Important notice
The course guide is provisional.
The PDF version of the course guide may take a few days to become available in the DDD.
Plant Systems Biology
Code: 44787Credits: 6
| Degree programme | Type | Course |
|---|---|---|
| Plant Biology, Genomics and Biotechnology | OP | 1 |
Contact lecturer
- Name :
- Ana Martin Hernandez
- Email :
- anamontserrat.martin@uab.cat
Teaching staff
- Juan Jose Lopez-Moya Gomez
- Elena Monte Collado
Teaching staff (external to UAB)
- Antoni Gacia-Molina
- Iban Eduardo
- Jae-Seong Yang
- Nicolas Bologna
Group languages
You can consult this information at the end of the document.
Prerequisites
Basic knowledge of Genetics and Molecular Biology
Objectives
To provide students with a comprehensive and current view of the techniques, fundamentals and applications
of Plant Genomics and introduce systems biology of plants. The specific objectives include understanding the
following aspects: the diversity and complexity of plant genomes, the techniques commonly used in genomics,
transcriptomics, proteomics and metabolomics studies and applications to the genetic improvement of crop
plants. The objectives also include the use of predictive modelling through integration of different omics data.
Learning outcomes
- CA12 (Use new bioinformatic tools to describe predictive models of experimental omics data in the fields of Plant Biology, Genomics and Biotechnology.) Use new bioinformatic tools to describe predictive models of experimental omics data in the fields of Plant Biology, Genomics and Biotechnology.
- CA17 (Apply scientific terminology to argue the results of research in terms of the genetic improvement of crop plants and communicate them orally and in writing in an international environment.) Apply scientific terminology to argue the results of research in terms of the genetic improvement of crop plants and communicate them orally and in writing in an international environment.
- KA15 (Describe the results of data analysis derived from proteomic and metabolomic studies applied to crop breeding.) Describe the results of data analysis derived from proteomic and metabolomic studies applied to crop breeding.
- KA16 (Select study methodologies in plant genomics and case studies across multiple omics data.) Select study methodologies in plant genomics and case studies across multiple omics data.
- SA28 (Communicate research results in the field of Plant Biology, Genomics and Biotechnology in English orally and in writing using appropriate scientific terminology.) Communicate research results in the field of Plant Biology, Genomics and Biotechnology in English orally and in writing using appropriate scientific terminology.
- SA29 (Apply knowledge of molecular genetics and plant breeding in different scientific and industrial fields.) Apply knowledge of molecular genetics and plant breeding in different scientific and industrial fields.
- SA30 (Apply the methods and techniques commonly used in genomic, phenomic, transcriptomic, proteomic and metabolomic studies.) Apply the methods and techniques commonly used in genomic, phenomic, transcriptomic, proteomic and metabolomic studies.
- SA31 (Apply bioinformatic tools to the genetic, evolutionary and functional study of plants and interpret the results obtained from the experiments carried out.) Apply bioinformatic tools to the genetic, evolutionary and functional study of plants and interpret the results obtained from the experiments carried out.
Contents
Systems Biology: Concepts, methodology, and case studies using multiple omics.
The case study will focus on the emergence of a new disease that affects and kills all tomato varieties. The students
will make a trip through all the -omics to unveil the cause and search for a scientific solution feasible for
application in crop plant breeding.
Specifically,
We will use practical applications of methods and techniques in plant phenomics and genomics, including the
use of molecular markers in breeding. Importance of QTL in this problem.
Analysis and application of data arising from genomics and transcriptomics studies to narrow down the problem.
Analysis and application of data arising from proteomics, interactomics, and metabolomics studies to find a
solution to the problem.
Integrative analysis of the applied case study, including Computational modelling, for crop plant breeding.
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Lectures and expert's talks | 12 | 0.48 | |
| Personal study | 84 | 3.36 | |
| Preparation of reports | 35 | 1.4 | |
| Problems and case studies | 18 | 0.72 |
Lectures and Expert talks
Problems and case studies
Preparation of reports.
Personal study
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Final quiz | 30% | 1 | 0.04 | CA12, CA17, KA16, SA29, SA30 |
| Lectures and expert's talks | Continuous evaluation of students participation | 0 | 0 | CA12, CA17, KA15, KA16, SA29, SA30, SA31 |
| Report | 60% | 0 | 0 | CA12, CA17, KA15, KA16, SA28, SA29, SA30, SA31 |
Continuous evaluation 10%
Report 60%
Final Quiz 30%
This subject/module does not include the single assessment system.
For this module, the use of Artificial Intelligence (AI) technologies is allowed exclusively in support tasks, such as bibliographic or information search, text correction or translations. The student must clearly identify which parts have been generated using this technology, specify the tools used and include a critical reflection on how these have influenced the process and the final result of the activity. The lack of transparency in the use of AI in this assessable activity will be considered a lack of academic honesty and may lead to a partial or total penalty in the grade of the activity, or greater sanctions in serious cases.
Bibliography
Yunbi Xu Molecular Plant Breeding. CAB International Oxfordshire, UK disponible online a Biblioteca UAB
:http://www.cabi.org/cabebooks/FullTextPDF/2010/20103101750.pdf
Articles and specific reviews recommended during classes
Software
MapQTL 6.0
JoinMap 5.0
R
RStudio
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE
| Type of teaching | Group | Language | Semester | Shift |
|---|---|---|---|---|
| (TEm) Theory (master) | 1 | English | second semester | morning-mixed |
| (PAULm) Classroom practices (master) | 1 | English | second semester | morning-mixed |