AXELIOS 1 Core Library Prep Kit

RUO For Research Use Only. Not for use in diagnostic procedures.

Library prep reagents for both DNA and cDNA (from RNA), as well as mechanical and enzymatic fragmentation inputs

The AXELIOS 1 DNA Library Prep Kits serve as the foundation for the entire workflow, accommodating diverse sample inputs, including both DNA and cDNA derived from RNA. Designed for versatility, these kits support both mechanical and enzymatic fragmentation methods to suit your specific experimental needs. By integrating proven KAPA technology, this kit delivers exceptional molecule conversion and recovery rates, ensuring that high-quality, representative libraries are generated at the very first step to provide the best possible input for downstream synthesis.1

Benefits at a glance

Benefits at a glance

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Overview

Ordering information

Product specifications

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Product specifications

Sample Type

Method

Sequencing readout

Target input range

Human genomic DNA

 

 WGS

 

Duplex

25-500 ng

Cell-free DNA

Duplex

2-10 ng

FFPE DNA

Duplex

100-300 ng 

(dependent on quality)

Human genomic DNA

Rapid WGS

Duplex

2000 ng

RNA

WTS

Simplex

25-150 ng

AXELIOS 1 Core Library Kit contents (24 reactions)

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AXELIOS 1 Core Library Kit contents (24 reactions)

Cap or plate colour

Component name

Red

AXELIOS 1 FragTail ReadyMix

Violet

AXELIOS 1 ERAT Enzyme Mix

Violet

AXELIOS 1 ERAT Buffer

Yellow

AXELIOS 1 Ligation Enzyme

Yellow

AXELIOS 1 Ligation Buffer

Orange

AXELIOS 1 Ligation Digest

Kits must be stored at -15°C to -20°C.
Kit box dimensions (width x length x height): 50mm x 75mm x 55mm
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For Research Use Only. Not for use in diagnostic procedures. AXELIOS is a trademark of Roche.

References

  1. F. Hoffmann-La Roche Ltd. Data on file.
  2. Chen C, et al. Single-Cell Whole Genome Analyses by Linear Amplification via Transposon Insertion (LIANTI). Science. 2017; 356(6334): 189–194.
  3. Jia H, et al. Chasing Sequencing Perfection: Marching Toward Higher Accuracy and Lower Costs. Genomics, Proteomics & Bioinformatics. 2024; 22(2): qzae024.