second law of thermodynamics lead us to expect great uniformity (disorder) or maximum entropy. My group is trying to investigate this nature ambiguity linking biology, thermodynamics and theory of information. We are also interested in using Next Generation techniques when studying the genome of normal and tumor cells of animal models.

DNA, or deoxyribonucleic acid, is the genetic material of all the living organisms. It contains information able to pass information from a generation to another. This information is stored in a code of for nitrogenous bases: adenine (A), guanine (G), cytosine (C), and thymine (T). Human DNA consists of about 3 billion bases for each of the two strands of the double helix, and only 2% of DNA code for proteins that are the bricks of living cells. The rules that regulating, however, the vast complexity of living organisms are still unknown. Most of the topics of "Tacclab" is focused on investigating genomic evolution, comparative and cancer genomics. For a list of forthcoming articles, see below.

FORTHCOMING ARTICLES

GMIEC: a shiny application for the identification of gene-targeted drugs for precision medicinePrecision medicine is a medical approach that takes into account individual genetic variability and often requires Next Generation Sequencing data in order to predict new treatments. Here we present GMIEC, Genomic Modules Identification et Characterization for genomics medicine, an application that is able to identify specific drugs at the level of single patient integrating multi-omics data such as RNA-sequencing, copy-number variation, methylation, Chromatin Immuno-Precipitation and Exome/Whole Genome sequencing. It is also possible to include clinical data related to each patient. GMIEC has been developed as a web-based R-Shiny platform and gives as output a table easy to use and explore. We present GMIEC, a Shiny application for genomics medicine. The tool allows the users the integration of two or more multiple omics datasets (e.g. gene-expression, copy-number), at sample level, to identify groups of genes that share common genomic and corresponding drugs. We demonstrate the characteristics of our application by using it to analyze a prostate cancer data set. GMIEC provides a simple interface for genomics medicine. GMIEC was develop with Shiny to provide an application that does not require advanced programming skills. GMIEC consists of three sub-application for the analysis (GMIEC-AN), the visualization (GMIEC-VIS) and the exploration of results (GMIEC-RES). GMIEC is an open source software and is available at https://github.com/guidmt/GMIEC-shiny

DNA sequence symmetries from randomness: the origin of the Chargaff’s second parity ruleAbstract. Most living organisms rely on double-stranded DNA (dsDNA) to store their genetic information and perpetuate themselves. This biological information ha

Abrogation of esophageal carcinoma development in miR-31 knockout ratsESCC is a deadly disease with few prevention or treatment options. In a dietary Zn deficiency-promoted rat ESCC model with miR-31–controlled inflammation pathway up-regulation, systemic antimiR-31 reduces miR-31 level and inflammation, suppressing ESCC development. We identified Egln3 as a direct miR-31 target and developed a constitutive miR-31 knockout rat model. Interactions of oncogenic miR-31, EGLN3 down-regulation, and inflammation occur in rat and human ESCC tissue. Since miR-31 genetic knockout prevents Zn deficiency-associated ESCC by eliminating or greatly reducing the entire miR-31-EGLN3/STK40-NF-κB–controlled inflammatory process, we conclude that miR-31 and downstream signaling proteins should be tested as prognostic and therapeutic targets and inexpensive Zn supplementation should be implemented for ESCC prevention in deficient populations.