Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions

Nucleic Acids Research

Volumn 44, Issue 5, 2016, Pages 2028-2035

  Capurso, Daniel ^a   Bengtsson, Henrik ^b   Segal, Mark R ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTION FACTOR; TRANSCRIPTION FACTOR SWI6; UNCLASSIFIED DRUG; CHROMATIN; CYTOCHROME P450; ERG11 PROTEIN, S CEREVISIAE; MSB2 PROTEIN, S CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEIN; SIGNAL PEPTIDE; SWI6 PROTEIN, S CEREVISIAE;

ARTICLE; CHROMATIN IMMUNOPRECIPITATION; CONTROLLED STUDY; ERG11 GENE; FUNGAL GENOME; GENE; GENE CONTROL; GENE TARGETING; GENETIC ALGORITHM; K NEAREST NEIGHBOR; MSB2 GENE; NONHUMAN; PATIENT RULE INDUCTION METHOD; PRIORITY JOURNAL; SACCHAROMYCES CEREVISIAE; STATISTICAL SIGNIFICANCE; THREE DIMENSIONAL IMAGING; ALGORITHM; CHEMISTRY; CHROMATIN; CHROMOSOMAL MAPPING; CONFORMATION; GENE EXPRESSION REGULATION; GENETICS; HIGH THROUGHPUT SEQUENCING; METABOLISM; MOLECULAR MODEL; ULTRASTRUCTURE;

ALGORITHMS; CHROMATIN; CHROMATIN IMMUNOPRECIPITATION; CHROMOSOME MAPPING; CYTOCHROME P-450 ENZYME SYSTEM; GENE EXPRESSION REGULATION, FUNGAL; GENOME, FUNGAL; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; INTRACELLULAR SIGNALING PEPTIDES AND PROTEINS; MODELS, MOLECULAR; MOLECULAR CONFORMATION; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; TRANSCRIPTION FACTORS;

EID: 84963812603     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkw070     Document Type: Article

References (57)

1. Yip, K.Y., Cheng, C., Bhardwaj, N., Brown, J.B., Leng, J., Kundaje, A., Rozowsky, J., Birney, E., Bickel, P., Snyder, M. et al. (2012) Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors. Genome Biol., 13, R48.
2. Misteli, T. (2007) Beyond the sequence: cellular organization of genome function. Cell, 128, 787-800.
3. Mitelman, F., Johansson, B. and Mertens, F. (2007) The impact of translocations and gene fusions on cancer causation. Nat. Rev. Cancer, 7, 233-245.
4. Marti-Renom, M.A. and Mirny, L.A. (2011) Bridging the resolution gap in structural modeling of 3D genome organization. PLoS Comput. Biol., 7, e1002125.
5. Dekker, J., Rippe, K., Dekker, M. and Kleckner, N. (2002) Capturing chromosome conformation. Science, 295, 1306-1311.
6. Lieberman-Aiden, E., van Berkum, N.L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B.R., Sabo, P.J., Dorschner, M.O. et al. (2009) Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 326, 289-293.
7. Duan, Z., Andronescu, M., Schutz, K., McIlwain, S., Kim, Y.J., Lee, C., Shendure, J., Fields, S., Blau, C.A. and Noble, W.S. (2010) A three-dimensional model of the yeast genome. Nature, 465, 363-367.
8. Van Bortle, K. and Corces, V.G. (2012) Nuclear organization and genome function. Annu. Rev. Cell Dev. Biol., 28, 163-187.
9. Taddei, A. and Gasser, S.M. (2012) Structure and function in the budding yeast nucleus. Genetics, 192, 107-129.
10. Meister, P. and Taddei, A. (2013) Building silent compartments at the nuclear periphery: a recurrent theme. Curr. Opin. Genet. Dev., 23, 96-103.
11. Ay, F., Bunnik, E.M., Varoquaux, N., Bol, S.M., Prudhomme, J., Vert, J.-P., Noble, W.S. and Le Roch, K.G. (2014) Three-dimensional modeling of the P. falciparum genome during the erythrocytic cycle reveals a strong connection between genome architecture and gene expression. Genome Res., 24, 974-988.
12. Zhang, Z., Li, G., Toh, K.-C. and Sung, W.-K. (2013) 3D chromosome modeling with semi-definite programming and Hi-C data. J. Comput. Biol., 20, 831-846.
13. Varoquaux, N., Ay, F., Noble, W.S. and Vert, J.P. (2014) A statistical approach for inferring the 3D structure of the genome. Bioinformatics, 30, i26-i33.
14. Lesne, A., Riposo, J., Roger, P., Cournac, A. and Mozziconacci, J. (2014) 3D genome reconstruction from chromosomal contacts. Nat. Methods, 11, 1141-1143.
15. Segal, M.R., Xiong, H., Capurso, D., Vazquez, M. and Arsuaga, J. (2014) Reproducibility of 3D chromatin configuration reconstructions. Biostatistics, 15, 442-456.
16. Witten, D.M. and Noble, W.S. (2012) On the assessment of statistical significance of three-dimensional colocalization of sets of genomic elements. Nucleic Acids Res., 40, 3849-3855.
17. Capurso, D. and Segal, M.R. (2014) Distance-based assessment of the localization of functional annotations in 3D genome reconstructions. BMC Genomics, 15, 992.
18. Park, D., Lee, Y., Bhupindersingh, G. and Iyer, V.R. (2013)Widespread misinterpretable ChIP-seq bias in yeast. PLoS One, 8, e83506.
19. Asbury, T.M., Mitman, M., Tang, J. and Zheng, W.J. (2010) Genome3D: a viewer-model framework for integrating and visualizing multi-scale epigenomic information within a three-dimensional genome. BMC Bioinformatics, 11, 444.
20. Friedman, J.H. and Fisher, N.I. (1999) Bump hunting in high-dimensional data. Stat. Comput., 9, 123-143.
21. Hastie, T., Tibshirani, R. and Friedman, J. (2009) The elements of statistical learning. 2nd edn. Springer, NY.
22. Osborne, C.S., Chakalova, L., Brown, K.E., Carter, D., Horton, A., Debrand, E., Goyenechea, B., Mitchell, J.A., Lopes, S., Reik, W. et al. (2004) Active genes dynamically colocalize to shared sites of ongoing transcription. Nat. Genet., 36, 1065-1071.
23. Hsu, P.-Y., Hsu, H.-K., Hsiao, T.-H., Ye, Z., Wang, E., Profit, A.L., Jatoi, I., Chen, Y., Kirma, N.B., Jin, V.X. et al. (2015) Spatiotemporal control of estrogen-responsive transcription in ERα-positive breast cancer cells. Oncogene, doi:10.1038/onc.2015.298.
24. Casolari, J.M., Brown, C.R., Komili, S., West, J., Hieronymus, H. and Silver, P.A. (2004) Genome-wide localization of the nuclear transport machinery couples transcriptional status and nuclear organization. Cell, 117, 427-439.
25. Hu, M., Deng, K., Selvaraj, S., Qin, Z., Ren, B. and Liu, J.S. (2012) HiCNorm: removing biases in Hi-C data via Poisson regression. Bioinformatics, 28, 3131-3133.
26. Leinonen, R., Sugawara, H., Shumway, M. and International Nucleotide Sequence Database Collaboration. (2011) The sequence read archive. Nucleic Acids Res., 39, D19-D21.
27. Langmead, B. and Salzberg, S.L. (2012) Fast gapped-read alignment with Bowtie 2. Nat. Methods, 9, 357-359.
28. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R. and 1000 Genome Project Data Processing Subgroup. (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25, 2078-2079.
29. Morgan, M., Anders, S., Lawrence, M., Aboyoun, P., Pagès, H. and Gentleman, R. (2009) ShortRead: a bioconductor package for input, quality assessment and exploration of high-throughput sequence data. Bioinformatics, 25, 2607-2608.
30. Pepke, S., Wold, B. and Mortazavi, A. (2009) Computation for ChIP-seq and RNA-seq studies. Nat. Methods, 6, S22-S32.
31. Leleu, M., Lefebvre, G. and Rougemont, J. (2011) Processing and analyzing ChIP-seq data: from short reads to regulatory interactions. Brief. Funct. Genomics Proteomic., 9, 466-476.
32. Kharchenko, P.V., Tolstorukov, M.Y. and Park, P.J. (2008) Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat. Biotechnol., 26, 1351-1359.
33. Friedman, J.H. (1984) A variable span scatterplot smoother. Laboratory for Computational Statistics. Stanford University, Technical Report No. 5.
34. The PyMOL Molecular Graphics System, Version 1.3 Schrödinger, LLC. The PyMOL Molecular Graphics System, Version 1.3 Schrödinger, LLC.
35. Bernstein, F.C., Koetzle, T.F., Williams, G.J., Meyer, E.F., Brice, M.D., Rodgers, J.R., Kennard, O., Shimanouchi, T. and Tasumi, M. (1977) The Protein Data Bank: a computer-based archival file for macromolecular structures. J. Mol. Biol., 112, 535-542.
36. Duong, T. (2014) prim: Patient Rule Induction Method (PRIM). R package version 1.0.15.
37. Beygelzimer, A., Kakadet, S., Langford, J., Arya, S., Mount, D. and Li, S. (2013) FNN: Fast Nearest Neighbor Search Algorithms and Applications. R package version 1.1.
38. Yaffe, E. and Tanay, A. (2011) Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture. Nat. Genet., 43, 1059-1065.
39. Imakaev, M., Fudenberg, G., McCord, R.P., Naumova, N., Goloborodko, A., Lajoie, B.R., Dekker, J. and Mirny, L.A. (2012) Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat. Methods, 9, 999-1003.
40. Li, W., Gong, K., Li, Q., Alber, F. and Zhou, X.J. (2015) Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data. Bioinformatics, 31, 960-962.
41. 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.
42. Horak, C.E., Luscombe, N.M., Qian, J., Bertone, P., Piccirrillo, S., Gerstein, M. and Snyder, M. (2002) Complex transcriptional circuitry at the G1/S transition in Saccharomyces cerevisiae. Genes Dev., 16, 3017-3033.
43. Vadaie, N., Dionne, H., Akajagbor, D.S., Nickerson, S.R., Krysan, D.J. and Cullen, P.J. (2008) Cleavage of the signaling mucin Msb2 by the aspartyl protease Yps1 is required for MAPK activation in yeast. J. Cell Biol., 181, 1073-1081.
44. Turi, T.G. and Loper, J.C. (1992) Multiple regulatory elements control expression of the gene encoding the Saccharomyces cerevisiae cytochrome P450, lanosterol 14 alpha-demethylase (ERG11). J. Biol. Chem., 267, 2046-2056.
45. Cherry, J.M., Hong, E.L., Amundsen, C., Balakrishnan, R., Binkley, G., Chan, E.T., Christie, K.R., Costanzo, M.C., Dwight, S.S., Engel, S.R. et al. (2012) Saccharomyces genome database: the genomics resource of budding yeast. Nucleic Acids Res., 40, D700-D705.
46. Müller, O., Neumann, H., Bayer, M.J. and Mayer, A. (2003) Role of the Vtc proteins in V-ATPase stability and membrane trafficking. J. Cell. Sci., 116, 1107-1115.
47. Venters, B.J., Wachi, S., Mavrich, T.N., Andersen, B.E., Jena, P., Sinnamon, A.J., Jain, P., Rolleri, N.S., Jiang, C., Hemeryck-Walsh, C. et al. (2011) A comprehensive genomic binding map of gene and chromatin regulatory proteins in Saccharomyces. Mol. Cell, 41, 480-492.
48. Altman, N.S. (1992) An introduction to kernel and nearest-neighbor nonparametric regression. Am. Statistician, 46, 175-185.
49. Ben-Elazar, S., Yakhini, Z. and Yanai, I. (2013) Spatial localization of co-regulated genes exceeds genomic gene clustering in the Saccharomyces cerevisiae genome. Nucleic Acids Res., 41, 2191-2201.
50. Adler, R.J., Bobrowski, O., Borman, M.S., Subag, E. and Weinberger, S. (2010) Persistent homology for random fields and complexes. Inst. Math. Stat. Collection, 6, doi:10.1214/10-IMSCOLL609.
51. Dixon, J.R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J.S. and Ren, B. (2012) Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature, 485, 376-380.
52. Rao, S.S.P., Huntley, M.H., Durand, N.C., Stamenova, E.K., Bochkov, I.D., Robinson, J.T., Sanborn, A.L., Machol, I., Omer, A.D., Lander, E.S. et al. (2014) A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell, 159, 1665-1680.
53. Cremer, T., Cremer, M., Dietzel, S., Müller, S., Solovei, I. and Fakan, S. (2006) Chromosome territories-a functional nuclear landscape. Curr. Opin. Cell Biol., 18, 307-316.
54. Lan, X., Witt, H., Katsumura, K., Ye, Z., Wang, Q., Bresnick, E.H., Farnham, P.J. and Jin, V.X. (2012) Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin linkages. Nucleic Acids Res., 40, 7690-7704.
55. Shavit, Y., Hamey, F.K. and Lio, P. (2014) FisHiCal: an R package for iterative FISH-based calibration of Hi-C data. Bioinformatics, 30, 3120-3122.
56. Nagano, T., Lubling, Y., Stevens, T.J., Schoenfelder, S., Yaffe, E., Dean, W., Laue, E.D., Tanay, A. and Fraser, P. (2013) Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. Nature, 502, 59-64.
57. Nagano, T., Lubling, Y., Yaffe, E., Wingett, S.W., Dean, W., Tanay, A. and Fraser, P. (2015) Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell. Nat. Protoc., 10, 1986-2003.