RSAT matrix-clustering: Dynamic exploration and redundancy reduction of transcription factor binding motif collections

Nucleic Acids Research

Volumn 45, Issue 13, 2017, Pages

  Castro Mondragon, Jaime Abraham ^a   Jaeger, Sébastien ^b   Thieffry, Denis ^c   Thomas Chollier, Morgane ^c   Van Helden, Jacques ^a  

^a Aix Marseille university   (France)

^b CENTRE D IMMUNOLOGIE DE MARSEILLE LUMINY   (France)

^c PSL RESEARCH UNIVERSITY   (France)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTION FACTOR; PROTEIN BINDING;

ANALYTIC METHOD; ARTICLE; AUTOMATION; BINDING SITE; CHROMATIN IMMUNOPRECIPITATION; COMPUTER INTERFACE; DATA BASE; MOLECULAR DYNAMICS; PRIORITY JOURNAL; PROTEIN MOTIF; STRUCTURE ACTIVITY RELATION; ALGORITHM; AMINO ACID SEQUENCE; ANIMAL; CHEMISTRY; CLUSTER ANALYSIS; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN; METABOLISM; MOUSE; PROTEIN DATABASE; SEQUENCE ANALYSIS; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; AMINO ACID MOTIFS; AMINO ACID SEQUENCE; ANIMALS; BINDING SITES; CHROMATIN IMMUNOPRECIPITATION; CLUSTER ANALYSIS; DATABASES, PROTEIN; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MICE; PROTEIN BINDING; SEQUENCE ANALYSIS, PROTEIN; TRANSCRIPTION FACTORS;

EID: 85026472374     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkx314     Document Type: Article

References (66)

1. Stormo,G.D. (2000) DNA binding sites: representation and discovery. Bioinformatics, 16, 16-23.
2. 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.
3. Weirauch,M.T., Cote,A., Norel,R., Annala,M., Zhao,Y., Riley,T.R., Saez-Rodriguez,J., Cokelaer,T., Vedenko,A., Talukder,S. et al. (2013) Evaluation of methods for modeling transcription factor sequence specificity. Nat. Biotechnol., 31, 126-134.
4. Jolma,A., Yan,J., Whitington,T., Toivonen,J., Nitta,K.R., Rastas,P., Morgunova,E., Enge,M., Taipale,M., Wei,G. et al. (2013) DNA-binding specificities of human transcription factors. Cell, 152, 327-339.
5. Mathelier,A. and Wasserman,W.W. (2013) The next generation of transcription factor binding site prediction. PLoS Comput. Biol., 9, e1003214.
6. Keilwagen,J. and Grau,J. (2015) Varying levels of complexity in transcription factor binding motifs. Nucleic Acids Res., 43, e119.
7. Mathelier,A., Fornes,O., Arenillas,D.J., Chen,C., Denay,G., Lee,J., Shi,W., Shyr,C., Tan,G.,Worsley-Hunt,R. et al. (2015) JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles. Nucleic Acids Res., 44, D110-D115.
8. Matys,V., Fricke,E., Geffers,R., Gössling,E., Haubrock,M., Hehl,R., Hornischer,K., Karas,D., Kel,A.E., Kel-Margoulis,O.V. et al. (2003) TRANSFAC(R): transcriptional regulation, from patterns to profiles. Nucleic Acids Res., 31, 374-378.
9. Weirauch,M.T., Yang,A., Albu,M., Cote,A.G., Montenegro-Montero,A., Drewe,P., Najafabadi,H.S., Lambert,S.A., Mann,I., Cook,K. et al. (2014) Determination and inference of eukaryotic transcription factor sequence specificity. Cell, 158, 1431-1443.
10. Sebastian,A. and Contreras-Moreira,B. (2014) FootprintDB: a database of transcription factors with annotated cis elements and binding interfaces. Bioinformatics, 30, 258-265.
11. Kulakovskiy,I. V., Vorontsov,I.E., Yevshin,I.S., Soboleva,A. V., Kasianov,A.S., Ashoor,H., Ba-Alawi,W., Bajic,V.B., Medvedeva,Y.A., Kolpakov,F.A. et al. (2016) HOCOMOCO: Expansion and enhancement of the collection of transcription factor binding sites models. Nucleic Acids Res., 44, D116-D125.
12. Mathelier,A., Zhao,X., Zhang,A.W., Parcy,F., Worsley-Hunt,R., Arenillas,D.J., Buchman,S., Chen,C., Chou,A., Ienasescu,H. et al. (2014) JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles. Nucleic Acids Res., 42, D142-D147.
13. Jolma,A., Yin,Y., Nitta,K.R., Dave,K., Popov,A., Taipale,M., Enge,M., Kivioja,T., Morgunova,E. and Taipale,J. (2015) DNA-dependent formation of transcription factor pairs alters their binding specificity. Nature, 527, 384-388.
14. O'Malley,R.C., Huang,S.C., Song,L., Lewsey,M.G., Bartlett,A., Nery,J.R., Galli,M., Gallavotti,A. and Ecker,J.R. (2016) Cistrome and epicistrome features shape the regulatory DNA landscape. Cell, 165, 1280-1292.
15. Thomas-Chollier,M., Herrmann,C., Defrance,M., Sand,O., Thieffry,D. and van Helden,J. (2012) RSAT peak-motifs: motif analysis in full-size ChIP-seq datasets. Nucleic Acids Res., 40, e31.
16. Machanick,P. and Bailey,T.L. (2011) MEME-ChIP: motif analysis of large DNA datasets. Bioinformatics, 27, 1696-1697.
17. Luehr,S., Hartmann,H. and Söding,J. (2012) The XXmotif web server for eXhaustive, weight matriX-based motif discovery in nucleotide sequences. Nucleic Acids Res., 40, 104.
18. Kulakovskiy,I. V, Boeva,V.A., Favorov,A.V and Makeev,V.J. (2010) Deep and wide digging for binding motifs in ChIP-Seq data. Bioinformatics, 26, 2622-2623.
19. Tanaka,E., Bailey,T., Grant,C.E., Noble,W.S. and Keich,U. (2011) Improved similarity scores for comparing motifs. Bioinformatics, 27, 1603-1609.
20. Habib,N., Kaplan,T., Margalit,H. and Friedman,N. (2008) A novel Bayesian DNA motif comparison method for clustering and retrieval. PLoS Comput. Biol., 4, e1000010.
21. Pape,U.J., Rahmann,S. and Vingron,M. (2008) Natural similarity measures between position frequency matrices with an application to clustering. Bioinformatics, 24, 350-357.
22. Mahony,S. and Benos,P. V (2007) STAMP: a web tool for exploring DNA-binding motif similarities. Nucleic Acids Res., 35, W253-W258.
23. Gupta,S., Stamatoyannopoulos,J.A., Bailey,T.L. and Noble,W.S. (2007) Quantifying similarity between motifs. Genome Biol., 8, R24.
24. Mahony,S., Auron,P.E. and Benos,P. V (2007) Inferring protein-DNA dependencies using motif alignments and mutual information. Bioinformatics, 23, i297-i304.
25. Stegmaier,P., Kel,A., Wingender,E. and Borlak,J. (2013) A discriminative approach for unsupervised clustering of DNA sequence motifs. PLoS Comput. Biol., 9, e1002958.
26. Kankainen,M. and Löytynoja,A. (2007) MATLIGN: a motif clustering, comparison and matching tool. BMC Bioinformatics, 8, 189.
27. Vorontsov,I.E., Kulakovskiy,I.V. and Makeev,V.J. (2013) Jaccard index based similarity measure to compare transcription factor binding site models. Algorithms Mol. Biol., 8, 23.
28. Broin,P.Ó., Smith,T.J. and Golden,A.A. (2015) Alignment-free clustering of transcription factor binding motifs using a genetic-k-medoids approach. BMC Bioinformatics, 16, 22.
29. Schones,D.E., Sumazin,P. and Zhang,M.Q. (2005) Similarity of position frequency matrices for transcription factor binding sites. Bioinformatics, 21, 307-313.
30. Zhang,S., Zhou,X., Du,C. and Su,Z. (2013) SPIC: a novel similarity metric for comparing transcription factor binding site motifs based on information contents. BMC Syst. Biol., 7(Suppl. 2), S14.
31. Sandelin,A. and Wasserman,W.W. (2004) Constrained binding site diversity within families of transcription factors enhances pattern discovery bioinformatics. J. Mol. Biol., 338, 207-215.
32. Kielbasa,S.M., Gonze,D. and Herzel,H. (2005) Measuring similarities between transcription factor binding sites. BMC Bioinformatics, 6, 237.
33. Communication,S. (2006) MACO: a gapped-alignment scoring tool for comparing transcription factor binding sites. In Silico Biol., 6, 307-310.
34. Grau,J., Grosse,I., Posch,S., Keilwagen,J. and Julius,K. (2015) Motif clustering with implications for transcription factor interactions. PeerJ Prepr., 10.7287/peerj.preprints.1302v1.
35. Ma,Q., Zhang,H., Mao,X., Zhou,C., Liu,B., Chen,X. and Xu,Y. (2014) DMINDA: an integrated web server for DNA motif identification and analyses. Nucleic Acids Res., 42, 12-19.
36. Xu,M. and Su,Z. (2010) A novel alignment-free method for comparing transcription factor binding site motifs. PLoS One, 5, e8797.
37. Mahony,S., Auron,P.E. and Benos,P. V. (2007) DNA familial binding profiles made easy: comparison of various motif alignment and clustering strategies. PLoS Comput. Biol., 3, e61.
38. Thomas-Chollier,M., Defrance,M., Medina-Rivera,A., Sand,O., Herrmann,C., Thieffry,D. and van Helden,J. (2011) RSAT 2011: regulatory sequence analysis tools. Nucleic Acids Res., 39, W86-W91.
39. Medina-Rivera,A., Defrance,M., Sand,O., Herrmann,C., Castro-Mondragon,J.A., Delerce,J., Jaeger,S., Blanchet,C., Vincens,P., Caron,C. et al. (2015) RSAT 2015: regulatory sequence analysis tools. Nucleic Acids Res., 43, W50-W56.
40. Thomas-Chollier,M., Darbo,E., Herrmann,C., Defrance,M., Thieffry,D. and van Helden,J. (2012) A complete workflow for the analysis of full-size ChIP-seq (and similar) data sets using peak-motifs. Nat. Protoc., 7, 1551-1568.
41. 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.
42. Heinz,S., Benner,C., Spann,N., Bertolino,E., Lin,Y.C., Laslo,P., Cheng,J.X., Murre,C., Singh,H. and Glass,C.K. (2010) Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell, 38, 576-589.
43. Hume,M.A., Barrera,L.A., Gisselbrecht,S.S. and Bulyk,M.L. (2015) UniPROBE, update 2015: new tools and content for the online database of protein-binding microarray data on protein-DNA interactions. Nucleic Acids Res., 43, D117-D122.
44. Forrest,A.R.R., Kawaji,H., Rehli,M., Baillie,J.K., de Hoon,M.J.L., Lassmann,T., Itoh,M., Summers,K.M., Suzuki,H., Daub,C.O. et al. (2014) A promoter-level mammalian expression atlas. Nature, 507, 462-470.
45. Xie,Z., Hu,S., Blackshaw,S., Zhu,H. and Qian,J. (2010) hPDI: a database of experimental human protein-DNA interactions. Bioinformatics, 26, 287-289.
46. Whitaker,J.W., Chen,Z. and Wang,W. (2015) Predicting the human epigenome from DNA motifs. Nat. Methods, 12, 265-272.
47. Wang,J., Zhuang,J., Iyer,S., Lin,X., Whitfield,T.W., Greven,M.C., Pierce,B.G., Dong,X., Kundaje,A., Cheng,Y. et al. (2012) Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors. Genome Res., 22, 1798-1812.
48. Bülow,L., Engelmann,S., Schindler,M. and Hehl,R. (2009) AthaMap, integrating transcriptional and post-transcriptional data. Nucleic Acids Res., 37, 983-986.
49. Franco-Zorrilla,J.M., López-Vidriero,I., Carrasco,J.L., Godoy,M., Vera,P. and Solano,R. (2014) DNA-binding specificities of plant transcription factors and their potential to define target genes. Proc. Natl. Acad. Sci. U.S.A., 111, 2367-2372.
50. Shazman,S., Lee,H., Socol,Y., Mann,R.S. and Honig,B. (2014) OnTheFly: a database of Drosophila melanogaster transcription factors and their binding sites. Nucleic Acids Res., 42, D167-D171.
51. Kulakovskiy,I. V, Favorov,A.V. and Makeev,V.J. (2009) Motif discovery and motif finding from genome-mapped DNase footprint data. Bioinformatics, 25, 128-131.
52. Zhu,L.J., Christensen,R.G., Kazemian,M., Hull,C.J., Enuameh,M.S., Basciotta,M.D., Brasefield,J.A., Zhu,C., Asriyan,Y., Lapointe,D.S. et al. (2011) FlyFactorSurvey: a database of Drosophila transcription factor binding specificities determined using the bacterial one-hybrid system. Nucleic Acids Res., 39, 111-117.
53. Down,T.A., Bergman,C.M., Su,J. and Hubbard,T.J.P. (2007) Large-scale discovery of promoter motifs in Drosophila melanogaster. PLoS Comput. Biol., 3, 0095-0109.
54. Bostock,M., Ogievetsky,V. and Heer,J. (2011) D3 data-driven documents. IEEE Trans. Vis. Comput. Graph., 17, 2301-2309.
55. Wingender,E., Schoeps,T. and Dönitz,J. (2013) TFClass: an expandable hierarchical classification of human transcription factors. Nucleic Acids Res., 41, D165-D170.
56. Mistri,T.K., Devasia,A.G., Chu,L.T., Ng,W.P., Halbritter,F., Colby,D., Martynoga,B., Tomlinson,S.R., Chambers,I., Robson,P. et al. (2015) Selective influence of Sox2 on POU transcription factor binding in embryonic and neural stem cells. EMBO Rep., 16, 1177-1191.
57. Mason,M.J., Plath,K. and Zhou,Q. (2010) Identification of context-dependent motifs by contrasting ChIP binding data. Bioinformatics, 26, 2826-2832.
58. Tantin,D., Gemberling,M., Callister,C. and Fairbrother,W.G. (2008) High-throughput biochemical analysis of in vivo location data reveals novel distinct classes of POU5F1(Oct4)/DNA complexes. Genome Res., 18, 631-639.
59. Morgan,G.T. and Middleton,K.M. (1990) Short interspersed repeats from Xenopus that contain multiple octamer motifs are related to known transposable elements. Nucleic Acids Res., 18, 5781-5786.
60. Gokhman,D., Livyatan,I., Sailaja,B.S., Melcer,S. and Meshorer,E. (2013) Multilayered chromatin analysis reveals E2f, Smad and Zfx as transcriptional regulators of histones. Nat. Struct. Mol. Biol., 20, 119-126.
61. Mahony,S., Golden,A., Smith,T.J. and Benos,P. V (2005) Improved detection of DNA motifs using a self-organized clustering of familial binding profiles. Bioinformatics, 21 Suppl 1, i283-i291.
62. Noyes,M.B., Christensen,R.G., Wakabayashi,A., Stormo,G.D., Brodsky,M.H. and Wolfe,S.A. (2008) Analysis of homeodomain specificities allows the family-wide prediction of preferred recognition sites. Cell, 133, 1277-1289.
63. Najafabadi,H.S., Mnaimneh,S., Schmitges,F.W., Garton,M., Lam,K.N., Yang,A., Albu,M., Weirauch,M.T., Radovani,E., Kim,P.M. et al. (2015) C2H2 zinc finger proteins greatly expand the human regulatory lexicon. Nat. Biotechnol., 33, 555-562.
64. de Oliveira,K.A.P., Kaergel,E., Heinig,M., Fontaine,J.-F., Patone,G., Muro,E.M., Mathas,S., Hummel,M., Andrade-Navarro,M.A., Hübner,N. et al. (2016) A roadmap of constitutive NF-κB activity in Hodgkin lymphoma: Dominant roles of p50 and p52 revealed by genome-wide analyses. Genome Med., 8, 28.
65. Medina-Rivera,A., Abreu-Goodger,C., Thomas-Chollier,M., Salgado,H., Collado-Vides,J. and van Helden,J. (2011) Theoretical and empirical quality assessment of transcription factor-binding motifs. Nucleic Acids Res., 39, 808-824.
66. Langfelder,P., Zhang,B. and Horvath,S. (2008) Defining clusters from a hierarchical cluster tree: the Dynamic tree cut package for R. Bioinformatics, 24, 719-720.