72709 - Advanced Genomic in Animal Production

Learning outcomes

The student is familiar with high-throughput technologies used to identify genes that control productive and reproductive traits in livestock species. The student understands the methodologies of structural and functional genomics for genome analysis aimed at improving selection efficiency. The student knows the main bioinformatics resources used in the context of animal genetic improvement.

Course contents

The course is structured as follows:

Phenomics: Technologies available for large-scale data acquisition on farms; precision livestock farming and most adopted sensors; management, processing, and interpretation of big data. The student will be able to describe the technologies currently available for monitoring animals in livestock production and identify key phenotypes to achieve selection goals across different sectors.

Genome Mapping: Linkage disequilibrium and pleiotropy; genetic correlation among phenotypes; markers and genomic sites of interest in animal breeding. The student will be able to calculate the map distance between two loci, distinguish between physical and genetic maps, and describe the different types of markers used in modern genetic improvement.

Genome Sequencing: SNP chip panels for genomic evaluation of animals; Next Generation Sequencing; polygenic risk for qualitative traits. The student will become familiar with the various techniques currently used for sequencing DNA segments or entire genomes; students will be able to identify genes/coding regions within the animals' reference genomes and evaluate the gene's products.

Genotype-Phenotype Association: Candidate gene approach and genome-wide association studies (GWAS). The student will learn approaches used to estimate the association of genetic markers with quantitative productive traits and pathogenic phenotypes relevant to livestock.

Similarity Among Individuals: Kinship and inbreeding matrices. The student will understand how to estimate the degree of genetic and genomic similarity among individuals within populations under genetic improvement programs, and the different kinship matrices used to estimate breeding values.

Ingredients for Genetic Improvement: Methods for estimating the breeding value of animals; objectives; selection response. The student will understand how to estimate variance components and how to estimate the breeding value of a reproductive candidate. The student will also learn how to assess a genetic improvement program.

Other Applications of Animal Genomics: Genomics applied to the study of livestock biodiversity, inbreeding depression, and runs of homozygosity. The student will learn how genomics can be used to manage confined populations with the goal of reducing inbreeding, and to monitor populations under selective pressure.

Practical Activities: Computer Lab Sessions with R software for introduction to bioinformatics for big data management and for the analysis of genomic and phenotypic data. The student will learn basic procedures for inspecting and conducting quality control on genotyping data. Students are required to produce a report applying genomic data, to be presented in class in groups at the end of Module 1. These activities are complemented by a field trip to a human genetics laboratory. Class notes, slides, and scientific articles will be provided during the course.

Readings/Bibliography

Notes, slides, and scientific articles will be provided during the course. The materials presented will be made available to students on the university’s VIRTUALE platform, accessible for enrolled students and other students upon password provided by the instructor.

Recommended textbooks for further study:

Genetica animale – applicazioni zootecniche e veterinarie, Giulio Pagnacco, Ambrosiana ed.

Genomes 4, T.A. Brown, EdiSES ed.

 

 

Teaching methods

Lectures face-to-face, seminars, and individual/group practical activities.

Assessment methods

The evaluation consists of a written test administered via the EOL platform, including multiple-choice questions and open-ended questions. Prior registration on AlmaEsami is required.

• Multiple-choice questions: 10 questions, each worth +1 point if correct, 0 if incorrect or unanswered.

• Open-ended questions: each worth +2 points if correct, 0 if incorrect or unanswered.

• Bonus points can be earned through the presentation of case studies related to phenomics.

The allotted time for the written test is 90 minutes. The use of any support materials such as textbooks, notes, or digital devices is not permitted during the exam.

The maximum score obtainable, with all correct and complete answers, is 30 cum laude. The exam is considered passed with a minimum score of 18/30.

Teaching tools

Lectures are delivered using audiovisual systems, PowerPoint or PDF presentations, video projectors, and the Teams platform.

Students with learning disorders and\or temporary or permanent disabilities: please, contact the office responsible 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.

Office hours

See the website of Angela Costa