I like to create new tools to solve already solved problems. This time I’ve
created a new tool for reference-based alignment of bacterial genomes, and
computation of sequence identity and coverage of some reference gene sequences
in a query assembly. The tool is called kbo
and is available from
https://github.com/tmaklin/kbo (written in Rust).
kbo comes with some interesting algorithmic bioinformatics that converts plain k-mer matching between a database and a query sequence into local alignments by looking at the longest common prefix length in each k-mer and its best match in a database (see the preprint by colleagues from Helsinki).
Overview
The basic idea is that if the longest common prefix length – a k-bounded matching statistic – of each k-mer match and their order in the query are known, then the following events are identifiable by looking at the (ordered) matching statistic vector:
- Matching region between query and reference: matching statistic has a high value.
- Region in query not present in reference: matching statistic has random value drawn from noise distribution.
- Single character mismatch or insertion in query: matching statistic decreases linearly from k to 0 and immediately goes back to a high value.
- Insertion in reference or jump from one region in query to another: matching statistic decreases linearly from k to 1 and immediately goes back to a high value.
These are described in documentation for the derandomize and translate modules, the kbo crate documentation, and will be turned into a pre-print in early 2025.
This post contains a guide and examples for the two main use cases I have in mind for kbo. You can replicate them using the kbo command-line interface.
Installation
Download a precompiled binary from here, or install the command-line interface using cargo:
cargo install kbo-cli
and then call kbo
to run the tool.
I am also developing a browser version at https://github.com/tmaklin/kbo-gui which will hopefully be available soon.
Finding genes of interest in a query
Assume you have sequenced and assembled a bacterial genome and are interested in
knowing whether the assembly contains some gene of interest or not. Typically,
this would be a task for blast, but we want to use kbo find
.
Setup:
- A database containing 19 interesting genes from GitHub.
- A genome which has variants of these genes from the ENA.
Run the following to see where the genes are located in the query
kbo find -r db.fasta GCA_000013265.1.fasta.gz
This will produce the output
This replaces the query.contig column with the name of the contig (click to expand)
query ref q.start q.end strand length mismatches gap_opens identity coverage query.contig ref.contig
GCA_000013265.1.fasta.gz db.fasta 56646 57164 + 519 0 0 100.00 1.03 ENA|CP000244|CP000244.1 Escherichia coli UTI89 plasmid pUTI89, complete sequence. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2165476 2166423 + 948 0 0 100.00 1.88 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2900668 2910288 - 9621 0 0 100.00 19.06 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2910329 2912929 - 2601 0 0 100.00 5.15 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2912939 2913808 - 870 0 0 100.00 1.72 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2913838 2914086 - 249 0 0 100.00 0.49 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2914090 2916485 - 2396 0 0 100.00 4.75 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2916533 2921329 - 4797 1 0 99.98 9.50 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2921379 2924411 - 3033 0 0 100.00 6.01 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2924455 2930955 - 6501 0 0 100.00 12.88 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2930966 2938886 - 7921 0 0 100.00 15.69 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2938948 2944751 - 5804 0 0 100.00 11.50 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2944782 2947241 - 2460 0 0 100.00 4.87 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2947254 2949483 - 2230 0 0 100.00 4.42 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
GCA_000013265.1.fasta.gz db.fasta 2949518 2950030 - 513 0 0 100.00 1.02 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. db.fasta
Note that the output doesn’t tell which genes were found, only where in the
query there are matches in the reference. If this is inconvenient for you, add the --detailed
flag which performs the analysis gene-by-gene at the cost of some extra runtime:
kbo find --detailed --threads 4 -r db.fasta GCA_000013265.1.fasta.gz
This replaces the query.contig column with the name of the contig (click to expand)
query ref q.start q.end strand length mismatches gap_opens identity coverage query.contig ref.contig
GCA_000013265.1.fasta.gz db.fasta 56646 57164 + 519 00 100.00 100.00 ENA|CP000244|CP000244.1 Escherichia coli UTI89 plasmid pUTI89, complete sequence. clbS-like_4ce09a
GCA_000013265.1.fasta.gz db.fasta 2165476 2165688 + 213 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbR|locus_tag=ECOK1_RS11410|product="colibactin biosynthesis LuxR family transcriptional regulator ClbR"|protein_id=WP_000357141.1
GCA_000013265.1.fasta.gz db.fasta 2165689 2166423 + 735 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbA|locus_tag=ECOK1_RS11415|product="colibactin biosynthesis phosphopantetheinyl transferase ClbA"|protein_id=WP_001217110.1
GCA_000013265.1.fasta.gz db.fasta 2900668 2910288 - 9621 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbB|locus_tag=ECOK1_RS11405|product="colibactin hybrid non-ribosomal peptide synthetase/type I polyketide synthase ClbB"|protein_id=WP_001518711.1
GCA_000013265.1.fasta.gz db.fasta 2910329 2912929 - 2601 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbC|locus_tag=ECOK1_RS11400|product="colibactin polyketide synthase ClbC"|protein_id=WP_001297908.1
GCA_000013265.1.fasta.gz db.fasta 2912939 2913808 - 870 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbD|locus_tag=ECOK1_RS11395|product="colibactin biosynthesis dehydrogenase ClbD"|protein_id=WP_000982270.1
GCA_000013265.1.fasta.gz db.fasta 2913838 2914086 - 249 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbE|locus_tag=ECOK1_RS11390|product="colibactin biosynthesis aminomalonyl-acyl carrier protein ClbE"|protein_id=WP_001297917.1
GCA_000013265.1.fasta.gz db.fasta 2914090 2915220 - 1131 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbF|locus_tag=ECOK1_RS11385|product="colibactin biosynthesis dehydrogenase ClbF"|protein_id=WP_000337350.1
GCA_000013265.1.fasta.gz db.fasta 2915217 2916485 - 1269 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbG|locus_tag=ECOK1_RS11380|product="colibactin biosynthesis acyltransferase ClbG"|protein_id=WP_000159201.1
GCA_000013265.1.fasta.gz db.fasta 2916533 2921329 - 4797 10 99.98 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbH|locus_tag=ECOK1_RS11375|product="colibactin non-ribosomal peptide synthetase ClbH"|protein_id=WP_001304254.1
GCA_000013265.1.fasta.gz db.fasta 2921379 2924411 - 3033 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbI|locus_tag=ECOK1_RS11370|product="colibactin polyketide synthase ClbI"|protein_id=WP_000829570.1
GCA_000013265.1.fasta.gz db.fasta 2924455 2930955 - 6501 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbJ|locus_tag=ECOK1_RS11365|product="colibactin non-ribosomal peptide synthetase ClbJ"|protein_id=WP_001468003.1
GCA_000013265.1.fasta.gz db.fasta 2929045 2930331 - 1287 20 99.84 19.91 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbK|locus_tag=ECOK1_RS11360|product="colibactin hybrid non-ribosomal peptide synthetase/type I polyketide synthase ClbK"|protein_id=WP_000222467.1
GCA_000013265.1.fasta.gz db.fasta 2930966 2937430 - 6465 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbK|locus_tag=ECOK1_RS11360|product="colibactin hybrid non-ribosomal peptide synthetase/type I polyketide synthase ClbK"|protein_id=WP_000222467.1
GCA_000013265.1.fasta.gz db.fasta 2934698 2935984 - 1287 20 99.84 19.80 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbJ|locus_tag=ECOK1_RS11365|product="colibactin non-ribosomal peptide synthetase ClbJ"|protein_id=WP_001468003.1
GCA_000013265.1.fasta.gz db.fasta 2937423 2938886 - 1464 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbL|locus_tag=ECOK1_RS11355|product="colibactin biosynthesis amidase ClbL"|protein_id=WP_001297937.1
GCA_000013265.1.fasta.gz db.fasta 2938948 2940387 - 1440 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbM|locus_tag=ECOK1_RS11350|product="precolibactin export MATE transporter ClbM"|protein_id=WP_000217768.1
GCA_000013265.1.fasta.gz db.fasta 2940384 2944751 - 4368 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbN|locus_tag=ECOK1_RS11345|product="colibactin non-ribosomal peptide synthetase ClbN"|protein_id=WP_001327259.1
GCA_000013265.1.fasta.gz db.fasta 2944782 2947241 - 2460 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbO|locus_tag=ECOK1_RS11340|product="colibactin polyketide synthase ClbO"|protein_id=WP_001029878.1
GCA_000013265.1.fasta.gz db.fasta 2947254 2948768 - 1515 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbP|locus_tag=ECOK1_RS11335|product="precolibactin peptidase ClbP"|protein_id=WP_002430641.1
GCA_000013265.1.fasta.gz db.fasta 2948761 2949483 - 723 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbQ|locus_tag=ECOK1_RS11330|product="colibactin biosynthesis thioesterase ClbQ"|protein_id=WP_000065646.1
GCA_000013265.1.fasta.gz db.fasta 2949518 2950030 - 513 00 100.00 100.00 ENA|CP000243|CP000243.1 Escherichia coli UTI89, complete genome. clbS|locus_tag=ECOK1_RS11325|product="colibactin self-protection protein ClbS"|protein_id=WP_000290498.1
kbo isn’t massively better for this task than blast but I believe the command-line syntax is somewhat easier to memorize. And it’s interesting that we can extract local alignments from pure k-mer matching by adding the k-bounded matching statistics.
My internal roadmap thinks of this as the main use case for the eventual browser version, which could support things like bundling databases with the executable to distribute analyses you need to run often.
Reference-based alignment
Next, we have the case of generating a reference-based alignment of two bacterial genome assemblies. For me, this was the original motivation to write kbo, as the existing tools are either somewhat slow (snippy) or require some megabytes of temporary disk space per query (snippy and ska2). Both factors scale poorly when running reference-based alignment for tens of thousands of genomes, although it’s still possible with the exisintg tools.
kbo can handle this task very easily, and takes a few seconds to run the alignment with no indexing step or temporary disk space required.
Setup
With the genomes downloaded, run
kbo map -r GCA_000013265.1.fasta.gz GCA_000333215.1.fasta.gz > alignment.fasta
The file alignment.fasta
will contain an alignment of GCA_000333215 against
GCA_000013265. If you need the nucleotide sequence of the reference in the
file, you need to add it to the file first in the same format that kbo will
output
echo ">GCA_000013265.1.fasta.gz" > alignment.fasta
gunzip -c GCA_000013265.1.fasta.gz | grep -v ">" | tr -d '\n' | sed 's/$/\n/g' >> alignment.fasta
kbo map -r GCA_000013265.1.fasta.gz GCA_000333215.1.fasta.gz > alignment.fasta
This will be added as an option to the command-line interface and the browser version in the future.
The main use case for kbo map
is to generate reference-based alignments of
large numbers of queries to build a phylogeny since kbo only takes ~a second per
genome comparison and uses no disk space. You can use the file to extract
SNPs but some quirks in the algorithm mean that the bases are not always called
correctly, so ska or snippy should be preferred if this is important to you (and
compare different approaches first).
TODO list
- Finish the browser version (more cumbersome than it seems).
- Write up the algorithmic parts and put it out as a pre-print.
If you want to contribute code, documentation, or something else feel free to do so in the GitHub repos:
Reading
Thanks to Jarno Alanko and Simon Puglisi from the University of Helsinki for introducing me to k-bounded matching statistics and especially Jarno for writing the sbwt Rust crate that I used within kbo.
Some papers if you are interested in the internals: