Advanced Genomics and Epigenomics

A.Y. 2021/2022
Overall hours
BIO/18 BIO/19
Learning objectives
The course can be split into two separate modules. In the Epigenomics module, students will first learn the genetic and epigenetic mechanisms underlying the regulation of gene expression. Then, they will learn the most widely used genome-wide NGS-based assays for their characterization, like ChIP-Seq, BS-Seq, etc, as well as the respective bioinformatic analysis pipelines. In the Advanced Genomics module, further genome-wide assays will be presented, expanding those already introduced in the Genomics and Transcriptomics course of the first year.
Expected learning outcomes
At the end of the course, students will be able to know apply state of the art bioinformatic pipelines, and understand their results, for:

- Genome wide characterization of transcription regulation (DNA methylation, nucleosome positioning, histone modifications, chromatin interactions, transcription factor binding)
- Advanced methods for the characterization and quantification of transcriptomes in both eukaryotes and prokaryotes, including small RNAs
- Metagenomics analyses
- Evolutionary genomics
Course syllabus and organization

Single session

Lesson period
First semester
Lessons will be held exclusively on line on the Microsoft Teams platform, and students will be able to follow them both in real time according to the course timetable, or through the recordings that will be made available to them.
Course syllabus

Introduction to epigenetics.
The DNA and the chromatin structure.
The nucleosome
Histone Post-translational modifications.
The Writers
The Readers
The biochemistry of DNA Methylation
The Yamanaka experiments and the role of Transcription Factors

Genome-wide assays and bioinformatic analysis protocols for the characterization of genetic and epigenetic regulation of gene transcription:
· Nucleosome occupancy and DNA accessibility (e.g. ATAC-Seq)
· DNA Methylation (e.g. BS-Seq)
· Chromatin conformation capture assays (e.g. Hi-C, ChIA-Pet)
· ChiP-Seq for Transcription Factors
· ChiP-Seq for histone modifications and chromatin states
· DAP-Seq
Computational approaches for the reconstruction of gene regulatory networks with DNA pattern scanning (Information Theory, Position weight matrices), gene expression compendia (CLR and similar), and integration of ChIP-Seq data.
Case studies examples (ChIP-Seq analysis with identification of transcription factor binding sites, CLR on a gene expression compendium of E. coli).

Tn-mutagenesis for the discovery of essential genes or genes involved in specific processes, with high fitness cost - experimental approaches (Tn-Seq, Tn-seq circle, TraDIS, Rb-Tn-seq...) and bioinformatic analysis
Iso-seq for full transcriptome characterization
The small RNA (sRNA) world:
- RNA in Bacteria, bioinformatic prediction of sRNAs. Dynamical properties of genetic circuits with sRNA-dependent regulation. Case studies: Quorum sensing regulation in Vibrio fischeri and in Vibrio cholerae
- sRNA in Plants and their pathogens. Experimental approaches, sequencing and the quest for targets aided by PARE (degradome sequencing) in plants. Immuno-precipitation of Ago1 protein. Bioinformatic approaches to target prediction. Phasing pattern identification. Mobile sRNAs in patho-systems: the Cuscuta case study.
Meta-taxonomics, meta-genomics, meta-transcriptomics for the characterization and the engineering of microbial communities e.g.
Metabolic engineering: basics of metabolic networks and FBA modelling
Quantitative Trait Loci in Plants and Animals
Evolutionary genomics, the pangenome concept, orthologs, paralogs and orthogroups, phylogenetic profiles;
Pathogens and the prediction of antibiotic resistance genes.
Predictive models based on genomic properties, DNA compositional models.
Prerequisites for admission
Genomics and transcriptomics course of the 1st year.
Teaching methods
Lectures that present the biological and methodological bases of the different analysis domains studied will alternate with practical exercises in which students will implement and apply to real data state of the art bioinformatic analysis methods and pipelines.
Teaching Resources
All the slides, lecture notes, articles, along with the code used during practical lectures will be made available through the Ariel web pages of the course.
Assessment methods and Criteria
Students will be assigned practical projects. At the exam, students will present and discuss with the instructors the results obtained.
BIO/18 - GENETICS - University credits: 0
BIO/19 - MICROBIOLOGY - University credits: 0
Lectures: 96 hours
Educational website(s)
Tuesday or Friday, h. 15.00- 17.00
Via Celoria 26 (Department of Biosciences), 2nd Floor Tower B