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Jul 2019

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ChIP-Seq from Limited Starting Material of K562 Cells and Drosophila Neuroblasts Using Tagmentation Assisted Fragmentation Approach
用Tagmentation Assisted Fragmentation法从K562细胞和果蝇神经母细胞的有限起始材料中提取芯片序列   

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Abstract

Chromatin immunoprecipitation is extensively used to investigate the epigenetic profile and transcription factor binding sites in the genome. However, when the starting material is limited, the conventional ChIP-Seq approach cannot be implemented. This protocol describes a method that can be used to generate the chromatin profiles from as low as 100 human or 1,000 Drosophila cells. The method employs tagmentation to fragment the chromatin with concomitant addition of sequencing adaptors. The method generates datasets with high signal to noise ratio and can be subjected to standard tools for ChIP-Seq analysis

Keywords: Low Input ChIP-Seq (低细胞量ChIP-Seq), Easy workflow (简易工作流程), High Signal-to-Noise ratio (高信噪比), Tagmentation (Tagmentation技术), High reproducibility (重现性好)

Background

Epigenetic state and transcription factors occupancy are critical determinants of gene expression. To understand this regulation, the precise mapping of chromatin features are very important. Chromatin immunoprecipitation coupled with next generation sequencing is a powerful technique that gives valuable insight into genome wide distributions of chromatin features (Ghavi-Helm et al., 2016). Although powerful, this technique is limited in its application owing to the need of significant starting material which in some conditions are hard to meet, if not completely impossible. This limitation has driven many recent efforts to adapt ChIP-Seq approach for low amount starting material or for rare cell types (Adli et al., 2010; Zheng et al., 2015). One of the key limitations of these efforts is the use of sonication or MNAse for fragmenting the chromatin. The former approach is detrimental for the epitope when present in limited amount as it can lead to destruction of the epitope used for subsequent immunoprecipitation (Stathopulos et al., 2004). The MNAse approach on the other hand is hard to control for its efficacy and saturation. The recent application of CUT&RUN approach was successful in generating profiles from samples of 100 cells using antibody-targeted micrococcal nuclease (Skene et al., 2018). However, all these approaches still resort to ligation-based library preparation approach involving multiple steps, potentially leading to increased variability as well as of loss of complexity (Seguin-Orlando et al., 2013). The method described here overcomes these limitations by using commercially available Tn5 enzyme for fragmenting the chromatin with simultaneous preparation of libraries with fewer intermediate steps. The direct comparison of CUT&RUN approach and TAF-ChIP reveals superior signal to noise ratio in the later, making use of standard bioinformatics pipeline amenable to this approach.

Materials and Reagents

  1. DNA Low binding 1.5 ml tubes (Eppendorf, catalog number: 0030108051)
  2. Phase Lock tubes (5Prime, catalog number: 2302830)
  3. Agencourt AMPure XP Beads (Beckmann Coultier, catalog number: A63381)
  4. Protein G Dynabeads (Thermo Fisher Scientific, catalog number: 10003D)
  5. BSA (Sigma-Aldrich, catalog number: A4737)
  6. Proteinase K (Thermo Fisher Scientific, catalog number: E00491)
  7. Yeast tRNA (Sigma-Aldrich, catalog number: R8759)
  8. Anti H3K27Me3 antibody (Active Motif, catalog number: 39155)
  9. Anti H3 antibody (Abcam, catalog number: ab1791)
  10. Anti H3K4Me3 antibody (Abcam, catalog number: ab8580)
  11. Anti H3K9Me3 antibody (Active Motif, catalog number: 39161)
  12. Collagenase I (Sigma-Aldrich, catalog number: 1148089)
  13. Papain (Sigma-Aldrich, catalog number: 1495005)
  14. Primers (Table 1)

    Table 1. List of primers with unique barcodes

    Primers
    fw ATAC-seq primer, general, no index
    AATGATACGGCGACCACCGAGATCTACACTCGTCGGCAGCGTCAGATGT*G
    rev ATAC-seq primer, Truseq index, 34 CATGGC
    CAAGCAGAAGACGGCATACGAGATGCCATGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 48 TCGGCA
    CAAGCAGAAGACGGCATACGAGATTGCCGAGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 22 CGTACG
    CAAGCAGAAGACGGCATACGAGATCGTACGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 15 ATGTCA
    CAAGCAGAAGACGGCATACGAGATTGACATGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 46 TCCCGA
    CAAGCAGAAGACGGCATACGAGATTCGGGAGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 45 TCATTC
    CAAGCAGAAGACGGCATACGAGATGAATGAGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 40 CTCAGA
    CAAGCAGAAGACGGCATACGAGATTCTGAGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 39 CTATAC CAAGCAGAAGACGGCATACGAGATGTATAGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 38 CTAGCT
    CAAGCAGAAGACGGCATACGAGATAGCTAGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 37 CGGAAT
    CAAGCAGAAGACGGCATACGAGATATTCCGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 36 CCAACA
    CAAGCAGAAGACGGCATACGAGATTGTTGGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 35 CATTTT
    CAAGCAGAAGACGGCATACGAGATAAAATGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 25 ACTGAT
    CAAGCAGAAGACGGCATACGAGATATCAGTGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 26 ATGAG
    CAAGCAGAAGACGGCATACGAGATGCTCATGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 27 ATTCCT
    CAAGCAGAAGACGGCATACGAGATAGGAATGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 28 CAAAAG
    CAAGCAGAAGACGGCATACGAGATCTTTTGGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 23 GAGTGG
    CAAGCAGAAGACGGCATACGAGATCCACTCGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 24 GGTAGC
    CAAGCAGAAGACGGCATACGAGATGCTACCGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 42 TAATCG
    CAAGCAGAAGACGGCATACGAGATCGATTAGTCTCGTGGGCTCGGAGATG*T
    rev ATAC-seq primer, Truseq index, 41 GACGAC
    CAAGCAGAAGACGGCATACGAGATGTCGTCGTCTCGTGGGCTCGGAGATG*T

  15. NEXTERA XT DNA Library prep Kit (Illumina, catalog number: FC-131-1024)
  16. NEBNext High-Fidelity 2x PCR Master Mix (New England Biolabs, catalog number: M0541)
  17. Glycogen (Roche, catalog number: 10901393001)
  18. 37% Formaldehyde (Sigma-Aldrich, catalog number: F8775)
  19. Glycine (Sigma-Aldrich, catalog number: 50046)
  20. Protease Inhibitor Cocktail (Bimake, catalog number: B14001)
  21. Tris Buffer pH 8.0 (Applichem, catalog number: A4577)
  22. EDTA (Sigma-Aldrich, EDS catalog number: EDS-500G)
  23. Sodium Chloride (Sigma-Aldrich, catalog number: S3014)
  24. Triton X-100 (Sigma-Aldrich, catalog number: T8787)
  25. 20% sodium dodecyl sulfate (Sigma-Aldrich, catalog number: 05030)
  26. Nuclease-free water (Qiagen, catalog number: 129115)
  27. Tris (hydroxymethyl) aminomethane (Sigma-Aldrich, catalog number: 252859)
  28. N,N-Dimethylformamide (Sigma-Aldrich, catalog number: D4551)
  29. Qubit dsDNA High Sensitivity Kit (Thermo Fisher Scientific, catalog number: Q33230)
  30. DNA High Sensitivity Kit for Bioanalyzer (Agilent, catalog number: 5067-4627)
  31. Schneider’s medium (Thermo Fisher Scientific, catalog number: 21720-001)
  32. Phenol:Chloroform (Sigma-Aldrich, catalog number: P3803)
  33. 3 M sodium acetate (Thermo Fisher Scientific, catalog number: AM9740)
  34. Ethanol (Sigma-Aldrich, catalog number: 51976)
  35. Hoechst stain (Thermo Fisher Scientific, catalog number: 62249)
  36. MgCl2 (Sigma-Aldrich, catalog number: 63068)
  37. Dissociation Solution (see Recipes)
  38. Blocking Buffer (see Recipes)
  39. RIPA (140 mM) (see Recipes)
  40. RIPA (250 mM) (see Recipes)
  41. TE Buffer (see Recipes)
  42. Tagmentation Buffer (Home-made) (see Recipes)

Equipment

  1. DiaMag 0.2 ml-magnetic rack (Diagenode, catalog number: B04000001)
  2. DynaMag-2 magnetic rack (Thermo Fisher Scientific, catalog number: 12321D)
  3. Bioruptor plus (Diagenode, catalog number: B01020001)
  4. Thermomix compact (Eppendorf, catalog number: T1317)
  5. Bio-Rad PCR Cycler (Bio-Rad, catalog number: C1000)
  6. Mini tube rotator (Biotools, AG, R2001)
  7. Tabletop minicentrifuge (Thermo Fisher Scientific, catalog number: 75002478)
  8. Agilent Bioanalyzer 2100 (Agilent, catalog number: G2939BA)
  9. Qubit Fluorometer 3 (Thermo Fisher Scientific, catalog number: Q33216)
  10. Flow cytometer (BD FACS Aria)

Software

  1. MACS2 (version 2.1.1.20160309, https://github.com/taoliu/MACS)
  2. Deeptools (version 3.1.3, https://github.com/deeptools/deepTools)
  3. Samtools (version 1.09, https://github.com/samtools/samtools)
  4. bowtie2 (version 2.3.5, https://github.com/BenLangmead/bowtie2)
  5. FastQC (version 0.10.1, https://github.com/s-andrews/FastQC)

Procedure

  1. Cell fixation and sorting (human cells)
    1. Harvest the cells in a 1.5 ml Eppendorf tube, and resuspend them in PBS.
    2. Fix the cells for 10 min at room temperature with 1% formaldehyde (in PBS).
    3. Quench the crosslink with 125 mM glycine and incubate for 5 min at room temperature.
    4. Stain the cells with Hoechst stain and use the flow cytometer to sort 100 cells into 200 μl of 140 mM RIPA buffer (Recipe 3).
      Note: Sorting small number of cells will have no effect on buffer composition owing to small volume.

  2. Cell isolation, fixation and sorting (Drosophila neuroblasts)
    1. Dissect the required number of larval brains in PBS (for example: transgenic flies expressing GFP-tagged deadpan (Dpn) protein under the control of its endogenous enhancer).
    2. Wash once with PBS and fix the brains with 1% formaldehyde (in PBT) for 10 min at room temperature.
    3. Quench the crosslink with 125 mM glycine and incubate for 5 min at room temperature.
    4. Remove the quenching solution and wash twice with PBS.
    5. Add the dissociation solution (Recipe 1) to the brain tissue and leave it for 1 h at 30 °C with constant shaking at 650 rpm. Stir the brains at every 15 min interval by pipetting them up and down.
    6. Pellet the cells by centrifuging them at 100 x g and resuspend in PBS.
    7. Sort cells on flow cytometer under GFP channel, and directly sort 1,000 cells into 200 μl of 140 mM RIPA buffer.
      Note: Sorting small number of cells will have no effect on buffer composition owing to small volume.

  3. Immunoprecipitation
    1. Bind 1 μg of antibody to 15 μl of protein G dynabeads in 200 μl blocking buffer (Recipe 2).
    2. Incubate at 4 °C for 2-3 h.
    3. Break the nuclei of the cells collected in RIPA for 3 cycles at low power setting in a Bioruptor sonicator, 30 sec “ON”/“OFF”.
    4. Remove the blocking buffer by putting the tubes on DynaMag-2 magnetic rack, and add the lysate from Step C1.
    5. Incubate at 4 °C for overnight with head over tail rotations.
    6. Separate the beads with magnetic rack and wash twice with 300 μl of home-made tagmentation buffer (Recipe 6) by resuspending the beads with 1,000 μl pipette. Pulse-spin the tubes on micro centrifuge and separate again with DynaMag-2 magnetic rack, remove the buffer as much as possible without disturbing the beads.

  4. Tagmentation, reverse cross linking, and Phenol:Chloroform extraction
    1. Resuspend the beads in 20 μl of 1x tagmentation buffer containing 1 μl of Tn5 transposase (from NEXTERA XT DNA Library prep Kit).
    2. Incubate the resuspended beads at 37 °C for 40 min in a thermoblock with constant shaking at 500 rpm.
    3. Remove tagmentation buffer by separating the beads on DynaMag-2 magnetic rack and wash the beads as following:
      1. Once with 140 mM RIPA;
      2. Four times with 250 mM RIPA (Recipe 4);
      3. Twice with TE buffer (Recipe 5).
      Note: Each wash should be for 3 min and with 200 μl of wash buffer. All the washes should be performed in cold room operating at 4 °C.
    4. Resuspend the washed beads in 100 μl of TE buffer, and add 5 μl of 20 mg/ml proteinase K. Incubate the beads for at least 6 h at 60 °C in thermoblock with shaking at 500 rpm.
    5. Add 100 μl of TE buffer, followed by 300 μl of Phenol:Chloroform. Vortex the tubes briefly and transfer the content to the phase lock tube (pre-spun at 14,000 rpm for 30 s). Centrifuge the tubes at 20,000 x g for 5 min at room temperature.
    6. Transfer the upper aqueous phase to fresh DNA low bind tube, add 5 μl of 20 mg/ml of glycogen and 20 μl of 3 M sodium acetate (pH 5.2) in the exact order, vortex briefly. Add 700 μl of absolute ethanol and vortex briefly. Incubate overnight at -80 °C to precipitate.
    7. Centrifuge the tubes at full speed (20,000 x g ) at 4 °C for 30-45 min. Wash the pellet once with 75% ethanol by centrifuging at 20,000 x g at 4 °C for 10 min and resuspend the pellet in 30 μl of TE buffer.

  5. PCR amplification and purification
    1. Set up the PCR reaction as per the following reaction mix.
      Forward primer (Universal) 20 μM: 2 μl
      Reverse primer (with index) 20 μM: 2 μl
      Reverse cross-linked material: 30 μl
      Nuclease free water: 16 μl
      2x NEBNext High-Fidelity PCR Mix: 50 μl
    2. Run the PCR reaction in a thermal cycler with heated lid set at 105 °C, according to following cycling parameter:
      72 °C for 3 min
      {98 °C for 10 s
      63 °C for 30 s
      72 °C for 30 s}, 12 cycles
      72 °C for 5 min
      Hold at 4 °C.
    3. In the meantime, when PCR reaction is running, remove the Ampure XP beads from 4 °C to room temperature. The Ampure beads should be left at room temperature for at least 30 min to equilibrate, prior to use.
    4. Add 0.2x volume (relative to PCR reaction volume) of Ampure XP beads to the PCR reaction and incubate at room temperature for 5 min. Separate the beads on DiaMag 0.2 ml magnetic rack and carefully transfer the solution without carrying over the beads to a new PCR tube. Discard the Ampure XP beads.
    5. Add 0.8x volume of Ampure XP (relative to PCR reaction volume) beads to the solution and incubate at room temperature for 5 min. Separate the beads on DiaMag 0.2 ml magnetic rack and carefully discard the solution without disturbing the beads.
    6. Wash the beads twice with 200 μl freshly prepared of 80% ethanol, without disturbing the beads.
    7. Dry the beads until the appearance of the bead surface turns from glossy to matte.
    8. Elute the finished library in 10-15 μl of nuclease free water.

  6. Quality control of libraries
    1. Measure the concentration of the library with Qubit dsDNA High Sensitivity Kit, following the manufacture’s protocol.
    2. Run the library on a DNA High Sensitivity Chip with Agilent Bioanalyzer, to check for size distribution of the DNA fragments. Follow the protocol provided with the DNA High Sensitivity Kit for loading and running the sample.
    3. Determine the molar concentration of the library and dilute it to 10 nM concentration or per the requirement of the sequencing facility.
      Note: The concentration of the library and average size fragment of the library (as revealed by Bioanalyzer) is used to calculate the molar concentration. The formula employed to calculate the concentration is, concentration in nM = (concentration in ng/μl from Qubit measurement)/ (660 g/mol x average size of the library) x 106.

Data analysis

  1. Sequence quality check
    Use FastQC to assess the sequencing quality, using fastqc files. Alternatively, one can also use other equivalent QC tools such as MAPQC.
  2. Generate index for reference genomes using bowtie2 (download the fasta files from Ensemble database)
    bowtie2-build -f $FASTA_PATH/genome.fa $INDEX_PATH/bowtie2_index
  3. Mapping the reads either to dm6 or hg38 assembly using bowtie2 (Langmead, 2010)
    bowtie2-x $INDEX_PATH/genome -p 24 -1$SEQ_PATH/*file_1*.gz -2 $SEQ_PATH/*file_2*.gz | samtools view -bS > file.bam
  4. Sorting mapped reads
    Samtools sort file.bam > file.sorted.bam
  5. Indexing bam files
    Samtools index file.bam file.bam.bai
  6. Generating coverage files using DeepTools (Ramirez et al. , 2016)
    bamCoverage–b file.bam–normalizeUsing RPKM-bs 50–smoothLength 175-o file.bw
    A representative track example after generating coverage files is shown in Figure 1.
  7. Peak calling using MACS2, and H3 as control (Zhang et al. , 2008)
    Macs2 callpeak-t $File-c $File -f BAMPE-g d–outdir–name
    Macs2 callpeak-t $File-c $File -f BAMPE-g hs–outdir–name
  8. Heatmaps using DeepTools
    ComputeMatrix scale-regions–S file.bw-R genes.bed–b 600–a 600-o matrix.mat.gz
    plotHeatmap-m matrix.mat.gz-out Heatmap.pdf


    A flow-chart displaying the major steps in the protocol is shown in Figure 1. A representative track example after generating coverage files is shown in Figure 2. The comparison of TAF-ChIP approach performed with 100 cells and recently published CUT&RUN datasets, together with the ENCODE datasets, is shown in Figure 3.


    Figure 1. Steps involved in the Tagmentation Assisted Fragmentation (TAF)-ChIP protocol and subsequent data processing. Steps involved in the TAF-ChIP workflow in chronological order represented as a flow-chart.


    Figure 2. Genome browser track example of H3K4Me3 generated by TAF-ChIP approach and conventional ChIP-Seq approach. Genome browser tracks of ChIP performed in 1,000 FACS sorted Drosophila neural stem cells (NSCs) with TAF-ChIP approach (TAF_K4Me3) and corresponding conventional ChIP-Seq datasets from 1.2 million FACS sorted NSCs (Conv_K4Me3) with independent biological duplicates. The label below the tracks shows the gene model and the y-axis represents normalized read density in reads per million.


    Figure 3. Comparison of TAF-ChIP with conventional ChIP-Seq and with another contemporary low amount method. A. Comparison of TAF-ChIP and CUT&RUN for H3K27Me3 in K562 cells using ROC curves. The plots were generated using the conventional ChIP-Seq ENCODE dataset as reference with 5% FDR cutoff. The peaks for TAF-ChIP replicates and the CUT&RUN datasets were generated with MACS2 without FDR thresholding. Peaks were mapped to 5 kb non-overlapping genomic windows to calculate true-positive rate, false-positive rate and precision for a changing P-Value threshold. Area under the curve (AUC) is indicated in the legend and the* indicates the failure to calculate the AUC. B. Precision-recall curve for TAF-ChIP and CUT&RUN datasets for H3K27Me3 in K562 cells. The figure is adapted from Akhtar et al. (2019).

Recipes

  1. Dissociation Solution
    Schneider’s medium
    1 mg/ml collagenase I
    1 mg/ml papain
  2. Blocking Buffer
    10 mM Tris-Cl pH 8.0
    140 mM NaCl
    0.5 mM EDTA pH 8.0
    1% Triton X-100
    0.1% SDS
    0.2 mg/ml BSA
    0.05 mg/ml Glycogen
    0.2 mg/ml Yeast tRNA
  3. RIPA (140 mM)
    10 mM Tris-Cl pH 8.0
    140 mM NaCl
    0.5 mM EDTA pH 8.0
    1% Triton X-100
    0.1% SDS
  4. RIPA (250 mM)
    10 mM Tris-Cl pH 8.0
    140 mM NaCl
    0.5 mM EDTA pH 8.0
    1% Triton X-100
    0.1% SDS
  5. TE Buffer
    10 mM Tris-Cl pH 8.0
    0.5 mM EDTA pH 8.0
  6. Tagmentation Buffer (Home-made)
    20 mM Tris(hydroxymethyl)aminomethane pH 7.6
    10 mM MgCl2
    20% (vol/vol) dimethyl formamide

Acknowledgments

This work was supported by the Deutsche Forschungsgemeinschaft (DFG) grant DFG BE 4728 1-1 and 3-1. The International PhD Programme (IPP) of the Institute of Molecular Biology, Mainz for supporting the PhD work of S.A. and P.M. We would also like to thank IMB FACS core facility for helping us in sorting.
  This work is a detailed and adapted version of our previously published work (Akhtar et al. , 2019). The FACS sorting workflow was adapted and modified from an earlier work (Berger et al. , 2012).

Competing interests

The authors declare no financial and non-financial competing interest.

Ethics

The described experiments in Drosophila were performed according to the guidelines (Invertebrates are not under animal welfare/ethics laws in Germany). None of the experiments were performed on human subjects.

References

  1. Adli, M., Zhu, J. and Bernstein, B. E. (2010). Genome-wide chromatin maps derived from limited numbers of hematopoietic progenitors. Nat Methods 7(8): 615-618.
  2. Akhtar, J., More, P., Albrecht, S., Marini, F., Kaiser, W., Kulkarni, A., Wojnowski, L., Fontaine, J. F., Andrade-Navarro, M. A., Silies, M. and Berger, C. (2019). TAF-ChIP: an ultra-low input approach for genome-wide chromatin immunoprecipitation assay. Life Sci Alliance 2(4).
  3. Berger, C., Harzer, H., Burkard, T. R., Steinmann, J., van der Horst, S., Laurenson, A. S., Novatchkova, M., Reichert, H. and Knoblich, J. A. (2012). FACS purification and transcriptome analysis of Drosophila neural stem cells reveals a role for Klumpfuss in self-renewal. Cell Rep 2(2): 407-418.
  4. Ghavi-Helm, Y., Zhao, B. and Furlong, E. E. (2016). Chromatin immunoprecipitation for analyzing transcription factor binding and histone modifications in Drosophila . Methods Mol Biol 1478: 263-277.
  5. Langmead, B. (2010). Aligning short sequencing reads with Bowtie. Curr Protoc Bioinformatics Chapter 11: Unit 11.7.
  6. Ramirez, F., Ryan, D. P., Gruning, B., Bhardwaj, V., Kilpert, F., Richter, A. S., Heyne, S., Dundar, F. and Manke, T. (2016). deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res 44(W1): W160-165.
  7. Seguin-Orlando, A., Schubert, M., Clary, J., Stagegaard, J., Alberdi, M. T., Prado, J. L., Prieto, A., Willerslev, E. and Orlando, L. (2013). Ligation bias in illumina next-generation DNA libraries: implications for sequencing ancient genomes. PLoS One 8(10): e78575.
  8. Skene, P. J., Henikoff, J. G. and Henikoff, S. (2018). Targeted in situ genome-wide profiling with high efficiency for low cell numbers. Nat Protoc 13(5): 1006-1019.
  9. Stathopulos, P. B., Scholz, G. A., Hwang, Y. M., Rumfeldt, J. A., Lepock, J. R. and Meiering, E. M. (2004). Sonication of proteins causes formation of aggregates that resemble amyloid. Protein Sci 13(11): 3017-3027.
  10. Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W. and Liu, X. S. (2008). Model-based analysis of ChIP-Seq (MACS). Genome Biol 9(9): R137.
  11. Zheng, X., Yue, S., Chen, H., Weber, B., Jia, J. and Zheng, Y. (2015). Low-Cell-Number epigenome profiling aids the study of lens aging and hematopoiesis. Cell Rep 13(7): 1505-1518.

简介

[摘要] 染色质免疫沉淀被广泛用于研究基因组中的表观遗传概况和转录因子结合位点。然而,当起始材料有限时,常规的ChIP -Seq方法无法实现。该协议描述了一种可用于从低至100个人或1,000 果蝇细胞生成染色质图谱的方法。该方法采用标签化法,以染色质片段化,同时添加测序适配器。该方法生成具有高信噪比的数据集,并且可以使用标准工具进行ChIP -Seq分析。

[背景 ] È pigenetic状态和转录因子的占用是基因表达的关键决定因素。要理解这个regulat 离子,染色质功能的精确测绘是非常重要的。染色质免疫沉淀与下一代测序相结合是一项强大的技术,可为深入了解染色质特征的全基因组分布提供有价值的见解(Ghavi-Helm 等人,2016)。这种技术虽然功能强大,但由于需要大量的起始原料而在某些情况下很难满足(即使不是完全不可能),但该技术的应用受到了限制。这种局限性促使许多近期努力使ChIP- Seq方法适用于少量起始原料或稀有细胞类型(Adli 等,2010 ;Zheng 等,2015 )。这些努力的主要限制之一是使用超声或MNAse 片段化染色质。前一种方法以有限的量存在对表位是有害的,因为它可以导致用于随后的免疫沉淀的表位的破坏(Stathopulos 等人,2004)。另一方面,MNAse 方法的功效和饱和度很难控制。CUT&RUN方法的最新应用已成功使用抗体靶向的微球菌核酸酶从100个细胞的样品中生成了谱图(Skene 等人,2018)。但是,所有这些方法仍然诉诸于基于连接的涉及多个步骤的文库制备方法,这可能导致变异性增加以及复杂性的损失(Seguin-Orlando 等人,2 0 13 )。此处描述的方法通过使用可商购的Tn5酶使染色质片段化,同时用较少的中间步骤s 制备文库,克服了这些限制。CUT&RUN方法与TAF- ChIP 的直接比较揭示了后者具有更高的信噪比,并使用了适合该方法的标准生物信息学管道。

关键字:低细胞量ChIP-Seq, 简易工作流程, 高信噪比, Tagmentation技术, 重现性好

材料和试剂


 


DNA低结合力1.5 ml管(Eppendorf,目录号:0030108051)
锁相管(5Prime,货号:2302830)
Agencourt AMPure XP珠子(Beckmann Coultier ,目录号:A63381)
Protein G Dynabeads (Thermo Fisher Scientific,目录号:10003D)
BSA(Sigma-Aldrich,目录号:A4737)
蛋白酶K(Thermo Fisher Scientific,目录号:E00491)
酵母tRNA(Sigma-Aldrich,目录号:R8759 )
抗H3K27Me3抗体(Active Motif,目录号:39155)
抗H3抗体(Abcam,目录号:ab1791)
抗H3K4Me3抗体(Abcam,目录号:ab8580)
抗H3K9Me3抗体(Active Motif,目录号:39161)
胶原酶I(Sigma-Aldrich,目录号:1148089)
木瓜蛋白酶(Sigma-Aldrich,目录号:1495005)
底漆(表1)
 


表1. 具有唯一条形码的引物列表


 


底漆


fw ATAC-seq底漆,常规,无索引


AATGATACGGCGACCACCGAGATCTACACTCGTCGGCAGCGTCAGATGT * G


rev ATAC-seq引物,Truseq 指数,34 CATGGC


CAAGCAGAAGACGGCATACGAGATGCCATGGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,48 TCGGCA


CAAGCAGAAGACGGCATACGAGATTGCCGAGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,22 CGTACG


CAAGCAGAAGACGGCATACGAGATCGTACGGTCTCGTGGGCTCGGAGATG * T


转ATAC-seq引物,Truseq 指数,15 ATGTCA


CAAGCAGAAGACGGCATACGAGATTGACATGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,46 TCCCGA


CAAGCAGAAGACGGCATACGAGATTCGGGAGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,45 TCATTC


CAAGCAGAAGACGGCATACGAGATGAATGAGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,40 CTCAGA


CAAGCAGAAGACGGCATACGAGATTCTGAGGTCTCGTGGGCTCGGAGATG * T


转ATAC-seq引物,Truseq 指数,39 CTATAC


CAAGCAGAAGACGGCATACGAGATGTATAGGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,38 CTAGCT


CAAGCAGAAGACGGCATACGAGATAGCTAGGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,37 CGGAAT


CAAGCAGAAGACGGCATACGAGATATTCCGGTCTCGTGGGCTCGGAGATG * T


转ATAC-seq引物,Truseq 指数,36 CCAACA


CAAGCAGAAGACGGCATACGAGATTGTTGGGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,35 CATTTT


CAAGCAGAAGACGGCATACGAGATAAAATGGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,25 ACTGAT


CAAGCAGAAGACGGCATACGAGATATCAGTGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,26 ATGAGC


CAAGCAGAAGACGGCATACGAGATGCTCATGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,27 ATTCCT


CAAGCAGAAGACGGCATACGAGATAGGAATGTCTCGTGGGCTCGGAGATG * T


修订版ATAC-seq引物,Truseq 指数,28 CAAAAG


CAAGCAGAAGACGGCATACGAGATCTTTTGGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,23 GAGTGG


CAAGCAGAAGACGGCATACGAGATCCACTCGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,24 GGTAGC


CAAGCAGAAGACGGCATACGAGATGCTACCGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,42 TAATCG


CAAGCAGAAGACGGCATACGAGATCGATTAGTCTCGTGGGCTCGGAGATG * T


rev ATAC-seq引物,Truseq 指数,41 GACGAC


CAAGCAGAAGACGGCATACGAGATGTCGTCGTCTCGTGTGGGCTCGGAGATG * T


 


NEXTERA XT DNA文库制备试剂盒(Illumina,目录号:FC-131-1024)
NEBNext 高保真2x PCR 预混液(New England Biolabs,目录号:M0541)
糖原(罗氏(Roche),货号:10901393001)
37%甲醛(Sigma-Aldrich,目录号:F8775)
甘氨酸(Sigma-Aldrich,目录号:50046 )
蛋白酶抑制剂混合物(乙imake的,猫考勤号:B14001)
Tris Buffer pH 8.0(Applichem ,目录号:A4577)
EDTA(Sigma-Aldrich,EDS 目录号:EDS-500G )
氯化钠(Sigma-Aldrich,目录号:S3014)
海卫一X-100(Sigma-Aldrich,目录号:T8787)
20%十二烷基硫酸钠(Sigma-Aldrich,目录号:05030)
核酸酶- ˚F REE 瓦特亚特(QIAGEN,目录号:129115)
三(羟甲基)氨基甲烷(Sigma-Aldrich,目录号:252859 )
N,N- - 二甲基甲酰胺(Sigma-Aldrich公司,目录号:D4551)
Qubit dsDNA高灵敏度试剂盒(Thermo Fisher Scientific,目录号:Q33230)
用于生物分析仪的DNA高灵敏度试剂盒(安捷伦,目录号:5067-4627)
施耐德的介质(Thermo Fisher Scientific ,目录号21720-001)
苯酚:氯仿(Sigma-Aldrich,目录号:P3803 )
3 M乙酸钠(Thermo Fisher Scientific,目录号:AM9740 )
乙醇(Sigma-Aldrich,目录号:51976 )
赫斯特染色(Thermo Fisher Scientific,目录号:62249)
MgCl 2 (Sig ma-Aldrich,目录号:63068 )
解离解决方案(请参阅食谱)
阻塞缓冲区(请参见配方)
RIPA(140 mM)(请参阅食谱)
RIPA(250 mM)(请参阅食谱)                           
TE缓冲液(请参阅配方)
标记缓冲液(自制)(请参见食谱)
 


设备


 


DiaMag 0.2 ml磁力架(Diagenode ,目录号:B04000001)
DynaMag-2磁架(Thermo Fisher Scientific,目录号:12321D)
Bioruptor plus(Diagenode ,目录号:B01020001)
紧凑型Thermomix(Eppendorf,目录号:T1317)
Bio-Rad PCR循环仪(Bio-Rad,目录号:C1000)
微型管旋转器(Biotools ,AG,R2001)
台式微型离心机(Thermo Fisher Scientific,目录号:75002478)
安捷伦生物分析仪2100(安捷伦,目录号:G2939BA)
Qubit荧光计3(Thermo Fisher Scientific,目录号:Q33216)
流式细胞仪(BD FACS Aria)
 


软件


 


MACS2(版本2.1.1.20160309,https://github.com/taoliu/MACS)
Deeptools(版本3.1.3,https://github.com/deeptools/deepTools)
Samtools(版本1.09,https://github.com/samtools/samtools)
bowtie2(版本2.3.5,https://github.com/BenLangmead/bowtie2)
FastQC (版本0.10.1,https://github.com/s-andrews/FastQC)
 


程序


 


细胞固定和小号奥廷(人类细胞)
将细胞收集在1.5 ml Eppendorf管中,并重悬于PBS中。
在室温下用1%甲醛(在PBS中)固定细胞10分钟。
用125 mM甘氨酸淬灭交联键,并在室温下孵育5分钟。
用Hoechst染色剂染色细胞,并使用流式细胞仪将100个细胞分类为200个 μ升的140mM的RIPA缓冲液(配方3)。
注意:由于小体积,对少量单元格进行排序不会对缓冲液成分产生影响。


 


细胞我溶胶化,固定和š 奥廷(果蝇神经母细胞)
在PBS中解剖所需数量的幼虫大脑(例如:在其内源性增强子的控制下表达GFP标记的无活性(Dpn )蛋白的转基因果蝇)。
用PBS洗涤一次,并在室温下用1%甲醛(在PBT中)固定大脑10分钟。
用125 mM甘氨酸淬灭交联键,并在室温下孵育5分钟。
重新移动至骤冷溶液,并用PBS洗两次。
解离溶液(配方1)添加到脑组织和离开它在30 1个小时 ℃下用恒定在650rpm下振荡培养。每隔15分钟向上或向下吹动一次,以搅动大脑。
通过以100 xg 离心将细胞沉淀,然后重悬于PBS中。
排序细胞上GFP通道下的流式细胞仪,并直接排序1 ,000细胞进入200 μ 升的140mM的RIPA缓冲液。
注意:由于小体积,对少量单元格进行排序不会对缓冲液成分产生影响。


 


 


免疫沉淀
绑定1 μ 克抗体至15中的μ 升G蛋白的磁珠在200 μ 升封闭缓冲液(配方2)。
在4 °C 孵育2-3小时。
在Bio ruptor 超声仪中,在低功率设置下,“打开” / “关闭” 30秒,将RIPA中收集的细胞的细胞核破碎3个循环。
将试管放在DynaMag-2磁力架上,除去封闭缓冲液,然后添加步骤C1中的裂解物。
头朝尾旋转,在4 °C下孵育过夜。
与磁性架分离珠和用300洗两次μ 升自制的tagmentation 通过再悬浮与1000珠缓冲液(配方6)μ 升移液管。在微量离心机上脉冲旋转离心管,然后用DynaMag-2磁力架再次分离,在不干扰磁珠的情况下尽可能多地除去缓冲液。
 


标记,反向交联和苯酚:氯仿萃取
重悬20珠粒μ 升1X的tagmentation 缓冲器含有1 μ 升Tn5转座酶(来自NEXTERA XT DNA文库制备试剂盒)。
将重悬的磁珠在热块中于37 °C 孵育40分钟,并以500 rpm的速度恒定摇动。
除去tagmentation 通过分离珠缓冲器上DynaMag-2磁架一第二洗珠如下:
一次使用140 mM RIPA ;
˚F 我们时代用250mM RIPA(配方4);
Ť WICE用TE缓冲液(配方5)。
注意:EAC ħ洗涤应该是3分钟,并用200 μ 升洗涤缓冲液中。所有洗涤均应在4 °C的冷藏室中进行。


在重悬在100洗涤的珠μ 升TE缓冲液中,并加入5 μ 升20毫克/毫升蛋白酶K孵育在60珠子至少6小时℃的热块中在500rpm摇动。
添加100 μ 升TE缓冲液中,接着300 μ 升的苯酚:氯仿。短暂涡旋试管,然后将内含物转移至锁相管(以14,000 rpm预纺30 s)。在室温下,将试管以20,000 xg离心5分钟。
上层水相转移到新鲜DNA低绑定管中,加入5 μ 升20毫克/毫升糖原和20的μ 升的的确切顺序3M乙酸钠(pH 5.2),涡流简要。加入700 μ 升的无水乙醇和涡简要介绍。在-80 °C下孵育过夜以沉淀。
将试管在4 °C下以全速(20,000 xg )离心30-45分钟。通过以20,000离心洗涤沉淀一次用75%乙醇X 克在4℃下10分钟,并重新悬浮在30颗粒μ 升TE缓冲液。
 


PCR扩增和纯化
按照以下反应混合物设置PCR反应。
正向引物(通用)20 μ 中号:2 μ 升


反向引物(具有索引)20 μ 中号:2 μ 升


反向的交联材料:30 μ 升


不含核酸酶的水:16 μ 升


2X NEBNext 高保真PCR混合物:50 μ 升


根据以下循环参数,在加热盖设为105 °C 的热循环仪中运行PCR反应:
72°C 3分钟


{98°C持续10 s


63°C持续30 s


72°C 30 s},12个循环


72°C 5分钟


保持在4℃。


同时,在进行PCR反应时,将Ampure XP珠子从4 °C 移至室温。使用前,应将Ampure 珠子在室温下放置至少30分钟以使其平衡。
将0.2x体积(相对于PCR反应体积)的Ampure XP微珠添加到PCR反应中,并在室温下孵育5分钟。在DiaMag 0.2 ml磁力架上分离珠子,小心转移溶液,不要将珠子移到新的PCR管中。丢弃Ampure XP珠子。
向溶液中加入0.8x 体积的Ampure XP(相对于PCR反应体积)珠子,并在室温下孵育5分钟。将珠子在DiaMag 0.2 ml磁力架上分开,小心丢弃溶液,不要打扰珠子。
用洗涤珠两次200 μ 升新鲜制备的80%乙醇,在不干扰珠子。
干燥小珠,直到小珠表面的外观从光泽变为无光泽。
洗脱成品库10-15 μ 升的无核酸酶的水。
 


图书馆的质量控制
按照制造商的规程,使用Qubit dsDNA高灵敏度试剂盒测量文库的浓度。
使用Agilent Bioanalyzer在DNA高灵敏度芯片上运行文库,以检查DNA片段的大小分布。按照DNA高灵敏度试剂盒随附的规程装载和运行样品。
确定文库的摩尔浓度,并按照测序设备的要求将其稀释至10 nM 浓度。
注意:文库的浓度和文库的平均大小片段(如Bioanalyzer所示)用于计算摩尔浓度。用来计算浓度的公式是,浓度在纳米=(以ng /浓度μ 升从量子比特测量)/(660克库/摩尔X平均大小)×10 6 。


 


数据一nalysis


 


序列质量检查
使用FastQC 通过fastqc 文件评估测序质量。或者,也可以使用其他等效的QC工具,例如MAPQC。


使用Bowtie2生成参考基因组的索引(从Ensemble数据库下载fasta 文件)
bowtie2-build -f $ FASTA_PATH / 基因组.fa $ INDEX_PATH / bowtie2_index


使用bowtie2 (Langmead,20 10 )将读取结果映射到dm6或hg38程序集
bowtie2 -x $ INDEX_PATH / genome -p 24 -1 $ SEQ_PATH / * file_1 * .gz -2 $ SEQ_PATH / * file_2 * .gz | samtools 查看- 将bS > file.bam


排序映射读
Samtools 排序file.bam > file.sorted.bam


索引bam文件
Samtools 索引file.bam file.bam.bai


使用DeepTools 生成coverage文件(Ramirez 等,20 16 )
bamCoverage –b file.bam –规范化使用RPKM -bs 50 – smoothLength 175 -o file.bw


生成coverage文件后的代表性跟踪示例如图1所示。


使用MACS2和H3作为控制的峰值调用(Zhang 等,20 08 )
Macs2 callpeak -t $ File -c $ File -f BAMPE-g d – outdir –name


Macs2 callpeak -t $ File -c $ File -f BAMPE-g hs – outdir – 名称


使用DeepTools的热图
C omputeMatrix 标度区域– S file.bw- Rgenes.bed –b 600 –a 600 -o matrix.mat.gz


plotHeatmap -m matrix.mat.gz -out Heatmap.pdf


 


                            流程图显示了协议中的主要步骤,如图1所示。生成覆盖文件后的代表性跟踪示例如图2所示。使用100个小区和最近发布的CUT&RUN数据集进行的TAF- ChIP 方法的比较,连同ENCODE数据集,如图3所示。


 






图1的步骤中涉及的Tagmentati 上辅助碎片(TAF)- 的ChIP 协议和随后的数据处理。TAF- ChIP 工作流程中涉及的步骤按时间顺序表示为流程图。


 






图2.通过TAF- ChIP 方法和常规ChIP - Seq 方法生成的H3K4Me3的基因组浏览器跟踪示例。的基因组浏览器轨道的ChIP 在1中执行,000 FACS分选的果蝇神经干细胞(NSCs)与TAF- 的ChIP 方法(TAF_K4Me3)和相应的传统的ChIP -Seq数据集从120万个FACS分选的与独立的生物重复的NSCs(Conv_K4Me3)。轨道下方的标签显示了基因模型,y轴表示标准化的读取密度(百万分之一读取)。


 






图3. TAF- ChIP 与常规ChIP- Seq以及另一种现代少量方法的比较。A. 使用ROC曲线比较K562细胞中H3K27Me3的TAF- ChIP 和CUT&RUN。使用常规ChIP -Seq ENCODE数据集作为参考,以FDR截止值为5%生成图。TAF- ChIP 复制和CUT&RUN数据集的峰是使用无FDR阈值的MACS2生成的。将峰映射到5 kb非重叠基因组窗口,以计算变化的P值阈值的真阳性率,假阳性率和精度。图例中显示了曲线下的面积(AUC),*表示无法计算AUC。B. K56 2细胞中H3K27Me3的TAF - ChIP 和CUT&RUN数据集的精确调用曲线。该图改编自Akhtar 等人。(2019)。


 


菜谱


 


解离溶液
施耐德的媒介


1 mg / ml胶原酶I


1毫克/毫升木瓜蛋白酶


阻塞缓冲
10毫米Tris-Cl pH 8.0             


140毫米氯化钠


0.5 mM EDTA pH 8.0


1%的Triton X-100


0.1%SDS


0.2 mg / ml牛血清白蛋白


0.05 mg / ml糖原


0.2 mg / ml酵母tRNA


RIPA(140毫米)
10毫米Tris-Cl pH 8.0


140毫米氯化钠


0.5 mM EDTA pH 8.0


1%的Triton X-100


0.1%SDS


RIPA(250毫米)                           
10毫米Tris-Cl pH 8.0             


140毫米氯化钠


0.5 mM EDTA pH 8.0


1%的Triton X-100


0.1%SDS


TE缓冲液
10毫米Tris-Cl pH 8.0


0.5 mM EDTA pH 8.0


标记缓冲液(自制)
20 mM三(羟甲基)氨基甲烷pH 7.6


10毫米MgCl 2


20%(体积/体积)二甲基甲酰胺


 


致谢


 


这项工作得到了德国联邦储蓄基金会(DFG)授予DFG BE 4728 1-1和3-1的支持。美因茨分子生物学研究所的国际博士学位计划(IPP)支持SA的博士学位工作。和PM 。我们还要感谢IMB FACS核心设施为我们的分类提供了帮助。


  这项工作是我们之前发表的工作的详细改编版本(Akhtar 等,2019)。FACS分拣工作流程是根据早期工作改编和修改的(Berger 等,2012 )。


 


利益争夺


 


作者声明没有任何金融和非金融竞争利益。


 


伦理


 


在果蝇中描述的实验是根据指导原则进行的(无脊椎动物不在德国的动物福利/道德法律范围内)。这些实验均未在人类受试者上进行。


 


 


 


参考文献


 


Adli ,M.,Zhu,J. and Bernstein,BE(2010)。全基因组染色质图谱来自有限数量的造血祖细胞。Nat Methods 7(8):615-618。
Akhtar,J.,More,P.,Albrecht,S.,Marini,F.,Kaiser,W.,Kulkarni,A.,Wojnowski L.,Fontaine,JF,Andrade-Navarro,MA,Silies ,M.和Berger,C.(2019年)。TAF-ChIP:全基因组染色质免疫沉淀测定的超低输入法。生命科学联盟2(4)。
Berger,C.,Harzer ,H.,Burkard,TR,Steinmann,J.,van der Horst,S.,Laurenson ,AS,Novatchkova M.,Reichert,H.和Knoblich ,JA(2012)。FACS净化和转录组分析d rosophila 神经干细胞揭示了Klumpfuss在自我更新的作用。Cell Rep 2(2):407-418。
Ghavi- Helm,Y.,Zhao B. and Furlong,EE(2016)。染色质免疫沉淀分析转录因子结合和组蛋白米在odifications 果蝇。方法分子生物学1478:263-277。
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引用:Akhtar, J., More, P. and Albrecht, S. (2020). ChIP-Seq from Limited Starting Material of K562 Cells and Drosophila Neuroblasts Using Tagmentation Assisted Fragmentation Approach. Bio-protocol 10(4): e3520. DOI: 10.21769/BioProtoc.3520.
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