SNP Analysis of bacterial genomes

Question

[Optimist]

Dear All,

I need to analyse two acinetobacter genomes isolated from 2 different patients who were in the same ward on the same day. We found similar Antibiotic resistance profile in both the isolates.

We have done WGS & submitted the reads to genbank.

I need help with regards to the SNP analysis for these isolates. Can you please suggest the right tool to be used for this analysis.

Regards Optimist

[harold.smith.tarheel]

Are you attempting to determine whether the two strains are identical, or the mechanism of antibiotic resistance? If the latter, be aware that resistance typically arises from acquisition of a resistance cassette (often transmitted via plasmid) rather than mutation. SNP analysis would not identify a resistance cassette.

[ori]

Are the species of two acinetobactor same?
Are there reference genomes of the species in database?
It is important to define what genomes you want to compare to detect SNPs.
Once that is decided, you will be able to refer to the tools described by ropolocan.

[Optimist]

Both the study genomes belong to same species. They are two different strains belonging to same species.

Yes, there exist a reference genome in the NCBI database.

I would like to detect SNPs between these two genomes.

Thanks & regards Optimist

Answer 1

[ropolocan]

Hello Optimist,

Some tools come to mind:

Snippy: Might be more appropriate in this case given the number of isolates you want to analyze.

https://github.com/tseemann/snippy

SNVPhyl: might be more useful if you sequence more genomes than those two since the end goal is to produce a SNV/SNP phylogeny

https://snvphyl.readthedocs.io/en/latest/

I hope this helps and that these tools are appropriate for what you want to do.

Answer 2

[Tm]

If your aim is to detect SNPs between these two genomes, then in that case you can denovo assemble one sample to generate scaffolds followed by mapping of reads of another sample on scaffolds of 1st sample. Using these approach you will come to know the difference between one strain against another in terms of SNPs.

But if you want to detect SNPs in both the samples with respect to reference genome in NCBI then in that case you can map the reads of sample individually on reference genome and can call SNP using their respective alignment (.BAM). Using these approach you will come to know the difference each strain is showing against NCBI's reference genome in terms of SNPs.

In any case, you can follow Variant calling for bacteria pipeline which I found worth in my study.

[Optimist]

Dear Toralmanvar,

Thanks for your inputs.

My aim is to detect SNPs between both the strains. I have fastQ, fasta files of both the sequences. Could help me out with the relevant tools n steps regarding SNP analysis.

I'm looking at getting an output where in I should be able to explain the the changes in the sequences (their location coordinates) along with the effect of the change (if the snp had an significant effect on the amino-acid)

Thanks

Optimist

[Tm]

Series of steps will be required to reach your aim:

1) Filteretaion of reads of both the sample to remove low quality bases (as it is very crucial when SNP calling is the aim) and adapter sequences using Trimmomatic/cutadapt/NGStoolkit 2) Denovo assembly of the reads of both the sample using SOAPdenovo2/Velvet 3) Gene prediction using Prodigal 4) Annotation of predicted genes against NR database using Blast 5) Mapping of reads of one sample onto scaffold of another sample and vise versa using BWA mem 6) SNP calling using GATK haplotypecaller/freebayes (very easy to use considering sorted bam as input) 7) Filteration of SNPs on the basis of read depth and quality 8) Annotation of the SNP using snpeff considering reference scaffold and its gene annotation gff obtained from combination of prodigal and blast result

At the end of SNP annotation you will get effect of SNP on the change of amino acid

for point 5 and 6 you can follow Variant calling for bacteria tutorial if GATK pipeline is to be followed

Hope this will help.

Answer 3

[Cliff Beall]

A possible workflow would be trim with Trimmomatic, assemble with SPAdes, check the assemblies with Quast and then submit to IMG/MER - they have a tool that could determine average nucleotide identity to other Acinetobacter genomes and to each other. I would expect random isolates to have ANI in 95-99% range while transmitted ones might be 99.9% plus. My experience is with oral commensal bacteria, not pathogens though.

You can also use IMG to look at gene functions and maybe find the cause of antibiotic resistance. The drawback is it takes a couple of weeks to get into the system.