FASTAptamer: A bioinformatic toolkit for high-throughput sequence analysis of combinatorial selections

Molecular Therapy Nucleic Acids

Volumn 4, Issue 3, 2015, Pages e230-

  Alam, Khalid K ^a   Chang, Jonathan L ^a   Burke, Donald H ^a  

^a University of Missouri   (United States)

Author keywords

Aptamer; Bioinformatics; High throughput sequence; Next generation sequencing; Phage display; Ribozyme; SELEX; Sequencing; Software

Indexed keywords

APTAMER;

ARTICLE; BIOINFORMATICS; COMBINATORIAL CHEMISTRY; COMPUTER PROGRAM; DNA SEQUENCE; GENETIC SELECTION; HIGH THROUGHPUT SEQUENCING; NEXT GENERATION SEQUENCING; NONHUMAN; PRIORITY JOURNAL;

EID: 84942106089     PISSN: None     EISSN: 21622531     Source Type: Journal    
DOI: 10.1038/mtna.2015.4     Document Type: Article

References (45)

1. Wang, AZ and Farokhzad, OC (2014). Current progress of aptamer-based molecular imaging. J Nucl Med 55: 353-356.
2. Sundaram, P, Kurniawan, H, Byrne, ME and Wower, J (2013). Therapeutic RNA aptamers in clinical trials. Eur J Pharm Sci 48: 259-271.
3. Fowler, DM, Araya, CL, Fleishman, SJ, Kellogg, EH, Stephany, JJ, Baker, D et al. (2010). High-resolution mapping of protein sequence-function relationships. Nat Methods 7: 741-746.
4. Pitt, JN and Ferré-D'Amaré, AR (2010). Rapid construction of empirical RNA fitness landscapes. Science 330: 376-379.
5. Ameta, S, Winz, ML, Previti, C and Jäschke, A (2014). Next-generation sequencing reveals how RNA catalysts evolve from random space. Nucleic Acids Res 42: 1303-1310.
6. Jiménez, JI, Xulvi-Brunet, R, Campbell, GW, Turk-MacLeod, R and Chen, IA (2013). Comprehensive experimental fitness landscape and evolutionary network for small RNA. Proc Natl Acad Sci USA 110: 14984-14989.
7. Vaidya, N, Manapat, ML, Chen, IA, Xulvi-Brunet, R, Hayden, EJ and Lehman, N (2012). Spontaneous network formation among cooperative RNA replicators. Nature 491: 72-77.
8. Jolma, A, Kivioja, T, Toivonen, J, Cheng, L, Wei, G, Enge, M et al. (2010). Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities. Genome Res 20: 861-873.
9. Cho, M, Xiao, Y, Nie, J, Stewart, R, Csordas, AT, Oh, SS et al. (2010). Quantitative selection of DNA aptamers through microfluidic selection and high-throughput sequencing. Proc Natl Acad Sci USA 107: 15373-15378.
10. Ravn, U, Gueneau, F, Baerlocher, L, Osteras, M, Desmurs, M, Malinge, P et al. (2010). Bypassing in vitro screening-next generation sequencing technologies applied to antibody display and in silico candidate selection. Nucleic Acids Res 38: e193.
11. Bayrac, AT, Sefah, K, Parekh, P, Bayrac, C, Gulbakan, B, Oktem, HA et al. (2011). In vitro Selection of DNA Aptamers to Glioblastoma Multiforme. ACS Chem Neurosci 2: 175-181.
12. Hoon, S, Zhou, B, Janda, KD, Brenner, S and Scolnick, J (2011). Aptamer selection by high-throughput sequencing and informatic analysis. Biotechniques 51: 413-416.
13. Berezhnoy, A, Stewart, CA, Mcnamara, JO 2nd, Thiel, W, Giangrande, P, Trinchieri, G et al. (2012). Isolation and optimization of murine IL-10 receptor blocking oligonucleotide aptamers using high-throughput sequencing. Mol Ther 20: 1242-1250.
14. Zimmermann, B, Gesell, T, Chen, D, Lorenz, C and Schroeder, R (2010). Monitoring genomic sequences during SELEX using high-throughput sequencing: neutral SELEX. PLoS One 5: e9169.
15. Thiel, WH, Bair, T, Wyatt Thiel, K, Dassie, JP, Rockey, WM, Howell, CA et al. (2011). Nucleotide bias observed with a short SELEX RNA aptamer library. Nucleic Acid Ther 21: 253-263.
16. Schütze, T, Wilhelm, B, Greiner, N, Braun, H, Peter, F, Mörl, M et al. (2011). Probing the SELEX process with next-generation sequencing. PLoS One 6: e29604.
17. Hoen, PA, Jirka, SM, Ten Broeke, BR, Schultes, EA, Aguilera, B, Pang, KH et al. (2012). Phage display screening without repetitious selection rounds. Anal Biochem 421: 622-631.
18. Pitt, JN, Rajapakse, I and Ferré-D'Amaré, AR (2010). SEWAL: an open-source platform for next-generation sequence analysis and visualization. Nucleic Acids Res 38: 7908-7915.
19. Fowler, DM, Araya, CL, Gerard, W and Fields, S (2011). Enrich: software for analysis of protein function by enrichment and depletion of variants. Bioinformatics 27: 3430-3431.
20. Hoinka, J, Zotenko, E, Friedman, A, Sauna, ZE and Przytycka, TM (2012). Identification of sequence-structure RNA binding motifs for SELEX-derived aptamers. Bioinformatics 28: i215-i223.
21. Ravn, U, Didelot, G, Venet, S, Ng, KT, Gueneau, F, Rousseau, F et al. (2013). Deep sequencing of phage display libraries to support antibody discovery. Methods 60: 99-110.
22. Hoinka, J, Berezhnoy, A, Sauna, ZE, Gilboa, E and Przytycka, TM (2014). AptaCluster - A Method to Cluster HT-SELEX Aptamer Pools and Lessons from its Application. Res Comput Mol Biol 8394: 115-128.
23. Ozer, A, Pagano, JM and Lis, JT (2014). New Technologies Provide Quantum Changes in the Scale, Speed, and Success of SELEX Methods and Aptamer Characterization. Mol Ther Nucleic Acids 3: e183.
24. Burke, DH, Scates, L, Andrews, K and Gold, L (1996). Bent pseudoknots and novel RNA inhibitors of type 1 human immunodeficiency virus (HIV-1) reverse transcriptase. J Mol Biol 264: 650-666.
25. Ditzler, MA, Lange, MJ, Bose, D, Bottoms, CA, Virkler, KF, Sawyer, AW et al. (2013). High-throughput sequence analysis reveals structural diversity and improved potency among RNA inhibitors of HIV reverse transcriptase. Nucleic Acids Res 41: 1873-1884.
26. Whatley, AS, Ditzler, MA, Lange, MJ, Biondi, E, Sawyer, AW, Chang, JL et al. (2013). Potent Inhibition of HIV-1 Reverse Transcriptase and Replication by Nonpseudoknot, "UCAA-motif" RNA Aptamers. Mol Ther Nucleic Acids 2: e71.
27. Di Niro, R, Sulic, AM, Mignone, F, D'Angelo, S, Bordoni, R, Iacono, M et al. (2010). Rapid interactome profiling by massive sequencing. Nucleic Acids Res 38: e110.
28. Kupakuwana, GV, Crill, JE 2nd, McPike, MP and Borer, PN (2011). Acyclic identification of aptamers for human alpha-thrombin using over-represented libraries and deep sequencing. PLoS One 6: e19395.
29. Cho, M, Soo Oh, S, Nie, J, Stewart, R, Eisenstein, M, Chambers, J et al. (2013). Quantitative selection and parallel characterization of aptamers. Proc Natl Acad Sci USA 110: 18460-18465.
30. Thiel, KW, Hernandez, LI, Dassie, JP, Thiel, WH, Liu, X, Stockdale, KR et al. (2012). Delivery of chemo-sensitizing siRNAs to HER2+-breast cancer cells using RNA aptamers. Nucleic Acids Res 40: 6319-6337.
31. Thiel, WH, Bair, T, Peek, AS, Liu, X, Dassie, J, Stockdale, KR et al. (2012). Rapid identification of cell-specific, internalizing RNA aptamers with bioinformatics analyses of a cell-based aptamer selection. PLoS One 7: e43836.
32. Szeto, K, Latulippe, DR, Ozer, A, Pagano, JM, White, BS, Shalloway, D et al. (2013). RAPID-SELEX for RNA aptamers. PLoS One 8: e82667.
33. Held, DM, Greathouse, ST, Agrawal, A and Burke, DH (2003). Evolutionary landscapes for the acquisition of new ligand recognition by RNA aptamers. J Mol Evol 57: 299-308.
34. Tuerk, C, MacDougal, S and Gold, L (1992). RNA pseudoknots that inhibit human immunodeficiency virus type 1 reverse transcriptase. Proc Natl Acad Sci USA 89: 6988-6992.
35. Dias-Neto, E, Nunes, DN, Giordano, RJ, Sun, J, Botz, GH, Yang, K et al. (2009). Next-generation phage display: integrating and comparing available molecular tools to enable cost-effective high-throughput analysis. PLoS One 4: e8338.
36. Giardine, B, Riemer, C, Hardison, RC, Burhans, R, Elnitski, L, Shah, P et al. (2005). Galaxy: a platform for interactive large-scale genome analysis. Genome Res 15: 1451-1455.
37. Goecks, J, Nekrutenko, A and Taylor, J; Galaxy Team (2010). Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol 11: R86.
38. Blankenberg, D, Von Kuster, G, Bouvier, E, Baker, D, Afgan, E, Stoler, N et al.; Galaxy Team. (2014). Dissemination of scientific software with Galaxy ToolShed. Genome Biol 15: 403.
39. Code share. (2014) Nature 514: 536.
40. Prlić, A and Procter, JB (2012). Ten simple rules for the open development of scientific software. PLoS Comput Biol 8: e1002802.
41. Seemann, T (2013). Ten recommendations for creating usable bioinformatics command line software. Gigascience 2: 15.
42. Sandve, GK, Nekrutenko, A, Taylor, J and Hovig, E (2013). Ten simple rules for reproducible computational research. PLoS Comput Biol 9: e1003285.
43. Leprevost, Fda V, Barbosa, VC, Francisco, EL, Perez-Riverol, Y and Carvalho, PC (2014). On best practices in the development of bioinformatics software. Front Genet 5: 199.
44. Martin, M (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17: 10-12.
45. Cock, PJ, Fields, CJ, Goto, N, Heuer, ML and Rice, PM (2010). The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res 38: 1767-1771.