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Master in

Plant genetics, genomics and breeding

Next edition: 1st part: October 2023 – June 2024 / 2nd part: September 2024 – June 2025

Master in

Plant genetics, genomics and breeding

General information on the Unit

ECTS: 3
Contact hours: 30 (19 lectures, 11 practicals)
Personal work hours: 45
Character: Compulsory
Venue: Mediterranean Agronomic Institute of Zaragoza (CIHEAM Zaragoza)
Scheduling:
- Developed during the first academic year of the Master, at the middle of the first semester.
- The assessment of this Unit consists of a written exam and the evaluation of practical exercise during the first semester.
Requisites and permanence
Knowledge on basic R software is required. A propaedeutic on basic R software is organized for students who need it.
Learning methods
Combination of theoretical and practical sessions consisting of lectures, computer work, and individual and group study and work.
Language
Lectures are delivered in English and the documents supplied by the lecturers are also in English. The exams can be taken either in English, Spanish or French.

 

Presentation of the Unit and context within the syllabus

The Unit complements Unit 4, presenting bioinformatics resources in depth, first dealing with the available databases, software tools and methods, to subsequently analysing data filtering, imputation phasing, formatting and exportation. Then the Unit deals with genome sequencing, alignment and mapping, and genome comparison.

 

Competences

Specific competences

  • SC1 Understanding the structure and functions of genomes and applying the technologies involved in their determination.
  • SC2 Mastering the use of bioinformatics databases and tools.

General competences

  • GC1 Integrating scientific and technical knowledge and applying it discerningly.
  • GC2 Performing scientific and/or technical information searches and processing them selectively.
  • GC3 Analysing results or strategies and elaborating conclusions which contribute to clarify the problems and to find possible solutions.
  • GC4 Learning and working autonomously, responding to unforeseen situations and re-aiming a strategy if necessary.
  • GC5 Writing presentations and synthesis, preparing and presenting oral communications, and defending them in public.

 

Learning outcomes

The student, at the end of the learning of this Unit:

  • Has gained experience in the use of different available genomic databases and computer software specific for genomic analysis.
  • Uses the most common bioinformatics databases and tools and characterizes sequences using comparative and functional genomics approaches.
  • Processes next-generation sequencing data, including assembly.
  • Assesses different alternatives for the analysis of diversity and mapping data.

 

Contents

  • Bioinformatics resources and databases
  • Data filtering, imputation, phasing, formatting and exporting
  • Alignment and mapping
  • Variant calling and effect prediction
  • Comparative genomics: orthology, collinearity

 

Learning activities

Learning activity 1: Lectures combined with applied examples
ECTS: 2.4
Hours: 60
Percentage of contact: 32%

Learning activity 2: Tutored individual work
(a) Production of different kinds of sequence alignments with standard software
(b) Discovering DNA motifs in regulatory regions of clusters of co-expressed genes, empirically controlling the significance of the result, and annotating any discovered motis
(c) Searching and getting data from ENA (European Nucleotide Archive) browser
(d) Benchmarking using Rstudio
Students, guided by the corresponding tutors, work individually on the exercises proposed. Thereafter, students have to present a brief document to the tutor with the results as homework.
(e) Alignment of Next-Generation sequencing data
(f) Variant calling
(g) Identification of 4 variants in wheat chromosome 1B
(h) Exercises on comparative genomics, preceded by two demos: gene trees and homologues and whole genome alignments
Students, guided by the tutor, work individually on the exercises proposed.
ECTS: 0.5
Hours: (a,b,c,d): 8; (e,f,g,h): 4
Percentage of contact: (a,b,c,d): 67%; (e,f,g,h): 32%

Learning activity 3: Tutored group work
Students, guided by the tutor, work in groups answering a series of questions about data filtering, imputation, phasing, formatting and exporting. At the end, the answers are discussed with the tutor and the other groups.
ECTS: 0.1
Hours: 3
Percentage of contact: 100%

 

Assessment method

Assessment system 1: Written exams composed of questions provided by all lecturers of the Unit.
The questions are multiple choice. The exam assesses the content of lectures and, the practical work, in addition to the home work exercises presented by the students.
Weighting: 65% of the final score of the Unit

Assessment system 2: Global assessment by the tutors of the individual work related to learning activities 2 (a, b, c, and d) based on the reports submitted by each student about the exercises performed. Understanding of the methodology and quality of the results will be assessed.
Weighting: 35% of the final score of the Unit

 

Lecturers

Bruno CONTRERAS, EEAD-CSIC, Zaragoza (Spain)
Rubén SANCHO, Univ. Zaragoza (Spain)
Louisse MARALBUENO, EMBL-EBI, Hinxton (UK)
Ricardo RAMIREZ-GONZALEZ, John Innes Centre, Norwich (UK)