B8794 - Genetic Engineering and Bioinformatics

Learning outcomes

By the end of the course, the student understands the principles underlying genetic material manipulation for the creation of in vitro and in vivo models, as well as gene therapy; is familiar with the main techniques for producing knock-out and knock-in cells and animals, for reporter gene expression, the main analysis methods, and the related bioinformatic tools; understands the technologies for genetic engineering of farm animals and their practical applications; knows the applications and potential of major imaging analysis systems; is able to perform basic analyses using open-source software applied to microscopic preparations for the evaluation and quantification of cellular and tissue structures; and is able to understand the impact of the learned techniques on animal health and welfare in both livestock and biomedical contexts.

Course contents

SPECIFIC PREREQUISITES FOR THIS COURSE:

To better understand the topics covered in this course, students are advised to have already acquired knowledge in the following areas: molecular and cellular biology.

 

SPECIFIC CONTENT FOR THIS COURSE:

 

MODULE 1 – Dr. Vito Antonio Baldassarro

The syllabus is structured as follows:

Lectures (16 h):

• Introduction to genetics applied to transgenesis (2h)
• Main strategies for genetic material manipulation (2h)
• In vivo Knock-out and Knock-in constitutive and conditional models (2h)
• Humanized animal models and their applications (2h)
• Reporter genes (2h)
• Genome and transcriptome in vitro manipulation and application examples (4h)
• Gene therapy in veterinary and human medicine (2h)

Laboratory Sessions (16h):

• Principles of bioinformatics analysis applied to the genome and transcriptome (4h)
• Bioinformatics analysis pipeline: from raw data to pathway analysis (4h)
• Principles of image analysis and main open-source software (4h)
• Case study (4h)

 

MODULE 2 – Prof. Barbara Bacci

The syllabus is structured as follows:

Lectures (16 h):

• Digitization and quality assessment of microscopic slides for image analysis (2h)
• Principles open-source image analysis software (QuPath) (2h)
• Basic principles of image analysis: recognition of cellular and tissue structures – classification, segmentation (2h)
• Quantification methods of cellular and tissue structures in digital microscopic slides (2h)

Laboratory Sessions (16h):

• Quantification of cellular and tissue structures in histological microscopic slides (4h)
• Quantification of cellular and tissue structures in immunohistochemical and in situ hybridization slides (4h)
• Presentation of a project with final dataset and results

 

 

MODULE 3 – Prof. Eleonora Iacono

The syllabus is structured as follows:

Lectures (8 h):

• Advantages and disadvantages of using genetic engineering in livestock animals (1h)
• Improvement of productive performance (1h)
• Genetic engineering and the welfare of farm animals (1h)
• Use of genetically engineered livestock animals in biomedical fields (1h)
• Case study (4h)

Readings/Bibliography

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

The reference updated bibliography will be uploaded on the online platform for each topic.

Teaching methods

The course includes both theoretical lectures and laboratory sessions: lectures will be delivered as frontal lessons, while the laboratory sessions will take place in the computer lab and through group work.

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 single-subject course “Genetic Engineering and Bioinformatic” consists of TWO parts:

· Module 2 (Prof. Barbara Bacci)

The assessment consists of the completion of three image analysis projects.

Attending students: Each project is carried out and completed during the scheduled practical sessions. At the end of each session, the project files and results will be collected for assessment.

Non-attending students: The same projects must be completed independently and submitted to the instructor. Detailed instructions for completing and submitting the assignments will be provided on the Virtuale platform (virtuale.unibo.it). In this case, students are required to use their own computer and the free software QuPath (https://qupath.github.io/).

Assessment will be based on the quality and completeness of the submitted projects.

· Modules 1 (Dr. Vito Antonio Baldassarro) and 3 (Prof. Eleonora Iacono)

Attending students: During the final four hours of practical activities, a joint session involving both modules will be held. Students will be divided into working groups, and each group will be assigned a scientific paper on genetic engineering. Each group will prepare a classroom presentation addressing the following aspects:

1. The scientific background and experimental questions underlying the study;
2. A critical review of the study and possible improvements or future applications based on the methodologies covered during the course;
3. A discussion of the advantages and limitations of genetic engineering, presented in a format suitable for science communication to a general audience.

During the discussion, students will also be assessed on their knowledge of the methodologies employed in the study and of the theoretical principles covered throughout the course.

The assessment results will be published within five working days on the instructor's Virtuale platform (https://virtuale.unibo.it/).

Non-attending students or students unable to participate in the group project: An individual assessment is available. This consists of a 10-minute oral presentation, supported by slides, on a scientific paper provided by the instructors through the Virtuale platform, followed by two questions on each of the two modules (approximately 15 minutes).

For the oral examination, performance will be assessed according to the following grading criteria:

• 18–22: Knowledge of only a very limited number of course topics; analytical skills demonstrated only with the instructor's guidance; generally appropriate use of scientific language.
• 23–26: Knowledge of a limited number of course topics; ability to perform independent analysis only on straightforward procedural aspects; appropriate use of scientific terminology.
• 27–29: Good knowledge of a broad range of course topics; ability to conduct independent critical analysis; confident command of subject-specific terminology.
• 30–30 with honours (30L): Comprehensive knowledge of the course topics; ability to perform independent critical analysis and establish connections between concepts; excellent command of subject-specific terminology together with strong reasoning and self-reflection skills.

Students are informed of their assessment results at the end of the project work or oral examination. Each assessment component is considered passed with a minimum mark of 18/30.

The exam is considered passed only if all parts are successfully completed. The final grade is determined by the weighted average of the assessment for Module 2 and the combined assessment for Modules 1 and 3. 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.

Grades for individual parts and the final grade will be published on the AlmaEsami platform (https://almaesami.unibo.it/?lang=en) within 5 working days of the date of the exam.

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

The designated course contact for this course is Vito Antonio Baldassarro.

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.

With regard to the learning assessment, limited, declared, and non-substantive use of AI is permitted for support activities, such as summarization and rephrasing. Substantive use of AI to complete parts of the assessment task is not permitted.

Teaching tools

Power Point presentations, videos, and dedicated softwares will be used.

In case of difficulty understanding the course content, the instructor is available for clarification meetings, which must be scheduled via email.

Office hours

See the website of Vito Antonio Baldassarro

See the website of Barbara Bacci

See the website of Eleonora Iacono