ChIL-sequencing

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ChIL sequencing (ChIL-seq), also known as Chromatin Integration Labeling sequencing, is a method used to analyze protein interactions with DNA. ChIL-sequencing combines antibody-targeted controlled cleavage by Tn5 transposase with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. It can be used to map global DNA binding sites precisely for any protein of interest. Currently, ChIP-Seq is the most common technique utilized to study protein–DNA relations, however, it suffers from a number of practical and economical limitations that ChIL-Sequencing does not. ChIL-Seq is a precise technique that reduces sample loss could be applied to single-cells. [1]

Uses[edit]

ChIL-sequencing can be used to examine gene regulation or to analyze transcription factor and other chromatin-associated protein binding. Protein-DNA interactions regulate gene expression and are responsible for many biological processes and disease states. This epigenetic information is complementary to genotype and expression analysis. ChIL-Seq is an alternative to the current standard of ChIP-seq. ChIP-Seq suffers from limitations due to the cross linking step in ChIP-Seq protocols that can promote epitope masking and generate false-positive binding sites.[2][3] As well, ChIP-seq suffers from suboptimal signal-to-noise ratios and poor resolution.[4] ChIL-sequencing has the advantage of being a simpler technique suitable for low sample input due to the high signal-to-noise ratio, requiring less depth in sequencing for higher sensitivity.[5]

Specific DNA sites in direct physical interaction with proteins such as transcription factors can be isolated by Protein-A (pA) conjugated Tn5 bound to a protein of interest. Tn5 mediated cleavage produces a library of target DNA sites bound to a protein of interest in situ. Sequencing of prepared DNA libraries and comparison to whole-genome sequence databases allows researchers to analyze the interactions between target proteins and DNA, as well as differences in epigenetic chromatin modifications. Therefore, the ChIL-Seq method may be applied to proteins and modifications, including transcription factors, polymerases, structural proteins, protein modifications, and DNA modifications.

Protocols[edit]

There are detailed ChIL-Seq workflows available in an open-access methods repository.[6]

Limitations[edit]

The primary limitation of ChIL-seq is the likelihood of over-digestion of DNA due to inappropriate timing of the Magnesium-dependent Tn5 reaction. This is biased towards open chromatin like ATAC-Seq and similar techniques.[5] A similar limitation exists for contemporary ChIP-Seq protocols where enzymatic or sonicated DNA shearing must be optimized. As with ChIP-Seq, a good quality antibody targeting the protein of interest is required. As with other techniques using Tn5, the library preparation has a strong GC bias and has poor sensitivity in low GC regions or genomes with high variance in GC content.[7][8][9]


ChIL-Seq requires numerous laboratory steps and takes longer than other techniques such as CUT&RUN or CUT&Tag. It is still a broadly applicable technique which avoids sample loss suitable for small numbers of cells. However, the consumables cost of ChIL-Seq is substantially lower allowing more samples to be processed. [10]

Similar methods[edit]

  • Sono-Seq: Identical to ChIP-Seq but without the immunoprecipitation step.
  • HITS-CLIP: Also called CLIP-Seq, employed to detect interactions with RNA rather than DNA.
  • PAR-CLIP: A method for identifying the binding sites of cellular RNA-binding proteins.
  • RIP-Chip: Similar to ChIP-Seq, but does not employ cross linking methods and utilizes microarray analysis instead of sequencing.
  • SELEX: Employed to determine consensus binding sequences.
  • Competition-ChIP: Measures relative replacement dynamics on DNA.
  • ChiRP-Seq: Measures RNA-bound DNA and proteins.
  • ChIP-exo: Employs exonuclease treatment to achieve up to single base-pair resolution
  • ChIP-nexus: Potential improvement on ChIP-exo, capable of achieving up to single base-pair resolution.
  • DRIP-seq: Employs S9.6 antibody to precipitate three-stranded DND:RNA hybrids called R-loops.
  • TCP-seq: Principally similar method to measure mRNA translation dynamics.
  • DamID: Uses enrichment of methylated DNA sequences to detect protein-DNA interaction without antibodies.

See also[edit]

References[edit]

  1. ^ "When less is more: A promising approach for low-cell-number epigenomic profiling". Science Daily. 11 December 2018. Retrieved 24 December 2019.
  2. ^ Meyer CA, Liu XS (November 2014). "Identifying and mitigating bias in next-generation sequencing methods for chromatin biology". Nature Reviews. Genetics. 15 (11): 709–21. doi:10.1038/nrg3788. PMC 4473780. PMID 25223782.
  3. ^ Baranello L, Kouzine F, Sanford S, Levens D (May 2016). "ChIP bias as a function of cross-linking time". Chromosome Research. 24 (2): 175–81. doi:10.1007/s10577-015-9509-1. PMC 4860130. PMID 26685864.
  4. ^ He C, Bonasio R (February 2017). "A cut above". eLife. 6. doi:10.7554/eLife.25000. PMC 5310838. PMID 28199181.
  5. ^ a b Harada A, Maehara K, Handa T, Arimura Y, Nogami J, Hayashi-Takanawa Y, Shirahige K, Kurumizaka H, Kimura H, Ohkawa Y (December 2018). "A chromatin integration labelling method enables epigenomic profiling with lower input". Nature Cell Biology. 21 (2): 287–296. doi:10.1038/s41556-018-0248-3. PMID 30532068. S2CID 54463772.
  6. ^ Ohkawa Y, Kimura H, Handa T, Harada A, Maehara K (20 Dec 2018). "Detailed protocol ─ Chromatin Integration labeling". Protocol Exchange. doi:10.1038/protex.2018.122.
  7. ^ Lan, James H.; Yin, Yuxin; Reed, Elaine F.; Moua, Kevin; Thomas, Kimberly; Zhang, Qiuheng (March 2015). "Impact of three Illumina library construction methods on GC bias and HLA genotype calling". Human Immunology. 76 (2–3): 166–175. doi:10.1016/j.humimm.2014.12.016. PMC 5089167. PMID 25543015.
  8. ^ Sato, Mitsuhiko P; Ogura, Yoshitoshi; Nakamura, Keiji; Nishida, Ruriko; Gotoh, Yasuhiro; Hayashi, Masahiro; Hisatsune, Junzo; Sugai, Motoyuki; Takehiko, Itoh; Hayashi, Tetsuya (1 October 2019). "Comparison of the sequencing bias of currently available library preparation kits for Illumina sequencing of bacterial genomes and metagenomes". DNA Research. 26 (5): 391–398. doi:10.1093/dnares/dsz017. PMC 6796507. PMID 31364694.
  9. ^ Chen, Yen-Chun; Liu, Tsunglin; Yu, Chun-Hui; Chiang, Tzen-Yuh; Hwang, Chi-Chuan (29 April 2013). "Effects of GC Bias in Next-Generation-Sequencing Data on De Novo Genome Assembly". PLOS ONE. 8 (4): e62856. Bibcode:2013PLoSO...862856C. doi:10.1371/journal.pone.0062856. PMC 3639258. PMID 23638157.
  10. ^ Handa, Tetsuya; Harada, Akihito; Maehara, Kazumitsu; Sato, Shoko; Nakao, Masaru; Goto, Naoki; Kurumizaka, Hitoshi; Ohkawa, Yasuyuki; Kimura, Hiroshi (October 2020). "Chromatin integration labeling for mapping DNA-binding proteins and modifications with low input". Nature Protocols. 15 (10): 3334–3360. doi:10.1038/s41596-020-0375-8. PMID 32807906. S2CID 221145784. Retrieved 3 December 2020.
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