Insegnamento ANIMAL GENOMICS

Corso
Scienze biotecnologiche mediche, veterinarie e forensi
Codice insegnamento
A003041
Curriculum
Veterinario
Docente
Stefano Capomaccio
Docenti
  • Stefano Capomaccio
Ore
  • 52 ore - Stefano Capomaccio
CFU
6
Regolamento
Coorte 2022
Erogato
2023/24
Attività
Caratterizzante
Ambito
Discipline veterinarie e riproduzione animale
Settore
AGR/17
Tipo insegnamento
Opzionale (Optional)
Tipo attività
Attività formativa monodisciplinare
Lingua insegnamento
Inglese
Contenuti

Testi di riferimento
Personal notes and Keynotes from the teacher available in Unistudium.
As optional reference material (student choice): Genomi 4 "T.A. Brown", Edises. 
Genetica Animale, Applicazioni Zootecniche e Veterinarie "G. Pagnacco" Casa Editrice Ambrosiana. 
Obiettivi formativi
The course will illustrate and review some concepts of molecular genetics and the main applications to animals of veterinary interest.
Prerequisiti
Background on genetics and molecular genetics as well as in bioinformatics are desirable but not mandatory.
Metodi didattici
Lectures and laboratory exercises (WET and DRY LAB)
Altre informazioni

Modalità di verifica dell'apprendimento
Evaluation is carried out through an oral exam. A typical exam consists in a 30 minutes interview aiming to assess knowledge level and understanding capabilities on theoretical and methodological contents acquired by the student. The oral exam will also test the student communication skills, lexical congruence and consistency when presenting enquired topics.
Programma esteso
Genome organization and functioning: functional units in complex genomes, transcription and gene expression, mobile genetic elements, epigenetic signals;
Recombinant DNA: manipulation of genetic material, mapping (genetic and physical maps), molecular markers;
New data: Next generation sequencing, assembly of contiguous DNA sequences, interpretation of a genomic sequence; SNP chips and their applications. Genotyping by sequencing.
Genes controlling hereditary diseases and their molecular diagnosis (with special focus on how to).
Analysis of molecular data: biological databases, NGS sequence alignments, GWAS, primer design, selection signatures, analysis of populations with dense data as well as molecular testing in silico.
Great attention will be given to build bioinformatics knowledge to make the student independent in managing high-throughput data.
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