• Indexed adapters for multiplexing Illumina® DNA-Seq libraries with flexible options
  • Considerably reduce your per-sample sequencing cost by using barcoded adapters for multiplexing
  • Increase your sequencing scale by pooling 100s of samples on a single flow cell
  • Compatible with Illumina® next-generation sequencing platforms
Download Manual
For research use only. Not for use in diagnostic procedures.

  • NOVA-514101


    48 RXNS

  • NOVA-514102


    96 RXNS

  • NOVA-514103


    192 RXNS

  • NOVA-514104


    384 RXNS

  • NOVA-514105


    96 BARCODES (in 96-well plate)
    768 RXNS

  • NOVA-514106


    96 BARCODES (in tubes)
    768 RXNS

Prevent Poor Reads from Single Base Errors Introduced During PCR

NEXTFLEX® DNA Barcodes are indexed adapters, compatible with Illumina® platforms, that provide flexibility and high-throughput capabilities in sequencing applications. Multiplexing with NEXTFLEX® DNA Barcodes significantly increases scale while reducing costs by allowing the user to pool multiple library preparations in a single flow cell lane. The NEXTFLEX® DNA Barcodes utilize an indexed adapter containing a 6 nt unique sequence. This allows for proper differentiation between samples by preventing poor reads from single base errors introduced during PCR. The NEXTFLEX® index is contained within the adapter sequence, reducing or eliminating the need to perform PCR.

These barcodes can be used with single, paired-end, and multiplex reads and are compatible with the NEXTFLEX® Rapid DNA-Seq Kit, NEXTFLEX® Methyl DNA-Seq Kit, the NEXTFLEX® Cell Free DNA-Seq Kit and other genomic DNA library prep protocols compatible with Illumina® sequencing.

Multiplex up to 384 DNA samples

Do you want to multiplex more than 48 samples? We also offer the NEXTFLEX-96 DNA Barcode kits, which contain 96 – 8 nt index barcodes in either a 96-well format (cat # NOVA-514105) or in microfuge tubes (cat # NOVA-514106). The NEXTFLEX-HT Barcodes are single index barcodes which allow multiplexing of up to 384 Illumina® libraries.

DNA-Seq Multiplexing Adapter

The NEXTFLEX® adapters contain the full complement of sequencing flow cell binding regions (A, B), which eliminates the need to perform PCR to add the barcode tag.

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 our 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.

DNA-Seq Multiplex Options

Deep Sequencing of NEXTFLEX® DNA Barcode Generated Sequencing. Libraries generated using the NEXTFLEX® DNA Barcodes have a consistent percentage of usable reads.


  • NEXTFLEX® DNA Barcode Adapter (25 µM)
  • NEXTFLEX® Primer Mix (12.5 µM)





Selected Publications that Cite Using the NEXTflex DNA Barcodes

  • Akagi, T., Henry, I. M., Tao, R., Comai, L. (2014) A Y-chromosome–encoded small RNA acts as a sex determinant in persimmons. Science 346, 646 doi: 10.1126/science.1257225.
  • Alia, M. A., et al. (2015) Transcriptional modulator ZBED6 affects cell cycle and growth of human colorectal cancer cells. PNAS. 112:25. 7743–7748. doi: 10.1073/pnas.1509193112.
  • Barth, S. et al. (2015) Experimental Evaluation of Faecal Escherichia coli and Hepatitis E Virus as Biological Indicators of Contacts Between Domestic Pigs and Eurasian Wild Boar. Transboundary and Emerging Diseases. 1865-1682. doi: 10.1111/tbed.12389.
  • Brodie, J., et al. (2016) Characterising the microbiome of Corallina officinalis, a dominant calcified intertidal red alga. FEMS Microbiology Ecology. doi: 10.1093/femsec/fiw110.
  • Brown, A. M. V., Huynh, L. Y., Bolender, C. M., Nelson, K. G. and McCutcheon, J. P. (2013), Population genomics of a symbiont in the early stages of a pest invasion. Molecular Ecology. doi: 10.1111/mec.12366.
  • Cabagnols, X., et al. (2016) Presence of atypical thrombopoietin receptor (MPL) mutations in triple-negative essential thrombocythemia patients. Blood. 127:3. pp. 333 – 342. doi: 10.1182/blood-2015-07-661983.
  • Campana, M. G., et al. (2014) False positives complicate ancient pathogen identifications using high-throughput shotgun sequencing. BMC Research Notes. 7:111
  • Campana, M. G., Robles García, N. M. and Tuross, N. (2015) America’s red gold: multiple lineages of cultivated cochineal in Mexico. Ecology and Evolution. doi: 10.1002/ece3.1398.
  • Campbella, M. A., et al. (2015) Genome expansion via lineage splitting and genome reduction in the cicada endosymbiont Hodgkinia. PNAS. doi: 10.1073/pnas.1421386112.
  • Carnes, M. U., et al. (2015) The Genomic Basis of Postponed Senescence in Drosophila melanogaster. PLoS ONE. doi: 10.1371/journal.pone.0138569.
  • Cervera-Juanes, R., et al. (2015) MAOA expression predicts vulnerability for alcohol use. Molecular Psychiatry. doi:10.1038/mp.2015.93.
  • Chatterjee, S., et al. (2015) Draft genome of a commonly misdiagnosed multidrug resistant pathogen Candida auris. BMC Genomics. 16:686. doi:10.1186/s12864-015-1863-z.
  • Chwialkowska, K., Nowakowska, U., Mroziewicz, A., Szarejko, I., and Kwasniewski, M. (2016) Water-deficiency conditions differently modulate the methylome of roots and leaves in barley (Hordeum vulgare L.) J. Exp. Bio. doi: 10.1093/jxb/erv552.
  • Cockrama, C. A., Filatenkovab, M., Danos, V., El Karouia, M. and Leacha, D. R. F. (2015) Quantitative genomic analysis of RecA protein binding during DNA double-strand break repair reveals RecBCD action in vivo. PNAS. doi: 10.1073/pnas.1424269112.
  • Cohn, L. B. et al. (2015) HIV-1 Integration Landscape during Latent and Active Infection Cell. 160:3, 420–432. doi:10.1016/j.cell.2015.01.020.
  • de Sousa, F., Bertrand, Y. J. K., Nylinder, S., Oxelman, B., Eriksson, J. S. and Pfeil, B. E. (2014) Phylogenetic Properties of 50 Nuclear Loci in Medicago (Leguminosae) Generated Using Multiplexed Sequence Capture and Next-Generation Sequencing. PLoS One. Doi 10.1371/journal.pone.0109704.
  • Dierynck, I., et. al (2014) Deep-Sequencing Analysis of the Gene Encoding the Hepatitis C Virus Nonstructural 3–4A Protease Confirms a Low Prevalence of Telaprevir-Resistant Variants at Baseline and the End of the REALIZE Study. The Journal of Infectious Diseases. doi: 10.1093/infdis/jiu340.
  • Duguma, D., Hall, M., Rugman-Jones, P., Stouthamer, R., Neufeld, J. D., and Walton, W. E. (2015) Microbial communities and nutrient dynamics in experimental microcosms are altered after application of a high dose of Bti. Journal of Applied Ecology.  doi: 10.1111/1365-2664.12422.
  • Duguma D, Rugman-Jones P, Kaufman MG, Hall MW, Neufeld JD, et al. (2013) Bacterial Communities Associated with Culex Mosquito Larvae and Two Emergent Aquatic Plants of Bioremediation Importance. PLoS ONE 8(8): e72522. doi:10.1371/journal.pone.0072522.
  • Eldholm, V. et. al. (2014) Evolution of extensively drug-resistant Mycobacterium tuberculosis from a susceptible ancestor in a single patient. Genome Biology, 15:490  doi:10.1186/s13059-014-0490-3.
  • Eldholm, V., et al. (2015) Four decades of transmission of a multidrug-resistant Mycobacterium tuberculosis outbreak strain. Nature Communications. doi:10.1038/ncomms8119.
  • Evrony G. D., Cai, et al. (2012) Single-Neuron Sequencing Analysis of L1 Retrotransposition and Somatic Mutation in the Human Brain. Cell. Vol. 151, Issue 3, pp. 483-496.
  • Evrony, G. D. et al. (2015)  Cell Lineage Analysis in Human Brain Using Endogenous Retroelements. Neuron. Doi: 10.1016/j.neuron.2014.12.028.
  • Gaines, T. A., et al. (2013) Identification of Genetic Elements Associated with EPSPS Gene Amplification. PLOS One. doi: 10.1371/journal.pone.0065819.
  • Gal, C., et al. (2015) Abo1, a conserved bromodomain AAA‐ATPase, maintains global nucleosome occupancy and organization. EMBO Reports. 16:11. pp 1409 – 1580. doi: 10.15252/embr.201540476.
  • Gal, C. et al. (2015) The impact of the HIRA histone chaperone upon global nucleosome architecture. Cell Cycle. 14:1, 123-134. doi:10.4161/15384101.2014.967123.
  • Gan, H. M., Tan, M. H., Lee, Y. P. and Austin, C. M. (2014) The complete mitogenome of the Australian tadpole shrimp Triops australiensis (Spencer & Hall, 1895) (Crustacea: Branchiopoda: Notostraca). Mitochondrial DNA doi:10.3109/19401736.2014.974173.
  • Gan, H. M., Tan, M. H., Lee, Y. P. and Austin, C. M. (2014) The complete mitogenome of the river blackfish, Gadopsis marmoratus (Richardson, 1848) (Teleostei: Percichthyidae). Mitochondrial DNA doi:10.3109/19401736.2014.974174.
  • Garcia-Murillas, I., et al. (2015) Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Science Translational Medicine. 7:302, 302ra133. doi: 10.1126/scitranslmed.aab0021.
  • 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.
  • Gandhi, S., Christiaen, L., Stolfi, A. (2016, Feb 28, 2016). Rational design and whole-genome predictions of single guide RNAs for efficient CRISPR/Cas9-mediated genome editing in Ciona. doi: 10.1101/041632.
  • Givnish, T. J., et al. (2016) Phylogenomics and historical biogeography of the monocot order Liliales: out of Australia and through Antarctica. Cladistics. doi: 10.1111/cla.12153.
  • Goh, H. F. and K. Philip (2014) Isolation and mode of action of bacteriocin BacC1 produced by nonpathogenic Enterococcus faecium C1, Journal of Dairy Science. 98:8, 5080-5090. doi: 10.3168/jds.2014-9240.
  • Goh, H. F. and Philip, K. (2015) Purification and Characterization of Bacteriocin Produced by Weissella confusa A3 of Dairy Origin. PLoS ONE. doi: 10.1371/journal.pone.0140434.
  • Gomez-Gil, B. et al. (2016) Photobacterium sanguinicancri sp. nov. isolated from marine animals. Antonie van Leeuwenhoek. doi: 10.1007/s10482-016-0681-x.
  • Gultekin, S. E., et al. (2016) Unusual Presentation of an Adenocarcinoma of the Lung Metastasizing to the Mandible, Including Molecular Analysis and a Review of the Literature. Journal of Oral and Maxillofacial Surgery, doi:10.1016/j.joms.2016.06.004.
  • Gutzwiller, F., et al. (2015) Dynamics of Wolbachia pipientis Gene Expression Across the Drosophila melanogaster Life Cycle. g3. 5: 2843 – 2856. doi: 10.1534/g3.115.021931.
  • Halley Y. A., et al. (2014) A Draft De Novo Genome Assembly for the Northern Bobwhite (Colinus virginianus) Reveals Evidence for a Rapid Decline in Effective Population Size Beginning in the Late Pleistocene. PLoS ONE 9(3): e90240. doi:10.1371/journal.pone.0090240.
  • Handley, K. M., Wrighton, K. C., Miller, C. S., Wilkins, M. J., Kantor, R. S., Thomas, B. C., Williams, K. H., Gilbert, J. A., Long, P. E. and Banfield, J. F. (2014) Disturbed subsurface microbial communities follow equivalent trajectories despite different structural starting points. Environmental Microbiology. doi: 10.1111/1462-2920.12467.
  • Harrisson, K., et al. (2016) Pleistocene divergence across a mountain range and the influence of selection on mitogenome evolution in threatened Australian freshwater cod species. Heredity. 1–10. doi:10.1038/hdy.2016.8.
  • Henry, I.M. et al. (2014) Efficient Genome-Wide Detection and Cataloging of EMS-Induced Mutations Using Exome Capture and Next-Generation Sequencing. The Plant Cell 26 (4) 1382-1397. dx.​doi.​org/​10.​1105/​tpc.​113.​121590.
  • Henry, I., Zinkgraf, M., Groover, A., and Comai, L. (2015) A System for Dosage-Based Functional Genomics in Poplar. Plant Cell 27:2370-2383.
  • Herron MD, Doebeli M (2013) Parallel Evolutionary Dynamics of Adaptive Diversification in Escherichia coli. PLoS Biol 11(2): e1001490. doi:10.1371/journal.pbio.1001490.
  • Hill, C. J. et al. (2016) Effect of room temperature transport vials on DNA quality and phylogenetic composition of faecal microbiota of elderly adults and infants. Microbiome. 4:19. doi: 10.1186/s40168-016-0164-3.
  • Hittalmani, S., Mahesh, H. B., Mahadevaiah, C. and Prasannakumar, M. K. (2016) De novo genome assembly and annotation of rice sheath rot fungus Sarocladium oryzae reveals genes involved in Helvolic acid and Cerulenin biosynthesis pathways. BMC Genomics. 17:271. doi: 10.1186/s12864-016-2599-0.
  • Hoffmanna, D., et al. (2015) Out of the Reservoir: Phenotypic and Genotypic Characterization of a Novel Cowpox Virus Isolated from a Common Vole. J. Virol. 89:21. 10959-10969. doi: 10.1128/JVI.01195-15.
  • Kaikkonen, M.U., et al. (2014) Control of VEGF-A transcriptional programs by pausing and genomic compartmentalization. Nuc Acid Res. doi:10.1093/nar/gku1036.
  • Kensche, P. R., et al. (2015) The nucleosome landscape of Plasmodium falciparum reveals chromatin architecture and dynamics of regulatory sequences. Nucl. Acids Res. doi:10.1093/nar/gkv1214.
  • Kloet, S. L., et al. (2016) The dynamic interactome and genomic targets of Polycomb complexes during stem-cell differentiation. Nature Structural & Molecular Biology. doi:10.1038/nsmb.3248.
  • König, K. et al. (2015) Implementation of Amplicon Parallel Sequencing Leads to Improvement of Diagnosis and Therapy of Lung Cancer Patients. Journal of Thoracic Oncology. 10 :7, 1049–1057. doi: 10.1097/JTO.0000000000000570.
  • Kuznetsova, T., et al. (2015) Glucocorticoid receptor and nuclear factor kappa-b affect three-dimensional chromatin organization. Genome Biology. 16:264. doi:10.1186/s13059-015-0832-9.
  • Lam, V. K. Y. Gomez, M. S. and Sean W. Graham, S. W. (2015) The Highly Reduced Plastome of Mycoheterotrophic Sciaphila (Triuridaceae) Is Colinear with Its Green Relatives and Is under Strong Purifying Selection. Genome Biol Evol. 7:8. 2220-2236. doi: 10.1093/gbe/evv134.
  • Laughlin, M. H., et al. (2015) Exercise-induced differential changes in gene expression among arterioles of skeletal muscles of obese rats. Journal of Applied Physiology. dio: 10.1152/japplphysiol.00316.2015.
  • Lemieux, J. E., et al. (2016) A global map of genetic diversity in Babesia microti reveals strong population structure and identifies variants associated with clinical relapse. Nature Microbiology, 16079. doi:10.1038/nmicrobiol.2016.79.
  • Ma, X., et al. (2015) Rise and fall of subclones from diagnosis to relapse in pediatric B-acute lymphoblastic leukaemia. Nature Communications. 6: 6604 doi:10.1038/ncomms7604.
  • Mandelker, D., et al. (2015) Comprehensive Diagnostic Testing for Stereocilin: An Approach for Analyzing Medically Important Genes with High Homology. The Journal of Molecular Diagnostics, 16:6, 639-647. doi:10.1016/j.jmoldx.2014.06.003.
  • Merlevede, J. et al. (2016) Mutation allele burden remains unchanged in chronic myelomonocytic leukaemia responding to hypomethylating agents. Nat. Commun. 7:10767 doi: 10.1038/ncomms10767.
  • Mira-Martinez, S. et al. (2013) Epigenetic switches in clag3 genes mediate blasticidin S resistance in malaria parasites. Cellular Microbiology 15(11): 1913-1923.
  • Moormann, S. M., Hampton-Marcell,J. T.,   Owens, S. M. and Gilbert J. A. (2014) Protocols for Metagenomic Library Generation and Analysis in Petroleum Hydrocarbon Microbe Systems. Springer Protocols Handbooks 2014. Published by Humana Press. doi: 10.1007/8623_2014_37.
  • Müller-Höcker, J., et. al. (2014) Oxyphil Cell Metaplasia in the Parathyroids Is Characterized by Somatic Mitochondrial DNA Mutations in NADH Dehydrogenase Genes and Cytochrome c Oxidase Activity–Impairing Genes. The Amer. J. of Path. 184:11, pg. 2.
  • Nair, R. G., et al. (2016) Genome Mining and Comparative Genomic Analysis of Five Coagulase Negative Staphylococci (CNS) Isolated from Human Colon and Gall Bladder. J Data Mining Genomics Proteomics. 7:2. doi: 10.4172/2153-0602.1000192.
  • Obholzer N. et al. (2012) Rapid positional cloning of zebrafish mutations by linkage and homozygosity mapping using whole-genome sequencing. doi: 10.1242/dev.083931.
  • O’Donnell, J. L., Kelly, R. P., Lowell, N. C. and Port, J. A. (2016) Indexed PCR Primers Induce Template-Specific Bias in Large-Scale DNA Sequencing Studies. PLOS One. doi: 10.1371/journal.pone.0148698.
  • O’Geen, H., Henry, I. M., Bhakta, M. S., Meckler, J. F. and Segal, D. J. (2015) A genome-wide analysis of Cas9 binding specificity using ChIP-seq and targeted sequence capture. Nucl. Acids Res. doi: 10.1093/nar/gkv137.922–2935.
  • Oke, A., Anderson, C.M., Yam, P. and Fung, J. C. (2014) Meiotic Recombinational Repair – Specifying the Roles of ZMMs, Sgs1 and Mus81/Mms4 in Crossover Formation. PLOS Genetics. doi: 10.1371/journal.pgen.100469.
  • Okhovat, M., Berrio, A., Wallace, G., Ophir, A. G. and Phelps, S. M. (2015) Sexual fidelity trade-offs promote regulatory variation in the prairie vole brain. Science. 350:6266. 1371-1374. doi:10.1126/science.aac5791.
  • Padilla, J. et al. (2014) Identification of genes whose expression is altered by obesity throughout the arterial tree. Physiol Genomics, 46: 821 – 832. doi:10.1152/physiolgenomics.00091.2014.
  • Palomo, A., et al. (2016) Metagenomic analysis of rapid gravity sand filter microbial communities suggests novel physiology of Nitrospira spp. The ISME Journal. doi:10.1038/ismej.2016.63.
  • Phillips, A. M., Calvo, R. A. and Kearns, D. B. (2015) Functional Activation of the Flagellar Type III Secretion Export Apparatus. PLOS Genetics. doi: 10.1371/journal.pgen.1005443.
  • Port, J. A., et al. (2015) Assessing Vertebrate Biodiversity in a Kelp Forest Ecosystem using Environmental DNA. Molecular Ecology. doi: 10.1111/mec.13481.
  • Proudhon, C., et al. (2016) Active and Inactive Enhancers Cooperate to Exert Localized and Long-Range Control of Gene Regulation. Cell Reports. doi: 10.1016/j.celrep.2016.04.087.
  • Ripma, L. A., Simpson, M. G. and Hasenstab-Lehman, K. (2014) Geneious! Simplified Genome Skimming Methods for Phylogenetic Systematic Studies: A Case Study in Oreocarya (Boraginaceae). Applications in Plant Sciences 2(12):1400062. doi:
  • Roberts, J. D. et. al. (2014) Deep Sequencing Reveals No Evidence for Somatic Mosaicism in Atrial Fibrillation. CIRCULATION: CARDIOVASCULAR GENETICS. doi: 10.1161/CIRCGENETICS.114.000650.
  • Rosario, R. C. H., et. al.   (2015) Sensitive detection of chromatin-altering polymorphisms reveals autoimmune disease mechanisms. Nature Methods. doi:10.1038/nmeth.3326.
  • Rube, H. T., et al. (2016) Sequence features accurately predict genome-wide MeCP2 binding in vivo. Nature Communications. 7:11025. doi:10.1038/ncomms11025.
  • Sanders, J. et al. (2015) Baleen whales host a unique gut microbiome with similarities to both carnivores and herbivores. Nature Communications. 6 (8285) doi:10.1038/ncomms9285.
  • Schlottau, K., et al. (2016) Detection of a Novel Bovine Astrovirus in a Cow with Encephalitis. Transboundary and Emerging Diseases. doi: 10.1111/tbed.12493.
  • Shain, A. H., et al. (2015) The Genetic Evolution of Melanoma from Precursor Lesions. The New England Journal of Medicine. 373:1926-1936. doi: 10.1056/NEJMoa1502583.
  • Shanker, S. et al. (2015) Evaluation of Commercially Available RNA Amplification Kits for RNA Sequencing Using Very Low Input Amounts of Total RNA. J Biomol Tech. 15, 2601-001. doi: 10.7171/jbt.15-2601-001.
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What is the concentration of the NEXTflex DNA Barcodes?
The concentration of the NEXTflex DNA Barcodes is 25 µM.

At what concentration are the NEXTflex PCR primers supplied?
The NEXTflex PCR Primers concentration is 12.5 µM.

Do the NEXTflex DNA-Seq Barcodes Kits contain PCR primers?
Yes, these barcodes are supplied with PCR primers.

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. Contact [email protected] for more information.

How is the quality of the NEXTflex DNA Barcodes ensured?
Each lot of the NEXTflex barcodes is sequence verified on an Illumina MiSeq.

What type of purification is used when the NEXTflex DNA Barcodes are synthesized?
In order to ensure the highest quality sequencing data, the NEXTflex Barcodes are HPLC-purified, minimizing the risk of mispriming events due to truncations and other data quality-compromising errors.

The NEXTFLEX® DNA Barcodes Kits contain 6, 12, 24, or 48 unique barcodes, enabling the user to multiplex up to 48 samples per flow cell lane. These kits ship on dry ice.

Preventing Cross Contamination of Samples and Adapter Barcodes During NGS Library Preparation

With the ever-increasing throughput of sequencing platforms, pooling multiple samples at once has become the common method for making sequencing more economical. Because samples are routinely prepared in parallel, great care must be taken throughout the entire library preparation and sequencing process to prevent cross contamination of the samples, or the unique barcodes that are used to identify each individual sample. Even very low amounts of cross contamination can be devastating to a sequencing experiment, costing thousands of dollars and countless hours of work. The following will identify areas of possible contamination and suggests methods of prevention.

Cross Contamination of Library Template

Cross contamination of starting material is just as damaging as, and is often mistakenly identified as barcode cross contamination. When multiple samples are prepared at the same time or multiple libraries are produced in parallel, there is a risk that individual samples may contaminate each other. The best way to avoid this type of contamination is to perform all sample and library preparations individually, thus eliminating all risk of cross contamination. If doing all sample and library preps individually is not a feasible solution, then strict measures need to be employed to keep your samples pure.

Good practices include:

  • Regularly clean pipettes and work surfaces.
  • Use aerosol barrier pipette tips.
  • Change pipette tips between each and every step
  • Use pierceable seals on plates during all pipetting steps. We use Sigma’s X-Pierce Seals.
  • Leave an empty well between each sample in the plate when possible.
  • Use a plate centrifuge to spin down plates before use.
  • Mix samples by pipetting up and down with a pierceable seal in place.
  • Never mix plates on vortexers. Placing a plate on a vortexer to mix samples or barcodes has been proven to lead to cross contamination, even if the plate appears to be securely sealed. We recommend that the NEXTflex-96 Barcodes be mixed by pipette and never on a vortexer.

Determining Cause of Contamination

In cases where sample contamination in amplicon-seq libraries is suspected because samples appear to be present in multiple barcoded libraries after demultiplexing, you need to determiner whether you cross-contaminated your starting material or the set of barcodes adapters. The cause can be determined by running a Bioanalyzer trace on the suspect library. If the contamination was caused by barcode impurity, the library in question should have only one amplicon peak, as distinct barcodes would not be distinguishable on a Bioanalyzer. Alternatively, if the issue is due to cross-contamination of starting material, the same barcode should be ligated to multiple amplicons and should be evidenced by multiple peaks on the Bioanalyzer. An example can be seen in Figure 1. Amplicon-seq libraries with sample contamination, along with non-contaminated samples, were run on a Bioanalyzer (Figure 1). The pure samples contained only one amplicon (Figure 1A); however, the contaminated samples contained multiple amplicons (Figure 1B). Running the starting material on the Bioanalyzer and observing multiple peaks in the contaminated samples further confirmed this result. This simple Bioanalyzer test clearly indicates that the contamination issue was a starting material problem and not a barcode problem.

Since most sequencing applications are not pure amplicon samples but complex mixtures in which slight contamination might go unnoticed, amplicon-seq datasets are uniquely able to demonstrate how to prevent cross-contamination.

Preventing Barcode Contamination during Library Preparation

As with sample preparation, using aerosol barrier tips, changing tips after every use, mixing by pipetting, and using pierceable seals during any pipetting steps, are all ways to reduce contamination during library preparation. All of these precautions are important not only during the enzymatic steps, but during the cleanup steps as well.

Other important methods to employ if using plated barcoded adapters are:

  • Making sure that the plate seal is securely affixed to all of the individual wells to prevent any aerosol contamination during incubation and cycling. A good way of accomplishing this is to run your finger down all of the columns and across all of the rows after you put the seal on the plate or use an adhesive film applicator.
  • Immediately spinning down plates upon sealing and after removal from the thermal cycler.
  • Gently removing plate seals by peeling them away from the wells in order to prevent splashing across wells.
  • Applying pierceable seals during any pipetting steps.

Handling of Barcoded Adapters

When using barcoded adapters for multiplexing, it is crucial that they be added in a systematic manner that ensures only the correct barcode is added to each sample. We offer our barcodes in both tubes and in plates, and there are different ways to handle both formats.

Methods to accomplish the accurate addition of barcodes are:

  • Only open one tube at a time when using barcodes that are provided in tubes.
  • Spin down tubes after thawing/mixing.
  • Organize rows of pipette tips so that each tip corresponds to a particular adapter. Doing this will decrease the chance of unintentionally adding two separate barcodes to the same sample.
  • When using barcodes that are provided in plates, make sure that the plate has been spun down before using. Our NEXTflex-96 barcode plate is sealed with a pierceable heat seal that does not need to be removed. This greatly reduces the chances of contamination occurring during the removal of seals.
  • After the barcodes have been added, simply place another seal on top of the pierced seal to store the remaining volume.

Sequencing Platform Issues

Even after producing individually barcoded libraries that are contamination free, problems can still arise during the sequencing run itself. The most troubling issue that has come to light is that MiSeq users have noticed small amounts of sample carryover between sequencing runs. Some good discussions of this issue can be found on SEQanswers. It appears that there can be up to 0.5% of the previous sample left over after cleaning the machine between runs, which will then be detected during subsequent runs. This is especially problematic in clinical studies and any other application attempting to uncover low prevalence mutations.

Illumina says that with prompt and thorough cleaning of instruments, the percentage of reads from carryover is 0.1% or less. Illumina recommends washing only with water and Tween, and discourages users from using bleach or other additives that may damage the machine. Although 0.1% may seem like a trivial amount, it is still far too high for many applications.

One of the easiest fixes suggested on SEQanswers is to alternate the sets of barcodes used between sequencing runs. Rotating three sets would guarantee that the machine is washed at least three times before a barcode was used again. Any template that is carried over from a previous run should not have a barcode that is on the next run’s sample sheet, and should therefore be thrown out during demultiplexing. While this may be a good solution for users that sequence in-house, it does not solve the problem for groups utilizing core facilities, so a further fix from Illumina may still be necessary. For further advice on how to deal with this issue, Genome Biology also has an informative article that discusses data analyses strategies that can be employed.

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