A ten-day workshop taking place between 25 February - 6 March 2014 providing detailed hands-on training for population and meta-genomics analysis for researchers with little or no background in mathematics or computing.

Venue: Dartington Hall, Totnes, Devon (nearest train station - Totnes)

Times: 25 February - 6th March 2014.

Arrival evening of Tuesday 25 February 2014. Departure morning of 6th March 2014. The course itself will take place 9am-12pm, 2pm-5pm and on some evenings 7pm-10pm everyday 26 February-5th March. Students are expected to attend the entire course.

Contact: research-events@exeter.ac.uk

Registration

The course itself is free of charged and is funded by a Professional Postgraduate Development Award from NERC.

A total of 30 funded places are available which cover the costs of accommodation and food, but not the cost of transportation to/from the venue.

An additional 10 places are available for participants from industry. The cost of accommodation and meals will need to be covered by the participants.

You should register your interest by 31 December 2013. Participants will be informed by 10th January 2014 as to whether they have been selected. Please note that preference will be given to researchers funded by NERC.

More at http://www.eventbrite.co.uk/e/nerc-workshop-on-population-and-metagenomics-analysis-tickets-8628888237

Natural selection and other evolutionary forces lead to particular patterns of evolutionary dynamics, and they leave characteristic signatures on the genetic variation within populations. We use a combination of theory and experiments to study the dynamics and population genetics of natural selection in asexual populations such as microbes and viruses.

We use both theory and experiments to study evolutionary dynamics and population genetics, particularly in situations where natural selection is pervasive.

http://desailab.oeb.harvard.edu/home

Address of the bookmark: https://github.com/lh3/psmc

Furthermore, it displays the tree in a mobile phone (iPhone and Android) if the input file size is small.  CITATION: Subramanian, S., Ramasamy, U. and Chen, D. (2019).  VCF2PopTree: a client-side software to construct population phylogeny from genome-wide SNPs.  Peer J. x:yy.

Address of the bookmark: https://github.com/sansubs/vcf2pop

Following are the weblink for different available browsers:

http://www.ensembl.org/index.html

http://ensemblgenomes.org/

http://genome.ucsc.edu/

http://www.ncbi.nlm.nih.gov/genome

http://www.ebi.ac.uk/genomes/

http://flybase.org/

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

http://www.sanger.ac.uk/resources/databases/

https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md

Address of the bookmark: http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/

Address of the bookmark: https://www.kegg.jp/blastkoala/

What is Bacterial Comparative Genomics?

Comparative genomics involves the systematic comparison of genomes across different bacterial species or strains. This approach allows scientists to:

• Identify conserved and unique genes.

• Explore genetic determinants of pathogenicity.

• Understand bacterial evolution and phylogenetics.

• Investigate horizontal gene transfer and its role in antibiotic resistance.

Bioinformatics is central to these analyses, enabling the processing and interpretation of large-scale genomic data.

Key Steps in Bacterial Comparative Genomics

1. Genome Sequencing and Assembly: The process begins with obtaining high-quality bacterial genome sequences. Advances in next-generation sequencing (NGS) technologies have made it faster and more affordable to sequence bacterial genomes. Tools such as SPAdes and Velvet are commonly used for genome assembly.

2. Genome Annotation: Annotating a genome involves identifying genes, regulatory elements, and other genomic features. Automated tools like Prokka and RAST provide functional annotations, allowing researchers to predict the roles of genes and proteins.

3. Genome Alignment: Aligning genomes is crucial for identifying conserved regions, single-nucleotide polymorphisms (SNPs), and structural variations. Tools like Mauve and progressiveMauve are commonly employed for whole-genome alignments.

4. Comparative Analyses:

   • Core and Pan-genome Analysis: The core genome consists of genes shared across all strains of a species, while the pan-genome includes all genes found in any strain. Software like Roary and BPGA can perform core and pan-genome analyses.

   • Phylogenetic Analysis: Comparative genomics often involves reconstructing evolutionary relationships. Tools such as MEGA and IQ-TREE facilitate phylogenetic tree construction based on genomic data.

   • Functional Enrichment Analysis: To understand the biological significance of unique or shared genes, functional enrichment analysis using databases like GO (Gene Ontology) and KEGG is essential.

Here are some additional bioinformatics tools that can aid bacterial comparative genomics:

• OrthoFinder: For accurate ortholog identification across multiple genomes.

• PanOCT: Specifically designed for pan-genome clustering and annotation.

• FASTANI: A tool for calculating Average Nucleotide Identity (ANI) for microbial genome comparisons.

• CIRCOS: For visually comparing genomic data through circular genome plots.

• Galaxy Platform: A user-friendly web-based platform offering numerous genomic analysis tools.

• BLAST: Essential for sequence alignment and similarity searches.

• PhyloSift: Focused on phylogenetic analysis of microbial genomes using marker genes.

These tools, in combination with the methods discussed, provide a robust framework for conducting comprehensive comparative genomic studies.

Applications of Bacterial Comparative Genomics

1. Understanding Pathogenicity: Comparative genomics helps identify virulence factors that distinguish pathogenic strains from non-pathogenic relatives. For instance, comparing genomes of Escherichia coli strains has revealed key genetic determinants of pathogenicity in enterohemorrhagic strains.

2. Antibiotic Resistance Research: The spread of antibiotic resistance genes through horizontal gene transfer is a major global concern. Comparative analyses can trace the origins and dissemination of resistance genes, aiding in the development of countermeasures.

3. Microbial Ecology and Evolution: By studying genomic variations, researchers can understand how bacteria adapt to different environments. This is particularly relevant for extremophiles and symbiotic bacteria.

4. Vaccine Development: Identifying conserved antigens across pathogenic strains is critical for vaccine design. Comparative genomics has been instrumental in developing vaccines against pathogens like Neisseria meningitidis.

5. Biotechnology Applications: Comparative studies can uncover unique metabolic pathways in bacteria, paving the way for applications in bioremediation, synthetic biology, and industrial microbiology.

Challenges in Bacterial Comparative Genomics

While the field has made significant strides, several challenges remain:

• Data Overload: The rapid growth of sequencing data requires robust computational infrastructure and efficient algorithms.

• Genome Plasticity: High rates of horizontal gene transfer and genome rearrangements in bacteria complicate comparative analyses.

• Annotation Accuracy: Automated annotation tools are not infallible, and manual curation is often needed for high-confidence results.

• Interpreting Non-Coding Regions: Understanding the functional significance of non-coding genomic regions remains a challenge.

Future Directions

The integration of bacterial comparative genomics with other ‘omics’ approaches—such as transcriptomics, proteomics, and metabolomics—promises a more comprehensive understanding of bacterial biology. Additionally, advancements in machine learning and artificial intelligence are likely to further enhance bioinformatics analyses, enabling the prediction of complex phenotypes from genomic data.

Conclusion

Bacterial comparative genomics, driven by bioinformatics, continues to unravel the complexities of bacterial life. From combating antibiotic resistance to uncovering the secrets of microbial evolution, this interdisciplinary field holds immense potential for addressing pressing challenges in microbiology and beyond. As technology advances, so too will our ability to harness the power of comparative genomics for scientific and societal benefit.

snippy --cpus 16 --outdir mysnps --ref Listeria.gbk --R1 FDA_R1.fastq.gz --R2 FDA_R2.fastq.gz

Address of the bookmark: https://github.com/tseemann/snippy

BakRep (Denglish blend of Bakterien & Repository) simplifies access to this data. It integrates enriched genomic information with metadata accessible via a flexible search-engine.

Key features

• Assembly statistics: ensure data quality with genome-based key metrics
• Taxonomic classification: robust, purely genome-based classifications (GTDB)
• MLST: subtyping for deeper insights into genetic variation
• Annotation: comprehensive & taxonomy-independent (Bakta)
• Metadata: full original submission records

Address of the bookmark: https://bakrep.computational.bio/