Biotechnology and Genomic for Industry and Environment

General aims: The course aims to introduce the students to the main approaches to functional genomics. Students will learn to apply the high-throughput techniques based on DNA microarrays and next generation sequencing NGS, measuring their potentials and their problems and limits. Focus will be placed on data mining methodologies, from image analysis to data normalization and statistical filtering to gene clustering and gene ontology. The availability of functional database and their use for improving biomedical research will also be explained. Specific Topics Functional genomics and high-throughput methodologies: Next generation sequencing and array-based techniques ; DNA microarrays technology: designing an experiment ; Preparing targets, labeling and hybridization; Image analysis, normalization and statistical filtering; Microarray analysis softwares; False discovery rate and experimental design ;Gene clustering and data mining methods;Gene ontology Il metaclustering; Local and general Databases; model organisms’ Databases; Chromatin Immunoprecipitation; Genomic localization of proteins; Transcriptional regulation of cell cycle ; Damage response; Transcriptional networks in eukaryotic genomes; Genome-wide analysis of epigenetic modifications; Protein Interaction networks and functional networks. Functional Genomics and high-throughput techniques: Microarrays and next generation sequencing 0.3 CFU DNA microarrays technology – experimental design 0.3 Target selection, probe labeling and hybridization 0.3 Data normalization and statistical filtering 0.2 Softwares for microarray analysis 0.3 False discovery rate and data significance 0. 2 Gene clustering methods and data mining 0.4 Gene ontology 0.4 Meta-clustering and meta-analysis 0.4 Using microarrays for pathology profiling 0.2 RNAseq Methodologies 0.2 Pipeline for processing RNAseq data 0.2 Transcriptomics databases 0.2 Model Organisms Databases 0.2 Chromatin Immunoprecipitation 0.2 Genomic mapping of proteins (ChIP on chip and Chipseq) 0.3 Analysis of genetic interactions 0.2 Analysis of physical interactions 0.2 Transcriptional networks and their evolution 0.3 Genomewide chromatin modification analysis 0.4 Techniques for studying single cell transcriptome and epigenome 0.2 Models for systems’ biology 0.2 Microbiome analysis tools 0.2

Basic knowledge of Cellular and Molecular Biology. Basic knowledge of statistics.

No textbooks but didactical materials available on e-learning Moodle platform

Lessons in classroom

4 hours/week

Presentation and discussion of Functional Genomics papers from recent scientific literature

Frontal lessons and computer-aided practical training sessions