Structural variants (SVs)—large insertions, deletions, translocations, and inversions—play a key role in tumor initiation, progression, and drug resistance

Yet they remain one of the most under-detected classes of somatic mutations due to the limitations of conventional sequencing:

• Short-read WGS often fails to capture large SVs due to limited molecule length
• False positives are common, requiring manual review and validation
• High molecular weight DNA or specialized platforms are often required—incompatible with FFPE and clinical workflows

As a result, many tumor samples are labeled “driver-negative”, even though structural drivers may be present but missed. That’s why we built Dovetail® LinkPrep assay paired with the Dovetail® Analysis Portal—a short-read-based, linked-read solution that empowers researchers to confidently detect structural variants alongside SNVs, InDels, and CNVs in a single assay.

Dovetail® LinkPrep Technology extends the capabilities of short-read sequencers by capturing long-range genomic information. When paired with the Dovetail® Analysis Portal, you gain a simplified, end-to-end workflow for somatic variant discovery—without specialized informatics or equipment.

The LinkPrep assay, WGS and RNA-seq were used to characterize structural variants in  a clinical ovarian sarcoma sample.

• The LinkPrep™ assay accurately identified three distinct translocations without any false positives, supported by robust read counts (minimum read support >500).
• These SVs involve several oncogenes known to be linked to ovarian cancer.
• WGS and RNA-seq methods fall short, detecting only two and one translocations, respectively, with minimal read support (less than 4 reads).
• These methods generated high numbers of false positives - 36 for RNA-seq and a staggering 402 for WGS - requiring extensive manual review and validation.

• Interactive Circos plot and variant class tables
• SV, CNV, and SNV/InDel visualization
• Variant annotation with cancer relevance
• Easily exportable for downstream use