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NEXTFLEX® Bisulfite-Seq Barcodes

Considerably reduce your per-sample sequencing cost by barcoded multiplexing

Increase your sequencing scale by pooling samples on a single flow cell

Compatible with bisulfite-sequencing on the Illumina® sequencing platforms

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  • Product description
  • Kit Contents
  • Citations

Pool Multiple Library Preparations in a Single Flow Cell Lane

The NEXTFLEX® Bisulfite-Seq Barcodes are designed to be used with the NEXTFLEX® Bisulfite-Seq Kit. Unlike other NEXTFLEX® Barcodes, the NEXTFLEX® Bisulfite-Seq Barcodes are methylated. The NEXTFLEX® Bisulfite-Seq Barcodes can be used to provide flexibility and high-throughput capabilities in sequencing applications. They significantly increase scale while reducing costs by allowing the user to pool multiple library preparations in a single flow cell lane. The NEXTFLEX® Bisulfite-Seq Barcodes kits accomplish this by using an indexed adapter with a 6 nt unique sequence. This allows for proper differentiation between samples, preventing poor reads from single base errors introduced during PCR.


These methylated adapters can be used with single, paired-end and multiplex reads.


Features

  • Up to 24 methylated adapters for multiplexing Illumina® RRBS and WGBS libraries are available

  • Considerably reduce your per-sample sequencing cost by barcoded multiplexing

  • Increase your sequencing scale by pooling samples on a single flow cell

  • Compatible with bisulfite-sequencing on the Illumina® sequencing platforms


Kit Specs


Cat #Name Quantity
NOVA-511911NEXTFLEX® Bisulfite-Seq Barcodes-648 RXNS
NOVA-511912NEXTFLEX® Bisulfite-Seq Barcodes-1296 RXNS
NOVA-511913NEXTFLEX® Bisulfite-Seq Barcodes-24192 RXNS


KIT CONTENTS


  • NEXTFLEX® Bisulfite-Seq Adapters (25 µM)

  • NEXTFLEX® Primer Mix (12.5 µM)


Selected Publications Citing the Use of the NEXTFLEX® Bisulfite-Seq Barcodes:

Agarwal, P., et al. (2015) CGGBP1 mitigates cytosine methylation at repetitive DNA sequences. BMC Genomics, 16:390. doi:10.1186/s12864-015-1593-2.

Berg, A., et al. (2015) Obesity is Associated With DNA Methylation in Population-Based Adolescents. Circulation. Poster: 131:AP260, Session Title: Obesity.

Bewick, A., et. al. (2016) On the origin and evolutionary consequences of gene body DNA methylation. PNAS. 113: 9111 – 9116.

Ramesh, V., et. al. (2016) Loss of Uhrf1 in neural stem cells leads to activation of retroviral elements and delayed neurodegeneration. Genes & Development. 30: 2199 – 2212.

Satgé, C. et. al. (2016) Reprogramming of DNA methylation is critical for nodule development in Medicago truncatula. Nature Plants 2, 16166. doi:10.1038/nplants.2016.166.

Urich, M. A., Nery, J. R., Lister, R., Schmitz, R. J. and Ecker, J. R. (2015) MethylC-seq library preparation for base-resolution whole-genome bisulfite sequencing. Nature Protocols 10, 475–483. doi:10.1038/nprot.2014.114.

van der Graafa, A., et al.  (2015) Rate, spectrum, and evolutionary dynamics of spontaneous epimutations. PNAS. 112:21. pg. 6676–6681. doi: 10.1073/pnas.1424254112.

Ye, R., et al. (2015) A Dicer-Independent Route for Biogenesis of siRNAs that Direct DNA Methylation in Arabidopsis. Molecular Cell. doi:10.1016/j.molcel.2015.11.015.


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