Genetic architecture of gene expression in the chicken

BMC Genomics

Volumn 14, Issue 1, 2013, Pages

  Stanley, Dragana ^a,b,d   Watson Haigh, Nathan S ^c   Cowled, Christopher J E ^a   Moore, Robert J ^a,b  

^a CSIRO   (Australia)

^b UNIVERSITY OF NEW ENGLAND   (Australia)

^c AUSTRALIAN WINE RESEARCH INSTITUTE   (Australia)

^d CENTRAL QUEENSLAND UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTION FACTOR;

ARTICLE; BINDING SITE; CHICKEN; GENE CONSTRUCT; GENE EXPRESSION; GENE FUNCTION; GENE IDENTIFICATION; GENE REGULATORY NETWORK; GENE STRUCTURE; GENETIC DATABASE; INTEGROME DATABASE; NONHUMAN;

ANIMALS; CHICKENS; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORKS; GENOMICS; MULTIGENE FAMILY; NUCLEOTIDE MOTIFS; SOFTWARE;

EID: 84872199061     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-14-13     Document Type: Article

References (26)

1. Choi JK, Yu U, Yoo OJ, Kim S. Differential coexpression analysis using microarray data and its application to human cancer. Bioinformatics 2005, 21(24):4348-4355. 10.1093/bioinformatics/bti722, 16234317.
2. Hudson NJ, Reverter A, Wang Y, Greenwood PL, Dalrymple BP. Inferring the transcriptional landscape of bovine skeletal muscle by integrating co-expression networks. PLoS One 2009, 4(10):e7249. 10.1371/journal.pone.0007249, 2749936, 19794913.
3. Childs KL, Davidson RM, Buell CR. Gene coexpression network analysis as a source of functional annotation for rice genes. PLoS One 2011, 6(7):e22196. 10.1371/journal.pone.0022196, 3142134, 21799793.
4. da Huang W, Sherman BT, Lempicki RA. Sy stematic and integrative analy sis of large gene lists using DAVID bioinfor matics resources. Nat Protoc 2008, 4(1):44-57.
5. Frith MC, Fu Y, Yu L, Chen JF, Hansen U, Weng Z. Detection of functional DNA motifs via statistical over-representation. Nucleic Acids Res 2004, 32(4):1372-1381. 10.1093/nar/gkh299, 390287, 14988425.
6. Portales-Casamar E, Thongjuea S, Kwon AT, Arenillas D, Zhao X, Valen E, Yusuf D, Lenhard B, Wasserman WW, Sandelin A. JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles. Nucleic Acids Res 2010, 38(Database issue):D105-110. 2808906, 19906716.
7. Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren J, Li WW, Noble WS. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res 2009, 37(Web Server issue):W202-208. 2703892, 19458158.
8. Barabasi AL. Scale-free networks: a decade and beyond. Science 2009, 325(5939):412-413. 10.1126/science.1173299, 19628854.
9. Barabasi AL, Oltvai ZN. Network biology: understanding the cell's functional organization. Nat Rev Genet 2004, 5(2):101-113. 10.1038/nrg1272, 14735121.
10. Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol 2005, 4:Article17.
11. Albert R, Jeong H, Barabasi AL. Error and attack tolerance of complex networks. Nature 2000, 406(6794):378-382. 10.1038/35019019, 10935628.
12. Stuart JM, Segal E, Koller D, Kim SK. A gene-coexpression network for global discovery of conserved genetic modules. Science 2003, 302(5643):249-255. 10.1126/science.1087447, 12934013.
13. Bergmann S, Ihmels J, Barkai N. Similarities and differences in genome-wide expression data of six organisms. PLoS Biol 2004, 2(1):E9. 10.1371/journal.pbio.0020009, 300882, 14737187.
14. Wolfe CJ, Kohane IS, Butte AJ. Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks. BMC Bioinforma 2005, 6:227.
15. Lee HK, Hsu AK, Sajdak J, Qin J, Pavlidis P. Coexpression analysis of human genes across many microarray data sets. Genome Res 2004, 14(6):1085-1094. 10.1101/gr.1910904, 419787, 15173114.
16. van Noort V, Snel B, Huynen MA. The yeast coexpression network has a small-world, scale-free architecture and can be explained by a simple model. EMBO Rep 2004, 5(3):280-284. 10.1038/sj.embor.7400090, 1299002, 14968131.
17. Wasserman WW, Fickett JW. Identification of regulatory regions which confer muscle-specific gene expression. J Mol Biol 1998, 278(1):167-181. 10.1006/jmbi.1998.1700, 9571041.
18. Leddin M, Perrod C, Hoogenkamp M, Ghani S, Assi S, Heinz S, Wilson NK, Follows G, Schonheit J, Vockentanz L, et al. Two distinct auto-regulatory loops operate at the PU.1 locus in B cells and myeloid cells. Blood 2011, 117(10):2827-2838. 10.1182/blood-2010-08-302976, 3062295, 21239694.
19. Pospisil V, Vargova K, Kokavec J, Rybarova J, Savvulidi F, Jonasova A, Necas E, Zavadil J, Laslo P, Stopka T. Epigenetic silencing of the oncogenic miR-17-92 cluster during PU.1-directed macrophage differentiation. EMBO J 2011, 30(21):4450-4464. 10.1038/emboj.2011.317, 3230374, 21897363.
20. Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 2007, 8(1):118-127. 10.1093/biostatistics/kxj037, 16632515.
21. Hahne F, Huber W, Gentleman R, Falcon S. Easy differential expression. Bioconductor case studies 2008, 83-88. Springer, Gentlemen R, Hornik K, Parmigiani G, 978-0-387-77239-4.
22. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma 2008, 9:559.
23. Zhao W, Langfelder P, Fuller T, Dong J, Li A, Hovarth S. Weighted gene coexpression network analysis: state of the art. J Biopharm Stat 2010, 20(2):281-300. 10.1080/10543400903572753, 20309759.
24. Killcoyne S, Carter GW, Smith J, Boyle J. Cytoscape: a community-based framework for network modeling. Methods Mol Biol 2009, 563:219-239. 10.1007/978-1-60761-175-2_12, 19597788.
25. Aerts S, Thijs G, Coessens B, Staes M, Moreau Y, De Moor B. Toucan: deciphering the cis-regulatory logic of coregulated genes. Nucleic Acids Res 2003, 31(6):1753-1764. 10.1093/nar/gkg268, 152870, 12626717.
26. Aerts S, Van Loo P, Thijs G, Mayer H, de Martin R, Moreau Y, De Moor B. TOUCAN 2: the all-inclusive open source workbench for regulatory sequence analysis. Nucleic Acids Res 2005, 33(Web Server issue):W393-396. 1160115, 15980497.