Bacterial Whole-Genome Resequencing — Strain-Level Variant Discovery & Population Genomics

SNP, InDel, structural variant (SV), and copy number variation (CNV) detection by alignment-based resequencing on PacBio HiFi, Oxford Nanopore PromethION, and Illumina platforms — for antimicrobial resistance profiling, phylogenetic analysis, population genomics, and comparative genomics across bacterial species of any genomic complexity

Bacterial whole-genome resequencing (WGS resequencing) determines the genetic differences between a newly sequenced bacterial strain and a pre-existing reference genome of the same or closely related species. Unlike de novo sequencing, which builds a genome from scratch, resequencing maps sequencing reads to a reference genome and identifies all classes of genetic variation — from single nucleotide polymorphisms (SNPs) and small insertions/deletions (InDels) to large structural variants (SVs), copy number variations (CNVs), and gene presence-absence polymorphisms. This reference-based approach is the method of choice when a high-quality reference genome is available for the target species, offering the lowest per-genome cost for population-scale studies while delivering the highest sensitivity for variant detection.

At CD Genomics, we provide bacterial WGS resequencing across all major sequencing platforms — PacBio HiFi (Sequel II / Revio), Oxford Nanopore (PromethION R10.4.1), and Illumina NovaSeq — as well as hybrid strategies that combine platforms for optimal variant detection. Our bioinformatics pipelines are optimized for each platform's read characteristics and tailored to the specific variant types most relevant to your study: whether you need ultra-sensitive SNP detection for phylogenetic epidemiology, complete structural variant resolution for AMR mechanism discovery, or population-scale screening of thousands of strains for genome-wide association studies (GWAS).

Why Choose Our Bacterial WGS Resequencing Service

• Comprehensive Variant Detection Across All Scales — From SNPs and InDels (single-base resolution) to large SVs, CNVs, and gene presence-absence polymorphisms — long reads capture variants that short reads systematically miss in repetitive and mobile regions
• Platform-Optimized Pipelines — DeepVariant / Clair3 for PacBio HiFi SNP calling, NanoCaller / Clair3 for ONT, and GATK best practices for Illumina — with platform-specific calibration to minimize false positives
• AMR & Mobile Element Resolution — Long reads spanning entire resistance gene clusters, plasmid backbones, and mobile genetic elements enable accurate assignment of AMR determinants to chromosomal or plasmid locations, resolving linkage and genomic context
• Scalable From Single Isolates to Large Cohorts — Multiplexed barcoding and efficient bioinformatics pipelines support projects from a single clinical isolate to population-scale cohorts of 1,000+ strains with consistent data quality across batches
• Flexible Platform Matching — Our platform-agnostic team recommends the optimal sequencing strategy based on your variant targets, genome complexity, sample number, and budget — from low-cost Illumina screening for well-characterized pathogens to comprehensive HiFi-based SV resolution for complex genomes
• Publication-Ready Deliverables — Annotated VCF files with platform-specific quality filters, comprehensive variant reports with functional impact annotations, phylogenetic trees, and detailed methods documentation for manuscript submission

Introduction

Bacterial whole-genome resequencing is the process of sequencing the genome of a bacterial isolate and comparing the resulting reads to an existing reference genome of the same or a closely related species to identify the complete repertoire of genetic differences between the two. Unlike de novo sequencing — which aims to reconstruct the genome sequence itself — resequencing focuses on differences: the specific mutations, insertions, deletions, rearrangements, and gene content changes that distinguish one strain from another. This approach is central to modern bacterial genomics, underpinning applications from outbreak investigation and antimicrobial resistance surveillance to population biology and evolutionary studies.

The choice of sequencing platform fundamentally determines which classes of variation can be reliably detected. Short-read resequencing (Illumina) provides cost-effective, highly accurate detection of SNPs and small InDels, but systematically fails to resolve variation in repetitive regions, mobile genetic elements, and large structural rearrangements — precisely the regions that drive clinically and evolutionarily important bacterial phenotypes. Long-read resequencing on PacBio HiFi or Oxford Nanopore platforms overcomes these limitations: a single contiguous read spanning a complete IS element, prophage integration, or multi-gene resistance cassette allows the bioinformatics pipeline to unambiguously determine the presence, copy number, and genomic context of these elements, rather than collapsing or mis-mapping them.

At CD Genomics, we have delivered bacterial resequencing projects across hundreds of bacterial species and tens of thousands of isolates, supporting clients in public health, clinical microbiology, pharmaceutical development, and academic research. Our service is built around platform-agnostic project design: we select the optimal sequencing and analysis strategy for your specific research question, budget, and sample volume.

Applications of Bacterial Whole-Genome Resequencing

Clinical Microbiology & Public Health

• Outbreak investigation and source tracking through high-resolution core-genome SNP phylogeny and cgMLST — identifying transmission chains at single-nucleotide resolution
• Antimicrobial Resistance (AMR) surveillance: comprehensive profiling of acquired resistance genes, chromosomal mutations, and plasmid-mediated resistance mechanisms with full genomic context
• Pathogen evolution monitoring during chronic infections (e.g., cystic fibrosis, device-associated infections) — detecting within-host adaptation, resistance emergence, and population dynamics
• Vaccine-preventable disease surveillance (e.g., Streptococcus pneumoniae, Neisseria meningitidis) through serotype and antigen gene profiling

Antimicrobial Resistance Mechanism Discovery

• Long-read resolution of complex AMR gene loci — multiple tandem resistance gene copies, hybrid beta-lactamase alleles, and IS element-mediated resistance gene mobilization
• Plasmid epidemiology: complete plasmid reconstruction (circular, closed) for tracking resistance plasmid dissemination across bacterial populations and geographic regions
• Identification of novel resistance determinants through comprehensive pangenome-wide association studies (pan-GWAS) that integrate gene presence-absence with phenotypic data

Population & Evolutionary Genomics

• Large-scale population genomics: genome-wide SNP discovery across hundreds to thousands of strains for phylogenetic reconstruction, phylogeography, and temporal evolution studies
• Pan-genome analysis: characterization of core and accessory genomes across populations, identification of lineage-specific genes, and detection of horizontal gene transfer events
• Mutation rate estimation and molecular clock calibration using time-structured sequence data from longitudinal collections

Industrial & Food Microbiology

• Quality control and stability monitoring: genomic comparison of production strains across fermentation batches to detect unintended genetic drift or contamination
• Strain improvement tracking: monitoring the accumulation of beneficial mutations during adaptive laboratory evolution (ALE) experiments
• Foodborne pathogen surveillance: WGS-based subtyping of Salmonella, Listeria, E. coli, and Campylobacter isolates for regulatory compliance and traceback investigations

Bioinformatics Analysis — Variant Detection & Interpretation

Our bioinformatics pipeline supports comprehensive variant detection across all sequencing platforms, with analysis features organized across two service tiers.

Sample Requirements

Case Study: Long-Read Resolves Carbapenemase Alleles Missed by Short-Read Sequencing in Klebsiella pneumoniae

Sierra R, Roch M, Moraz M, Prados J, Vuilleumier N, Emonet S, Andrey DO. Contributions of Long-Read Sequencing for the Detection of Antimicrobial Resistance. Pathogens. 2024;13(9):730. doi:10.3390/pathogens13090730.

1. Background

Antimicrobial resistance (AMR) is one of the most pressing global health threats, and accurate detection of resistance genes is critical for effective patient management, infection control, and epidemiological surveillance. Short-read whole-genome sequencing (WGS) has become the standard tool for AMR gene surveillance, but its limitations in resolving repetitive regions, multi-gene duplications, and complex genomic contexts can lead to incorrect resistance gene allele identification — with potentially serious clinical consequences.

In this study, Sierra et al. performed a head-to-head comparison of Illumina short-read and Oxford Nanopore long-read sequencing for AMR gene detection in a Klebsiella pneumoniae clinical isolate, with a focus on the blaNDM carbapenemase gene family — a group of genes encoding metallo-beta-lactamases that confer resistance to last-resort carbapenem antibiotics.

2. Methods

A K. pneumoniae clinical isolate (VS17) was sequenced on both Illumina (short-read, paired-end) and Oxford Nanopore (ONT R9.4.1, MinION) platforms. Short-read assemblies were generated with SPAdes; long-read assemblies were generated with Flye followed by Medaka polishing and Illumina-based Pilon polishing. AMR gene content was analyzed using ResFinder and CARD RGI. The blaNDM alleles identified by each platform were validated by Sanger sequencing of PCR products spanning the resistance gene locus and by conjugation assays to confirm plasmid transfer and phenotypic resistance profiles.

3. Results

Figure 2. Comparison of short-read and long-read sequencing for AMR gene detection in Klebsiella pneumoniae. Short-read assembly incorrectly identified a single blaNDM-4 allele, while long-read assembly correctly resolved two distinct alleles (blaNDM-1 and blaNDM-5) located on separate plasmids — confirmed by Sanger sequencing and conjugation assays. Adapted from Sierra et al. (2024), Pathogens, CC BY 4.0.

Key Findings

• Short-read misidentification: Illumina-only assembly identified a single blaNDM-4 allele — a false consensus artifact produced by the assembler collapsing two distinct alleles into a chimeric sequence.
• Long-read correct resolution: ONT long-read assembly correctly resolved two distinct carbapenemase alleles — blaNDM-1 and blaNDM-5 — located on separate plasmid backbones, each confirmed by Sanger sequencing.
• Clinical significance: Accurate discrimination between NDM variants is clinically critical because different NDM alleles confer different resistance profiles and have different epidemiological implications. NDM-1 is the most globally prevalent variant, while NDM-5 has increased carbapenemase activity.
• Plasmid context: Long-read sequencing enabled complete circularization of both resistance plasmids, revealing the full genetic environment of each blaNDM allele — including IS element insertions, transposon structures, and conjugation machinery — providing insights into the mobilization and transfer potential of each resistance determinant.

4. Conclusions

This study provides direct evidence that short-read sequencing alone can produce clinically misleading AMR gene profiles when multiple resistance gene alleles or gene duplications are present. Long-read sequencing resolves these complex loci unambiguously, delivering accurate allele identification and full genomic context. The case underscores the importance of incorporating long-read or hybrid sequencing into clinical AMR surveillance workflows, particularly when accurate resistance gene allele discrimination is required for patient management, outbreak investigation, or molecular epidemiology.

Demo

Deliverable Examples for Bacterial WGS Resequencing Projects

1. Variant call file (VCF) with high-confidence SNP, InDel, and SV calls — annotated with functional impact predictions (SnpEff) and platform-specific quality filters (QUAL, GQ, DP).

2. Genome-wide variant landscape visualization — Circos plot showing variant density, SV breakpoints, AMR gene locations, and GC content across the reference genome, with comparative tracks for multiple strains.

3. Phylogenetic tree (Newick format) constructed from core-genome SNP alignments, with bootstrap support values, metadata integration (source, date, phenotype), and publication-ready figure files.

4. Comprehensive project report PDF documenting sample processing, sequencing QC metrics, alignment statistics, variant detection results, annotated gene tables, and detailed methods for manuscript inclusion.

Figure 3. Representative deliverable formats for bacterial WGS resequencing projects. Left: genome-wide variant density and SV Circos plot. Center: core-genome SNP phylogeny with metadata. Right: AMR gene profile and variant annotation summary. AI-generated representative data.