B8775 - Applications of Veterinary Genomics

Learning outcomes

At the end of the course, the student is familiar with high-throughput technologies for the genotypic and phenotypic characterization of livestock and companion animals; understands the principles and applications of genetic and genomic selection; and is able to apply genome sequencing methodologies and perform bioinformatic analysis of genomic data.

Course contents

This course consists of Module 1 (3 ECTS, 24 hours) taught by Prof. Giulio Visentin, and Module 2 (1 ECTS, 12 hours) taught by Prof. Fabio Gentilini.

SPECIFIC PREREQUISITES:

To better understand the topics covered in this course, students are advised to have prior knowledge of basic statistics, biochemistry, and animal production science.

COURSE CONTENT – MODULE 1 (Prof. Giulio Visentin)

Lectures:

• Current topics and future perspectives in animal production, workflow of an animal breeding program (3 hours): Goals and objectives of animal production. Development of a genetic improvement program. Definition of the breeding objective. Data requirements for the genetic and genomic selection process. The student understands the purposes of selection and learns the key steps of a breeding program.
• High-throughput genotyping (4 hours): SNP and other molecular markers. DNA-chip technology. Genome-wide association studies and candidate gene approach. The student understands the molecular markers useful for animal genetic improvement, the DNA-chip genotyping technology, and different approaches for estimating the association between molecular markers and traits of interest.
• High-throughput phenotyping (4 hours): Collection of phenotypic data relevant for animal genetic improvement. Large-scale phenotypic data acquisition. The student learns the methods for collecting key phenotypes in breeding programs and understands advanced techniques for high-throughput animal data generation.
• Similarity among individuals (3 hours): Genetic and genomic relationships, inbreeding. Relationship matrices relevant in genetic improvement. The student understands how to estimate genetic and genomic similarity between individuals in breeding populations, and learns about the different relationship matrices used in breeding value estimation.
• The animal model (3 hours): Genetic basis of quantitative traits. Components of the animal model. The concept of allelic substitution effect and breeding value. Genetic parameters. The student learns the principles of the animal model in quantitative genetics, with a focus on the genetic basis of quantitative traits.
• Genetic and genomic evaluation of breeding animals (4 hours): Evaluation process of breeding candidates. Genetic vs genomic selection. Methods for genomic evaluation. The student learns the concepts and applications of selection processes in livestock species.
• Evaluation of the breeding program (3 hours): Selection response and implications of genomic selection. Use of genomics for monitoring animal biodiversity. The student understands how genomics can be applied to manage populations under genetic selection programs.

COURSE CONTENT – MODULE 2 (Prof. Fabio Gentilini)

Practical classes/Laboratory sessions:

• Introduction: Overview of Sequencing Technologies (2 hours): The main sequencing technologies will be presented, with an analysis of their advantages and disadvantages. Students will acquire theoretical and practical knowledge regarding the characteristics of reads generated by different platforms, the implications for file formats, read quality assessment, and the selection of appropriate tools for downstream analysis.
• Bioinformatics Tools for Genomic Analysis in Veterinary Medicine (2 hours): Introduction to major Linux distributions and the various methods for operating system installation, including the use of WSL (Windows Subsystem for Linux). This will be followed by an introduction to the Bash shell and a hands-on session to familiarize students with basic command-line operations.
• Installation of Bioinformatics Tools (1 hour): Installation of software developed in various programming languages (Python, R, Perl) using package managers such as pip, conda, CRAN, and CPAN. The module includes practical exercises using tools like samtools and bcftools.
• Isolated Execution Environments (1 hour): Conda and Docker will be introduced and compared to highlight their functionalities and differences. Students will execute the same bioinformatics tool using both environments to evaluate reproducibility and portability.
• Genetic Variant Analysis (1 hour): A hands-on module focused on variant calling and annotation using tools such as VEP, VariantScanR, and Longshot, working with real input files (VCF, BAM).
• Metagenomic Analysis (2 hours): Introduction to 16S rRNA sequencing and the use of QIIME2 for data processing. Results will be explored through the MicrobiomeAnalyst platform to analyze microbial composition and diversity.
• Interactive Notebooks (1 hour): Presentation and practical use of Jupyter Notebook and Google Colab, with exercises involving VCF data and Python/R code for visualization and filtering of results.
• GUI Platforms for Data Analysis (Galaxy) (2 hours):The course concludes with an introduction to the Galaxy platform, a web-based graphical interface for bioinformatics analysis. Students will learn how to upload data, use preconfigured tools, and build simple analysis workflows without the need for command-line operations.

Readings/Bibliography

The teaching materials for this course are available on the Virtuale Learning Environment (https://virtuale.unibo.it/?lang=en ).

Required readings:

• Genetica animale - applicazioni zootecniche e veterinaria. Giulio Pagnacco, casa editrice Ambrosiana
• Genomi 4. T.A. Brown, casa editrice EdiSE

Supplementary reading:

• Scientific articles provided by the professors
• Review material on basic statistics and animal production provided by the professors

Teaching methods

The course includes both theoretical lectures and practical/laboratory sessions.

Bioinformatics practical activities will take place in the classroom, with students organized into working groups. Each student will use their own personal device (laptop), on which they will install the necessary software for the exercises. The teacher will provide guidance and technical support for the installation of required tools, including the use of preconfigured environments (such as Conda, Docker, QIIME2, Galaxy, etc.).

Throughout the course, interactive notebooks in Google Colab format, prepared by the teacher, will also be distributed. These can be executed directly from the browser without the need for complex local configurations. The practical sessions will involve the analysis of real datasets derived from theteacher’s research projects, with the aim of contextualizing the use of bioinformatics tools in real-world and professionally relevant scenarios.

Considering the types of activities and teaching methods adopted, attendance for this course requires the successful completion of Modules 1 and 2 via e-learning, and Module 3 on health and safety training in study environments. Information about the schedule and access to Module 3 is available in the dedicated section of the Degree Program website.

Participation in practical and laboratory sessions requires wearing a lab coat and appropriate footwear. Suitable personal protective equipment (PPE), such as disposable latex gloves, will be provided as needed.

Assessment methods

The assessment for the Course consists of a written exam, done in EOL platform (https://eol.unibo.it/?lang=en) comprising 40 questions, as follows:

• 30 multiple-choice questions (24 on the subject of Module 1, 8 on Module 2). Each correct answer is worth 0.8 points; incorrect or unanswered questions receive 0 points.
• 8 short open-ended questions (6 on Module 1, 2 on Module 2). Each correct answer is worth 1.8 points; incorrect or unanswered questions receive 0 points.

The exam duration is 60 minutes. The maximum score is 40 points. To pass the exam, students must obtain a minimum of 24 points out of 40, including at least 18 points (rounded) from the Module 1, and at least 6 points from the Module 2.

No supplementary materials or electronic devices (e.g., calculators, tablets, smartwatches, computers) may be used during the exam, except for those explicitly allowed by the instructor.

The results of the written exam will be published within 5 working days on the Virtuale Learning Environment (https://virtuale.unibo.it/?lang=en) by the designated course contact.

The final grade for the Integrated Course is determined by the score obtained in the written exam, expressed out of thirty (30*written exam score/40). A minimum final grade of 18/30 is required.

Negative results are not graded numerically but recorded as “withdrawn” or “failed” in the electronic transcript on AlmaEsami, and do not affect the student’s academic record.

Students may reject the final grade 1 time, by informing the course examiner via email within 5 working days.

The designated course contact for this course is Prof. Giulio Visentin.

Students can register for exams through the AlmaEsami platform (http://almaesami.unibo.it/). Exams are scheduled during the designated periods in the academic calendar. Additional sessions are available for students beyond the standard program duration.

Students with learning disorders and/or temporary or permanent disabilities: please, contact the office responsible (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students) as soon as possible so that they can propose acceptable adjustments. The request for adaptation must be submitted in advance (15 days before the exam date) to the lecturer, who will assess the appropriateness of the adjustments, taking into account the teaching objectives.

Teaching tools

The lessons are delivered with the support of audiovisual systems, including PowerPoint presentations, a video projector, and the Teams platform. In case of difficulty in understanding the course content, the instructor is available for clarification meetings, which must be scheduled via email.

Office hours

See the website of Giulio Visentin

See the website of Fabio Gentilini