Binding site discovery from nucleic acid sequences by discriminative learning of hidden Markov models

Nucleic Acids Research

Volumn 42, Issue 21, 2014, Pages 12995-13011

  Maaskola, Jonas ^a   Rajewsky, Nikolaus ^a  

^a MAX DELBRÜCK CENTER FOR MOLECULAR MEDICINE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DNA BINDING PROTEIN; RNA BINDING PROTEIN; TRANSCRIPTION FACTOR;

ANIMAL; BINDING SITE; CHROMATIN IMMUNOPRECIPITATION; DNA SEQUENCE; EMBRYONIC STEM CELL; HUMAN; METABOLISM; MOUSE; NUCLEOTIDE MOTIF; PROBABILITY; PROCEDURES; SEQUENCE ANALYSIS;

ANIMALS; BINDING SITES; CHROMATIN IMMUNOPRECIPITATION; DNA-BINDING PROTEINS; EMBRYONIC STEM CELLS; HUMANS; MARKOV CHAINS; MICE; NUCLEOTIDE MOTIFS; RNA-BINDING PROTEINS; SEQUENCE ANALYSIS, DNA; SEQUENCE ANALYSIS, RNA; TRANSCRIPTION FACTORS;

EID: 84945241769     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gku1083     Document Type: Article

References (102)

1. Ren, B., Robert, F., Wyrick, J. J., Aparicio, O., Jennings, E. G., Simon, I., Zeitlinger, J., Schreiber, J., Hannett, N., Kanin, E. et al. (2000) Genome-wide location and function of DNA binding proteins. Science, 290, 2306-2309.
2. Iyer, V. R., Horak, C. E., Scafe, C. S., Botstein, D., Snyder, M. And Brown, P. O. (2001) Genomic binding sites of the yeast cell-cycle transcription factors SBF and MBF. Nature, 409, 533-538.
3. Tenenbaum, S. A., Carson, C. C., Lager, P. J. And Keene, J. D. (2000) Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays. Proc. Natl. Acad. Sci. USA, 97, 14085-14090.
4. Keene, J. D., Komisarow, J. M. And Friedersdorf, M. B. (2006) RIP-Chip: The isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts. Nat. Protoc., 1, 302-307.
5. Robertson, G., Hirst, M., Bainbridge, M., Bilenky, M., Zhao, Y., Zeng, T., Euskirchen, G., Bernier, B., Varhol, R., Delaney, A. et al. (2007) Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat. Methods, 4, 651-657.
6. Johnson, D. S., Mortazavi, A., Myers, R. M. And Wold, B. (2007) Genome-wide mapping of in vivo protein-DNA interactions. Science, 316, 1497-1502.
7. Licatalosi, D. D., Mele, A., Fak, J. J., Ule, J., Kayikci, M., Chi, S. W., Clark, T. A., Schweitzer, A. C., Blume, J. E., Wang, X. et al. (2008) HITS-CLIP yields genome-wide insights into brain alternative RNA processing. Nature, 456, 464-469.
8. Sanford, J. R., Wang, X., Mort, M., Vanduyn, N., Cooper, D. N., Mooney, S. D., Edenberg, H. J. And Liu, Y. (2009) Splicing factor SFRS1 recognizes a functionally diverse landscape of RNA transcripts. Genome Res., 19, 381-394.
9. Hafner, M., Landthaler, M., Burger, L., Khorshid, M., Hausser, J., Berninger, P., Rothballer, A., Ascano, M., Jungkamp, A.-C., Munschauer, M. et al. (2010) Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell, 141, 129-141.
10. Ellington, A. D. And Szostak, J. W. (1990) In vitro selection of RNA molecules that bind specific ligands. Nature, 346, 818-822.
11. Tuerk, C. And Gold, L. (1990) Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science, 249, 505-510.
12. Jolma, A., Kivioja, T., Toivonen, J., Cheng, L., Wei, G., Enge, M., Taipale, M., Vaquerizas, J. M., Yan, J., Sillanpäaäa, M. J. et al. (2010) Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities. Genome Res., 20, 861-873.
13. Bulyk, M. L., Huang, X., Choo, Y. And Church, G. M. (2001) Exploring the DNA-binding specificities of zinc fingers with DNA microarrays. Proc. Natl. Acad. Sci. USA, 98, 7158-7163.
14. Berger, M. F., Philippakis, A. A., Qureshi, A. M., He, F. S., Estep, P. W. 3rd and Bulyk, M. L. (2006) Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities. Nat. Biotechnol., 24, 1429-1435.
15. Das, M. K. And Dai, H.-K. (2007) A survey of DNA motif finding algorithms. BMC Bioinformatics, 8(Suppl. 7), S21.
16. Stormo, G. D. And Fields, D. S. (1998) Specificity, free energy and information content in protein-DNA interactions. Trends Biochem. Sci., 23, 109-113.
17. Rabiner, L. R. (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE, 77, 257-286.
18. Berg, O. G. And von Hippel, P. H. (1987) Selection of DNA binding sites by regulatory proteins. Statistical-mechanical theory and application to operators and promoters. J. Mol. Biol., 193, 723-750.
19. Stormo, G. D. (2000) DNA binding sites: representation and discovery. Bioinformatics, 16, 16-23.
20. Foat, B. C., Morozov, A. V. And Bussemaker, H. J. (2006) Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE. Bioinformatics, 22, e141-e149.
21. Durbin, R., Eddy, S. R., Krogh, A. And Mitchison, G. (1998) Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press, Cambridge.
22. Krogh, A., Mian, I. S. And Haussler, D. (1994) A hidden Markov model that finds genes in E. coli DNA. Nucleic Acids Res., 22, 4768-4778.
23. Eddy, S. R. (1998) Profile hidden Markov models. Bioinformatics, 14, 755-763.
24. Bailey, T. L. And Elkan, C. (1994) Fitting a mixture model by expectation maximization to discover motifs in biopolymers. Proc. Int. Conf. Intell. Syst. Mol. Biol., 2, 28-36.
25. Wickens, M., Bernstein, D. S., Kimble, J. And Parker, R. (2002) A PUF family portrait: 3'UTR regulation as a way of life. Trends Genet., 18, 150-157.
26. Wang, Y., Gogol-Döring, A., Hu, H., Fröhler, S., Ma, Y., Jens, M., Maaskola, J., Murakawa, Y., Quedenau, C., Landthaler, M. et al. (2013) Integrative analysis revealed the molecular mechanism underlying RBM10-mediated splicing regulation. EMBO Mol. Med., 5, 1431-1442.
27. Wilks, S. S. (1962) Mathematical Statistics. Wiley, New York.
28. Lawrence, C. E., Altschul, S. F., Boguski, M. S., Liu, J. S., Neuwald, A. F. And Wootton, J. C. (1993) Detecting subtle sequence signals: A Gibbs sampling strategy for multiple alignment. Science, 262, 208-214.
29. Liu, X., Brutlag, D. L. And Liu, J. S. (2001) BioProspector: discovering conserved DNA motifs in upstream regulatory regions of co-expressed genes. Pac. Symp. Biocomput., 6, 127-138.
30. Liu, X. S., Brutlag, D. L. And Liu, J. S. (2002) An algorithm for finding protein-DNA binding sites with applications to chromatin-immunoprecipitation microarray experiments. Nat. Biotechnol., 20, 835-839.
31. Sinha, S. (2006) On counting position weight matrix matches in a sequence, with application to discriminative motif finding. Bioinformatics, 22, e454-e463.
32. Huggins, P., Zhong, S., Shiff, I., Beckerman, R., Laptenko, O., Prives, C., Schulz, M. H., Simon, I. And Bar-Joseph, Z. (2011) DECOD: fast and accurate discriminative DNA motif finding. Bioinformatics, 27, 2361-2367.
33. Sinha, S. And Tompa, M. (2000) A statistical method for finding transcription factor binding sites. Proc. Int. Conf. Intell. Syst. Mol. Biol., 8, 344-354.
34. Sinha, S. And Tompa, M. (2002) Discovery of novel transcription factor binding sites by statistical overrepresentation. Nucleic Acids Res., 30, 5549-5560.
35. Sinha, S. And Tompa, M. (2003) YMF: A program for discovery of novel transcription factor binding sites by statistical overrepresentation. Nucleic Acids Res., 31, 3586-3588.
36. Mason, M. J., Plath, K. And Zhou, Q. (2010) Identification of context-dependent motifs by contrasting ChIP binding data. Bioinformatics, 26, 2826-2832.
37. Barash, Y., Bejerano, G. And Friedman, N. (2001) A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites. In: WABI '01 Proceedings of the First International Workshop on Algorithms in Bioinformatics. Springer, Berlin, pp. 278-293.
38. Leung, H. C. M. And Chin, F. Y. L. (2006) Finding motifs from all sequences with and without binding sites. Bioinformatics, 22, 2217-2223.
39. Bailey, T. L. (2011) DREME: motif discovery in transcription factor ChIP-seq data. Bioinformatics, 27, 1653-1659.
40. Elemento, O., Slonim, N. And Tavazoie, S. (2007) A universal framework for regulatory element discovery across all genomes and data types. Mol. Cell, 28, 337-350.
41. Lieber, D. S., Elemento, O. And Tavazoie, S. (2010) Large-scale discovery and characterization of protein regulatory motifs in eukaryotes. PLoS One, 5, e14444.
42. Goodarzi, H., Najafabadi, H. S., Oikonomou, P., Greco, T. M., Fish, L., Salavati, R., Cristea, I. M. And Tavazoie, S. (2012) Systematic discovery of structural elements governing stability of mammalian messenger RNAs. Nature, 485, 264-268.
43. Redhead, E. And Bailey, T. L. (2007) Discriminative motif discovery in DNA and protein sequences using the DEME algorithm. BMC Bioinformatics, 8, 385.
44. Valen, E., Sandelin, A., Winther, O. And Krogh, A. (2009) Discovery of regulatory elements is improved by a discriminatory approach. PLoS Comput. Biol., 5, e1000562.
45. Keilwagen, J., Grau, J., Paponov, I. A., Posch, S., Strickert, M. And Grosse, I. (2011) De-novo discovery of differentially abundant transcription factor binding sites including their positional preference. PLoS Comput. Biol., 7, e1001070.
46. Smith, A. D., Sumazin, P. And Zhang, M. Q. (2005) Identifying tissue-selective transcription factor binding sites in vertebrate promoters. Proc. Natl. Acad. Sci. USA, 102, 1560-1565.
47. Smith, A. D., Sumazin, P., Das, D. And Zhang, M. Q. (2005) Mining ChIP-chip data for transcription factor and cofactor binding sites. Bioinformatics, 21(Suppl. 1), i403-i412.
48. Smith, A. D., Sumazin, P., Xuan, Z. And Zhang, M. Q. (2006) DNA motifs in human and mouse proximal promoters predict tissue-specific expression. Proc. Natl. Acad. Sci. USA, 103, 6275-6280.
49. Ng, A. And Jordan, M. (2002) On discriminative vs. generative classifiers: A comparison of logistic regression and naive Bayes. Adv. Neural Inf. Process. Syst., 14, 841-848.
50. Greiner, R., Su, X., Shen, B. And Zhou, W. (2005) Structural extension to logistic regression: discriminative parameter learning of belief net classifiers. Mach. Learn., 59, 297-322.
51. Roos, T., Wettig, H., Grünwald, P., Myllymäki, P. And Tirri, H. (2005) On discriminative Bayesian network classifiers and logistic regression,. Mach. Learn., 59, 267-296.
52. Shannon, C. E. (1948) A mathematical theory of communication. Bell Syst. Techn. J., 27, 379-423.
53. Cover, T. M. And Thomas, J. A. (1991, 2006) Elements of Information Theory. Wiley-Interscience, New Jersey.
54. MacKay, D. J. (2003) Information Theory, Inference, and Learning Algorithms. Cambridge University Press, Cambridge.
55. Bahl, L., Brown, P., de Souza, P. And Mercer, R. (1986) Maximum mutual information estimation of hidden Markov model parameters for speech recognition. In: Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing ICASSP '90. IEEE, New Jersey, 11, pp. 49-52.
56. Normandin, Y. (1991) Hidden Markov models, maximum mutual information estimation, and the speech recognition problem. Ph. D Thesis. McGill University Montreal, Quebec.
57. Ljolje, A., Ephraim, Y. And Rabiner, L. R. (1990) Estimation of hidden Markov model parameters by minimizing empirical error rate. In: Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing ICASSP '90. IEEE, New Jersey, pp. 709-712.
58. Schneider, T. D., Stormo, G. D., Gold, L. And Ehrenfeucht, A. (1986) Information content of binding sites on nucleotide sequences. J. Mol. Biol., 188, 415-431.
59. Goecks, J., Nekrutenko, A., Taylor, J. And Galaxy Team. (2010) Galaxy: A comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol., 11, R86.
60. Baum, L. E. (1972) An inequality and associated maximization technique in statistical estimation for probabilistic functions of markov processes. Inequalities, 3, 1-8.
61. Moré, J. J. And Thuente, D. J. (1994) Line search algorithms with guaranteed sufficient decrease. ACM Trans. Math. Softw., 20, 286-307.
62. Krogh, A. (1994) Hidden Markov models for labeled sequences. In: Proc. 12th IAPR Int. Pattern Recognition Conf. B: Computer Vision & Image Processing. IEEE, New Jersey, 2, pp. 140-144.
63. Wilks, S. S. (1938) The large-sample distribution of the likelihood ratio for testing composite hypotheses. Ann. Math. Statist., 9, 60-62.
64. Gerber, A. P., Herschlag, D. And Brown, P. O. (2004) Extensive association of functionally and cytotopically related mRNAs with Puf family RNA-binding proteins in yeast. PLoS Biol., 2, E79.
65. Kershner, A. M. And Kimble, J. (2010) Genome-wide analysis of mRNA targets for Caenorhabditis elegans FBF, a conserved stem cell regulator. Proc. Natl. Acad. Sci. USA, 107, 3936-3941.
66. Gerber, A. P., Luschnig, S., Krasnow, M. A., Brown, P. O. And Herschlag, D. (2006) Genome-wide identification of mRNAs associated with the translational regulator PUMILIO in Drosophila melanogaster. Proc. Natl. Acad. Sci. USA, 103, 4487-4492.
67. Galgano, A., Forrer, M., Jaskiewicz, L., Kanitz, A., Zavolan, M. And Gerber, A. P. (2008) Comparative analysis of mRNA targets for human PUF-family proteins suggests extensive interaction with the miRNA regulatory system. PLoS One, 3, e3164.
68. Morris, A. R., Mukherjee, N. And Keene, J. D. (2008) Ribonomic analysis of human Pum1 reveals cis-trans conservation across species despite evolution of diverse mRNA target sets. Mol. Cell Biol., 28, 4093-4103.
69. Nagalakshmi, U., Wang, Z., Waern, K., Shou, C., Raha, D., Gerstein, M. And Snyder, M. (2008) The transcriptional landscape of the yeast genome defined by RNA sequencing. Science, 320, 1344-1349.
70. Anders, G., Mackowiak, S. D., Jens, M., Maaskola, J., Kuntzagk, A., Rajewsky, N., Landthaler, M. And Dieterich, C. (2012) doRiNA: A database of RNA interactions in post-transcriptional regulation. Nucleic Acids Res., 40, D180-D186.
71. Chen, X., Xu, H., Yuan, P., Fang, F., Huss, M., Vega, V. B., Wong, E., Orlov, Y. L., Zhang, W., Jiang, J. et al. (2008) Integration of external signaling pathways with the core transcriptional network in embryonic stem cells. Cell, 133, 1106-1117.
72. Marson, A., Levine, S. S., Cole, M. F., Frampton, G. M., Brambrink, T., Johnstone, S., Guenther, M. G., Johnston, W. K., Wernig, M., Newman, J. et al. (2008) Connecting microRNA genes to the core transcriptional regulatory circuitry of embryonic stem cells. Cell, 134, 521-533.
73. Cartwright, P., McLean, C., Sheppard, A., Rivett, D., Jones, K. And Dalton, S. (2005) LIF/STAT3 controls ES cell self-renewal and pluripotency by a Myc-dependent mechanism. Development, 132, 885-896.
74. Jiang, J., Chan, Y.-S., Loh, Y.-H., Cai, J., Tong, G.-Q., Lim, C.-A., Robson, P., Zhong, S. And Ng, H.-H. (2008) A core Klf circuitry regulates self-renewal of embryonic stem cells. Nat. Cell Biol., 10, 353-360.
75. Bieda, M., Xu, X., Singer, M. A., Green, R. And Farnham, P. J. (2006) Unbiased location analysis of E2F1-binding sites suggests a widespread role for E2F1 in the human genome. Genome Res., 16, 595-605.
76. Kim, T. H., Abdullaev, Z. K., Smith, A. D., Ching, K. A., Loukinov, D. I., Green, R. D., Zhang, M. Q., Lobanenkov, V. V. And Ren, B. (2007) Analysis of the vertebrate insulator protein CTCF-binding sites in the human genome. Cell, 128, 1231-1245.
77. Ivanova, N., Dobrin, R., Lu, R., Kotenko, I., Levorse, J., DeCoste, C., Schafer, X., Lun, Y. And Lemischka, I. R. (2006) Dissecting self-renewal in stem cells with RNA interference. Nature, 442, 533-538.
78. Ying, Q. L., Nichols, J., Chambers, I. And Smith, A. (2003) BMP induction of Id proteins suppresses differentiation and sustains embryonic stem cell self-renewal in collaboration with STAT3. Cell, 115, 281-292.
79. Niwa, H., Burdon, T., Chambers, I. And Smith, A. (1998) Self-renewal of pluripotent embryonic stem cells is mediated via activation of STAT3. Genes Dev., 12, 2048-2060.
80. Cole, M. F., Johnstone, S. E., Newman, J. J., Kagey, M. H. And Young, R. A. (2008) Tcf3 is an integral component of the core regulatory circuitry of embryonic stem cells. Genes Dev., 22, 746-755.
81. Tam, W.-L., Lim, C. Y., Han, J., Zhang, J., Ang, Y.-S., Ng, H.-H., Yang, H. And Lim, B. (2008) T-cell factor 3 regulates embryonic stem cell pluripotency and self-renewal by the transcriptional control of multiple lineage pathways. Stem Cells, 26, 2019-2031.
82. Yi, F., Pereira, L. And Merrill, B. J. (2008) Tcf3 functions as a steady-state limiter of transcriptional programs of mouse embryonic stem cell self-renewal. Stem Cells, 26, 1951-1960.
83. Tompa, M., Li, N., Bailey, T. L., Church, G. M., Moor, B. D., Eskin, E., Favorov, A. V., Frith, M. C., Fu, Y., Kent, W. J. et al. (2005) Assessing computational tools for the discovery of transcription factor binding sites. Nat. Biotechnol., 23, 137-144.
84. Caputi, M., Casari, G., Guenzi, S., Tagliabue, R., Sidoli, A., Melo, C. A. And Baralle, F. E. (1994) A novel bipartite splicing enhancer modulates the differential processing of the human fibronectin EDA exon. Nucleic Acids Res., 22, 1018-1022.
85. Fairbrother, W. G., Yeh, R.-F., Sharp, P. A. And Burge, C. B. (2002) Predictive identification of exonic splicing enhancers in human genes. Science, 297, 1007-1013.
86. Bechara, E. G., Sebestyn, E., Bernardis, I., Eyras, E. And Valcrcel, J. (2013) RBM5, 6, and 10 differentially regulate NUMB alternative splicing to control cancer cell proliferation. Mol. Cell, 52, 720-733.
87. Loughlin, F. E., Mansfield, R. E., Vaz, P. M., McGrath, A. P., Setiyaputra, S., Gamsjaeger, R., Chen, E. S., Morris, B. J., Guss, J. M. And Mackay, J. P. (2009) The zinc fingers of the SR-like protein ZRANB2 are single-stranded RNA-binding domains that recognize 5' splice site-like sequences. Proc. Natl. Acad. Sci. USA, 106, 5581-5586.
88. Nguyen, C. D., Mansfield, R. E., Leung, W., Vaz, P. M., Loughlin, F. E., Grant, R. P. And Mackay, J. P. (2011) Characterization of a family of RanBP2-type zinc fingers that can recognize single-stranded RNA. J. Mol. Biol., 407, 273-283.
89. Zhang, M. Q. (1998) Statistical features of human exons and their flanking regions. Hum. Mol. Genet., 7, 919-932.
90. Ast, G. (2004) How did alternative splicing evolve? Nat. Rev. Genet., 5, 773-782.
91. Inoue, A., Yamamoto, N., Kimura, M., Nishio, K., Yamane, H. And Nakajima, K. (2014) RBM10 regulates alternative splicing. FEBS Lett., 588, 942-947.
92. Gupta, S., Stamatoyannopoulos, J. A., Bailey, T. L. And Noble, W. S. (2007) Quantifying similarity between motifs. Genome Biol., 8, R24.
93. Bailey, T. L. And Machanick, P. (2012) Inferring direct DNA binding from ChIP-seq. Nucleic Acids Res., 40, e128.
94. Benos, P. V., Bulyk, M. L. And Stormo, G. D. (2002) Additivity in protein-DNA interactions: how good an approximation is it? Nucleic Acids Res., 30, 4442-4451.
95. Tacke, R. And Manley, J. L. (1995) The human splicing factors ASF/SF2 and SC35 possess distinct, functionally significant RNA binding specificities. EMBO J., 14, 3540-3551.
96. Ramchatesingh, J., Zahler, A. M., Neugebauer, K. M., Roth, M. B. And Cooper, T. A. (1995) A subset of SR proteins activates splicing of the cardiac troponin T alternative exon by direct interactions with an exonic enhancer. Mol. Cell Biol., 15, 4898-4907.
97. Wang, X., Juan, L., Lv, J., Wang, K., Sanford, J. R. And Liu, Y. (2011) Predicting sequence and structural specificities of RNA binding regions recognized by splicing factor SRSF1. BMC Genomics, 12(Suppl. 5), S8.
98. Saulière, J., Murigneux, V., Wang, Z., Marquenet, E., Barbosa, I., Le Tonquèze, O., Audic, Y., Paillard, L., Roest Crollius, H. And Le Hir, H. (2012) CLIP-seq of eIF4AIII reveals transcriptome-wide mapping of the human exon junction complex. Nat. Struct. Mol. Biol., 19, 1124-1131.
99. Jin, W., Niu, Z., Xu, D. And Li, X. (2012) RBM5 promotes exon 4 skipping of AID pre-mRNA by competing with the binding of U2AF65 to the polypyrimidine tract. FEBS Lett., 586, 3852-3857.
100. Mitchell, S. A., Spriggs, K. A., Bushell, M., Evans, J. R., Stoneley, M., Le Quesne, J. P. C., Spriggs, R. V. And Willis, A. E. (2005) Identification of a motif that mediates polypyrimidine tract-binding protein-dependent internal ribosome entry. Genes Dev., 19, 1556-1571.
101. Kishore, S., Jaskiewicz, L., Burger, L., Hausser, J., Khorshid, M. And Zavolan, M. (2011) A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins. Nat. Methods, 8, 559-564.
102. Friedersdorf, M. B. And Keene, J. D. (2014) Advancing the functional utility of PAR-CLIP by quantifying background binding to mRNAs and lncRNAs. Genome Biol., 15, R2.