When a bacterial genome assembly is worth it

data2biology assembles bacterial genomes de novo from Illumina, Oxford Nanopore and PacBio data, reaching — where the material allows — a closed chromosome with its plasmids, and then adds functional annotation and screening for resistance and virulence genes. A bacterial genome is usually a single circular chromosome of a few million base pairs, sometimes with additional plasmids. With suitable data it can now be closed into complete sequences rather than left as a set of contigs. Such a genome underpins the characterisation of a new isolate, a strain description in a publication, resistance gene analysis, epidemiological tracking or pangenome comparisons.

We work with short-read (Illumina), long-read (Oxford Nanopore, PacBio) and hybrid data. Closing a genome in practice requires long reads — Illumina data alone usually stops at a few dozen contigs because of repeats, primarily rRNA operons.

How the data flows

Below we describe how we typically run this type of analysis. It is not a fixed procedure: the choice of tools depends on the organism, library type, sequencing depth and research question, and standards in bioinformatics change quickly. We agree the methodology with you before the project starts and update it as tools and reference databases evolve.

Input

Illumina and/or ONT/PacBio reads (FASTQ) · species or genus information · optionally a reference genome of a close strain

Read quality control

Separate metrics for short and long reads, assessment of length and coverage distributions, and detection of foreign contamination.

FastQCMultiQCNanoPlotKraken2

Trimming and filtering

Removal of adapters and low-quality reads. For long reads we usually keep the longest and best subset rather than using everything.

fastpPorechopFiltlong

Assembly

The assembler depends on the data: hybrid for Illumina plus ONT, long-read for long reads alone, graph-based for Illumina only.

UnicyclerFlyeSPAdesRaven

Polishing

Correction of single-base errors and indels, particularly important for nanopore data where uncorrected indels break reading frames.

MedakaRaconPolypolishPilon

Assembly quality assessment

Contiguity statistics, completeness of single-copy gene sets, and estimates of contamination and genome closure.

QUASTBUSCOCheckM2

Structural and functional annotation

Prediction of protein-coding genes, rRNA, tRNA and other ncRNAs, with assignment of products, EC numbers and functional categories.

BaktaProkkaInterProScaneggNOG-mapper

Strain characterisation

Taxonomic identification, plasmid detection and screening for resistance and virulence genes — scope agreed according to project goals.

GTDB-TkAMRFinderPlusPlasmidFinderMOB-suite

Reporting and submission preparation

Result summary plus files in the format required by NCBI or ENA if the genome is to be deposited publicly.

NCBI table2asnMultiQC

Output

Genome and plasmid sequences · GFF3/GenBank annotation · proteins and genes · annotation and resistance tables · quality reports

A typical data flow for bacterial genome assembly. Steps 3 and 4 depend on the read types available.

What we pay attention to

Closure versus contig count

Not every project needs a closed genome. For strain typing or resistance gene screening, a draft assembly of a few dozen contigs is entirely sufficient. Closure matters when you care about plasmid structure, the genomic context of pathogenicity islands, or the copy number of rRNA operons. We say plainly when additional data is worthwhile and when it would be expense without informational gain.

Contamination in the culture

Before assembly we check the taxonomic composition of the reads. Contamination with another bacterium or host material can produce contigs that look like fascinating horizontal transfer but are in fact a culture artefact. We always show this check in the report, including when it comes back clean.

Annotation is prediction, not measurement

Functional assignments come from comparison to reference databases, which contain both experimental and predicted annotations. A substantial share of bacterial genes receives a "hypothetical protein" description, and that is an honest result rather than carelessness. Our tables mark the source and confidence of each assignment so a hit to a characterised protein can be told apart from a match to a domain family.

What you receive

File	Format	What it contains
assembly.fasta	FASTA	The genome sequence. In a closed assembly each record is a separate molecule. chromosome — the chromosome, with circularity noted in the header plasmid_1, plasmid_2, … — plasmids with length and coverage given
annotation.gff3	GFF3	Annotation in plain text, one feature per line, nine tab-separated columns. Loads into IGV, Artemis, JBrowse or Biopython. seqid, source — the contig and the tool that produced the entry type — CDS, gene, tRNA, rRNA, tmRNA, ncRNA start, end, strand — coordinates and orientation on the contig attributes — ID, locus_tag, gene, product, EC_number, cross-references to external databases
annotation.gbk	GenBank	The same annotation set with the sequence in a single file — the format read by Artemis, SnapGene and Geneious.
proteins.faa / genes.ffn	FASTA	Amino acid sequences of all predicted proteins and nucleotide sequences of the genes, ready for your own comparative analyses.
annotation_table.xlsx	XLSX	The whole annotation as a spreadsheet, one row per gene — the file people open most often. locus_tag, contig, start, end, strand, length in bp and aa gene, product — gene name and product description EC_number, KEGG KO, COG category, GO terms Annotation source and similarity measure to the reference record
strain_report.xlsx	XLSX	Strain characterisation, scope as agreed. Taxonomic assignment and distance to the nearest reference genome Resistance genes: name, antibiotic class, identity, coverage, location Virulence factors and detected plasmid replicons
quality/	HTML + TSV	The full set of quality reports. QUAST: contig count, total length, N50, GC content BUSCO and CheckM2: completeness and estimated contamination MultiQC: read statistics before and after filtering
methods.docx	DOCX	A methods section draft with tool versions, parameters and citations, ready to paste into a manuscript.

What we need from you

Raw FASTQ files — for ONT also the kit version and basecalling model used
The species or at least genus if known, and the origin of the isolate
Whether you expect a draft assembly or an attempt at closing the genome
The scope of strain characterisation: resistance, virulence, plasmids, pangenome
Whether the genome will go to NCBI or ENA — we will prepare compliant files

Quotation and how we work

We quote every project individually. The cost depends mainly on the number of samples, the availability of a reference genome, the number of comparisons and the scope of analyses you ask for.

You tell us what you want to find out and what data you have.
If anything needs clarifying we arrange a short call — free of charge and without obligation.
Within 3–5 working days you receive a quote with the scope of work, the list of result files and a delivery date.
You decide. The quote carries no obligation.

The scope and cost of projects like these vary widely enough that quoting a single representative figure would be misleading. If you need a ballpark before a formal quote, just ask — we can give a rough range straight away.

Any figures given are indicative and net of tax; VAT is added according to the applicable regulations. They do not constitute a binding offer. More about how we work in the FAQ.

De novo genome assembly — bacteria