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Product summary

  • Technology NGS
  • Application Haematology
  • Areas of interest CLL
  • Panel Size 142 kb
  • Gene Targets 16
  • DNA input recommended >500ng high-quality DNA
  • Gene list ATM, BCL2, BIRC3, BRAF, BTK, CXCR4, KRAS, MYB, MYD88, NOTCH1, NRAS, PLCG2, SAMHD1, SF3B1, TP53 and XPO1
  • CNV list 17p (covering TP53), 11q (covering ATM), 13q (covering RB1/DLEU2/DLEU7), 6q (6q23.2-6q23.3 covering MYB) and Trisomy 12
  • Sample tracking SRY + 24 SNP profiling panel
  • LOH detection size CN-LOH ≥10 Mb
  • SureSeq Reference Human DNA DNA: SureSeq Reference Human Female DNA, SureSeq Reference Male DNA
  • Product Code 780104-24
  • Regulatory Status For research use only; not for diagnostic procedures.



Chronic lymphocytic leukaemia (CLL) is the most common type of leukaemia in adults. A wide variety of chromosomal abnormalities are associated with CLL, ranging from single nucleotide variants (SNVs) and insertions/deletions (indels) up to large copy number variations (CNVs), including trisomies.

The SureSeq™ CLL + CNV V3 Panel has been designed in collaboration with recognised cancer experts to detect 16 key genes and 5 chromosomal regions implicated in CLL progression (Table 1). The SureSeq CLL + CNV V3 Panel alleviates the burden of running multiple assays and streamlines your CLL research to deliver a comprehensive genomic profile for each CLL sample using a single workflow.

  • Gain a more complete understanding of CLL progression: Accurately detect low-frequency SNVs and indels in 16 key CLL-implicated genes, including TP53, BTK, PLCG2, BCL2 and NRAS
  • Enhanced CNV detection ranging from loss of single exons to full chromosome arms and trisomy 12: Profile your samples for CNVs in the 5 most commonly aberrant regions in CLL
  • Time savings: Replace multiple assays with a single NGS panel, increasing throughput and reducing turnaround time
  • Complimentary data analysis software: Analyse your data with Interpret NGS Analysis Software, OGT’s powerful and easy-to-use analysis solution for accurate identification of all variants and CNVs

Gene targets

Select a gene to view exon coverage examples:

* Exon examples not yet available

Want to customise these gene targets?

We have a regularly updated, expert-curated library of pre-optimised cancer panel content for you to select from. Simply mix and match the gene, exonic or intronic content you need to create a CLL next generation sequencing cancer panel that meets your exact requirements.


Contains the latest evidence-based content

Investigating both chromosomal aberrations and SNVs/indels is imperative to advance research into CLL progression and treatment. Cytogenetic abnormalities are present in more than 80% of patients with previously untreated CLL, the most frequent being del(13q), del(11q), del(17p), del(6q) and trisomy 121. Some of these CNVs cover important tumour suppressors, such as del(17p) resulting in the loss of the TP53 gene. More recently, other genes have also been found to be mutated in CLL, including NOTCH1, SF3B1, MYD88 and BIRC3, adding to the genomic complexity of this leukaemia2. Together with leading cancer experts, we continue to monitor the latest CLL research, which is reflected in the latest V3 panel design through enhanced gene coverage for BTK and PLCG2, plus the inclusion of baits for BCL2 and NRAS genes.

Due to this genetic heterogeneity, current analysis strategies for CLL require multiple methods to obtain a comprehensive genetic picture, often using microarray or fluorescence in situ hybridisation (FISH) to detect structural abnormalities in combination with NGS for somatic variants. With OGT’s SureSeq CLL + CNV V3 Panel, you can now obtain a more complete understanding of the genetic makeup of CLL progression in each sample using a single assay.

Superior coverage uniformity allowing reliable variant and somatic CNV detection

OGT’s expert bait design delivers outstanding uniformity and depth of coverage, capable of detecting low frequency SNVs and indels down to 1–2.5% variant allele frequency (VAF) in 16 genes (Figure 1), plus the SRY gene and 24 SNPs to allow for easy sample tracking3. Reference DNA is also included to provide a baseline for CNV calling, reducing spurious calls due to run-to-run variability.

The SureSeq CLL + CNV V3 Panel covers the 5 most common CNVs in CLL. Compared to array data, often considered the gold standard for CNV detection, the events reported with the SureSeq CLL + CNV V3 Panel were 100% concordant, even in genomic regions containing multiple aberrations (Figures 2 - 3). More so, facilitated by OGT’s excellent bait design, loss-of-heterozygosity (LOH) can be identified. With a CNV size detection range from single exon to whole gene, up to complete loss of a chromosomal arm and whole chromosome gains (trisomy 12), your data provides a more comprehensive genetic picture for each sample from a single assay.

Complimentary analysis software

Interpret NGS Analysis Software is OGT’s powerful and easy-to-use data analysis solution, facilitating analysis and visualisation of a wide range of somatic variants and structural aberrations. Designed to work seamlessly with all SureSeq panels, Interpret perfectly complements the SureSeq CLL + CNV V3 Panel, delivering fast and accurate detection of all SNVs, indels, LOH and CNVs covered by the panel. Following detection, all events can be readily visualised in the user-friendly variant browser, for an effortless translation of all your CLL data into meaningful results (Figure 4).

Bespoke panel content

Does the SureSeq CLL + CNV V3 Panel not meet your exact requirements? With OGT, you never have to sequence genes you’re not interested in and can always modify each panel to what’s most relevant for your research. Choose from our regularly updated, expert-curated library of pre-optimised cancer content to create your ideal custom CLL Panel.

SureSeq CLL + CNV V3 NGS Panel workflow

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Content selection

Sure Seq Bar 1
  • SureSeq CLL + CNV V3 NGS Panel
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Sure Seq Bar 3
  • Illumina sequencers


  1. Döhner et al., N Engl J Med 2000;343:1910-1916
  2. Rossi et al., Blood 2013;121:1403-1412
  3. Pengelly et al., Genome Med 2013;5:89

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