OMICS: BIOTECHNOLOGY AND AI FOR HEALTH
Academic year2023/24
CourseBIOTECHNOLOGIES AND APPLIED ARTIFICIAL INTELLIGENCE FOR HEALTH
Code552EE
Credits6
PeriodSemester 1
LanguageEnglish
| Modules | Area | Type | Hours | Teacher(s) |
| OMICS: BIOTECHNOLOGY AND AI FOR HEALTH | BIO/18,BIO/11 | LEZIONI | 64 | |
Obiettivi di apprendimento
Conoscenze
Lo studente imparerà I principali concetti alla base del sequenziamento high throughput, della genotipizzazione attraverso gli array. Imparerà inoltre le metodologie alla base dell’interpretazione dei dati genomici in relazione a fenotipi patologici. Imparerà, inoltre, come si applicano dati genomici nel contesto di study di tipo “genome wide association study” (GWAS) o (Whole genome sequencing)
In particolare il corso si concentrerà su:
- Studi di genomica attraverso micro-array
- Studi di genomica attraverso NGS
- applicazioni pratiche di GWAs ed NGS
- Come analizzare i dati di GWAS ed NGS (dati grezzi, QCs)
Knowledge
The student will learn the principles of high throughput sequencing, array genotyping and data analysis to understand the effect of human genetic variation in health and disease.In addition, the student will learn current applications of genomics data in relation to human health such as, for example, Genome Wide Association studies (GWAs), NGS for resequencing studies to discover rare variants and meta-genomics. By the end of the course The student will also deepen the knowledge about the mechanisms of regulation of gene expression in eukaryotes, especially mechanisms related to epigenetics and regulation by non-coding RNA. The student should acquire knowledge about modern methodologies for high throughput studies of transcriptomics and epigenomics and proteomics. He/she will gain ability to perform a basic data analysis of transcriptomics.
The acquired knowledge will concern:
- genomics through microarray (Genome wide association studies)
- Genomics through Next Generation Sequencing
- Applications of GWAS and NGS
- An overview on how to analyse GWAs and NGS
- epigenetics and epigenomics
- transcriptional, co-transcriptional and post-transcriptional regulation of gene expression by non-coding RNA
- how to perform a transcriptomic analysis
- how to analyse transcriptomic data
Modalità di verifica delle conoscenze
Per controllare l’apprendimento da parte degli studenti i docenti
Durante le prime lezioni introdurranno loro stessi e chiederanno agli studenti di fare altrettanto. Questo è fondamentale per instaurare un dialogo in classe con la funzione di facilitare un dialogo tra i docenti e gli studenti.
- Chiederanno spesso ragguagli sulla chiarezza delle spiegazioni
- Porranno agli studenti delle domande per valutare l’apprendimento degli studenti
- Porranno problemi da risolvere ed esempi per un maggiore coinvolgimento degli studenti
Assessment criteria of knowledge
For the assessment of knowledge the teacher:
- at the first meeting introduces themselves and asks to the students to do the same. This helps to establish a class dialogue, which facilitates the communication between students and teacher
- often asks about the clarity of the explanation
- asks the students questions about the concepts to evaluates the level of understanding
- provides practical examples to the class or poses problems / questions asking to volunteers to find the solution
Capacità
Alla fine del Corso gli studenti saranno capaci di
- Analizzare dati genomici nel contesto di studi di associazione
- Sapranno pianificare esperimenti di genomica/trascrittomica
- Leggere e comprendere articoli metodologici per scegliere approcci omici adeguati al problema biologico che devono affrontare
- Analizzare dataset di genomica trascrittomica
Skills
By the end of the course:
- Acquisition of the understanding on how to analyse genomics data in the contest of genetic epidemiology studies and associatin studies
- Acquisition of notions about the mechanisms of regulation of gene expression in eukaryotes, with particular attention to epigenetics and regulation by non-coding RNA. Study of the "omics" science, with particular attention to transcriptomics and epigenomics. Focus on micro-arrays as a platform for conducting high throughput studies.
- The student will learn how to plan molecular experiments with a "data driven" approach rather than "hypothesis driven"
- the student will be able to critically review the best technological approach for solving a specific "omics" problem
- the student will be able to analyse genomic/transcriptomic datasets
Modalità di verifica delle capacità
Gli obbiettivi formativi del Corso verranno raggiunti, se lo studente sarà in grado di discutere criticamente dataset omici. Inoltre, lo studente sarà in grado di comprendere, ed analizzare studi omici, come per esempio studi eseguite con metodiche NGS o basate su array. Il raggiungimento degli obbiettivi formativi verrà verificato durante l’esame orale.
Assessment criteria of skills
The course objective is reached if the student can critically discuss transcriptome datasets. The student will be able to read, review and understand omics data such as those published on scientific papers. Additionally, the student will be able to understand genomic association studies and will be able to employ genomic methodologies to in genome wide association studies. This will be evaluated during the oral examination.
Modalità di verifica dei comportamenti
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Assessment criteria of behaviors
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Prerequisiti (conoscenze iniziali)
Conoscenze pregresse di Biologia Molecolare di Genetica e di Statistica sono essenziali per seguire al meglio Il corso
Lo studente è invitato a verificare l'esistenza di eventuali propedeuticità consultando il Regolamento del Corso di studi relativo al proprio anno di immatricolazione. Un esame sostenuto in violazione delle regole di propedeuticità è nullo (Regolamento didattico d’Ateneo, art. 24, comma 3)"
Prerequisites
Knowledge of molecular biology, genetics, and biostatistics makes learning more fruitful
Students are invited to verify the existence of any preparatory requirements by consulting the Regulatory documents of the course of study of the academic year of matriculation. An exam taken in violation of the propaedeutic rules is invalid (University teaching regulations, art. 24, paragraph 3)"
Prerequisiti per studi successivi
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Prerequisites for further study
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Indicazioni metodologiche
Le lezioni sono frontali, con ausilio di slide e schemi. Durante i laboratori inforamtici (in silico lab) si usano i PC delle aule informatiche o i PC personali degli studenti. Il sito di elearning del corso verrà utilizzato per lo scaricamento del materiale didattico fornito dall docente.
Il docente si rende disponibile a ricevere gli studenti previa comunicazione di una mail per accordarsi sull'orario.
Teaching methods
lectures, with the aid of slides.
Lab experiences: PC and ad hoc software for data analysis will be used.
elearning website: download of ppts and communications between teacher-student
type of interaction between student and teacher: meeting, email, skype, teams
Programma (contenuti dell'insegnamento)
- Introduzione alla seconda parte del corso. La genetica moderna e gli approcci di genomica nelle patologie umane. Gli studi su tutto il genoma i Genome wide association studies (GWAS)
- I microarray utilizzati per la genotipizzazione, strumenti analitici e statistici utilizzati negli studi di tipo GWAS
- Il linkage disequilibrium come strumento per l’imputazione genetica
- Tecniche di Next Generation Sequencing (NGS) per analizzare interi esomi e genomi, come si analizzano le varianti rare nel contesto delle degli studi di popolazione.
- Strumenti informatici per interpretare dati genomici e comprendere la funzione delle varianti
- Calcolo degli score poligenici per valutare l’effetto complessivo delle varianti nella suscettibilità alle patlogie
Syllabus
- Introduction to the first part of the course. Definition of Epigenomics, Transcriptomics, miRNomics. General description of the biomolecules of interest: methylated DNA, chromatin, RNA, and miRNA. Numerosity of these biomolecules in eukaryotic biological systems.
- Epigenetic modifications of DNA: methylation of cytosines and CpG islands. Demethylases de novo and maintenance demethylases, proteins involved and mechanism of function. Examples of DNA methylation during embryonic and nervous system development and in pathology.
- Methods for the study of DNA methylation: historical methods, sodium bisulfite methods, use of restriction enzymes, immunoprecipitation. Difference between the microarray and the sequencing approach.
- Description of chromatin. String necklace of beads and 30 nm fiber (solenoid pattern and zigzag pattern), higher order chromatin compaction degrees. Histone proteins and nucleosome formation. Histone/DNA interaction in the nucleosome. Histone H1. Role of chromatin in the regulation of gene expression. Histone modifications and regulatory role.
- The other proteins in chromatin: enhancers, replication factors, transcription factors, regulators of RNA maturation and of RNA export. Main features of DNA binding proteins and RNA binding proteins. Chromatin proteins and modifications as drug targets.
- Methods to study chromatin modification and activation state, DNA-protein and protein-protein interactions. Immunoprecipitation of chromatin and its variants (for maps of changes in histone proteins, nucleosome occupancy, transcription factors). Implementation of these techniques in epigenomic approaches. Description of the ATAC-seq approach.
- The RNA word in the eukaryotic cell. Description and numerosity of coding and non-coding RNA. Small-and long-non coding RNA. Biogenesis and maturation of miRNAs and their regulation of gene expression. Extracellular release of miRNAs. miRNA and siRNA as therapeutics.
- Competing endogenous RNA (ceRNA). Classification and biogenesis of long non coding RNAs: epigenetic, transcriptional and post-transcriptional regulation. Description of the Xist non coding RNA. Biogenesis and function of circular RNAs (circRNA, ciRNA, EIciRNA).
- Microarray: focus on the technological platforms. How to select the appropriate array. Sample preparation. Gene level /exon level / alternative splicing analysis. TAC software. Table view, "Scatter plot", "Volcano Plot", "Hierarchical clustering", "WikiPathway". How to analyse and interpret "alternative splicing data". Principal component analysis. Gene Onytology. AI for gene ontology.
- Introduction to the second part of the course. Modern Genetics of Genomics approaches in health and diseases. Genome wide association studies (GWAS) to study the genetic susceptibility of human traits.
- Microarray methods for genotyping large number of single nucleotide polymorphisms (SNPs) analytical and statistical methods used for GWAS analysis.
- Linkage disequilibrium (LD) and imputation of genomic data.
- Next generation sequencing (NGS) to analyze whole genomes and whole exomes. How to analyze rare variants in the context of population studies.
- Informatic tools to interpret genomic data and understand the function of the variants.
- Computation of polygenic risk score, to calculate the overall effect of the genetic variants in disease susceptibility.
Bibliografia e materiale didattico
Articoli forniti dal docente e slide in power point fornite dal docente.
Bibliography
Papers (reviews) selected by the teacher. Basic concepts can be found in textbooks of the student (Amaldi, Cox or GeneX or other editions)
Indicazioni per non frequentanti
La frequenza alle attività di laboratorio, nella misura di almeno il 70%, è obbligatoria.
Non-attending students info
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Modalità d'esame
L'esame sarà orale consisterà in una serie di domande riguardanti gli argomenti del corso. Durante l’esame verranno valutate anche la capacità di affrontare problemi sperimentali attraverso il disegno di un piano sperimentale appropriato. L’interpretazione di un dataset o di grafici specifici potrebbe anche essere inclusa nell’esame orale. Sarà richiesto agli studenti di condurre l'analisi di un dataset di trascrittomica e presentarlo all'esame. L’esame durerà circa trenta minuti ed il numero di domande sarà generalmente 3
Assessment methods
The assesmnet will be an oral examination, that consist of an interview between the candidate and the teachers. During the oral examination the candidate may be asked to explain key concepts of the course, solve problems that a researcher may encounter or to try to approach an experimental problem with the proper scientific plan. Interpretation of sample datasets and graphs may also be included. The student will perform the analysis of a transcriptome data and he/she will present it during the examination. The average duration of the interview is 30 minutes, the number of questions is generally 3.
Note
Commissione di esame
Presidente: Daniele Campa
Due membri: Vittoria Raffa, Laura Marchetti
Presidente supplente: Vittoria Raffa
Notes
Examination Committee
President: Daniele Campa
Members: Vittoria Raffa, Laura Marchetti
Vice-President: Vittoria Raffa
Updated: 31/08/2023 09:17
