Whole genome resequencing analysis is a powerful next-generation sequencing approach that maps sequencing reads from an individual organism onto a reference genome to comprehensively detect SNPs, indels, copy number variations, and structural variants across the entire genome. This technology has become indispensable in agricultural breeding, disease research, population genetics, and evolutionary biology. This article provides a detailed technical overview of whole genome resequencing workflows, sample requirements, analytical items, and practical applications.
Technical Overview
Whole genome resequencing (WGR) refers to the complete sequencing of the genome of an individual organism belonging to a species for which a high-quality reference genome already exists. Unlike de novo genome assembly, resequencing does not require assembling reads from scratch; instead, short sequencing reads are aligned back to the reference genome, and differences between the individual and the reference are systematically identified as genetic variants.
The technique typically employs second-generation sequencing platforms such as the Illumina NovaSeq series, generating paired-end reads of 150 base pairs (PE150). Depending on the research objective, sequencing depth generally ranges from 10x to 30x coverage for population-level studies, while human clinical research and precision variant detection may require 30x or higher depth. For large plant genomes, simplified strategies or lower depth combined with imputation may be applied to control costs while maintaining statistical power.
Because resequencing captures genome-wide variation in a single experiment, it delivers an unbiased and comprehensive variant catalogue that supports downstream analyses including genome-wide association studies (GWAS), population genetic structure analysis, selective sweep mapping, and molecular breeding design.
Testing Samples
Animal Tissue Samples
Suitable animal sample types include whole blood collected with EDTA anticoagulant tubes, ear notches, muscle tissue, liver, spleen, and tail tips. Samples should be fresh or rapidly frozen in liquid nitrogen and stored at -80°C to prevent DNA degradation. A minimum of 200 mg tissue or 50 µL blood per individual is generally recommended for genomic DNA extraction.
Plant Tissue Samples
Fresh young leaves are the preferred plant material because they contain high-quality DNA with reduced secondary metabolite interference. Samples should be collected from healthy, actively growing tissue, immediately frozen in liquid nitrogen, and shipped on dry ice. Approximately 1–5 g of fresh leaf tissue per individual is recommended, and field samples should be protected from repeated freeze-thaw cycles.
Purified Genomic DNA Samples
Directly submitted genomic DNA should meet the following quality criteria:
- Total DNA quantity: at least 1 µg per sample, with 3 µg preferred for PCR-free library preparation
- Concentration: no less than 20 ng/µL as measured by fluorometric quantification
- Purity: OD260/280 ratio between 1.8 and 2.0, OD260/230 ratio above 1.8
- Integrity: main band intact on agarose gel electrophoresis, with no visible degradation or smearing
- Free from contamination by proteins, phenol, polysaccharides, or pigments
Microbial and Special Samples
Fungal mycelium, bacterial pellets, and mixed environmental DNA can also be analyzed when a suitable reference genome is available. Formalin-fixed or heavily degraded samples are generally unsuitable for standard resequencing and may require specialized protocols.
Testing Items
Whole genome resequencing analysis covers a complete chain of data generation and bioinformatics interpretation, delivering the following core deliverables:
- Single nucleotide polymorphism (SNP) detection, filtering, and genome-wide distribution characterization
- Insertion and deletion (InDel) identification and length distribution statistics
- Copy number variation (CNV) detection based on read depth analysis
- Structural variation (SV) detection, including deletions, duplications, inversions, and translocations
- Transition/transversion ratio analysis, heterozygosity estimation, and variant density profiling
- Functional annotation of variants against gene models and public databases
- Linkage disequilibrium (LD) decay analysis and haplotype block construction
- Genome-wide association study (GWAS) mapping of complex traits using GLM, MLM, or FarmCPU models
- Population genetics analysis, including nucleotide diversity (π), FST differentiation, phylogenetic tree construction, principal component analysis (PCA), and population structure inference
- Selective sweep analysis using π ratio, FST, Tajima's D, and composite likelihood methods to identify genomic regions under selection
- Candidate gene identification and pathway enrichment analysis for target traits
Testing Methods
Library Preparation and Sequencing
Qualified genomic DNA is fragmented by ultrasonication to approximately 350 bp target insert size. End repair, A-tailing, adapter ligation, and polymerase chain reaction amplification (or PCR-free workflow for high-input samples) are performed to construct sequencing libraries. Library quality is verified using fluorometric quantification, qPCR, and fragment size distribution analysis. Sequencing is then conducted on the Illumina NovaSeq platform with PE150 strategy, generating raw data in FASTQ format.
Bioinformatics Analysis Pipeline
The standard computational workflow proceeds through the following steps:
- Raw data quality evaluation using per-base quality profiles, GC content, adapter contamination, and duplication rate statistics
- Data filtering to remove adapters, low-quality reads, and reads with excessive ambiguous bases
- Read alignment to the reference genome using BWA-MEM, generating BAM format files
- Alignment processing including duplicate marking, local realignment, and base quality score recalibration
- Variant calling using GATK HaplotypeCaller or BCFtools to produce raw VCF files
- Hard filtering or variant quality score recalibration to retain high-confidence SNPs and InDels
- Variant annotation using tools such as ANNOVAR, SnpEff, or Ensembl VEP against gene function databases
- Advanced analyses including population structure, GWAS, selective sweep, and candidate gene screening according to project design
All bioinformatics procedures follow reproducible, documented pipelines, and sequencing data quality is monitored at every stage to ensure reliable and publication-ready results.
Applications
Whole genome resequencing supports a broad spectrum of research and breeding applications:
- Molecular breeding: development of high-density molecular markers, genomic selection, and marker-assisted selection in crops and livestock
- Gene mining: identification of causal genes and causal variants controlling important agronomic traits, disease resistance, and quality traits
- Population genetics: characterization of genetic diversity, domestication history, and adaptive evolution in natural and breeding populations
- Medical research: discovery of disease-associated germline variants, rare disease mutation screening, and pharmacogenomic studies
- Conservation biology: assessment of genetic health, inbreeding levels, and effective population size in endangered species
- Germplasm resource evaluation: classification of germplasm accessions and construction of core collections based on genome-wide variation
- Microbial research: strain-level identification, virulence factor screening, and comparative genomic analysis of bacterial and fungal isolates
FAQ
What sequencing depth is recommended for whole genome resequencing?
For most plant and animal population studies, 10x depth per individual is sufficient for reliable SNP calling. For studies requiring accurate genotype calling of InDels and structural variants, 20x to 30x depth is recommended. Human clinical-grade analysis typically requires at least 30x depth to ensure sensitivity and accuracy.
What is the difference between resequencing and de novo sequencing?
Resequencing relies on an existing high-quality reference genome to which reads are aligned for variant discovery, making it faster and more cost-effective. De novo sequencing assembles a genome without a reference and is necessary only when no suitable reference exists for the species.
What if my species lacks a reference genome?
When no reference genome is available, alternatives include de novo genome sequencing and assembly, resequencing against a closely related species reference with caution regarding mapping bias, or survey sequencing to estimate genome size, heterozygosity, and repeat content as a preliminary step.
How many individuals are needed for population analysis?
Population genetics and GWAS studies generally require at least 20 to 30 individuals per subgroup for meaningful structure analysis, while GWAS typically benefits from populations of several hundred individuals to achieve adequate statistical power for trait association.
What is the typical project turnaround time?
Standard whole genome resequencing projects, including library preparation, sequencing, and standard bioinformatics analysis, are typically completed within 45 to 60 working days, depending on sample number, sequencing depth, and the complexity of customized analyses.
Can archived or low-quality DNA samples be processed?
Moderately degraded DNA may be handled using optimized library preparation protocols after technical evaluation. Severely degraded or contaminated samples are discouraged, as they compromise mapping rates and variant calling accuracy.
What deliverables are provided upon project completion?
Deliverables include raw sequencing data, clean data with quality reports, alignment files, filtered variant call sets in VCF format, annotated variant tables, population analysis figures and tables, GWAS results, and a comprehensive analysis report with methodological documentation.