Obiettivi Formativi

Il corso permetterà di acquisire le nozioni e le abilità computazionali necessarie per lo studio di network molecolari che controllano la miriade di processi biologici che governano le strutture e le funzioni cellulari. In particolare, gli studenti acquisiranno competenze su approcci bioinformatici e tools necessari per la ricerca in database, realizzazione di allineamenti e analisi di sequenze, ed impareranno ad analizzare metagenomi e complessi microbiomi, la filogenesi e l’evoluzione genomica, interi trascrittomi ed i non-coding RNA.

Learning Goals

Students will be provided with basic knowledge and computational skills necessary for an in-depth understanding of molecular networks that control the myriad of biological processes governing cell structure and function. In particular, the students will acquire competence on bioinformatics approaches and tools needed for database searching, sequence alignment and analysis and will learn to investigate metagenomes and complex microbiomes, phylogeny and genome evolution as well as whole-transcriptomes and non-coding RNAs.

Metodi didattici

Il corso viene erogato attraverso lezioni frontali in aula integrate con esercitazioni pratiche in aula e nel laboratorio di bioinformatica

Teaching Methods

The course is delivered through lectures, integrated with classroom exercises and hands-on sessions in the laboratory of bioinformatics.

Prerequisiti

Gli studenti devono possedere basi di biologia cellulare, biologia molecolare, biochimica, anatomia umana e fisiologia umana.

Prerequisites

Good knowledge of statistics, molecular biology, genetics, biochemistry, and microbiology is required.

Verifiche dell'apprendimento

L’esame finale consisterà in una prova orale valutata in trentesimi ed eventuale lode. Sarà valutato il livello delle conoscenze maturate sui contenuti specifici del corso, la proprietà di linguaggio e la chiarezza espositiva.

Assessment

The final exam will consist of an oral test assessed in thirtieths and possible praise. The level of knowledge gained on the specific contents of the course, the property of language and the clarity of exposition will be evaluated.

Programma del Corso

Il corso si svolge nel secondo semestre. L’itinerario di apprendimento inizierà dal contributo della bioinformatica verso la genetica e la genomica moderna trattando i concetti base del sequenziamento del DNA, database biologici (tipi, classificazione e sistemi di recupero dati), allineamento di sequenze di DNA e proteine (es. dot-matrix; Algoritmi di Needleman-Wunsch e Smith-Waterman; matrici di punteggio come matrici PAM e BLOSUM; algoritmo BLAST) e filogenesi molecolare. Il corso proseguirà introducendo gli studenti al sequenziamento degli acidi nucleici di seconda e terza generazione combinando sessioni sia teoriche che pratiche che illustrano i concetti del sequenziamento moderno, i pro e i contro delle diverse piattaforme di Next Generation Sequencing (NGS); principali metodi di preparazione delle librerie genomiche e strategie di analisi dei dati NGS. In particolare, il lavoro di bioinformatica includerà un'introduzione all’analisi di qualità dei dati NGS e alla loro pre-elaborazione, incluso il filtraggio delle reads, la mappatura delle reads e l'analisi dei dati di sequenziamento genomico, metagenomico e del trascrittoma. Il corso si concluderà con sessioni teoriche e lavoro pratico che descrivono le complessità dell'assemblaggio del genoma e del trascrittoma, l'analisi del microbioma e le reti di regolazione genica ricostruite dai dati di RNA-seq e metagenomici. Le sessioni saranno combinate al fine di offrire agli studenti un'esperienza di apprendimento equilibrata garantendo molto tempo alle sessioni pratiche, e fornendo così agli studenti gli strumenti computazionali e le esperienze necessarie per l'analisi NGS di reti molecolari e “pathways” che controllano i principali processi cellulari. PROGRAM PART I: Introduction to bioinformatics and biological databases The objectives of bioinformatics; Contribution of bioinformatics toward modern genetics and genomics; Introduction to biological databases: types of databases, classification and data retrieval; Nucleotide sequence databases (EMBL/DDBJ/GenBank; RefSeq); The Ensembl database; Protein sequence databases (TrEMBL; Uniprot; Enterez Protein). Introduction to nucleic acid sequencing Overview of first-, second-, and third-generation sequencing; Sanger Sequencing Data Analysis; Whole genome/transcriptome sequencing using Next Generation Sequencing (NGS); Ins and outs of different NGS platforms; Metagenomics; Targeted and De-novo sequencing; Raw data generated by NGS technologies. Comparison of DNA and amino acid sequences and molecular phylogeny Biological sequences and their analysis; Introduction to pairwise alignment; Global and local alignment; Sequence similarity and scoring methods; Dot-Matrix method; Scoring matrices (PAM and BLOSUM matrices); The BLAST algorithm and database search; Multiple sequence alignment and phylogenetic analysis; Statistical validation methods: Bootstrap analysis; Tools and software used for tree construction. PART II: Bioinformatics tools and methods in NGS data analysis FASTQ file format, and base quality score; NGS data quality control and preprocessing; Read mapping; SAM/BAM as the standard mapping file format; De novo genome assembly; Contig assembly algorithms; Scaffolding; Assembly quality evaluation; Gap closure; RNA-Seq data analysis; Identification of differentially expressed genes; Functional analysis of identified genes; Metagenomics; Taxonomic characterization of a microbial community; Identification of differentially abundant species or operational taxonomic units (OTUs). Biological Networks: Tools, Methods, and Analysis Types of biological networks: protein-protein interaction networks, disease-gene interaction networks; metabolic networks, and gene regulatory networks; Gene Ontology (GO) and KEGG Orthology (KO) vocabularies for annotating gene and protein functions; Bioinformatics utilities for GO/KO annotation/enrichment analysis.

Course Syllabus

The course takes place in the second semester. The training course will start from the contribution of bioinformatics towards modern genetics and genomics dealing with the basic concepts of standard DNA sequencing, biological databases (types, classification and data retrieval), alignment of DNA and protein sequences (i.e. dot-matrix method; Needleman-Wunsch and Smith-Waterman algorithms; scoring matrices such as PAM and BLOSUM matrices; BLAST algorithm) and molecular phylogeny. The course will continue by introducing students to second- and third-generation nucleic acids sequencing by combining both theoretical and hands-on practical sessions that illustrate the concepts of modern sequencing, ins and outs of different Next-Generation Sequencing (NGS) platforms; principal library preparation methods, and data analysis strategies. In particular, bioinformatics work will include an introduction to the quality control NGS data and their pre-processing including read filtering, read mapping, and the analysis of genomic, metagenomic and transcriptome sequencing data. The course will conclude with both theoretical sessions and practical work detailing the complexities of genome and transcriptome assembly, microbiome analysis, and gene regulatory networks reconstructed from RNA-seq and metagenomics data. Sessions will be combined in order to offer a balanced learning experience by ensuring a plenty of time in hands-on sessions, thus providing students with the necessary computational tools, and experiences, for NGS analysis of molecular networks and signalling pathways that control fundamental cellular processes. PROGRAM PART I: Introduction to bioinformatics and biological databases The objectives of bioinformatics; Contribution of bioinformatics toward modern genetics and genomics; Introduction to biological databases: types of databases, classification and data retrieval; Nucleotide sequence databases (EMBL/DDBJ/GenBank; RefSeq); The Ensembl database; Protein sequence databases (TrEMBL; Uniprot; Enterez Protein). Introduction to nucleic acid sequencing Overview of first-, second-, and third-generation sequencing; Sanger Sequencing Data Analysis; Whole genome/transcriptome sequencing using Next Generation Sequencing (NGS); Ins and outs of different NGS platforms; Metagenomics; Targeted and De-novo sequencing; Raw data generated by NGS technologies. Comparison of DNA and amino acid sequences and molecular phylogeny Biological sequences and their analysis; Introduction to pairwise alignment; Global and local alignment; Sequence similarity and scoring methods; Dot-Matrix method; Scoring matrices (PAM and BLOSUM matrices); The BLAST algorithm and database search; Multiple sequence alignment and phylogenetic analysis; Statistical validation methods: Bootstrap analysis; Tools and software used for tree construction. PART II: Bioinformatics tools and methods in NGS data analysis FASTQ file format, and base quality score; NGS data quality control and preprocessing; Read mapping; SAM/BAM as the standard mapping file format; De novo genome assembly; Contig assembly algorithms; Scaffolding; Assembly quality evaluation; Gap closure; RNA-Seq data analysis; Identification of differentially expressed genes; Functional analysis of identified genes; Metagenomics; Taxonomic characterization of a microbial community; Identification of differentially abundant species or operational taxonomic units (OTUs). Biological Networks: Tools, Methods, and Analysis Types of biological networks: protein-protein interaction networks, disease-gene interaction networks; metabolic networks, and gene regulatory networks; Gene Ontology (GO) and KEGG Orthology (KO) vocabularies for annotating gene and protein functions; Bioinformatics utilities for GO/KO annotation/enrichment analysis.