Phylogenetics and metagenomics 1400-228MiFM-en
The course consists of two thematic blocks covering molecular phylogenetics and metagenomics (amplicon analysis), with a focus on environmental research. Each class will be preceded by a brief theoretical introduction.
The first classes will begin with basic computer handling using the Linux operating system through the command line, working on a server, and learning about fasta, fastq, and newick file formats.
Molecular Phylogenetics block:
• Alignment of nucleotide and protein sequences for phylogenetic analysis; evaluating the reliability of alignments and selecting homologous positions for analysis.
• Choosing substitution models for phylogenetic analyses.
• Phylogenetic analyses: maximum parsimony, distance methods, maximum likelihood, Bayesian analysis.
• Evaluating the strength of trees and internal branch support: different methods for estimating branch support, posterior probability; testing tree topologies
• Detecting adaptive evolution in molecular data.
• Dating phylogenies using Bayesian methods.
• Estimating ancestral states of morphological features – maximum parsimony and maximum likelihood methods; evolution models for continuous and categorical features.
• Historical biogeography – reconstruction of the distribution and dispersal of taxa in time and space.
Metagenomics - Amplicon Analysis block:
• Introduction to NGS data processing: basics of sequencing methodology using the Illumina platform, quality analysis of obtained data.
• Preprocessing of high-throughput amplicon sequencing results: quality filtering, read merging, dereplication, ASV and OTU analysis.
• Taxonomic classification of sequences – different methods and reference sequence databases; visualization and analysis of taxonomic composition.
• Calculation of biological diversity indices (alpha and beta diversity); species richness, Shannon index, principal component analysis (PCA), and multiparametric scaling.
• Linking environmental factors (metadata) to the obtained results of species composition and diversity indices.
• Mapping obtained reads to the phylogenetic tree.
Mode
Course coordinators
Learning outcomes
KNOWLEDGE:
1. The graduate understands the mutual relationships of all living organisms. They know advanced phylogenetic methodology that allows establishing relationships between organisms (K_W07 BI2).
2. The graduate recognizes the need for advanced statistical methods to describe phenomena and analyze data in biological sciences and environmental protection (K_W08 BI2).
3. The graduate knows specialized bioinformatics tools used in phylogenetics and metagenomics, with particular emphasis on the specifics of environmental research (K_W09 BI2).
4. The graduate knows molecular methods used in nature conservation and ecology (K_W08 Os2).
SKILLS:
1. The graduate applies appropriate statistical methods as well as computer algorithms and techniques to describe
biological phenomena and analyze biological data (K_U06 BI2).
2. The graduate uses advanced statistical methods and tools to analyze empirical data and describe natural processes (K_U01 Os2).
3. The graduate predicts the direction of changes in the natural environment based on analytical data (K_U02 Os2).
4. The graduate has the ability to write a research paper based on their own scientific research in Polish and a short scientific report in a foreign language (K_U11 Os2).
SOCIAL COMPETENCES:
1. Demonstrates the need for constant updating and deepening of knowledge in the field of phylogenetics and metagenomics (K_K02 Os2).
2. Expands interests in the direction of exact sciences (K_K03 Os2).
3. Demonstrates the need for constant updating of knowledge in the field of mathematical and natural sciences (K_K04 Os2).
4. Feels the need for constant self-education and updating of knowledge, using scientific sources related to phylogenetics and metagenomics (K_K07 BI2).
Assessment criteria
Evaluation based on points awarded for tasks performed.
Bibliography
Bioinfromatyka i ewolucja molekularna. Paul G. Higgs i Teresa K. Attwood. Tłumaczenie K. Murzyn, P. Liguziński, M. Kurdziel. PWN, Warszawa, 2011.
Łatwe drzewa filigenetyczne. Hall Barry G. PWN, Warszawa, 2008.
CHANGE IN MARINE COMMUNITIES: An Approach to Statistical Analysis and Interpretation. K R Clarke, R N Gorley, P J Somerfieldb & R M Warwick, PRIMER-E: Plymouth, 2014
https://docs.qiime2.org/2022.2/
https://cme.h-its.org/exelixis/resource/download/NewManual.pdf
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: