BIOTECHNOLOGY FOR THE GENETIC IMPROVEMENT OF TREE SPECIES
Module BIOINFORMATICS TOOLS FOR THE ANALYSIS OF AGRONOMIC TRAITS

Academic Year 2026/2027 - Teacher: GAETANO DISTEFANO

Expected Learning Outcomes

Knowledge and understanding: The student will acquire specific knowledge on biotechnologies applied to the genetic improvement of fruit species, genome editing techniques and assisted selection with molecular markers.

Ability to apply knowledge and understanding: The student will be able to analyze genetic data to be used in plans for the improvement.

Autonomy of judgment (making Judgments): The knowledge and skills acquired during the course and in particular the individual study of some literature, and the critical analysis of literature will allow the student to achieve autonomy of judgment and ability to study and to operate independently.

Communication skills (communication skills): Lectures, other activities and individual study on selected teaching material will allow the student to acquire the basics of technical language, also in English. The student will be stimulated to use technical language in the relevant classroom, as well as during the other activities. The property of technical language contributes to the final evaluation of the student.

Learning skills (learning skills): During the course, the activity of collecting and examining scientific literature and writing scientific reports is aimed at preparing the student for self-employment and critical analysis of literature. These skills are useful for the preparation of the degree thesis, for the drafting of a research project for access to the doctorate and for the continuous updating of the knowledge and skills necessary for the profession.


Course Structure

The course (3 ECTS) includes 7 hours of lectures and 14 hours of other activities. For lectures, the instructor will make use of PowerPoint presentations, also in English. As part of the other activities, computer-based exercises will be carried out in the form of a mini-course on some main topics (e.g., population genetics, identification of polymorphisms in genomic data), as well as seminars (including online).

In order to guarantee equal opportunities and in compliance with current legislation, interested students may request a personal meeting to plan any compensatory and/or dispensatory measures, based on the learning objectives and specific needs. It is also possible to contact the CInAP (Center for Active and Participatory Inclusion – Services for Disabilities and/or Specific Learning Disorders) representative of our Department.

Required Prerequisites

Knowledge of principles of plant genetics and biomolecular methodologies is recommended

Attendance of Lessons

Attendance is not compulsory but strongly recommended

Detailed Course Content

ntroduction to Bioinformatics

Population Genetics

  • PCA

  • Structure

  • Admixture analysis

  • Phylogenetic trees

Sequencing Techniques

Genome Assembly

  • Evaluation of assembly quality: metrics, coverage analysis, and BUSCO

Transcriptomics

  • RNA-Seq analysis

In silico Identification of Polymorphisms

  • SNPs

  • Structural Variants

  • INDELs

  • SSRs

Textbook Information

Fondamenti di bioinformatica; Helmer Citterich, Ferrè, Pavesi, Romualdi, Pesole; Zanichelli [1]

Materiale didattico fornito dal docente [2]

Course Planning

 SubjectsText References
1Introduzione alla bioinformatica
2Genetica di popolazione
3Tecniche di sequenziamento
4Assemblaggio di genomi
5Trascrittomica
6Identificazione in silico di polimorfismi: SNP, Varianti Strutturali, INDELs, SSR

Learning Assessment

Learning Assessment Procedures

Oral examination. In particular, the relevance of the answers to the questions asked, the quality of the contents, the ability to connect with other topics covered by the program, the ability to report examples, the technical language properties and the overall expressive ability of the student will be assessed.

 

Verification of learning can also be carried out electronically, should the conditions require it.

 

Learning assessment may also be carried out on line, should the conditions require it.

 

 

 

 

 

Verification of learning takes place through an oral interview. The evaluation of the student's preparation will take place on the basis of the following criteria: learning ability and level of depth of the topics covered, properties of synthesis and exposition, and the student's ability to reason.

 

The vote follows the following scheme:

 

Unsuitable

 

Knowledge and understanding of the topic: Important shortcomings. Significant inaccuracies

 

Analysis and synthesis skills: Irrelevant. Frequent generalizations. Inability to synthesize

 

Use of references: Completely inappropriate

 

18-20

 

Knowledge and understanding of the topic: At the threshold level. Obvious imperfections

 

Ability to analyze and synthesize: Just enough skills

 

Use of references: As appropriate

 

21-23

 

Knowledge and understanding of the topic: Routine knowledge Analysis and synthesis skills: It is capable of correct analysis and synthesis. Argue logically and consistently

 

Use of references: Use standard references

 

24-26

 

Knowledge and understanding of the topic: Good knowledge

 

Analysis and synthesis skills: Has good analysis and synthesis skills. The arguments are expressed consistently

 

Use of references: Use standard references

 

27-29

 

Knowledge and understanding of the topic: Knowledge more than good

 

Ability to analyze and synthesize: He has considerable abilities of analysis and synthesis

 

Use of references: Has explored the topics

 

30-30L

 

Knowledge and understanding of the topic: Excellent knowledge

 

Ability to analyze and synthesize: He has considerable abilities of analysis and synthesis.

 

 


Examples of frequently asked questions and / or exercises

  • The candidate should illustrate the logical steps for genome assembly.

  • The candidate should illustrate the main techniques for studying genetic variability within a germplasm collection.

  • The candidate should describe the characteristics of a Variant Calling Format (VCF) file.