C8491 - Applied and Functional Genomics

Learning outcomes

Upon completion of the course, students will acquire the theoretical and practical foundations for independently conducting genomic analyses, specifically: i) reconstruction and characterization of eukaryotic and prokaryotic genomes; ii) reconstruction and analysis of transcriptomes; iii) identification of interactions between proteins, DNA, and RNA; iv) identification of epigenetic modifications; v) identification of regulatory modules; vi) identification of pathological variants for diagnosis and prognosis, and reconstruction of the molecular mechanisms of pathologies; vii) personalized intervention strategies based on an individual's genomic characteristics.

Course contents

1. Sequencing technologies & genome reconstruction
Short-read vs. long-read platforms; library prep; QC metrics. De novo assembly and reference-based mapping. Genome annotation. Comparative genomics and pan-genome analysis (prokaryotes). Challenges in eukaryotic assembly (repeats, heterozygosity, structural variants).

2. Transcriptome analysis
RNA-seq design and library prep. Alignment, transcript assembly, differential expression. Alternative splicing and isoform quantification. Single-cell and spatial transcriptomics.

3. Protein-DNA and protein-RNA interactions
ChIP-seq, CUT&RUN/CUT&Tag: design, peak calling, motif discovery. CLIP-seq variants for RNA-protein interactions. Identification of TF binding sites and RNA-binding targets.

4. Epigenomics and chromatin architecture
DNA methylation (bisulfite sequencing, arrays). Histone modifications. Chromatin accessibility (ATAC-seq). 3D genome organization (Hi-C). Multi-layer data integration.

5. Regulatory modules and gene networks
Cis-regulatory elements (promoters, enhancers, silencers, insulators). Integrative network inference from multi-omics data. Non-coding RNAs (miRNA, lncRNA) in regulation.

6. Pathological variants: diagnosis, prognosis, mechanisms
Variant calling (SNVs, indels, CNVs, SVs) and functional annotation. Key databases (ClinVar, gnomAD, COSMIC). From genotype to phenotype: monogenic, complex, and cancer genomics case studies.

7. Personalized medicine
Pharmacogenomics. Genomic profiling for treatment selection. Polygenic risk scores. Ethical, legal, and social implications.

Laboratory
Hands-on on UCSC genome browser. Gene annotation, differential expression, variant annotation, data integration.

Students with learning disorders and\or temporary or permanent disabilities: please, contact the office responsible [https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students] as soon as possible so that they can propose acceptable adjustments. The request for adaptation must be submitted in advance (15 days before the exam date) to the lecturer, who will assess the appropriateness of the adjustments, taking into account the teaching objectives.

 

 

Readings/Bibliography

Articles and reviews indicated by the teacher.

Teaching methods

Lectures and PC tutorials.

Practical use of UCSC genome browser and of Galaxy for accessing and analyzing genomic data

Assessment methods

The exam assesses if the student knows the organization of eukaryotic and prokaryotic genomes, the genomic analysis techniques and their application to medicine and pharmacology, and how to analyze gene expression and its regulation. The exam will also assess if the student knows how to access UCSC Genome database, and how to retrieve and analyze genomic data using the UCSC genome browser and Galaxy.

The exam consists of: a) a written exam on the course topics; b) a written test on methodologies used during the laboratory, and c) an optional oral exam.
The maximum score is 30/30. To pass the exam, students need to get at least 18/30.

Teaching tools

PC, internet, videoprojector, board.

Bioinformatic laboratory at the Biotecnology Education Center at Battiferro teaching complex.

Office hours

See the website of Giovanni Capranico