Structural Variant Detection
Genome-Wide Genotyping Targeted Genotyping Custom Genotyping Copy Number Variation Analysis High-Throughput Genotyping Preimplantation Genetic Screening Karyomapping SNP and SNV Genotyping Structural Variant Detection

Structural variant detection

NGS solutions for streamlined structural variant detection

What are structural variants?

Structural variations (SVs) are large alterations in the genome ≥ 50 base pairs (bp) in length. Consequently, SVs can alter genome structure, copy number, and the positions of DNA segments in the genome, potentially impacting gene function and regulation. The main types of structural variants include deletions, insertions, duplications, inversions, and translocations. These genomic alterations are often implicated in diseases and cancer.1 Illumina offers a highly simplified next-generation sequencing (NGS) solution that streamlines traditional library prep steps and provides comprehensive structural variant detection, visualization, and reporting.

Profile image of a male scientist examining a 25B flow cell cartridge before inserting into a NovaSeq X drawer.

The impact of structural variants in rare disease and oncology

Compared with short indels (insertions and deletions) and single-nucleotide variants (SNVs), SVs affect a larger number of bases, which can impact regulatory architecture, gene dosage, and phenotype. Abnormalities in chromosomal structure are an important source of genetic variability with direct impacts on phenotypic variation and disease susceptibility.2 NGS enables researchers to detect breakpoints where the DNA is disrupted and breakends that represent one side of the breakpoint. The data gained from this detection capability are often used to help describe complex genomic rearrangements relating to rare diseases and cancer.3

How structural variants are detected

Structural variants are detected across diverse sample types using NGS or microarray technologies, specialized SV callers, and established methods such as whole-genome sequencing (WGS), targeted sequencing, and chromosomal microarray analysis (CMA).4

Method Definition Key benefits Considerations for use
Whole-genome sequencing with proximity mapped read technology Combines WGS with proximity mapped read technology enabling comprehensive, accurate, and simplified variant detection for novel insights A simplified, on-flow cell library prep workflow that harnesses the ease and accuracy of short-read sequencing to resolve difficult-to-map regions of the genome, improve SV detection, and generate phased reads and variant calls The use of proximity information allows for accessible and accurate mapping of ambiguous genomic regions with a high degree of confidence compared to traditional WGS methods
Whole-genome sequencing (WGS) Provides comprehensive sequence coverage of the genome, including coding and noncoding regions The most comprehensive method; detects all variant types, including single nucleotide polymorphisms (SNPs), indels, copy number variation (CNVs), and balanced SVs Provides a high-resolution view of the entire genome but requires more computational demand compared to targeted panels. While WGS data analysis may initially intimidate new users, intuitive NGS data analysis tools alleviate this concern
Targeted sequencing Uses enrichment or amplicon-based capture to isolate specific sequences, focusing on regions of interest such as gene panels or exomes High sequencing depth and detection within specific regions of interests with fast turnaround and reduced data burden Limited to SV detection within predefined target regions with gaps for breakpoints in repetitive or noncoding regions
Chromosomal microarray analysis (CMA) Relies on hybridization of DNA samples to specific probes to detect the loss or gain of genetic material throughout the genome Well-established method with high sensitivity for detecting large-scale CNVs like duplications and deletions Unable to detect small indels, novel SVs, and balanced rearrangements (inversions and translocations), and are primarily used for analysis of known genomic regions

Illumina solutions for structural variant detection

Our high-throughput solutions support reliable structural variant detection, from library preparation to sequencing, data analysis, and interpretation. Proximity mapped read technology for SV detection combines enhanced mapping to resolve challenging variants and genomic regions with proven, scalable sequencing chemistry. Together, these capabilities help streamline SV analysis and interpretation with efficient, flexible solutions for diverse research studies, including genetic disease, oncology, multiomics, infectious disease, and population genomics.

Discover proximity mapped read technology
Thumbnail

Proximity mapped read technology for SV detection

Explore how proximity mapped reads technology maintains the link between the original long DNA template and short sequencing reads to enable enhanced detection of structural variants.

Structural variant detection workflow

1
Prep

TruPath Genome

TruPath Genome provides the simplest workflow to generating a comprehensive human genome for resolving difficult-to-map regions, enhanced structural variant detection, and ultralong phasing.

2
Sequence

NovaSeq X Series

NovaSeq X Series production-scale sequencing systems deliver a comprehensive, high-quality genome.

3
Analyze

DRAGEN Germline

DRAGEN Germline is an accurate and efficient end-to-end (FASTQ to VCF) secondary analysis solution that improves the mapping of Illumina reads in difficult-to-map regions for whole genome, whole exome, and targeted panel NGS data.

Streamlined SV detection: The DRAGEN pipeline advantage

Traditional single-reference alignments can leave variants in complex or highly polymorphic regions of the genome undiscovered. DRAGEN multigenome aligns to multiple references, and when paired with scalable Illumina NGS systems, DRAGEN multigenome mapping improves resolution of difficult-to-map regions and increases the number of variants detected.5 Discover the latest DRAGEN secondary analysis advancements, from enhanced SV calling accuracy to streamlined, pushbutton analysis for oncology research.

View DRAGEN secondary analysis webinar
Explore DRAGEN secondary analysis

Featured resources

Cancer whole-genome sequencing

Cancer WGS solutions, from library prep, sequencing, and data analysis, to help researchers detect SVs, chromosomal changes, somatic variants, and more.

Population genomics

Sequencing and informatics solutions to expand access to NGS technologies, generate large-scale genomic data sets, and drive innovation in health care. 

NovaSeq X Series benchmarking

A comparison of the Illumina NovaSeq X Series against the Ultima Genomics UG 100 platform for whole-genome sequencing.

Structural variant FAQ

All copy number variants are structural variants, but the structural variant family includes more than just changes in copy number. Deletions, insertions, and duplications are examples of copy number variants and represent a class of unbalanced structural variants as there is a resulting net gain or loss of genetic material. Balanced structural variants, such as inversions and translocations, do not change the total amount of DNA.6

Learn more about copy number variant analysis.

Structural variants are defined by the way that they alter the DNA within the genome with a minimum size of ≥ 50 bp in length. SV types include the following: 

  1. Deletions: Deletions remove genomic DNA from the original reference genome, potentially disrupting regulatory elements or genes. 
  2. Insertions: Insertions add DNA into the genome, which can disrupt coding sequences or alter gene expression. 
  3. Duplications: Duplications result in an extra copy of the genomic region, which may increase gene dosage, lead to overexpression of genes, and contribute to disorders like developmental syndromes. 
  4. Inversions: Inversions flip a DNA segment within the genome and reverse its orientation, which may break genes at inversion points or disrupt gene regulation. 
  5. Translocations: Translocations move DNA from one chromosome to another. These movements often create fusion genes, disrupt regulatory regions, and are commonly associated with chromosomal disorders and cancer.1

Yes, Illumina NovaSeq X Sequencing Systems, proximity mapped read technology, and DRAGEN secondary analysis bioinformatics pipeline that uses graph-based alignment and callers excel at SV detection.

Learn more about proximity mapped read technology.

Explore our NovaSeq X Sequencing Systems and DRAGEN secondary analysis with SV detection capabilities.

Structural variant detection is considered difficult because SVs range widely in size and configuration, resulting in varying read depth requirements depending on the SV type. Furthermore, SV callers differ in their precision and sensitivity. This combined variability of SVs and SV callers makes it challenging for sequencing and computational methods to detect SVs, especially using standard read depth–based approaches.7

Discover proximity mapped read technology, which leverages on-flow cell library preparation and novel informatics for enhanced SV detection.

Learn about DRAGEN secondary analysis pipeline to streamline your SV detection analyses.

Short-read sequencing offers a flexible, reliable method for performing high-accuracy whole-genome sequencing, but has struggled with specific regions and variant types such as SVs. Long-read sequencing methods offer read continuity across larger, more complex genomic regions and can help resolve SVs, but tend to have laborious workflows with well-established accuracy challenges that lead to variable results.8–11

Proximity mapped read technology allows researchers to harness the ease and accuracy of short-read sequencing to improve SV detection and resolve other difficult-to-map regions of the genome.  

/ Results

Speak to a specialist

Talk to an expert to learn more about structural variant detection solutions.

References

  1. Collins RL, Talkowski ME. Diversity and consequences of structural variation in the human genome. Nat Rev Genet. 2025;26(7):443-462. doi:10.1038/s41576-024-00808-9 
  2. Pande S, Dawood M, Grochowski CM. Structural Variants: Mechanisms, Mapping, and Interpretation in Human Genetics. Genes (Basel). 2025;16(8):905. Published 2025 Jul 29. doi:10.3390/genes16080905 
  3. Meng X, Wang M, Luo M, Sun L, Yan Q, Liu Y. Systematic evaluation of multiple NGS platforms for structural variants detection. J Biol Chem. 2023;299(12):105436. doi:10.1016/j.jbc.2023.105436 
  4. Austin-Tse CA, Jobanputra V, Perry DL, et al. Best practices for the interpretation and reporting of clinical whole genome sequencing. NPJ Genom Med. 2022;7(1):27. Published 2022 Apr 8. doi:10.1038/s41525-022-00295-z 
  5. Behera S, Catreux S, Rossi M, et al. Comprehensive genome analysis and variant detection at scale using DRAGEN. Nat Biotechnol. 2025;43(7):1177-1191. doi:10.1038/s41587-024-02382-1 
  6. Du H, Lun MY, Gagarina L, et al. An integrated platform for concurrent structural and single-nucleotide variants improves copy-number detection and reveals pathogenic alleles in undiagnosed Mendelian families. Genome Med. Published online December 31, 2025. doi:10.1186/s13073-025-01593-8 
  7. Liu Z, Roberts R, Mercer TR, Xu J, Sedlazeck FJ, Tong W. Towards accurate and reliable resolution of structural variants for clinical diagnosis. Genome Biol. 2022;23(1):68. Published 2022 Mar 3. doi:10.1186/s13059-022-02636-8 
  8. Pacific Biosciences. Preparing DNA for PacBio HiFi sequencing—Extraction and quality control. pacb.com/wpcontent/uploads/Technical-Note-Preparing-DNA-forPacBioHiFi-Sequencing-Extraction-and-Quality-Control.pdf.
Published 2022. Accessed December 8, 2025. 
  9. Pacific Biosciences. Preparing whole genome and metagenome libraries using SMRTbell prep kit 3.0. pacb.com/ wp-content/uploads/Procedure-checklist-Preparing-wholegenomeand-metagenome-libraries-using-SMRTbell-prepkit-3.0.pdf. Published 2022. Accessed December 8, 2025. 
  10. Oxford Nanopore Technologies. Ligation Sequencing Kit. store.nanoporetech.com/us/ligation-sequencing-kit-v14.html. Accessed December 8, 2025. 
  11. Pacific Biosciences. Low Yield Troubleshooting Guide. pacb.com/wp-content/uploads/Guide-Low-Yield-Troubleshooting.pdf. Published 2018. Accessed December 8, 2025.