AlleleProfileR: A versatile tool to identify and profile sequence variants in edited genomes
Autoři:
Arne A. N. Bruyneel aff001; Alexandre R. Colas aff003; Ioannis Karakikes aff001; Mark Mercola aff001
Působiště autorů:
Stanford Cardiovascular Institute, Stanford School of Medicine, Stanford, CA United States of America
aff001; Department of Medicine, Division of Cardiovascular Medicine, Stanford School of Medicine, Stanford, CA, United States of America
aff002; Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, United States of America
aff003; Department of Cardiothoracic Surgery, Stanford School of Medicine, Stanford, CA, United States of America
aff004
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0226694
Souhrn
Gene editing strategies, such as zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeat/Cas9 (CRISPR/Cas9), are revolutionizing biology. However, quantitative and sensitive detection of targeted mutations are required to evaluate and quantify the genome editing outcomes. Here we present AlleleProfileR, a new analysis tool, written in a combination of R and C++, with the ability to batch process the sequence analysis of large and complex genome editing experiments, including the recently developed base editing technologies.
Klíčová slova:
Genome analysis – Sequence alignment – Point mutation – Embryos – Genome complexity – CRISPR – Non-homologous end joining – Zinc finger nucleases
Zdroje
1. Kim YG, Cha J, Chandrasegaran S. Hybrid restriction enzymes: zinc finger fusions to Fok I cleavage domain. Proc Natl Acad Sci U S A. 1996;93(3):1156–60. doi: 10.1073/pnas.93.3.1156 8577732; PubMed Central PMCID: PMC40048.
2. Boch J, Scholze H, Schornack S, Landgraf A, Hahn S, Kay S, et al. Breaking the code of DNA binding specificity of TAL-type III effectors. Science. 2009;326(5959):1509–12. doi: 10.1126/science.1178811 19933107.
3. Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, Charpentier E. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science. 2012;337(6096):816–21. Epub 2012/06/28. doi: 10.1126/science.1225829 22745249.
4. Jasin M, Rothstein R. Repair of strand breaks by homologous recombination. Cold Spring Harb Perspect Biol. 2013;5(11):a012740. Epub 2013/11/01. doi: 10.1101/cshperspect.a012740 24097900; PubMed Central PMCID: PMC3809576.
5. Chiruvella KK, Liang Z, Wilson TE. Repair of double-strand breaks by end joining. Cold Spring Harb Perspect Biol. 2013;5(5):a012757. Epub 2013/05/01. doi: 10.1101/cshperspect.a012757 23637284; PubMed Central PMCID: PMC3632057.
6. Kaur B, Perea-Gil I, Karakikes I. Recent Progress in Genome Editing Approaches for Inherited Cardiovascular Diseases. Curr Cardiol Rep. 2018;20(7):58. Epub 2018/06/02. doi: 10.1007/s11886-018-0998-3 29860642.
7. Gaudelli NM, Komor AC, Rees HA, Packer MS, Badran AH, Bryson DI, et al. Programmable base editing of A•T to G•C in genomic DNA without DNA cleavage. Nature. 2017;551(7681):464–71. Epub 2017/10/25. doi: 10.1038/nature24644 29160308; PubMed Central PMCID: PMC5726555.
8. Komor AC, Kim YB, Packer MS, Zuris JA, Liu DR. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature. 2016;533(7603):420–4. Epub 2016/04/20. doi: 10.1038/nature17946 27096365; PubMed Central PMCID: PMC4873371.
9. Wang H, Yang H, Shivalila CS, Dawlaty MM, Cheng AW, Zhang F, et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell. 2013;153(4):910–8. Epub 2013/05/02. doi: 10.1016/j.cell.2013.04.025 23643243; PubMed Central PMCID: PMC3969854.
10. Crispo M, Mulet AP, Tesson L, Barrera N, Cuadro F, dos Santos-Neto PC, et al. Efficient Generation of Myostatin Knock-Out Sheep Using CRISPR/Cas9 Technology and Microinjection into Zygotes. PLoS One. 2015;10(8):e0136690. Epub 2015/08/25. doi: 10.1371/journal.pone.0136690 26305800; PubMed Central PMCID: PMC4549068.
11. Sato M, Miyoshi K, Nagao Y, Nishi Y, Ohtsuka M, Nakamura S, et al. The combinational use of CRISPR/Cas9-based gene editing and targeted toxin technology enables efficient biallelic knockout of the α-1,3-galactosyltransferase gene in porcine embryonic fibroblasts. Xenotransplantation. 2014;21(3):291–300. Epub 2014/02/21. doi: 10.1111/xen.12089 24919525.
12. Edvardsen RB, Leininger S, Kleppe L, Skaftnesmo KO, Wargelius A. Targeted mutagenesis in Atlantic salmon (Salmo salar L.) using the CRISPR/Cas9 system induces complete knockout individuals in the F0 generation. PLoS One. 2014;9(9):e108622. Epub 2014/09/25. doi: 10.1371/journal.pone.0108622 25254960; PubMed Central PMCID: PMC4177897.
13. Cho SW, Lee J, Carroll D, Kim JS. Heritable gene knockout in Caenorhabditis elegans by direct injection of Cas9-sgRNA ribonucleoproteins. Genetics. 2013;195(3):1177–80. Epub 2013/08/26. doi: 10.1534/genetics.113.155853 23979576; PubMed Central PMCID: PMC3813847.
14. Shalem O, Sanjana NE, Hartenian E, Shi X, Scott DA, Mikkelson T, et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science. 2014;343(6166):84–7. Epub 2013/12/12. doi: 10.1126/science.1247005 24336571; PubMed Central PMCID: PMC4089965.
15. Cunningham TJ, Yu MS, McKeithan WL, Spiering S, Carrette F, Huang CT, et al. Id genes are essential for early heart formation. Genes Dev. 2017;31(13):1325–38. Epub 2017/08/09. doi: 10.1101/gad.300400.117 28794185; PubMed Central PMCID: PMC5580654.
16. Zhou J, Shen B, Zhang W, Wang J, Yang J, Chen L, et al. One-step generation of different immunodeficient mice with multiple gene modifications by CRISPR/Cas9 mediated genome engineering. Int J Biochem Cell Biol. 2014;46:49–55. Epub 2013/11/20. doi: 10.1016/j.biocel.2013.10.010 24269190.
17. Park J, Lim K, Kim JS, Bae S. Cas-analyzer: an online tool for assessing genome editing results using NGS data. Bioinformatics. 2017;33(2):286–8. Epub 2016/08/24. doi: 10.1093/bioinformatics/btw561 27559154; PubMed Central PMCID: PMC5254075.
18. Güell M, Yang L, Church GM. Genome editing assessment using CRISPR Genome Analyzer (CRISPR-GA). Bioinformatics. 2014;30(20):2968–70. Epub 2014/07/01. doi: 10.1093/bioinformatics/btu427 24990609; PubMed Central PMCID: PMC4184265.
19. Pinello L, Canver MC, Hoban MD, Orkin SH, Kohn DB, Bauer DE, et al. Analyzing CRISPR genome-editing experiments with CRISPResso. Nat Biotechnol. 2016;34(7):695–7. doi: 10.1038/nbt.3583 27404874; PubMed Central PMCID: PMC5242601.
20. Xue LJ, Tsai CJ. AGEseq: Analysis of Genome Editing by Sequencing. Mol Plant. 2015;8(9):1428–30. Epub 2015/06/06. doi: 10.1016/j.molp.2015.06.001 26057235.
21. Lindsay H, Burger A, Biyong B, Felker A, Hess C, Zaugg J, et al. CrispRVariants charts the mutation spectrum of genome engineering experiments. Nat Biotechnol. 2016;34(7):701–2. doi: 10.1038/nbt.3628 27404876.
22. Kluesner MG, Nedveck DA, Lahr WS, Garbe JR, Abrahante JE, Webber BR, et al. EditR: A Method to Quantify Base Editing from Sanger Sequencing. CRISPR J. 2018;1:239–50. doi: 10.1089/crispr.2018.0014 31021262.
23. Hwang GH, Park J, Lim K, Kim S, Yu J, Yu E, et al. Web-based design and analysis tools for CRISPR base editing. BMC Bioinformatics. 2018;19(1):542. Epub 2018/12/27. doi: 10.1186/s12859-018-2585-4 30587106; PubMed Central PMCID: PMC6307267.
24. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884–i90. doi: 10.1093/bioinformatics/bty560 30423086; PubMed Central PMCID: PMC6129281.
25. Zhang J, Kobert K, Flouri T, Stamatakis A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics. 2014;30(5):614–20. Epub 2013/10/18. doi: 10.1093/bioinformatics/btt593 24142950; PubMed Central PMCID: PMC3933873.
26. Magoč T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27(21):2957–63. Epub 2011/09/07. doi: 10.1093/bioinformatics/btr507 21903629; PubMed Central PMCID: PMC3198573.
27. Aronesty E. Comparison of Sequencing Utility Programs. The Open Bioinformatics Journal 2013;7:1–8. Epub 31/1/2013. doi: 10.2174/1875036201307010001
28. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26(5):589–95. Epub 2010/01/15. doi: 10.1093/bioinformatics/btp698 20080505; PubMed Central PMCID: PMC2828108.
29. Wagih O. ggseqlogo: a versatile R package for drawing sequence logos. Bioinformatics. 2017;33(22):3645–7. doi: 10.1093/bioinformatics/btx469 29036507.
30. Eddelbuettel D, Francois R. Rcpp: Seamless R and C++ Integration. Journal of Statistical Software. 2011;40(8). doi: 10.18637/jss.v040.i08
31. Wang X, Tilford C, Neuhaus I, Mintier G, Guo Q, Feder JN, et al. CRISPR-DAV: CRISPR NGS data analysis and visualization pipeline. Bioinformatics. 2017;33(23):3811–2. doi: 10.1093/bioinformatics/btx518 28961906.
Článok vyšiel v časopise
PLOS One
2019 Číslo 12
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Methylsulfonylmethane increases osteogenesis and regulates the mineralization of the matrix by transglutaminase 2 in SHED cells
- Oregano powder reduces Streptococcus and increases SCFA concentration in a mixed bacterial culture assay
- The characteristic of patulous eustachian tube patients diagnosed by the JOS diagnostic criteria
- Parametric CAD modeling for open source scientific hardware: Comparing OpenSCAD and FreeCAD Python scripts