Functional Genomic (Bioinformatic Approach)

Code:

BIOL4012

Acronym:

BIOL4012

Keywords
Classification	Keyword
OFICIAL	Biology

Instance: 2021/2022 - 2S

Active?	Yes
Responsible unit:	Department of Biology
Course/CS Responsible:	Master in Functional Biology and Biotechnology of Plants

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:BFBP	10	Plano de Estudos M:BFBP_2015_2016.	1	-	6	42	162

Teaching language

Suitable for English-speaking students

Objectives

Principal aims: To develop an integrated view of the structure and function of genomes, transcriptomes and proteomes and to know the modern methodologies  such as,  sequencing, annotation and analysis of functional genomics.

Specific aims: -

-Compare the genes and / or gene family among model plants like Arabidopsis, Solanum, Oryza Popullus and other non-model plants.
- To use the main bioinformatics tools for the characterization of genes and proteins in plants.

 -To use a methodology , and RNAseqs expressed in different organs and tissues of the plant and / or subject to different treatments.


-To analyze proteomics data, in order to characterize proteins: as biochemical parameters, prediction of subcellular localization and post-translational modifications - phosphorylation and glicosilation; 3D structure prediction.

Learning outcomes and competences

General skills in the understanding of the different fields of  functional genomics and their applications.

Working method

Presencial

Program

Analysis of genomes and transcriptomes comparing genes / genomes using databases (Ensemble).
Identification of open reading frames (ORF Finding). Search similarity between sequences (NCBI BLAST). Multiple sequence alignment (ClustalW2 in EBI).
Research and manipulation of DNA sequences using BLAST / MEGA. 
Methodology to analyze the transcriptome of plants. Some techniques will be studied as to its basic principles and applicability, Microarrays, RNA seq. Proteomics.  Tools of interpretation and analysis of proteins and metabolic patway 
Review of basic concepts in NGS and transcriptomics analysis by RNA-Seq. Tutorials and pipelines for data analysis.Bioinformatics exercice on RNASeq – IRIS-EDA: read count analysis (read counts, normalization), discovery-driven analysis (PCA, MDS, Clustering), differential expression analysis (methods, MA and volcano plots), DEG list analysis. Some important concepts in bioinformatics: LINUX environment; terminal vs GUI; command (one-liners) vs scripts; main programming languages (Pearl, Python, Java); infrastructures for cloud computation.Bioinformatics exercise on LINUX: orientation in the LINUX command line, handling of .fasta files.
Characterization of proteins: biochemical parameters; prediction of subcellular localization; prediction of post-translational modifications - phosphorylation and glycosylation and physiological inferences; 3D structure prediction.such as KEGG and UNIPORT.
Comparative genomics: analysis of genes synteny between different plants,such as PLAZA is an access point for plant comparative genomics, centralizing genomic data produced by different genome sequencing initiatives.

Mandatory literature

Bob B. Buchanan; Biochemistry & molecular biology of plants. ISBN: 0-943088-39-9

Complementary Bibliography

Watson JD, Baker TA, Bell SP, Gann A, Levine M & Losick R; Molecular Biology of the Gene, Pearson
Philip Meneely; Genetic Analysis, , genes, genomes and networks in Eukarytes , Oxford, 2020. ISBN: ISBN-13: 978-0198809906

Teaching methods and learning activities

Integrating contents of Molecular Biology and Bioinformatics include 42 hours of contact essentially theoretical-practical, to study the genomes and transcriptomes of plants. 
The teaching methodologies include structured formal lectures, followed by a discussion period whenever appropriate; interactive lectures, which engage the students in a more active process, with problem solving exercises and case studies to illustrate major problems and solutions encountered in topics of the curricular unit

keywords

Natural sciences > Biological sciences > Biology > Computational biology

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	30,00
Trabalho prático ou de projeto	70,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Elaboração de relatório/dissertação/tese	100,00
Estudo autónomo	20,00
Frequência das aulas	42,00
Total:	162,00

Eligibility for exams

Calculation formula of final grade

Continuous and distributed evaluation throughout the curricular unit, presentation of an individual report, on silico analysis of a gene or family of genes of interest in a particular study. (12/20) Assessment based on the presentation of a proposed topic, in an individual report on one of the topics covered in the classes (2/20) values). Final exam (6/20)

Classification improvement

Examination and/or  of the individual  report