C8345 - COMPARATIVE GENOME ANALYSIS

Learning outcomes

By the end of the course, the student is able to identify phenotypes of interest for the genetic improvement of laboratory, food, and companion animals and set up tailored selection indexes. The student has the ability to master open-access software for the management and editing of high-density DNA chip data of eukaryotes, identification of population structure by using imputed or genotyped SNP alleles’ frequency, and identification of ROH to reveal ancient and recent bottlenecks or artificial selection. Student is also competent in carrying out association studies (genome-wide and candidate gene approach) and performing functional enrichment analysis based on gene ontology and KEGG pathways.

Course contents

 

Contents

The course syllabus is articulated as follows:

1. Comparative genomics and genome resources (1.5 h)

   Genome organization and evolution; reference genomes and genome assemblies; comparative analysis of laboratory, livestock and companion animal genomes; public genomic databases and genome browsers.

   Learning outcomes: Students will understand the principles of comparative genomics and be able to describe genomic resources for animal genome analysis.

2. Genomic variation and SNP data analysis (2 h)

   Genetic variation (alleles frequency); high-density SNP arrays; quality control and genotype imputation; introduction to next-generation sequencing data.

   Learning outcomes: Students will be able to manage, edit and evaluate high-density SNP datasets and distinguish between genotyped and imputed data.

3. Population genomics (1.5 h)

   Population structure; principal component analysis (PCA); genomic relationship matrices; runs of homozygosity (ROH); genetic diversity, bottlenecks and signatures of selection.

   Learning outcomes: Students will be able to assess population structure, genomic diversity and ROH patterns, and interpret their biological significance.

4. Genotype–phenotype association (3 h)

   Genetic architecture of quantitative and qualitative complex traits; candidate gene approach; genome-wide association studies (GWAS); identification and interpretation of genomic regions associated with phenotypes of interest.

   Learning outcomes: Students will understand and apply candidate gene and GWAS approaches to identify genotype–phenotype associations.

5. Functional genomics (1 h)

   Gene annotation; Gene Ontology (GO) and KEGG pathway enrichment analyses; functional interpretation of candidate genes and genomic regions.

   Learning outcomes: Students will be able to interpret genomic data through functional enrichment analyses and identify relevant biological pathways.

6. Applications in animal genetics (1 h)

Comparative genomics for genetic improvement and biodiversity conservation; genomic evaluation; principles of selection indexes integrating genomic and phenotypic information.

Learning outcomes: Students will understand the application of comparative genomics to animal breeding, biodiversity management and the design of selection indexes.

Practical activities

Computer lab sessions: introduction to bioinformatics tools for comparative genome analysis, SNP data quality control and editing, genotype imputation, population structure analysis (PCA), genomic relationship estimation, ROH detection, genome-wide association studies (GWAS), candidate gene identification, and GO/KEGG enrichment analyses. Students will prepare and present a report based on the analysis of a real genomic dataset. Practical activities may also include a guided visit to the University dairy cattle farm to observe biological sample collection for DNA extraction and discuss the integration of phenotypic and genomic data.

 

Prerequisites: for a better understanding, students are advised to have already acquired knowledge in basic principles of genetics and biology.

Readings/Bibliography

The teaching materials for this course are available on the Virtuale Learning Environment (https://virtuale.unibo.it/?lang=en ). Notes, slides, and scientific articles will be provided during the course.

Recommended textbooks for further study that can be retrieved from the internet or requested to the instructor:

• Genomes 4, T.A. Brown, EdiSES ed.
• Textbook Animal Breeding and Genetics (second edition, 2024), Kor Oldenbroek and Mario Calus , https://wiki.groenkennisnet.nl/space/TAB
• Genome wide association studies and genomic prediction (2013), C. Gondro, J. van der Werf, B. Hayes. Human Press https://link.springer.com/book/10.1007/978-1-62703-447-0

Teaching methods

Presentations (.ppt, .pdf), digital material online such as textbook and scientific articles.
Living animals and facilities of the experimental farm of the university.
The teaching material, including scientific articles discussed during classes, is available on the Virtuale platform.
In case of any difficulties, the instructor is available for individual clarification meetings, which must be scheduled via email.

Assessment methods

Registration for exams is possible in the AlmaEsami platform exclusively.
The assessment consists of a written test covering all topics covered, aimed at assessing the acquisition of expected knowledge. The test is administered via the EOL platform, including multiple-choice questions and open-ended questions, scored as follows:
- 12 multiple-choice questions: each worth +1 pt. if correct, 0 pt. if incorrect or unanswered;
- 10 open-ended questions: each worth +2 pt. if correct, +1 pt. if partially correct, 0 pt. if incorrect or unanswered.

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 as well as electronic devices (e.g., calculators, tablets, smartwatches, computers), except when explicitly allowed by the instructor.

The exam is considered as passed with a minimum score of 18/30, with maximum score obtainable being 30 cum laude. When indicated, bonus points can be earned through the presentation of case studies related to phenomics.
The results of the written exam will be published within 5 working days on the Virtuale.
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. To reject the grade, even if passed, students have to inform the instructor as per instructions that will be provided. The use of AI is prohibited and any use constitutes a breach of academic integrity.
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 dedicated 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.

Teaching tools

Presentations (.ppt, .pdf), digital material online such as textbook and scientific articles.
Living animals and facilities of the experimental farm of the university.
Teaching material uploaded on the Virtuale platform.
In case of difficulty understanding the course content, the instructor is available for individual clarification meetings, which must be scheduled via email.

Office hours: the instructor is available from Monday to Friday (08:00am-5:00pm) by appointment via e-mail either in person or remotely.

Office hours

See the website of Angela Costa