Advanced Neurogenomics

Period of duration of course
‌‌
Course info
Number of course hours
60
Number of hours of lecturers of reference
60
CFU 9
‌‌

Modalità esame

oral exam

Prerequisiti

PhD students

Programma

1) A primer on regulation of gene expression and statistical considerations

2) RNA-seq: how it works

3) Sequence quality control and mapping algorithms

4) Introduction to long-read sequencing (L. Pandolfini)

5) Hands-on: Long Read Sequencing Data Formats (L. Pandolfini)

6) Detection of differential gene expression

7) Clustering and other methods to reduce dimensionality

8) Gene Ontology and Gene Set Enrichment

9) Network analysis

10) RNA metabolism: splicing, stability & decay (L. Pandolfini)

11) Epitranscriptomics (L. Pandolfini)

12) Applications of network analysis to the brain

13) Hands-on: Analysis of differential expression using DESeq2

14) Hands-on: Analysis of GO terms and pathways using WebGestalt

15) Riboseq e miRNAs

16) Single-cell RNA-seq, methods and analysis

17) Single-cell RNA-seq, applications to the nervous system

18) Methods for spatial transcriptomics

19) ScRNA and vertebrate brain evolution (L. Pandolfini)

20) Patchseq and STARMAP

21) hands-on: exploration of ScRNAseq data

22) Proteome analysis by mass-spectroscopy

23) Local synaptic translation

24) Epigenetic analysis: DNA methylation and

ChIP-seq

25) Chromatin 3D conformation and evolution (L. Pandolfini)

26) Examples of epigenetic studies in the nervous system


27) Hands-on: Exploration of ENCODE datasets (L. Pandolfini)


28) - Comparative Genomics 1/3: from Assembly to Evolution (L. Pandolfini)

29) - Comparative Genomics 2/3: Gene Synteny (L. Pandolfini)

30) - Comparative Genomics 3/3: Advanced Transgenesis (L. Pandolfini)

Obiettivi formativi

Aims of the course are: 1) to educate students in the critical reading of omics-based publication both for the experimental and data analysis parts 2) to illustrate how these technologies have provided novel insights into the functional organization of the nervous system and 3) to provide students with the knowledge necessary to design their own omics-based projects, perform initial data analysis and interact with bioinformaticians for more complex anaylsis

Riferimenti bibliografici

Cellerino & Sanguanini "Transcriptome analysis" Ed. Scuola Normale and articles from scientific journals