Applications of Genomic Science
Code: 107990 ECTS Credits: 3| Degree | Type | Year |
|---|---|---|
| Genetics | OT | 4 |
Contact
- Name:
- Marta Puig Font
- Email:
- marta.puig@uab.cat
Teachers
- Antoni Barbadilla Prados
- Jaime Martinez Urtaza
- Sònia Casillas Viladerrams
- Maria Cinta Pegueroles Queralt
Teaching groups languages
You can view this information at the end of this document.
Prerequisites
An intermediate level of English is required and basic genomics knowdlege.
Objectives and Contextualisation
The general objective of the subject is to provide an advanced vision of the application of genomic sciences in different areas with the description of practical examples. The different subjects that will be taught include recent advances in sequencing, epigenomics, metagenomics, single cell genomics, or advanced transcriptomics technologies. Maximum priority will be given to the application of the subject taught in different scientific areas, so that students can receive advanced training in genomic techniques by describing practical cases for each of the disciplines. Given the current importance of this scientific area, which is very dynamic and constantly changing, students will be favored by receiving an applied and current vision of the different fields of genomics that can complement their basic training.
Competences
- Apply an entrepreneurial spirit in the area of genetics and genomics from an integrated vision of R+D+I processes.
- Apply knowledge of theory to practice.
- Describe the organisation, evolution, inter-individual variation and expression of the human genome.
- Design and interpret studies associating genetic polymorphisms and phenotypical characters to identify genetic variants that affect the phenotype, including those associated to pathologies and those that confer susceptibility to human illnesses or those of other species of interest.
- Design experiments and interpret the results.
- Perceive the strategic, industrial and economic importance of genetics and genomics to life sciences, health and society.
- Take account of social, economic and environmental impacts when operating within one's own area of knowledge.
- Take sex- or gender-based inequalities into consideration when operating within one's own area of knowledge.
Learning Outcomes
- Apply acquired knowledge and skills regarding genetics and genomics to potential technology based business projects involving genetics and genomics.
- Apply association studies to the prediction of phenotypes of individuals or specimens.
- Apply knowledge of theory to practice.
- Describe the structure and variation of the human genome from a functional and evolutionary perspective.
- Design experiments and interpret the results.
- Recognise the strategic importance and potential for industrial and economic development of genetic progress in the fields of life sciences, health and society.
- Take account of social, economic and environmental impacts when operating within one's own area of knowledge.
- Take sex- or gender-based inequalities into consideration when operating within one's own area of knowledge.
Content
This course provides extensive details of the most recent high-throughput methodologies used in genomics and their applications to solve several different types of problems in the field of genomics:
All classes will be in English.
Topic 1. Sequencing technologies: Sanger sequencing. 2nd and 3rd generation sequencing techniques (Illumina, Oxford-Nanopore, PacBio). Processing of DNA sequencing data.
Topic 2. Applications of DNA-seq: genome sequencing, re-sequencing and variant calling.
Topic 3. Metagenomics and microbiome: applications, pipelines and data analysis to study natural environments and public health.
Topic 4. RNA sequencing and analysis of RNA-seq data.
Topic 5. Applications of RNA-seq: gene expression and splicing variant annotation, metatranscriptomics.
Topic 6. Epigenomics and epigenetic modifications on the genetic material: data processing and analyses for differential DNA methylation
Topic 7. Hi-C for 3D genome organization: Hi-C protocols and general processing of Hi-C data
Topic 8. Single-cell genomics: applications and analysis.
Activities and Methodology
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Seminars | 6 | 0.24 | 8, 7, 1, 3, 2, 4, 5, 6 |
| Theory classes | 16 | 0.64 | 8, 7, 1, 2, 4, 5, 6 |
| Type: Supervised | |||
| Individual tutoring | 2 | 0.08 | 8, 7, 1, 3, 2, 4, 5, 6 |
| Type: Autonomous | |||
| Recommended reading and seminar activities | 20 | 0.8 | 1, 3, 2, 5 |
| Study | 28 | 1.12 | 8, 7, 1, 3, 2, 5 |
The contents will be presented in theoretical sessions to provide the basic concepts needed to apply and interpret genomic data.
The course will include different seminar sessions describing ongoing projects based on the use of advanced genomic technologies in different fields. In these seminars, the student will discover practical aspects of the application of these techniques.
Individual or group tutoring sessions can take place for students who wish to do so with the teachers online or in person. These sessions are useful to gauge the student's progress in understanding the subject and to help them with the most difficult concepts.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Assessment
Continous Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Attendance | 10 | 0 | 0 | 8, 7, 1, 3, 2, 4, 5, 6 |
| Engagement | 10 | 0 | 0 | 8, 7, 1, 3, 2, 4, 5, 6 |
| Seminar evaluation | 30 | 1.5 | 0.06 | 8, 7, 1, 3, 2, 4, 5, 6 |
| Written exam | 50 | 1.5 | 0.06 | 8, 7, 1, 3, 2, 4, 5, 6 |
The assessment of the subject will be based on a written test (50%), together with the activities resulting from the assessment of the seminars (30%). The rest of the grade will come from attendance and participation in the classes of the subject. To pass the subject it is necessary to obtain a minimum grade of 5 in the exam.
To participate in the retake, students must have previously been evaluated in a set of activities the weight of which is equivalent to a minimum of two thirds of the total grade of the subject. Therefore, students will obtain the grade of "Not Assessed" when the evaluation activities carried out have a weight of less than 67% in the final grade.
For this subject, the use of Artificial Intelligence (AI) technologies is allowed exclusively in study support tasks, such as bibliographic or information searches, text correction or translation into another language. The student should clearly identify which parts have been generated with this technology, specify the tools used, and include critical reflection on how these have influenced the process and the final outcome of the activity. The non-transparency of the use of AI in this assessable activity will be considered academic dishonesty and may lead to a partial or total penalty in the grade of the activity, or greater sanctions in cases of severity.
Bibliography
Gibson, Greg; Muse, Spencer V, A primer of genome science, Sinauer Associates, 2009 , ISBN:9780878932368.
Brown. Terry A, Genomes 5, CRC Press, 2023, ISBN:9780367674076.
Lesk, Arthur, Introduction to Genomics, Oxford University Press, 2025, ISBN:9780198866893.
https://global.oup.com/academic/product/introduction-to-genomics-9780198866893?cc=es&lang=en&
Suravajhala, Prashanth N; Bizzaro, Jeff W, Next-Generation Sequencing, CRC Press, 2025, ISBN:9781003354062.
Software
No specific software is required.
Groups and Languages
Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.