Prokka Annotations

Custom Prokka Annotations

We annotated the genomes with Prokka v1.14.6 (Seemann, 2014) in two different ways for proper compatibility and strain labeling with both GET_HOMOLOGUES and anvi’o.

Prokka annotations for GET_HOMOLOGUES

We annotated the 92 Corynebacterium strain genomes described in Table S2. These genomes are listed in NovCor_AnnotationProkka_GenomeList_v02.csv.

This step annotates all the .fasta files in the selected input folder (path_i) and places all the output annotated files in the output folder (path_o). Output files headers get updated with –genus ‘Corynebacterium’ –species ‘sp’ and –strain based on the file name. We used default parameters, including gene recognition and translation initiation site identification with Prodigal (Hyatt et al., 2010).

#conda activate Prokka

path_i="data/genomes"
path_o="data/GET_HOMOLOGUES/Prokka_out"
mkdir -p "$path_o"

for file in $path_i/*.f*; do
    FILENAME=`basename ${file%.*}`
    prokka --prefix $FILENAME --outdir $path_o --genus 'Corynebacterium' --species 'sp' --strain $FILENAME --centre X --compliant --cpus 0 --force $file; 
done

Prokka annotation for anvi’o

We selected 30 Corynebacterium strains for analysis of KEGG metabolic capabilities using anvi’o. These genomes are listed in NovCor_AnnotationAnvio_GenomeList_v02.csv and included in data/genomes as .fasta files.

More information about importing Prokka annotations into anvi’o can be found here: https://merenlab.org/2017/05/18/working-with-prokka/#note-for-the-pangenomics-workflow

Fasta reformatting

Before the annotation step with Prokka we need to reformat the .fasta files using anvi-script-reformat-fasta. This script creates .fasta files with simplified deflines and also by using --seq-type NT prevents downstream errors with “characters that are not any of A, C, T, G, N, a, c, t, g, n.”

#conda activate anvio-dev

path_i="data/genomes"
path_o="data/Anvio8/Reformatted"
mkdir -p "$path_o"

for file in $path_i/*.f*; do
    FILENAME=`basename ${file%.*}`
    anvi-script-reformat-fasta -o $path_o/$FILENAME.fa --min-len 0 --simplify-names $file --seq-type NT; 
done

Prokka annotation

This step repeats the Prokka annotation using the anvi’o reformatted .fasta files.

Output files headers get updated with –genus –species and –strain based on the info in the genomes list .csv file.

#conda activate Prokka

csv_file="data/genome_lists/NovCor_AnnotationAnvio_GenomeList_v01.csv"
path_i="data/Anvio8/Reformatted"
path_o="data/Anvio8/Prokka_out"
mkdir -p "$path_o"

while IFS=',' read -r name genus species; do
    if [[ "$name" != "name" ]]; then  # Skip the header
        prokka --prefix "$name" --outdir "$path_o" --genus "$genus" --species "$species" --strain "$name" --cpus 0 --force "$path_i/$name.fa"
    fi
done < "$csv_file"

Parsing .gff files

This step is to parse Prokka annotated genomes to import both the external Prodigal gene calls and functions independently into anvi’o. The input (path_i) is the annotation in GFF3 format and outputs (path_o) are two tab-delimited text files, one for gene calls (calls_*.txt) and one for annotations (annot_*.txt).

This is done with the script gff_parser.py described in this tutorial.

#conda activate gffutils

path_i="data/Anvio8/Prokka_out"
path_o="data/Anvio8/Parsed_prokka"
mkdir -p "$path_o"

for file in $path_i/*.gff; do
    FILENAME=`basename ${file%.*}`
    python scripts/gff_parser.py $file \
    --gene-calls $path_o/calls_$FILENAME.txt \
    --annotation $path_o/annot_$FILENAME.txt;
done

Generating contigs databases

In this step the reformatted .fa files (path_i) and the external gene calls (calls_*.txt) from Prokka (path_e) get imported to generate anvi’o contig databases (path_o). Initially we got a lot of early stop codon errors. Therefore, we add the –ignore-internal-stop-codons flag.

#conda activate anvio-dev

path_i="data/Anvio8/Reformatted"
path_e="data/Anvio8/Parsed_prokka"
path_o="data/Anvio8/Contigs_db"
mkdir -p "$path_o"

for file in $path_i/*.fa; do
    FILENAME=`basename ${file%.*}`
    anvi-gen-contigs-database -f $file \
                              -o $path_o/$FILENAME.db \
                              --external-gene-calls $path_e/calls_$FILENAME.txt \
                              --ignore-internal-stop-codons \
                              -n $FILENAME;
done

Importing Prokka functional annotation

Finally, the external functional annotations (annot_*.txt) from Prokka (path_e) get imported into the Anvi’o contigs databases (path_i).

#conda activate anvio-dev

path_i="data/Anvio8/Contigs_db"
path_e="data/Anvio8/Parsed_prokka"

for file in $path_i/*.db; do
    FILENAME=`basename ${file%.*}`
    anvi-import-functions -c $file \
                          -i $path_e/annot_$FILENAME.txt
      
done

# Prokka Annotations {.unnumbered} ```{r} #| echo: FALSE #| message: FALSE ``` ## Custom Prokka Annotations We annotated the genomes with [Prokka v1.14.6](https://github.com/tseemann/prokka) [@Seemann2014] in two different ways for proper compatibility and strain labeling with both GET_HOMOLOGUES and anvi'o. ### Prokka annotations for GET_HOMOLOGUES We annotated the 92 *Corynebacterium* strain genomes described in Table S2. These genomes are listed in `NovCor_AnnotationProkka_GenomeList_v02.csv`. ::: {.content-hidden when-profile="manuscript"} These assemblies are located in `data/genomes` as `.fasta` files. ::: This step annotates all the `.fasta` files in the selected input folder (`path_i`) and places all the output annotated files in the output folder (`path_o`). Output files headers get updated with --genus 'Corynebacterium' --species 'sp' and --strain based on the file name. We used default parameters, including gene recognition and translation initiation site identification with Prodigal [@Hyatt2010]. ```{bash} #| eval: FALSE #conda activate Prokka path_i="data/genomes" path_o="data/GET_HOMOLOGUES/Prokka_out" mkdir -p "$path_o" for file in $path_i/*.f*; do FILENAME=`basename ${file%.*}` prokka --prefix $FILENAME --outdir $path_o --genus 'Corynebacterium' --species 'sp' --strain $FILENAME --centre X --compliant --cpus 0 --force $file; done ``` ### Prokka annotation for anvi'o We selected 30 *Corynebacterium* strains for analysis of KEGG metabolic capabilities using anvi'o. These genomes are listed in `NovCor_AnnotationAnvio_GenomeList_v02.csv` and included in `data/genomes` as `.fasta` files. More information about importing Prokka annotations into anvi'o can be found here: <https://merenlab.org/2017/05/18/working-with-prokka/#note-for-the-pangenomics-workflow> #### Fasta reformatting Before the annotation step with Prokka we need to reformat the `.fasta` files using `anvi-script-reformat-fasta`. This script creates `.fasta` files with simplified deflines and also by using `--seq-type NT` prevents downstream errors with "characters that are not any of A, C, T, G, N, a, c, t, g, n." ```{bash} #| eval: FALSE #conda activate anvio-dev path_i="data/genomes" path_o="data/Anvio8/Reformatted" mkdir -p "$path_o" for file in $path_i/*.f*; do FILENAME=`basename ${file%.*}` anvi-script-reformat-fasta -o $path_o/$FILENAME.fa --min-len 0 --simplify-names $file --seq-type NT; done ``` #### Prokka annotation This step repeats the Prokka annotation using the anvi'o reformatted `.fasta` files. Output files headers get updated with --genus --species and --strain based on the info in the genomes list `.csv` file. ```{bash} #| eval: FALSE #conda activate Prokka csv_file="data/genome_lists/NovCor_AnnotationAnvio_GenomeList_v01.csv" path_i="data/Anvio8/Reformatted" path_o="data/Anvio8/Prokka_out" mkdir -p "$path_o" while IFS=',' read -r name genus species; do if [[ "$name" != "name" ]]; then # Skip the header prokka --prefix "$name" --outdir "$path_o" --genus "$genus" --species "$species" --strain "$name" --cpus 0 --force "$path_i/$name.fa" fi done < "$csv_file" ``` #### Parsing .gff files This step is to parse Prokka annotated genomes to import both the external Prodigal gene calls and functions independently into anvi'o. The input (`path_i`) is the annotation in GFF3 format and outputs (`path_o`) are two tab-delimited text files, one for gene calls (`calls_*.txt`) and one for annotations (`annot_*.txt`). This is done with the script `gff_parser.py` described in this [tutorial](https://merenlab.org/2017/05/18/working-with-prokka/). ```{bash} #| eval: FALSE #conda activate gffutils path_i="data/Anvio8/Prokka_out" path_o="data/Anvio8/Parsed_prokka" mkdir -p "$path_o" for file in $path_i/*.gff; do FILENAME=`basename ${file%.*}` python scripts/gff_parser.py $file \ --gene-calls $path_o/calls_$FILENAME.txt \ --annotation $path_o/annot_$FILENAME.txt; done ``` #### Generating contigs databases In this step the reformatted `.fa` files (`path_i`) and the external gene calls (`calls_*.txt`) from Prokka (`path_e`) get imported to generate anvi’o contig databases (`path_o`). Initially we got a lot of early stop codon errors. Therefore, we add the `–ignore-internal-stop-codons` flag. ```{bash} #| eval: FALSE #conda activate anvio-dev path_i="data/Anvio8/Reformatted" path_e="data/Anvio8/Parsed_prokka" path_o="data/Anvio8/Contigs_db" mkdir -p "$path_o" for file in $path_i/*.fa; do FILENAME=`basename ${file%.*}` anvi-gen-contigs-database -f $file \ -o $path_o/$FILENAME.db \ --external-gene-calls $path_e/calls_$FILENAME.txt \ --ignore-internal-stop-codons \ -n $FILENAME; done ``` #### Importing Prokka functional annotation Finally, the external functional annotations (`annot_*.txt`) from Prokka (`path_e`) get imported into the Anvi’o contigs databases (`path_i`). ```{bash} #| eval: FALSE #conda activate anvio-dev path_i="data/Anvio8/Contigs_db" path_e="data/Anvio8/Parsed_prokka" for file in $path_i/*.db; do FILENAME=`basename ${file%.*}` anvi-import-functions -c $file \ -i $path_e/annot_$FILENAME.txt done ``` ::: {.content-hidden when-profile="manuscript"} ## NCBI annotations The 9 genome assemblies listed in `NovCor_GenomeListNCBI_v01.txt` and included in `data/genomes_NCBIAnnotation` where used as references for comparisons on the KEGG metabolic analysis only. These genomes were not part of the phylogenetic/pangenomic analysis, and we were interested in keeping the original NCBI annotations in the anvi'o contig databases. They were downloaded from NCBI in `.gbff` format and processed as follows: ### Parsing .gbff files downloaded from NCBI First we used `anvi-script-process-genbank` to parse the `.gbff` files (`path_i`) in order to output (`path_o`) the corresponding properly formatted `.fa` files, plus two tab-delimited text files, one for gene calls (`calls_*.txt`) and one for annotations (`annot_*.txt`). ```{bash} #| eval: FALSE #conda activate anvio-dev path_i="data/genomes_NCBIAnnotation" path_o="data/Anvio8/Parsed_NCBI" mkdir -p "$path_o" for file in $path_i/*.gbff; do FILENAME=`basename ${file%.*}` anvi-script-process-genbank -i $file \ --output-gene-calls $path_o/calls_$FILENAME.txt \ --output-functions $path_o/annot_$FILENAME.txt \ --output-fasta $path_o/$FILENAME.fa \ --annotation-source prodigal done ``` ### Generating contigs databases In this step the `.fa` files and the gene calls from NCBI (`path_i`) get imported to generate anvi'o contigs databases (`path_o`). ```{bash} #| eval: FALSE #conda activate anvio-dev path_i="data/Anvio8/Parsed_NCBI" path_o="data/Anvio8/Contigs_db" mkdir -p "$path_o" for file in $path_i/*.fa; do FILENAME=`basename ${file%.*}` anvi-gen-contigs-database -f $file \ -o $path_o/$FILENAME.db \ --external-gene-calls $path_i/calls_$FILENAME.txt \ -n $FILENAME; done ``` ### Importing Prokka functional annotation Then the NCBI external annotations (`path_e`) get imported into the Anvi'o contigs databases (`path_i`). ```{bash} #| eval: FALSE #conda activate anvio-dev path_i="data/Anvio8/Contigs_db" path_e="data/Anvio8/Parsed_NCBI" for file in $path_i/*.db; do FILENAME=`basename ${file%.*}` anvi-import-functions -c $file \ -i $path_e/annot_$FILENAME.txt done ``` :::