NEXTflex™ ChIP-Seq Barcodes

Illumina-compatible ChIP-Seq Barcodes for library prep

Catalog# Product Name Quantity US List Price
514120 NEXTflex™ ChIP-Seq Barcodes - 6 48 rxns $233 Buy Now
514121 NEXTflex™ ChIP-Seq Barcodes - 12 96 rxns $460 Buy Now
514122 NEXTflex™ ChIP-Seq Barcodes - 24 192 rxns $910 Buy Now
514123 NEXTflex™ ChIP-Seq Barcodes - 48 384 rxns $1,791 Buy Now
514124 NEXTflex-96™ ChIP-Seq Barcodes - 96 768 rxns $3,463 Buy Now

 

  • 6 nt index contained within adapter sequence
  • Up to 48 multiplexed samples (up to 384 reactions per kit)
  • Considerably reduce your per-sample sequencing cost by barcoded multiplexing
  • Increase your sequencing scale by pooling 100s of samples on a single flow cell
  • Compatible with Illumina next-generation sequencing platforms

 

The NEXTflex™ ChIP-Seq Barcodes are adapters containing indexed sequences that offer an improved multiplexing workflow and flexible setup. These barcodes are available in sets of 6, 12, 24, and 48 unique adapters. The ability to pool samples in an efficient way significantly decreases hands-on time while providing robust data quality. These barcodes can be used with single, paired-end, and multiplex reads. These adapters are compatible with the NEXTflex ChIP-Seq and the NEXTflex Rapid DNA-Seq workflows. 


Do you want to index 96 samples? We also offer the NEXTflex-96™ ChIP-Seq Barcode Kits, which contain 96 - 8 nt index barcodes. 

For larger volume requirements, customized and bulk packaging is available. Please contact nextgen@biooscientific.com for further information. 


Avoiding registration failure with low level multiplexing

Registration failure could occur if the color balance was not maintained between the red and green lasers (used to sequence A/C bases and G/T bases, respectively). Read Bioo Scientific’s recent blog post, Tech Tips – Barcode Recommendations for Low Level Multiplexing, to learn how to avoid registration failure on an Illumina sequencer caused by lack sufficient index sequence diversity. 


Selected Publications that Reference Using the NEXTflex ChIP-Seq Barcodes:

Achour, M. et al. (2015) Neuronal Identity Genes Regulated by Super-Enhancers Are Preferentially Down-Regulated in the Striatum of Huntington's Disease Mice. Hum. Mol. Genet. ddv099v1-ddv099.

Auclair, G., et al. (2015) EHMT2 directs DNA methylation for efficient gene silencing in mouse embryos. Genome Res. 26: 192-202. doi: 10.1101/gr.198291.115.

Baker, C. L., et al. (2015) Multimer Formation Explains Allelic Suppression of PRDM9 Recombination Hotspots. PLOS Genetics. doi: 10.1371/journal.pgen.1005512.

Baker, C. L., et al. (2015) PRDM9 Drives Evolutionary Erosion of Hotspots in Mus musculus through Haplotype-Specific Initiation of Meiotic Recombination. PLOS Genetics. doi: 10.1371/journal.pgen.1004916.

Baker, C. L., et al. (2014) PRDM9 binding organizes hotspot nucleosomes and limits Holliday junction migration. Genome Res.    24(5):724-32.

Bjorn-Mortensen, K., et al. (2015) Direct DNA Extraction from Mycobacterium tuberculosis Frozen Stocks as a Reculture-Independent Approach to Whole-Genome Sequencing. J. Clin. Microbiol. 53:8 2716-2719. doi:10.1128/JCM.00662-15.

Bonocora, Joseph R, P. and Wade, T.  (2015) ChIP-Seq for Genome-Scale Analysis of Bacterial DNA-Binding Proteins. Bacterial Transcriptional Control, Methods in Molecular Biology 1276, 327-340. doi: 10.1007/978-1-4939-2392-2_20.

Boo, K., et al. (2015) Pontin functions as an essential coactivator for Oct4-dependent lincRNA expression in mouse embryonic stem cells. Nature Communications 6:6810. doi:10.1038/ncomms7810.

Bubier, J. et al. (2014) Identification of a QTL in Mus musculus for Alcohol Preference, Withdrawal, and Ap3m2 Expression Using Integrative Functional Genomics and Precision Genetics. Genetics 197(4): 1377-1393.

Chiu, W. T. et. al. (2014) Genome-wide view of TGFβ/Foxh1 regulation of the early mesendoderm program. Development. 141:4537-4547.  

Clop A, Bertoni A, Spain SL, Simpson MA, Pullabhatla V, et al. (2013) An In-Depth Characterization of the Major Psoriasis Susceptibility Locus Identifies Candidate Susceptibility Alleles within an HLA-C Enhancer Element. PLoS ONE 8(8): e71690. doi:10.1371/journal.pone.0071690 

Cvejic A, Haer-Wigman L, Stephens JC et al. (2013) SMIM1 underlies the Vel blood group and influences red blood cell traits. Nature Genetics. doi:10.1038/ng.2603.

Deng, X. et al. (2014) Molecular mechanisms of two-component system RhpRS regulating type III secretion system in Pseudomonas syringae. Nucl. Acids Res. 42 (18): 11472-11486 doi: 10.1093/nar/gku865

De Nardo, D, et. al. (2014) High-density lipoprotein mediates anti-inflammatory reprogramming of macrophages via the transcriptional regulator ATF3 Nature Immunology 15:152-60.

Dong, Q., Fang, M., Roychowdhury, S. and Bauer, C. E. (2015) Mapping the CgrA regulon of Rhodospirillum centenum reveals a hierarchal network controlling Gram-negative cyst development. BMC Genomics. 16:1066. doi:10.1186/s12864-015-2248-z.

Filleton, F., Chuffart, F., Nagarajan, M., Bottin-Duplus, H. and Yvert, G. (2015) The complex pattern of epigenomic variation between natural yeast strains at single-nucleosome resolution. Epigenetics Chromatin. 8:26. doi:  10.1186/s13072-015-0019-3.

Fischer, N., et al. (2014) Rapid metagenomic diagnostics for suspected outbreak of severe pneumonia [letter]. Emerg Infect Dis. doi: 10.3201/eid2006.131526.

Garrido, D., et al. (2015) Comparative transcriptomics reveals key differences in the response to milk oligosaccharides of infant gut-associated bifidobacteria. Scientific Reports. 5:13517. doi:10.1038/srep13517.

Golomb, B. L., Hirao, L. A., Dandekar, S. and Marco, M. L. (2016) Gene expression of Lactobacillus plantarum and the commensal microbiota in the ileum of healthy and early SIV-infected rhesus macaques. Scientific Reports 6:24723. doi:10.1038/srep24723.

Gosselin, D. et al. (2014) Environment Drives Selection and Function of Enhancers Controlling Tissue-Specific Macrophage Identities. Cell. 159:6, 1327–1340. doi:10.1016/j.cell.2014.11.023.

Gregor, A. et al. (2013) De Novo Mutations in the Genome Organizer CTCF Cause Intellectual Disability. AJHG. 93:1. 124–131.

Haycocks, J. R. J., et al. (2015) The Molecular Basis for Control of ETEC Enterotoxin Expression in Response to Environment and Host. PLOS Pathogens. doi: 10.1371/journal.ppat.1004605.

Jones, CJ. et. al. (2014) ChIP-Seq and RNA-Seq reveal an AmrZ-mediated mechanism for cyclic di-GMP synthesis and biofilm development by Pseudomonas aeruginosa. PLoS Pathog. e1003984.

Juntawong, P., Girke, T., Bazin, J. and Bailey-Serres, J. (2014) Translational dynamics revealed by genome-wide profiling of ribosome footprints in Arabidopsis. Proc. Natl. Acad. Sci. U.S.A. 111:1, E203-12.

Kieffer-Kwon, KR, et. al. (2013) Interactome maps of mouse gene regulatory domains reveal basic principles of transcriptional regulation. Cell 155:1507-20.

Kong, W., et al. (2015) ChIP-seq reveals the global regulator AlgR mediating cyclic di-GMP synthesis in Pseudomonas aeruginosa. Nucl. Acids Res. 43:17. 8268-8282, doi: 10.1093/nar/gkv747.

Le Billan, F., et al. (2015) Cistrome of the aldosterone-activated mineralocorticoid receptor in human renal cells. FASEB J. 29: 3977 - 3989.

Lelandais, G., Blugeon, C. and Merhej, J. (2016) ChIPseq in Yeast Species: From Chromatin Immunoprecipitation to High-Throughput Sequencing and Bioinformatics Data Analyses. Yeast Functional Genomics: Methods and Protocols, Methods in Molecular Biology, 1361. Pg 1-11. Springer Science+Business Media New York. Doi: 10.1007/978-1-4939-3079.

Li, Y., et al. (2015) The histone methyltransferase SDG8 mediates the epigenetic modification of light and carbon responsive genes in plants. Genome Biology. 16:79, doi:10.1186/s13059-015-0640-2.

Liang, H., et. al. (2014) Molecular mechanisms of master regulator VqsM mediating quorum-sensing and antibiotic resistance in Pseudomonas aeruginosa. Nucleic Acids Research. doi: 10.1093/nar/gku586.

Liang, X. et al. (2015) Transcription factor ISL1 is essential for pacemaker development and function. J Clin Invest. doi:10.1172/JCI68257.

Lam, M. T. Y., Cho, H., Lesch, H. P. et al. (2013) Rev-Erbs repress macrophage gene expression by inhibiting enhancer-directed transcription. Nature. doi:10.1038/nature12209.

Malysheva, V., Mendoza-Parra, M. A., Saleem, M.-A. M. and Gronemeyer, H. (2016) Reconstruction of gene regulatory networks reveals chromatin remodelers and key transcription factors in tumorigenesis. Genome Medicine. 8:57. doi: 10.1186/s13073-016-0310-3.

Menafra, R., et al. (2014) Genome-Wide Binding of MBD2 Reveals Strong Preference for Highly Methylated Loci. PLOS One. doi: 10.1371/journal.pone.0099603.

Mendoza-Parra, M.-A., et al. (2016) Antibody performance in ChIP-sequencing assays: From quality scores of public data sets to quantitative certification. F1000 Research. doi: 10.12688/f1000research.7637.1v1.

Meyer, M. et al. (2014) The RUNX2 Cistrome in Osteoblasts Characterization, Down-Regulation Following Differentiation, and Relationship to Gene Expression. The Journal of Biological Chemistry. 289, 16016-16031.  doi: 10.1074/jbc.M114.552216.

Otia, M., Kouwenhovena, E. N. and Zhoua, H. (2015) Genome-wide p63-regulated gene expression in differentiating epidermal keratinocytes. Genomics Data. 5, 159–163.

Parobek, C. M., Bailey, J. A., Hathaway, N. J., Socheat, D., Rogers, W. O. and Juliano, J. J. (2014) Differing Patterns of Selection and Geospatial Genetic Diversity within Two Leading Plasmodium vivax Candidate Vaccine Antigens. PLoS Neglected Tropical Diseases. doi: 1 0.1371/journal.pntd.0002796.

Paul, E., Zhuc, Z. I., Landsmanc, D., Morsea, R. H. (2014) Genome-wide association of Mediator and RNA Polymerase II in wild type and Mediator mutant yeast. Mol. Cell. Biol. doi:10.1128/MCB.00991-14.

Pfeiffer, A., Shia, H., Teppermana, J. M., Zhanga, Y. and Quaila, P. H. (2014) Combinatorial Complexity in a Transcriptionally Centered Signaling Hub in Arabidopsis. Mol. Plant 7 (11): 1598-1618. doi: 10.1093/mp/ssu087.

Proudhon, C., et al. (2016) Active and Inactive Enhancers Cooperate to Exert Localized and Long-Range Control of Gene Regulation. Cell Reports. 15:10, 2159–2169. doi: 10.1016/j.celrep.2016.04.087.

Rossetto, C. C., Tarrant-Elorza M., Pari G. S. (2013) Cis and Trans Acting Factors Involved in Human Cytomegalovirus Experimental and Natural Latent Infection of CD14 (+) Monocytes and CD34 (+) Cells. PLoS Pathog 9(5): e1003366. doi:10.1371/journal.ppat.1003366.

Sakashita, A., et al. (2015) Sex Specification and Heterogeneity of Primordial Germ Cells in Mice. PLoS ONE. 10:12. doi:10.1371/journal.pone.0144836.

Salehi, F., et al. (2015) CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing. PLoS ONE. Doi: 10.1371/journal.pone.0116877.

Scharer, C. D., et al. (2015) Genome-wide CIITA-binding profile identifies sequence preferences that dictate function versus recruitment. Nuc. Acids Res. doi: 10.1093/nar/gkv182.

Schmidt, S. V., et al. (2016) The transcriptional regulator network of human inflammatory macrophages is defined by open chromatin. Cell Research. doi: 10.1038/cr.2016.1.

Shin, H.-J., R., et al. (2016) AMPK–SKP2–CARM1 signalling cascade in transcriptional regulation of autophagy. Nature, doi:10.1038/nature18014.

Stelloh, C., et al. (2016) The cohesin-associated protein Wapal is required for proper Polycomb-mediated gene silencing. Epigenetics & Chromatin. 9:14, doi: 10.1186/s13072-016-0063-7.

Stenzig, J., et al. (2016) DNA methylation in an engineered heart tissue model of cardiac hypertrophy: common signatures and effects of DNA methylation inhibitors. Basic Research in Cardiology. 111:9. doi: 10.1007/s00395-015-0528-z.

Takahashi, J. S. et al. (2014) ChIP-seq and RNA-seq Methods to Study Circadian Control of Transcription in Mammals. Methods in Enzymology. doi:10.1016/bs.mie.2014.10.059.

Thakur J. and Sanyal K. (Feb 2013) Efficient neocentromere formation is suppressed by gene conversion to maintain centromere function at native physical chromosomal loci in Candida albicans. Genome Research. doi: 10.1101/gr.141614.112.

Wallerman, O., Nord, H., Bysani, M., Borghini, L. and Wadelius, C. (2015) lobChIP: from cells to sequencing ready ChIP libraries in a single day. Epigenetics Chromatin. 8:25. doi:  10.1186/s13072-015-0017-5.

Wang X, Jiang L, Wallerman O et al. (2013) Transcription factor ZBED6 affects gene expression, proliferation, and cell death in pancreatic beta cells. PNAS. doi: 10.1073/pnas.1303625110 

Watson E., MacNeil L.T. et al. (2013) Integration of Metabolic and Gene Regulatory Networks Modulates the C. elegans Dietary Response. Cell. 

Wu, J., et al. (2015) An alternative pluripotent state confers interspecies chimaeric competency. Nature. doi:10.1038/nature14413.

Wu, Y, et al. (2014) Phosphorylation of p53 by TAF1 inactivates p53-dependent transcription in the DNA damage response. Mol. Cell 53(1):63-74.

Xu, Z., Chen, H., Ling, J., Yu, D., Struffi, P., and Small, S. (2014) Impacts of the ubiquitous factor Zelda on Bicoid-dependent DNA binding and transcription in Drosophila. Genes & Dev. 28: 608 - 621. 

Xue, X., et al. (2015) LncRNA HOTAIR enhances ER signaling and confers tamoxifen resistance in breast cancer. Oncogene. doi:10.1038/onc.2015.340.

Yamane A., et al. (2013) RPA 

Xiong, W., Li, J. Zhang, E. and Huang, H. (2016) BMAL1 regulates transcription initiation and activates circadian clock gene expression in mammals. Biochemical and Biophysical Research Communications. doi:10.1016/j.bbrc.2016.04.009.

Yamane A. et al. (2013) RPA Accumulation during Class Switch Recombination Represents 5′–3′ DNA-End Resection during the S–G2/M Phase of the Cell Cycle. Cell Reports.

Yang, H., Kwon, C. S., Choi, Y. and Lee, D. (2016) Both H4K20 mono-methylation and H3K56 acetylation mark transcription-dependent histone turnover in fission yeast. Biochemical and Biophysical Research Communications. doi: 10.1016/j.bbrc.2016.05.155.

Zhao, J., et al. (2016) Structural and Molecular Mechanism of CdpR Involved in Quorum-Sensing and Bacterial Virulence in Pseudomonas aeruginosa. doi: 10.1371/journal.pbio.1002449.


Kit Specs

The NEXTflex ChIP-Seq Barcodes Kits contain 6, 12, 24 or 48 unique barcodes, enabling the user to multiplex up to 48 samples per flow cell lane. This kit is shipped on dry ice.

Kit Contents

NEXTflex™ ChIP Adapter (0.6 µM)
NEXTflex™ Primer Mix (12.5 µM)
 

Sequences of NEXTflex ChIP-Seq Barcode Indexes - Excel / PDF

Sequences of NEXTflex-96 ChIP-Seq Barcode Indexes - Excel / PDF

Instructions for installing NEXTflex Barcode Indices in Illumina Experiment Manager

Read out blog post to learn how to use barcodes with different index lengths in a single run.


What is the concentration of the NEXTflex ChIP-Seq Barcodes?

The concentration of the NEXTflex ChIP-Seq Barcodes is 0.6 µM.

 

Do the NEXTflex Chip-Seq Barcodes Kits contain PCR primers?

Yes, these barcodes are supplied with PCR primers.

 

What concentration are the NEXTflex PCR primers supplied at?

The NEXTflex PCR Primers concentration is 12.5 µM.

 

Can I order more NEXTflex PCR primers alone?

Yes. The NEXTflex PCR Primers are available in sets of 48, 96, 192, 384 or 768 reactions. For more information, contact sales@biooscientific.com.

 

How is the quality of the NEXTflex ChIP-Seq Barcodes ensured?

Each lot of the NEXTflex barcodes is sequence-verified on an Illumina MiSeq.

 

What type of purification is used when the NEXTflex ChIP-Seq Barcodes are synthesized?

To minimize the risk of mispriming events due to truncations and other errors that may compromise sequencing data quality, NEXTflex Barcodes are HPLC-purified.