| BMC Systems Biology | |
| Combinatorial regulation of transcription factors and microRNAs | |
| Minghua Deng2  Minping Qian1  Yufu Wang3  Naifang Su3  | |
| [1] Center for Theoretical Biology, Peking University, Beijing 100871, China;Center for Statistical Science, Peking University, Beijing 100871, China;LMAM, School of Mathematical Sciences, Peking University, Beijing 100871, China | |
| Others : 1216737 DOI : 10.1186/1752-0509-4-150 |
|
| received in 2010-06-18, accepted in 2010-11-08, 发布年份 2010 | |
PDF
|
|
【 摘 要 】
Background
Gene regulation is a key factor in gaining a full understanding of molecular biology. Cis-regulatory modules (CRMs), consisting of multiple transcription factor binding sites, have been confirmed as the main regulators in gene expression. In recent years, a novel regulator known as microRNA (miRNA) has been found to play an important role in gene regulation. Meanwhile, transcription factor and microRNA co-regulation has been widely identified. Thus, the relationships between CRMs and microRNAs have generated interest among biologists.
Results
We constructed new combinatorial regulatory modules based on CRMs and miRNAs. By analyzing their effect on gene expression profiles, we found that genes targeted by both CRMs and miRNAs express in a significantly similar way. Furthermore, we constructed a regulatory network composed of CRMs, miRNAs, and their target genes. Investigating its structure, we found that the feed forward loop is a significant network motif, which plays an important role in gene regulation. In addition, we further analyzed the effect of miRNAs in embryonic cells, and we found that mir-154, as well as some other miRNAs, have significant co-regulation effect with CRMs in embryonic development.
Conclusions
Based on the co-regulation of CRMs and miRNAs, we constructed a novel combinatorial regulatory network which was found to play an important role in gene regulation, particularly during embryonic development.
【 授权许可】
2010 Su et al; licensee BioMed Central Ltd.
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| 20150702042604912.pdf | 1199KB | ||
| Figure 3. | 26KB | Image | |
| Figure 2. | 31KB | Image | |
| Figure 1. | 55KB | Image |
【 图 表 】
Figure 1.
Figure 2.
Figure 3.
【 参考文献 】
- [1]Zhou Q, Wong WH: CisModule: De novo discovery of' cis-regulatory modules by hierarchical mixture modeling. Proceedings of the National Academy of Sciences of the United States of America 2004, 101(33):12114-12119.
- [2]Yu HY, Luscombe NM, Qian J, Gerstein M: Genomic analysis of gene expression relationships in transcriptional regulatory networks. Trends in Genetics 2003, 19(8):422-427.
- [3]Kato M, Hata N, Banerjee N, Futcher B, Zhang MQ: Identifying combinatorial regulation of transcription factors and binding motifs. Genome Biology 2004., 5(8) BioMed Central Full Text
- [4]Liu YL, Taylor MW, Edenberg HJ: Model-based identification of cis-acting elements from microarray data. Genomics 2006, 88(4):452-461.
- [5]Bartel DP: MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 2004, 116(2):281-297.
- [6]Zhou YM, Ferguson J, Chang JT, Kluger Y: Inter-and intra-combinatorial regulation by transcription factors and microRNAs. Bmc Genomics 2007., 8
- [7]Shalgi R, Lieber D, Oren M, Pilpel Y: Global and local architecture of the mammalian microRNA-transcription factor regulatory network. Plos Computational Biology 2007, 3(7):1291-1304.
- [8]Brosh R, Shalgi R, Liran A, Landan G, Korotayev K, Nguyen GH, Enerly E, Johnsen H, Buganim Y, Solomon H, et al.: p53-repressed miRNAs are involved with E2F in a feed-forward loop promoting proliferation. Molecular Systems Biology 2008., 4
- [9]Yu X, Lin J, Zack DJ, Mendell JT, Qian J: Analysis of regulatory network topology reveals functionally distinct classes of microRNAs. Nucleic Acids Res 2008, 36(20):6494-6503.
- [10]Wang GH, Wang YD, Feng WX, Wang X, Yang JY, Zhao YM, Wang Y, Liu YL: Transcription factor and microRNA regulation in androgen-dependent and -independent prostate cancer cells. Bmc Genomics 2007., 9
- [11]Liang Y, Ridzon D, Wong L, Chen CF: Characterization of microRNA expression profiles in normal human tissues. Bmc Genomics 2007., 8
- [12]Marson A, Levine SS, Cole MF, Frampton GM, Brambrink T, Johnstone S, Guenther MG, Johnston WK, Wernig M, Newman J, et al.: Connecting microRNA genes to the core transcriptional regulatory circuitry of embryonic stem cells. Cell 2008, 134(3):521-533.
- [13]Altuvia Y, Landgraf P, Lithwick G, Elefant N, Pfeffer S, Aravin A, Brownstein MJ, Tuschl T, Margalit H: Clustering and conservation patterns of human microRNAs. Nucleic Acids Research 2005, 33(8):2697-2706.
- [14]Qiu C, Wang J, Yao P, Wang E, Cui Q: microRNA evolution in a human transcription factor and microRNA regulatory network. BMC Syst Biol 4:90. BioMed Central Full Text
- [15]Wang GH, Wang X, Wang YD, Yang JY, Li L, Nephew KP, Edenberg HJ, Zhou FC, Liu YL: Identification of transcription factor and microRNA binding sites in responsible to fetal alcohol syndrome. Bmc Genomics 2007., 9
- [16]Tu K, Yu H, Hua YJ, Li YY, Liu L, Xie L, Li YX: Combinatorial network of primary and secondary microRNA-driven regulatory mechanisms. Nucleic Acids Res 2009, 37(18):5969-5980.
- [17]Blattner C: 'Junk' DNA meets the p53 network. Mol Syst Biol 2008, 4:231.
- [18]Hu JF, Hu HY, Li XM: MOPAT: a graph-based method to predict recurrent cis-regulatory modules from known motifs. Nucleic Acids Research 2008, 36(13):4488-4497.
- [19]Lewis BP, Burge CB, Bartel DP: Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 2005, 120(1):15-20.
- [20]Sharan R, Ovcharenko I, Ben-Hur A, Karp RM: CREME: a framework for identifying cis-regulatory modules in human-mouse conserved segments. Bioinformatics 2003, 19(Suppl 1):i283-291.
- [21]Rodriguez A, Griffiths-Jones S, Ashurst JL, Bradley A: Identification of mammalian microRNA host genes and transcription units. Genome Res 2004, 14(10A):1902-1910.
- [22]Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, Pfeffer S, Rice A, Kamphorst AO, Landthaler M, et al.: A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 2007, 129(7):1401-1414.
- [23]Nishiyama A, Xin L, Sharov AA, Thomas M, Mowrer G, Meyers E, Piao Y, Mehta S, Yee S, Nakatake Y, et al.: Uncovering early response of gene regulatory networks in ESCs by systematic induction of transcription factors. Cell Stem Cell 2009, 5(4):420-433.
- [24]Cui Q, Yu Z, Purisima EO, Wang E: MicroRNA regulation and interspecific variation of gene expression. Trends Genet 2007, 23(8):372-375.
- [25]Gene Expression Omnibus [http://www.ncbi.nlm.nih.gov/geo/] webcite
- [26]Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ: miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 2006, (34 Database):D140-144.
- [27]Blake JA, Richardson JE, Bult CJ, Kadin JA, Eppig JT: MGD: the Mouse Genome Database. Nucleic Acids Res 2003, 31(1):193-195.
- [28]Yu Z, Jian Z, Shen SH, Purisima E, Wang E: Global analysis of microRNA target gene expression reveals that miRNA targets are lower expressed in mature mouse and Drosophila tissues than in the embryos. Nucleic Acids Res 2007, 35(1):152-164.
- [29]Ensembl [http://www.ensembl.org/index.html] webcite
- [30]Matys V, Fricke E, Geffers R, Gossling E, Haubrock M, Hehl R, Hornischer K, Karas D, Kel AE, Kel-Margoulis OV, et al.: TRANSFAC: transcriptional regulation, from patterns to profiles. Nucleic Acids Res 2003, 31(1):374-378.
PDF