Corso di Laurea Magistrale in Biotecnologie vegetali - BV

This course objectives fit with the general objectives of the Biotechnology Course aimed at providing knowledge on biological and molecular data emerging through "-omics" approaches (eg: genomics and transcriptomics), and the tools necessary for their processing. Particular emphasis will be granted to data from crop species and micro-organisms, in the light of for their biotechnological exploitation.

Aim of the course is:
 -to know the principals sequence databases
-to use sequence retrieval tools
-to became autonomous in handling search algorithm (for genomics, transcriptomics analyses) 

Knowledge and understanding
At the end of the course the student will be able to:
- Moving on a Linux-based operating system
- Learn and consult primary and secondary databases (archival, curated)
- Know DNA sequences from a structural point of view
- Know the procedures for manipulating NGS sequences
- Know the methods for assembling DNA sequences
- Know the analytical procedures for genomic / transcriptional re-sequencing
- Understand gene expression data by clustering algorithms

Ability to apply knowledge and understanding
At the end of the course the student will be able to:
- Use the Linux operating system and basic Linux shell commands (cd, ls, cp, rm, rmd cat, grep, pipes, toilets, etc.)
- Run the download file, read and modify the permissions of a file
- Install the most common bioinformatics programs (binaries. Sh,. Deb)
- Perform the analysis with the software  Velvet, BWA, SamTools, Bowtie2, cuffdiff
- Launch Perl scripts (. pl)
- Analyse primary and secondary sequence databases (archival and curated) using Boolean operator (AND, OR, NOT)
- Analyse DNA and protein sequence and predict protein post-translational modifications
- predict intron, exon and regulatory elements using pattern recognition algorithm
- mine SNPs from sequence alignments
- search repetitive elements from genomic database
- design PCR primers
- Perform a simplified assembly analysis of DNA/RNA sequences (genome / transcriptome)
- Perform a simplified SNP mining analysis.
- Perform a simplified RNAseq data analysis.
- Perform a simplified clustering (hierarchical and non-hierarchical) analysis. 

Making judgments
At the end of the course students will be able to:
- Identify genes involved in a biological phenomenon
- Identify allelic forms and distinguish them from sequence errors
- Hypothesise co-regulations of genes
- Assess the effectiveness of a genomic assembly process 

Communication skills
At the end of the course students will be able to:
- report the results of a genome / genomic database query
- report the results of a genomic assembly or resequencing experiment.

General education area
The course aims to illustrate the major bioinformatics databases based on biological information and tools for "Sequence Retrieval" as well as the basic tools to investigate biological information. The course aims to illustrate the use of the main searching/analysing algorithms for genomics, transcriptomics (using both remote web-based tools and local programs).

- Introduction to bioinformatics
- Introduction to Linux (Ubuntu GUI and command shell)
- Basic commands (cd, ls, cp, rm, rmd cat, grep, pipes, toilets, etc.)
- Managing permissions of a file
- Installing packages and programs in bioinformatics
- Primary, secondary, archival and curated databases.
- Refseq vs GenBank, protein database.
- Use of booleian operators (AND, OR, NOT); retrieval systems (Entrez, SRS); literature searching (Web of Science and "TROVA UNITO")
- Sequence format (description and construction of fasta and GBF files) 
- Multi fasta file editing, viewing and manipulating chromatograms (Scan sequence and Bioedit); submission of sequences (via BANKIT)
- Analysis of DNA sequences, conceptual translation; characterization of genomic DNA and cDNA sequence elements; pattern recognition for intron, exon, promoter and mining. 
- Analysis of protein sequences.
- Oligo design Primer3 (single gene and in batch)
- Searches for similarities. Local Alignment (BLAST and its variants) global alignment (ClustalOmega, for nucleic acids and proteins analyses)
- Description and use of a Genome Browser 
- SRA manipulation tools
- Genomic/transcriptomic denovo assembly (Velvet)
- Structural genome sequence annotation using MAKER and analysis of a .gff file
- SNP mining (using Sanger and NGS data), and analysis of a .vcf file
- BWA alignment of sequences (Burrel Wheeler aligner)
- Hierarchical clustering and K-means data analysis (Genesis).
- Functional annotation, Gene Ontology and gene enrichment functions
- Basics on descriptive statistics. 
- Quick reminders on the calculation of probability. 
- Confidence intervals
- Gaussian populations (normal distribution) and their properties. Quantiles.
- Problems and examples of biological populations (use of Excel commands).
- The statistical tests: null hypothesis, significance and p-value. The Student t-test. The contents will be studied in depth through practical activities/exercises (e.g .: PC exercises).

The course will be taught entirely in computer room using PCs with Virtual machines running a Linux operating system (Ubuntu). For lectures the teacher makes use of presentations and slides that are available to students.

In itinere
At the beginning of each lesson, the teacher will stimulate discussion with students on the topics covered in previous lessons with the aim to clarify any doubts and verify the state of learning in the class.

Final Examination
The final exam will be written, on the Moodle teaching platform, and divided into two parts (theoretical and practical), which will take place one after the other. The sum of the two parts will compose the final grade:

1 - Theoretical part - 31 questions (test on Moodle).
Maximum time: 35 minutes; Score: 15.5 pts
2 - Practical part - 2-3 exercises to be done on the VM (or Windows) with results to be reported on Moodle
Maximum time: 100 minutes; Score: 15 pts

The test will be scored between 0 and 30. All questions in the exam will be on topics that were covered during the teaching and applied during the exercise activities. The maximum duration of the test will be 2 hours and 15 minutes.

-The course will take place entirely in the computer classroom
-Any student will have a PC (operating systems: Window and Linux on virtual machine)
-Any student will received, for the study period, a Virtual Machine as a portable operating system with preinstalled data and programs or a USB flash drive with a bootable version of Ubuntu 15.04
- Lessons will be recorded (screen and voice) and available, along with all the material presented in the classroom, on the Moodle platform.
 

For home study is made available  the material presented by the teacher during the course (pdf presentations and audio-video recordings of the lectures).

The way in which the teaching activity is carried out may vary according to the limitations imposed by the current health crisis.