1. Authors

Yorgo EL MOUBAYED
Maroua CHAHDIL

2. Purpose

Select four close and distant genomes to a chosen bacterial genome on which comparative genomics will be carried out.

3. Genome selection

3.1. Select bacterial genome

Requirements: complete genome, CDS ranging from 500 to 1000 and in the COGs list.

Mesoplasma florum W37 (CDS: 723).
NCBI link: https://www.ncbi.nlm.nih.gov/genome/1129?genome_assembly_id=170599
COG link: https://ftp.ncbi.nih.gov/pub/COG/COG2014/static/lists/listMesflo.html?fbclid=IwAR2tomiADkkGKvWh3yXSz5esG87EctMiGbecWbNGTbg5TrNusD3Xm7G-e1A

3.2. Select two other genomes from the same genre

Requirements: complete genome.

• Mesoplasma chauliocola.
  NCBI link: https://www.ncbi.nlm.nih.gov/genome/17787?genome_assembly_id=328413

• Mesoplasma coleopterae.
  NCBI link: https://www.ncbi.nlm.nih.gov/genome/65381?genome_assembly_id=355498

3.3. Select two other genomes from a neighbor genre

Requirements: complete genome.

• Entomoplasma somnilux.
  NCBI link: https://www.ncbi.nlm.nih.gov/genome/31059?genome_assembly_id=355484

• Entomoplasma melaleucae.
  NCBI link: https://www.ncbi.nlm.nih.gov/genome/31909?genome_assembly_id=355486

4. Download RefSeq FTP repositories

5. Create summary table to compare features

Check the google doc on the drive.
Link: https://docs.google.com/document/d/1C0SZWxOWL4sVVi6IUKGRYBFbmO15DUQLDtyrBipb7dE/edit?usp=sharing

6. eggNOG analysis

eggNOG-mapper is a tool for functional annotation of large sets of sequences based on fast orthology assignments using precomputed eggNOG clusters and phylogenies.

6.1. Sequence search on target CDS

We chose the first CDS from Mesoplasma florum (mesoplasma_florum_proteom.faa) and stored it in mesoplasma_florum_single_protein.faa. To get the results you should resubmit the job because we couldn't recover the results.

6.2. eggNOG-mapper-v2 (mandatory for one genome and optional for other genomes)

• Job was submitted for Mesoplasma florum.
  Link to results: http://eggnog-mapper.embl.de/job_status?jobname=MM_roi_s3js

• Job was submitted for Mesoplasma chauliocola.
  Link to results: http://eggnog-mapper.embl.de/job_status?jobname=MM_eqwo9l8l

• Job was submitted for Mesoplasma coleopterae.
  Link to results: http://eggnog-mapper.embl.de/job_status?jobname=MM_q3od6t4t

• Job was submitted for Entomoplasma somnilux.
  Link to results: http://eggnog-mapper.embl.de/job_status?jobname=MM_vmfu5790

• Job was submitted for Entomoplasma melaleucae.
  Link to results: http://eggnog-mapper.embl.de/job_status?jobname=MM_fftg5l_n

6.3. Compare eggNOG and COG functional categories (refer to summary table)

eggNOG functional categories were stored in eggnog_cog.csv.
COGs functional categories were stored in ftp_cog.csv.
Final values were calculated through the eggnog_cog.py and cog.py scripts and reported in the summary table.

7. Genome signatures

7.1. Create a table with the ratios of dinucleotides frequencies for each genome (observed/expected)

• The dinucleotides frequencies were determined by:

  • generating random genomes through shuffleseq. All random genomes are stored in the "random genomes" directory.
  • compseq for the observed and expected genomes.

• The observed/expected ratio was calculated using the ratio_obsexp.py script.

7.2. Create table of the cumulative frequency of the codon usage (RSCU) for each genome

• The frequency of codon usage was calculated using compseq.
• The cumulative frequency of codon usage was calculated using the cumulative_frequence_codon.py script.
• The RSCU was calculated using the rscu.py script.

Summary results were reported in dinucleotide_ratio.ods and trinucleotide_cumulative_frequence_rcsu.ods

• Link to compseq: https://www.bioinformatics.nl/cgi-bin/emboss/compseq
• Link to shuffleseq: http://www.bioinformatics.nl/cgi-bin/emboss/shuffleseq

8. MUMmer: align chosen genome against one close and one distant genome

MUMmer is a system for rapidly aligning large DNA sequences to one another. It can align:

• Whole genomes to other genomes.
• Large genome assemblies to one another.
• Partial (draft) genomes sequences to one another.

8.1. Installing MUMmer

To install the MUMmer package (v3.23) and dependencies (gnuplot v5.2.7) with conda run the following:

conda install -c bioconda mummer
conda install -c conda-forge gnuplot

Or just setup the following conda environment:

conda env create -f mummer.yml

• Conda source: https://anaconda.org/bioconda/mummer, https://anaconda.org/conda-forge/gnuplot
• MUMmer GitHub page (for detailed explanations): https://mummer4.github.io/index.html

8.2. Running mummer

mummer -mum -b -c mesoplasma_florum_genome.fna entomoplasma_melaleucae_genome.fna > distant_mummer.mums

mummer -mum -b -c mesoplasma_florum_genome.fna mesoplasma_chauliocola_genome.fna > close_mummer.mums

8.3. Running mummerplot

mummerplot -x "[0,825824]" -y "[0,85478]" -postscript -p mummer close_mummer.mums

mummerplot -x "[0,825824]" -y "[0,845295]" -postscript -p mummer distant_mummer.mums

The following output files were generated for both distant and close genomes analysis:

• mummer.gp
• mummer.fplot
• mummer.rplot
• mummer.ps (plot figure)

9. Core & Pan-genome

9.1. Bidirectional Best Hits (BBH) and calculate ANI, AF, AAI

9.1.1. Installing blast

To install the blast package (v2.10.1) with conda run the following:

conda install -c bioconda blast

• Conda source: https://anaconda.org/bioconda/blast

Or run the following to create and activate the custom conda environment:

conda env create blastenv
conda env activate blastenv

9.1.2. BBH and local blast

Perform BBH for each pair of genomes (AA: Criteria 30% identity / 80% coverage)

• Build a genome databse with only one genome (here we used florum_protein.faa > florumDB):

makeblastdb -in florum_protein.faa -out florumDB -dbtype prot

• Run blastp for proteins (i.e. for mesoplasma_chauliocola). 80% coverage is determined by -qcov_hsp_perc 80:

blastp -query mesoplasma_chauliocola.faa -db florumDB -out QmesochauDBflorum -qcov_hsp_perc 80

• To get to 30% identity we use the command awk and filter the third columns (which is the identity) then put the result into a new file named final_result.

awk '$3>=30' QmesochauDBflorum >> final_result.txt

9.2. Calculate ANI, AF, AAI

Average Nucleotide Identity (ANI) and Alignment Fraction (AF) are calculated through the IMG website

AAI is similar to ANI. It's the measure of global protein similarity between the set of gene products (protein) between the genomes.

9.3. OrthoVenn2

OrthoVenn is a web platform for comparison and annotation of orthologous gene clusters among multiple species.

Job was submitted using the 5 species' proteoms files as input.
Link to results: https://orthovenn2.bioinfotoolkits.net/task/result/00a4e2ed85b530f9b9de2af5b4b1e2b0

References

• Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Jaime Huerta-Cepas, Kristoffer Forslund, Luis Pedro Coelho, Damian Szklarczyk, Lars Juhl Jensen, Christian von Mering & Peer Bork.

• eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Jaime Huerta-Cepas, Damian Szklarczyk, Davide Heller, Ana Hernández-Plaza, Sofia K Forslund, Helen Cook, Daniel R Mende, Ivica Letunic, Thomas Rattei, Lars J Jensen, Christian von Mering, Peer Bork

• NCBI Resource Coordinators. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res.

• Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, Salzberg SL. Versatile and open software for comparing large genomes. Genome biology. 2004 Jan 1;5(2):R12.

• Villesen, P (2007), FaBox: an online fasta sequence toolbox, http://www.birc.au.dk/software/fabox

• Rice P., Bleasby A and Ison J. The EMBOSS Users Guide. Cambridge University Press

• Xu L, Dong Z, Fang L, Luo Y, Wei Z, Guo H, Zhang G, Gu YQ, Coleman-Derr D, Xia Q, Wang Y. OrthoVenn2: a web server for whole-genome comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Res. 2019 Jul.

• Chen IA, Chu K, Palaniappan K, Pillay M, Ratner A, Huang J, Huntemann M, Varghese N, White JR, Seshadri R, Smirnova T, Kirton E, Jungbluth SP, Woyke T, Eloe-Fadrosh EA, Ivanova NN, Kyrpides NC. IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res. 2019 Jan.