Assay for Transposase-Accessible Chromatin coupled with high-throughput sequencing (ATAC-seq) is a genome-wide method to uncover accessible chromatin. This is a step-by-step ATAC-seq protocol, from molecular to the final computational analysis, optimized for human lymphocytes (Th1/Th2). This protocol can be adopted by researchers without prior experience in next-generation sequencing methods.
Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions of chromatin. These regions represent regulatory DNA elements (e.g., promoters, enhancers, locus control regions, insulators) to which transcription factors bind. Mapping the accessible chromatin landscape is a powerful approach for uncovering active regulatory elements across the genome. This information serves as an unbiased approach for discovering the network of relevant transcription factors and mechanisms of chromatin structure that govern gene expression programs. ATAC-seq is a robust and sensitive alternative to DNase I hypersensitivity analysis coupled with next-generation sequencing (DNase-seq) and formaldehyde-assisted isolation of regulatory elements (FAIRE-seq) for genome-wide analysis of chromatin accessibility and to the sequencing of micrococcal nuclease-sensitive sites (MNase-seq) to determine nucleosome positioning. We present a detailed ATAC-seq protocol optimized for human primary immune cells i.e. CD4+ lymphocytes (T helper 1 (Th1) and Th2 cells). This comprehensive protocol begins with cell harvest, then describes the molecular procedure of chromatin tagmentation, sample preparation for next-generation sequencing, and also includes methods and considerations for the computational analyses used to interpret the results. Moreover, to save time and money, we introduced quality control measures to assess the ATAC-seq library prior to sequencing. Importantly, the principles presented in this protocol allow its adaptation to other human immune and non-immune primary cells and cell lines. These guidelines will also be useful for laboratories which are not proficient with next-generation sequencing methods.
ATAC-seq1,2 is a robust method that enables identification of regulatory3 open chromatin regions and nucleosome positioning. This information is applied for inferring the location, identity, and activity of transcription factors. The method's sensitivity for measuring quantitative variations in chromatin structure allows the study of the activity of chromatin factors, including chromatin remodelers and modifiers, as well as the transcriptional activity of RNA polymerase II1. Thus ATAC-seq provides a powerful and unbiased approach for deciphering mechanisms that govern transcriptional regulation in any cell type of interest. We describe the adaptation of ATAC-seq to primary human Th1 and Th2 cells.
In ATAC-seq, hyperactive Tn5 transposase loaded with adaptors for next-generation sequencing (NGS) couples DNA fragmentation with tagging of DNA with adaptors (i.e., the "tagmentation" process)1. Following PCR amplification, the resulting DNA libraries are ready for next-generation sequencing (Figure 1). The preferential tagmentation of accessible chromatin is detected by the analysis of local enrichment of ATAC-seq sequencing reads.
The short experimental procedure and requirement for less starting material, relative to other methods for measuring chromatin accessibility and nucleosomal positioning such as DNase-seq4, FAIRE-seq5, and MNase-seq6, has promoted the use of ATAC-seq in multiple biological systems including human primary cells1,7 and clinical samples8, as well as unicellular organisms9, plants10, fruit flies11, and various mammals12.
The identity of transcription factors which are bound to accessible loci can be uncovered by analyzing the enrichment of their binding sequence motifs or combining ATAC-seq with chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq). This approach enabled the identification of lineage-specific transcription factors important for hematopoiesis in mouse13. The unbiased and global nature of ATAC-seq allows studying gene regulation in organisms for which reagents such as antibodies for ChIP analysis are not available. For example, evolutionary variations in cis-regulatory regions have been identified by studying cranial neural crest cells from humans and chimpanzees14, developmental variations in regulatory elements during early mouse embryogenesis15, changes in the regulatory landscape during a life cycle of unicellular C. owzarzaki9, and the evolution of promoters and enhancers across 20 mammal species12.
ATAC-seq has also been instrumental for measuring chromatin accessibility in single cells, thus revealing variability within cell populations, which usually evades genome-wide studies7,16. In addition, ATAC-seq can be used to study changes that occur in DNA regulatory regions in disease conditions, in which samples are rare. For example, ATAC-seq can be used to study changes in the regulatory landscape during the onset of acute myeloid leukemia (AML)17 or Ras-driven oncogenesis11.
All the procedures were approved by institutional review board of Bar Ilan University and the protocol follows guidelines provided by the committee approving the experiments.
1. Purification of Naïve Human CD4+ Cells and Polarization to T Helper 1 (Th1) and Th2 Cells
Note: Here we describe the procedure starting from frozen human peripheral blood mononuclear cells (PBMCs). The first step consists of isolating CD4+ cells using microbeads and columns that usually give us more than 95% of CD4+ cells. However, this step may vary according to the preferred protocol in each lab. The protocol for T cell activation and polarization was modified from Jenner et al. (2009)18. Isolation of CD4+ cells from 10 million PBMCs gives rise to 4 – 6 million of CD4+ cells. They are split into two flasks and grown under Th1 and Th2 polarizing conditions yielding 3-5 million Th1 and Th2 cells within just a week.
Note: Cool down the centrifuge to 4 °C before starting.
2. Nuclei Isolation
NOTE: ATAC-seq is performed with intact nuclei. Lysis buffer containing 0.05% nonylphenyl polyethylene glycol (see Table of Materials/Equipment) was calibrated for isolating nuclei from primary human Th1 and Th2 cells. We recommend calibrating this step with the laboratory reagents and cells. An excess of intact cells from insufficient detergent decreases the efficiency of the transposition reaction. Cell lysis efficiency is determined by the number of nuclei (trypan blue positive cells) relative to the total number of cells.
NOTE: Prepare the lysis buffer (10 mM Tris-HCl, pH 7.5, 10 mM NaCl, 3 mM MgCl2). Cool down a centrifuge with a swing-bucket rotor to 4 °C. Pelleting the cells in a swing-bucket centrifuge instead of a fixed angle centrifuge reduces cell/nuclei loss. To avoid nuclei or cell loss, pipet carefully when discarding the supernatant.
3. Transposition reaction
NOTE: In this step, isolated nuclei are incubated with prokaryotic Tn5 transposase (TDE1) loaded with adapters for NGS sequencing. Hyperactive Tn5 simultaneously fragments DNA and ligates adapters into accessible regions of the genome (tagmentation process). The ratio between nuclei and Tn5 transposase is critical for preferential cleavage at accessible chromatin. This protocol is calibrated for 100,000 nuclei in a 100 μL reaction volume. However, the reaction can be scaled down.
4. PCR Enrichment of ATAC-seq Libraries
NOTE: This step is aimed to amplify the ATAC-seq library i.e., DNA fragments with inserted adapters. To allow mixing of several ATAC-seq libraries in the same next-generation sequencing lane ("multiplexing") use unindexed Primer 1 (Ad1_noMx)1 for all samples, and a different indexed (barcoded) Primer 2 (Ad 2.1 – 2.24)1 for each sample. The primer sequences are provided in the supplemented Table of Materials/Equipment.
5. Size Selection of ATAC-Seq Libraries
NOTE: In our experience, size selection of amplified ATAC-seq libraries improves next-generation sequencing results because it eliminates high molecular weight library fragments from the final ATAC-seq library.
NOTE: Allow the magnetic beads to warm to room temperature 30 min before use.
Prepare fresh 70% ethanol in nuclease-free water.
6. Quality Analysis of the ATAC-Seq Libraries
7. Analysis of the Obtained Next-Generation Sequencing Results
The final outcome of this protocol is an ATAC-seq library of typically 3 – 20 ng/µL. When run on a system for DNA integrity analysis (see Table of Materials/Equipment), they show ladder-like appearance2 (Figure 3A). The average size of DNA fragments is typically ~450 – 530 bp.
Proper quality control of the ATAC-seq libraries prior to performing next-generation sequencing is important to save time and money. We consider the libraries suitable for next-generation sequencing (NGS) when the enrichment of positive controls is more than 25- and 75-fold (for primer pairs 3 and 4, respectively) relative to negative controls (Figure 3B) and when they show the previously mentioned nucleosomal, ladder-like appearance. When analyzing qPCR data, we are also verifying that the Cq values for negative and positive control primers are similar in the reactions with the genomic DNA as a template and that the Cq values for the negative control regions (in the reactions with ATAC-seq DNA fragments) are constant between the experiments. For example, in the case of suddenly lower Cq values, we suspect that the nuclei were over-transposed and thus DNA fragments originating from heterochromatin regions are over-represented. Moreover, if the gel image (obtained by high-sensitivity tape-based electrophoresis) of ATAC-seq libraries indicates the presence of the adaptors (~120 bp), excessive DNA degradation (the majority of the fragments are ~200 bp), or large fragments (over 1 kb), we would not continue to the NGS step.
Furthermore, we always perform initial NGS in which we aim for 10 million reads per library. If the results of this sequencing are satisfactory (the sample passes all the parameters in FastQC report file and we can obtain 1000 – 2000 peaks after performing peak calling), the libraries are sequenced more deeply (more than 30 million reads/ATAC-seq library).
In ATAC-seq experiments on mammalian cells, anywhere from ~ 30 – 70% of the sequenced reads can come from mtDNA10. In contrast, our libraries contained 6-20% reads mapped to the mitochondrial genome. This is lower than the reported 46% in the ATAC-seq library from human CD4+ T lymphocytes1. After eliminating these contaminating reads, we were left with ~7 – 32 million unique reads mapping to the reference human genome (58%-91% of all reads). From these, 0.1 – 2 million reads (6.8% – 12% of all reads) were in ATAC-seq peaks (Figure 4).
Figure 1. Workflow of experimental steps. Representation of the major steps in this ATAC-seq protocol. Stopping points are indicated by yellow hexagons. An optional step is represented with an orange hexagon. Please click here to view a larger version of this figure.
Figure 2. Calculation of the additional number of PCR cycles required for the final enrichment of ATAC-seq libraries. PCR amplification curves for three different ATAC seq libraries are shown in red, blue and pink. The amplification reactions reached a plateau at 2,350 RFU (upper green horizontal line). The number of additional PCR cycles intersects with 783 RFU (2,350/3) on the amplification curve. Two libraries (red and blue) require 8 additional amplification cycles while the third library (pink) requires 9 cycles. Non-template control (NTC) is shown as the lower green line. X-axis, cycle number. Y-axis, RFU units. Please click here to view a larger version of this figure.
Figure 3. Quality control analysis of ATAC-seq libraries. (A) Results of tape-based automated electrophoresis of amplified ATAC-seq libraries. L, ladder; A-D, libraries of biological repeats from Th1 and Th2 cells. (B) qPCR quality control analysis of ATAC-seq libraries. Genomic DNA and four ATAC-seq libraries were amplified by negative control primer pairs (1 and 2) and positive control primers (3 and 4). The obtained values for ATAC-seq libraries (blue) were first normalized to the amplification levels of genomic DNA (arbitrarily set to a value of 1; red). Subsequently, values for the positive control regions were normalized to the negative control regions (lower chart). Libraries #1 and #2 were sent to NGS sequencing. The values represent mean ± SEM. Please click here to view a larger version of this figure.
Figure 4. Genome browser snapsh ots of accessible chromatin regions in Th1 and Th2 cells. ATAC-seq tracks are shown for NFKB1, JUN, CD28, IFNG (expressed only in Th1) and IL4 and IL13 (expressed only in Th2) loci in Th1 and Th2 cells (two biological repeats for each). Please click here to view a larger version of this figure.
TD buffer | 50 | μL |
TDE1 transposase | 5 | μL |
Nuclease-free water | 45 | μL |
Total volume | 100 | μL |
Table 1: Preparation of transposition reaction mixture.
ATAC-seq library | 15 | μL |
Primer 1 (Ad1_noMx) * | 2.5 | μL |
Primer 2 * | 2.5 | μL |
NEBNext High-Fidelity 2 x PCR Master Mix** | 25 | μL |
Nuclease-free water | 5 | μL |
Total volume | 50 | μL |
*Final concentration of each primer is 1.25 μM. | ||
**PCR reagent provided in the kit are not recommended | ||
(Buenrostro et al., 2015. ATAC-seq: A method for assaying chromatin accessibility genome-wide) . | ||
In addition, we have also performed successful amplifications with | ||
NEBNext Q5 Hot Start HiFi PCR Master Mix (extension temperature is 65 °C). |
Table 2: Components of initial PCR reaction mix (step 5.1.1.).
CYCLE STEP | TEMPERATURE | TIME | CYCLES |
Extension* | 72 °C | 5 min | 1 |
Initial Denaturation | 98 °C | 30 s | |
Denaturation | 98 °C | 10 s | 5 |
Annealing | 63 °C | 30 s | |
Extension | 72 °C | 3 min | |
Hold | 4 °C | ∞ | |
*This step is required to extend both | |||
ends of the primers after transposition reaction. |
Table 3: PCR cycling conditions for initial library amplification (step 5.1.2.)
Aliquot of PCR reaction (step 4.1.1) * | 5 | μL |
Primer 1 (Ad1_noMx)** | 1 | μL |
Primer 2 | 1 | μL |
2x SYBR master mix *** | 7.5 | μL |
Nuclease-free water | 0.5 | μL |
Total volume | 15 | μL |
*For non-template control instead of the DNA template add ultra-pure water. | ||
**The final concentration of each primer is 417 nM. | ||
***Use preferred master mix for qPCR. | ||
It should contain polymerase, dNTPs, MgCl2, and fluorescent dye. |
Table 4: Preparation of qPCR reaction mixture (step 5.2.2).
CYCLE STEP | TEMPERATURE | TIME | CYCLES |
Initial denaturation | 98 °C | 30 s | 1 |
Denaturation | 98 °C | 10 s | 20 |
Annealing | 63 °C | 30 s | |
Extension | 72 °C | 3 min | |
Hold | 4 °C | ∞ |
Table 5: Cycling conditions for qPCR-based assesment of additional number of amplification cycles (N) (step 5.2.3.)
CYCLE STEP | TEMPERATURE | TIME | CYCLES |
Initial denaturation | 98 °C | 30 s | 1 |
Denaturation | 98 °C | 10 s | N |
Annealing | 63 °C | 30 s | |
Extension | 72 °C | 3 min | |
Hold | 4 °C | ∞ |
Table 6: Cycling conditions for the final PCR enrichment step (step 5.3.).
For a single PCR reaction: | ||
Dilution of the library of genomic DNA | 2.5 | μL |
10 μM Primer F (F1 or F2 or F3 or F4)* | 0.3 | μL |
10 μM Primer R (R1 or R2 or R3 or R4)** | 0.3 | μL |
2x SYBR master mix *** | 5 | μL |
Nuclease-free water | 1.9 | μL |
Total volume | 10 | μL |
*The final concentration of each primer in the reaction mixture is 300 nM. | ||
**If using primer F1 than the R primer should be R1 etc. | ||
***Use preferred 2x master mix suitable for the qPCR instrument in your laboratory. |
Table 7: Reaction conditions for QC analysis (step 7.1.3.).
Target | Sample | Mean Cq | Cq SEM | Relative quantity | Normalized | |
1 | Negative control | ATAC-seq | 30.39 | 0.11 | 1 | 1.01 |
gDNA | 30.4 | 0.16 | 0.99 | 1 | ||
2 | ATAC-seq | 30.3 | 0.18 | 1 | 1 | |
gDNA | 30.34 | 0.09 | 0.99 | 1 | ||
3 | Positive control | ATAC-seq | 23.27 | 0.03 | 1 | 173.14 |
gDNA | 30.7 | 0.06 | 0.01 | 1 | ||
4 | ATAC-seq | 21.55 | 0.24 | 1 | 750.31 | |
gDNA | 31.1 | 0.03 | 0 | 1 |
Table 8: Calculation of the enrichment of positive controls over negative controls (step 7.1.5.).
The ATAC-seq protocol described here has been successfully employed for the analysis of accessible chromatin in primary cells (human Th1, Th2 cells, and B cells) as well as the cultured cell lines (MCF10A human breast cancer cells and U261 glioblastoma cells). Applying ATAC-seq to other cell types may require some protocol optimization, especially in the lysis step. If the concentration of non-ionic detergent is too high, there may be a higher percentage of mitochondrial DNA contamination. This can be reduced by decreasing the detergent concentration in the lysis buffer without reducing the nuclei yield. In our experience, lysis buffer with 0.05% of detergent gave the most satisfactory results. In addition, spinning the nuclei in a swing-bucket instead of fixed angle rotor allowed reducing the G force to 500, which reduced the mitochondria in the pellet. Researchers may also test other types of detergents, for example, digitonin17. However, even with optimized lysis conditions, mtDNA contamination is inevitable. To completely remove the mtDNA, the CRISPR/Cas9 system can be used15. In this case, ATAC-seq libraries are incubated with sgRNAs to target mtDNA and Cas9 nuclease to digest mtDNA15.
The number of nuclei required for this ATAC-seq protocol (100,000) may be limiting in cases where cell number from clinical samples is scarce7. ATAC-seq has been successfully scaled down to 5,000 and 500 cells1,13,17 by reducing the reaction volume1,13, performing cleanup with magnetic beads instead of with columns13, or avoiding the cleanup step1. In addition, single-cell ATAC-seq (scATAC-seq) may be performed using a microfluidic device to separate individual nuclei16. Notably, other methods for measuring chromatin accessibility, such as DNase-seq and FAIRE-seq, require more starting material and a few more days to perform the experiment.
It is now widely appreciated that biases in various NGS methods are common phenomena25. One of the causes for variations in different chromatin accessibility measures is the enzymatic cleavage step25. It has been shown that DNase I shows cleavage bias26 and now it is recognized that Tn5 transposase shows cleavage preference as well27. Fortunately, the potential bias can be identified computationally by using a quality control pipeline such as ChiLin28. Another common source of bias is the PCR amplification step20,25. This frequently manifests as a bias for the amplification of GC-rich fragments25. Since the bias increases with every PCR amplification step, we do not exceed 9 additional cycles (N) in the final PCR amplification of ATAC-seq libraries.
The proper ratio between Tn5 transposase and nuclei is critical for successful ATAC-seq2. An excess of enzyme would lead to "over transposition" in inaccessible loci and high background. This is reflected in high amplification of the negative control regions in the qPCR quality control step. An excess of nuclei would lead to "under-transposition". In this case, too distant cleavage sites will result in fewer PCR-amplified fragments and low library complexity. To determine the number of nuclei accurately, we introduced an additional counting step after cell lysis and prior to the transposition reaction.
Chromatin accessibility is an important epigenetic regulatory layer as it permits the activity of transcription regulators at specific genomic locations. Thus, the DNA sequence within the accessible chromatin profile provides a wealth of information about the identity and target loci of tens of possible transcription factors. Combining this information (obtained by ATAC-seq) with an RNA expression profile allows a focus on the relevant transcription factors that can be further analyzed by ChIP-seq13,22. In addition, only 10% of disease-associated polymorphisms are in the coding genome30. Thus applying ATAC-seq to clinical samples can reveal which of the non-coding variants are at regulatory elements that may affect gene regulation in the disease state (for example, in systemic lupus erythematosus8). We hope that this ATAC-seq protocol will help and encourage interested investigators to use this powerful method to advance their research.
The authors have nothing to disclose.
This work is supported by the Israel Science Foundation (grant 748/14), Marie Curie Integration grant (CIG)- FP7-PEOPLE-20013-CIG-618763 and I-CORE Program of the Planning and Budgeting Committee and The Israel Science Foundation grant no. 41/11.
50 mL tubes | Lumitron | LUM-CFT011500-P | Can be from other vendors. |
Microtubes | Axygen Inc | MCT-175-C | Can be from other vendors. |
25 mL serological pipettes | Corning Costar | 4489 | Can be from other vendors. |
Tissue culture flask | Lumitron | LUM-TCF-012-250-P | Can be from other vendors. |
Countes Automated Cell Counter | Invitrogen | C10227 | |
NucleoSpin Tissue | MACHEREY-NAGEL | 740952.5 | |
Peripheral blood mononuclear cells (PBMC) | ATCC | PCS800011 | Can be from other vendors. |
RPMI 1640 Medium | Biological Industries | 01-103-1A | Can be from other vendors. |
L-Glutamine Solution (200 mM) | Biological Industries | 03-020-1B | Can be from other vendors. |
Penicillin-Streptomycin | Biological Industries | 03-031-1B | Can be from other vendors. |
Fetal Bovine Serum (FBS), Heat Inactivated, European Grade | Biological Industries | 04-127-1 | Can be from other vendors. |
MACS CD4 microbeads, human | Miltenyi Biotec | 130-045-101 | |
MACS MS columns | Miltenyi Biotec | 130-042-201 | |
Anti-Human CD4 FITC | Biogems | 06121-50 | |
Mouse IgG1 Isotype Control FITC | Biogems | 44212-50 | |
Anti-Human CD3 (OKT3) | Tonbo biosciences | 40-0037 | |
Anti-Human CD28 SAFIRE Purified | Biogems | 10311-25 | |
Recombinant Human IL2 | Peprotech | 200-02 | |
Recombinant Human IL4 | Peprotech | 200-04 | |
Recombinant Human IL12 p70 | Peprotech | 200-12 | |
In Vivo Ready Anti-Human IL-4 (MP4-25D2) | Tonbo | 40-7048 | |
LEAF Purified anti-human IFN-γ | BioLegend | 506513 | |
NaCl, analytical grade | Carlo Erba | 479687 | Can be from other vendors. |
Magnesium chloride, Hexahydrate, molecular biology grade | Calbiochem | 442611 | Can be from other vendors. |
EDTA | MP Biomedicals | 800682 | Can be from other vendors. |
Tris, ultra pure, 99.9% pure | MP Biomedicals | 819620 | Can be from other vendors. |
NP-40 alternative (Nonylphenyl Polyethylene Glycol) | Calbiochem | 492016 | Can be from other vendors. |
Protease Inhibitors | Sigma | P2714 | this protease inhibitor coctail is a powder. To make 100 x solution dilute in 1 mL of molecular-biology grade water. |
Magnetic solid phase reverse immobilization beads: AMPure XP beads | Beckman | 63881 | |
PCR purification kit | HyLabs | EX-GP200 | Can be from other vendors. |
Nextera DNA Library Preparation Kit (TDE1 transposase and TD buffer) | Illumina | FC-121-1030 | |
NEBNext High-Fidelity 2 x PCR Master Mix | New England BioLabs | M0541 | |
NEBNext Q5 Hot Start HiFi PCR Master Mix | New England BioLabs | M0543 | |
SYBR Green I | Invitrogen | S7585 | |
CFX Connect Real-Time PCR Detection System | Bio-rad | 185-5200 | Can be from other vendors. |
CFX Manager Software | Bio-rad | 1845000 | |
master mix for qPCR: iTaq Universal SYBR Green Supermix | Bio-rad | 172-5124 | Can be from other vendors. |
Qubit fluorometer 2.0 | Invitrogen | Q32866 | |
Qubit dsDNA HS Assay Kit | Invitrogen | Q32854 | |
Magnet for eppendorf tubes | Invitrogen | 12321D | Can be from other vendors. |
Swing bucket cooling centrifuge with the buckets for 15 mL falcon tubes and eppendorf tubes | Thermo Scientific | 75004527 | Could be from other vendors. It is important that it has buckets for eppendorf tubes. |
Thermo-shaker | MRC | Can be from other vendors. | |
High Sensitivity D1000 ScreenTape | Agilent Technologies | 5067-5584 | |
High Sensitivity D1000 Reagents | Agilent Technologies | 5067-5585 | |
4200 TapeStation system | Agilent Technologies | G2991AA | Tape-based platform for electrophoresis |
High Sensitivity DNA kit | Agilent Technologies | 5067-4626 | Reagent for high-sensitivity TapeStation analysis |
Primer name and sequence | Company | ||
Ad1_noMX: 5'-AATGATACGGCGACCACCGAGA TCTACACTCGTCGGCAGCGTC AGATGTG-3' |
IDT | Ad1-noMx: 5'-P5 sequence-transposase sequence-3' | |
Ad2.1_TAAGGCGA: 5'-CAAGCAGAAGACGGCATACGAG AT[TCGCCTTA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.1_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.2_CGTACTAG: 5'-CAAGCAGAAGACGGCATACGAG AT[CTAGTACG]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.2_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.3_AGGCAGAA: 5'-CAAGCAGAAGACGGCATACGA GAT[TTCTGCCT]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.3_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.4_TCCTGAGC: 5'-CAAGCAGAAGACGGCATACGAG AT[GCTCAGGA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.4_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.5_GGACTCCT: 5'-CAAGCAGAAGACGGCATACGA GAT[AGGAGTCC]GTCTCGTGGG CTCGGAGATGT-3' |
IDT | Ad2.5_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.6_TAGGCATG: 5'-CAAGCAGAAGACGGCATACGA GAT[CATGCCTA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.6_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.7_CTCTCTAC: 5'-CAAGCAGAAGACGGCATACGA GAT[GTAGAGAG]GTCTCGTGGG CTCGGAGATGT-3' |
IDT | Ad2.7_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.8_CAGAGAGG: 5'-CAAGCAGAAGACGGCATACGA GAT[CCTCTCTG]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.8_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.9_GCTACGCT: 5'-CAAGCAGAAGACGGCATACGA GAT[AGCGTAGC]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.9_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.10_CGAGGCTG: 5'-CAAGCAGAAGACGGCATACG AGAT[CAGCCTCG]GTCTCGTGG GCTCGGAGATGT-3' |
IDT | Ad2.10_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.11_AAGAGGCA: 5'-CAAGCAGAAGACGGCATACG AGAT[TGCCTCTT]GTCTCGTGGG CTCGGAGATGT-3' |
IDT | Ad2.11_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.12_GTAGAGGA: 5'-CAAGCAGAAGACGGCATACG AGAT[TCCTCTAC]GTCTCGTGGG CTCGGAGATGT-3' |
IDT | Ad2.12_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.13_GTCGTGAT: 5'-CAAGCAGAAGACGGCATACGA GAT[ATCACGAC]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.13_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.14_ACCACTGT: 5'- CAAGCAGAAGACGGCATACGA GAT[ACAGTGGT]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.14_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.15_TGGATCTG: 5'- CAAGCAGAAGACGGCATACGA GAT[CAGATCCA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.15_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.16_CCGTTTGT: 5'- CAAGCAGAAGACGGCATACGA GAT[ACAAACGG]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.16_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.17_TGCTGGGT: 5'- CAAGCAGAAGACGGCATACGA GAT[ACCCAGCA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.17_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.18_GAGGGGTT: 5'-CAAGCAGAAGACGGCATACGA GAT[AACCCCTC]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.18_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.19_AGGTTGGG: 5'-CAAGCAGAAGACGGCATACGA GAT[CCCAACCT]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.19_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.20_GTGTGGTG: 5'-CAAGCAGAAGACGGCATACGA GAT[CACCACAC]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.20_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.21_TGGGTTTC: 5'-CAAGCAGAAGACGGCATACGA GAT[GAAACCCA]GTCTCGTGGGC TCGGAGATGT-3' |
IDT | Ad2.21_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.22_TGGTCACA: 5'- CAAGCAGAAGACGGCATACGA GAT[TGTGACCA]GTCTCGTGGGCT CGGAGATGT-3' |
IDT | Ad2.22_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.23_TTGACCCT: 5'-CAAGCAGAAGACGGCATACGA GAT[AGGGTCAA]GTCTCGTGGGCT CGGAGATGT-3' |
IDT | Ad2.23_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
Ad2.24_CCACTCCT: 5'-CAAGCAGAAGACGGCATACGA GAT[AGGAGTGG]GTCTCGTGGGCT CGGAGATGT-3' |
IDT | Ad2.24_expected index sequence read: 5'-P7 sequence-[index sequence]-transposase sequence-3' | |
F1: 5'-CCTTTTTATTTGCCCATACACTC-3' | IDT | ||
R1: 5'-CCCAGATAGAAAGTTGGAGAGG-3' | IDT | ||
F2: 5'-TTGAGGGATGCCATAACAGTC-3' | IDT | ||
R2: 5'-CTGCTGAACAACATCCTTCAC-3' | IDT | ||
F3: 5'-GGTTTGCAGGTTGCGTTG-3' | IDT | ||
R3: 5'-AGAGGAATCTGGGAGTGACG-3' | IDT | ||
F4: 5'-TGCTCATTCCGTTTCCCTAC-3' | IDT | ||
R4: 5'-AGCCGGAAAGAAAGTTCCTG-3' | IDT |