选择性多聚腺苷酸化在多形性胶质母细胞瘤中的分布及其对蛋白质结合的影响
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摘要
人类基因组中广泛存在着选择性多聚腺苷酸化(APA)现象。polyA位点的选择是组织特异的,可能通过改变mRNA3' UTR序列使对应的mRNA获得不同的转录后调控而影响最终的基因表达。本论文的主要工作是从多形性胶质母细胞瘤(GBM)与正常脑组织来源的MPSS数据中寻找GBM特异的APA位点,并分析APA现象是否影响RNA结合蛋白(RBP)与RNA的结合。
首先我们开发了一个计算机分析流程,用于鉴定polyA位点及其对应mRNA的表达量。结果共找到约24%的基因具有APA,其中182个APA异构体(来自148个基因)在GBM和正常脑组织的表达量差异显著。MEF2D、HSBP1与PHCl基因都有两个polyA位点,其总体基因表达量在GBM与正常脑组织中无明显差异,在正常脑组织中能检出2个polyA位点,而GBM中却只有其中一个polyA位点。随后在GBM细胞系和组织以及正常脑组织中用3' RACE PCR方法确定上述3个基因的所有polyA位点,其中两个位点为全新发现,进一步通过测序验证了这两个位点。
其次,我们选取AUF1,HNRNPA1,HuR,MSI1,NCL,PUM2和SSB等7个RBP的靶点RNA序列,开发出一个基于CM模型(covariance model)的工具RNAelements (http://sysbio.zju.edu.cn/RNAelements/),找到每个RBP的特异性结合模体,并用于预测每个RBP在RNA序列上的结合位点。测试结果表明RNAelements优于同类型算法RNApromo。
最后,我们应用RNAelements预测MEF2D、HSBP1与PHC1这3个基因mRNA上的RBP结合位点,发现大部分RBP结合位点位于上游polyA位点之后的可变区域。由于这7个RBP与mRNA的稳定性及翻译效率有关,因此两种APA异构体的稳定性及翻译效率会因为受不同RBP的调控而发生变化。来自doRiNA数据库的HuR蛋白质的CLIP片段及AREsite数据库的保守ARE元件也有部分位于上游polyA位点之后,从实验和计算角度同时证明了APA会改变mRNA序列上的调控位点。
通过以上工作,我们发现GBM脑组织表达的mRNA会有特异的polyA位点选择偏好。选择上游polyA位点可能会使mRNA失去部分RBP的结合位点。
Most eukaryotic cells produce mRNAs with polyA tail, which is required for mRNA stability. Alternative polyadenylation (APA) is widely present in human genome, resulting in one gene with various3'ends. Here we conducted a comprehensive analysis of the APA products for glioblastoma and normal brain tissues using a data set from massively parallel signature sequencing of mRNAs. As a result, we found24%of the expressed genes having more than one polyadenylation site. Among them,182APA isoforms from148genes showed significantly differential expression between normal and GBM brain tissues, suggesting that APA plays a role in glioma development. Moreover, we found that APA isoforms of a same gene could show contradict expression levels between normal and GBM brain tissues. In this study, three genes including MEF2D (myocyte enhancer factor2D), HSBP1(Heat shock factor binding protein1) and PHC1(Polyhomeotic homolog1(Drosophila)) fit the criteria. All the polyadenylation sites of the3genes were validated by3'RACE PCR in both GBM cell lines and tissues. The novel sites were further determined by sequencing.
3'UTR is found to be binding sites for microRNAs or RNA binding proteins (RBP) that might affect RNA stability or translation efficiency. We thus wondered whether the differential3'UTR regions of APA isoforms contained RBP binding sites. In order to identify binding motifs for RNA binding proteins in the APA regions, we first developed a computational pipeline named RNAelements using covariance model from known RBP-RNA interaction datasets acquired by RIP methods, and tested the tool with segments from CLIP methods. Here the RBPs were now limited to AUF1, HNRNPA1, HuR, MSI1, NCL, PUM2and SSB. RNAelements can be accessed at:http://sysbio.zju.edu.cn/RNAelements/.
Not surprisingly, we found that RBPs were enriched in the alternative regions between the upstream and the downstream polyadenylation sites using RNAelements. For MEF2D, HSBP1and PHC1, we found that most RBPs specifically bound to the regions between the two alternative polyadenylation sites, which would result in the shorter APA isoform to escape regulation by these RBPs. Moreover, doRiNA database was searched to find the experimental RBP binding segments, and AREsite database was applied to find the conserved ARE sites in the mRNA sequence of of MEF2D, HSBP1and PHC1. Both results showed that the shorter one would lose some regulation sites.
In the end, we extracted all the3' UTR SNPs from dbSNP137, and checked whether the SNPs were located in polyadenation signals or altered the RBP bining motifs. In conclusion, our data provided a novel RBP mediated mechanism controlling RNA stability and translation for APA isoforms.
首先我们开发了一个计算机分析流程,用于鉴定polyA位点及其对应mRNA的表达量。结果共找到约24%的基因具有APA,其中182个APA异构体(来自148个基因)在GBM和正常脑组织的表达量差异显著。MEF2D、HSBP1与PHCl基因都有两个polyA位点,其总体基因表达量在GBM与正常脑组织中无明显差异,在正常脑组织中能检出2个polyA位点,而GBM中却只有其中一个polyA位点。随后在GBM细胞系和组织以及正常脑组织中用3' RACE PCR方法确定上述3个基因的所有polyA位点,其中两个位点为全新发现,进一步通过测序验证了这两个位点。
其次,我们选取AUF1,HNRNPA1,HuR,MSI1,NCL,PUM2和SSB等7个RBP的靶点RNA序列,开发出一个基于CM模型(covariance model)的工具RNAelements (http://sysbio.zju.edu.cn/RNAelements/),找到每个RBP的特异性结合模体,并用于预测每个RBP在RNA序列上的结合位点。测试结果表明RNAelements优于同类型算法RNApromo。
最后,我们应用RNAelements预测MEF2D、HSBP1与PHC1这3个基因mRNA上的RBP结合位点,发现大部分RBP结合位点位于上游polyA位点之后的可变区域。由于这7个RBP与mRNA的稳定性及翻译效率有关,因此两种APA异构体的稳定性及翻译效率会因为受不同RBP的调控而发生变化。来自doRiNA数据库的HuR蛋白质的CLIP片段及AREsite数据库的保守ARE元件也有部分位于上游polyA位点之后,从实验和计算角度同时证明了APA会改变mRNA序列上的调控位点。
通过以上工作,我们发现GBM脑组织表达的mRNA会有特异的polyA位点选择偏好。选择上游polyA位点可能会使mRNA失去部分RBP的结合位点。
Most eukaryotic cells produce mRNAs with polyA tail, which is required for mRNA stability. Alternative polyadenylation (APA) is widely present in human genome, resulting in one gene with various3'ends. Here we conducted a comprehensive analysis of the APA products for glioblastoma and normal brain tissues using a data set from massively parallel signature sequencing of mRNAs. As a result, we found24%of the expressed genes having more than one polyadenylation site. Among them,182APA isoforms from148genes showed significantly differential expression between normal and GBM brain tissues, suggesting that APA plays a role in glioma development. Moreover, we found that APA isoforms of a same gene could show contradict expression levels between normal and GBM brain tissues. In this study, three genes including MEF2D (myocyte enhancer factor2D), HSBP1(Heat shock factor binding protein1) and PHC1(Polyhomeotic homolog1(Drosophila)) fit the criteria. All the polyadenylation sites of the3genes were validated by3'RACE PCR in both GBM cell lines and tissues. The novel sites were further determined by sequencing.
3'UTR is found to be binding sites for microRNAs or RNA binding proteins (RBP) that might affect RNA stability or translation efficiency. We thus wondered whether the differential3'UTR regions of APA isoforms contained RBP binding sites. In order to identify binding motifs for RNA binding proteins in the APA regions, we first developed a computational pipeline named RNAelements using covariance model from known RBP-RNA interaction datasets acquired by RIP methods, and tested the tool with segments from CLIP methods. Here the RBPs were now limited to AUF1, HNRNPA1, HuR, MSI1, NCL, PUM2and SSB. RNAelements can be accessed at:http://sysbio.zju.edu.cn/RNAelements/.
Not surprisingly, we found that RBPs were enriched in the alternative regions between the upstream and the downstream polyadenylation sites using RNAelements. For MEF2D, HSBP1and PHC1, we found that most RBPs specifically bound to the regions between the two alternative polyadenylation sites, which would result in the shorter APA isoform to escape regulation by these RBPs. Moreover, doRiNA database was searched to find the experimental RBP binding segments, and AREsite database was applied to find the conserved ARE sites in the mRNA sequence of of MEF2D, HSBP1and PHC1. Both results showed that the shorter one would lose some regulation sites.
In the end, we extracted all the3' UTR SNPs from dbSNP137, and checked whether the SNPs were located in polyadenation signals or altered the RBP bining motifs. In conclusion, our data provided a novel RBP mediated mechanism controlling RNA stability and translation for APA isoforms.
引文
1. Kedde, M., et al., RNA-binding protein Dndl inhibits microRNA access to target mRNA Cell, 2007.131(7):p.1273-86.
2. McKee, A.E. and P.A. Silver, Systems perspectives on mRNA processing. Cell Res,2007. 17(7):p.581-90.
3. Chatterjee, S. and J.K. Pal, Role of 5'- and 3'-untranslated regions of mRNAs in human diseases. Biol Cell,2009.101(5):p.251-62.
4. Triboulet, R. and R.I. Gregory, Pumilio turns on microRNA function. Nature cell biology,2010. 12(10):p.928-9.
5. Lutz, C.S. and A. Moreira, Alternative mRNA polyadenylation in eukaryotes:an effective regulator of gene expression. WIREs RNA,2011.2(1):p.23-31.
6. Morris, A.R., N. Mukherjee, and J.D. Keene, Systematic analysis of posttranscriptional gene expression. Wiley Interdiscip Rev Syst Biol Med,2010.2(2):p.162-80.
7. Ray, D., et al., Rapid and systematic analysis of the RNA recognition specificities of RNA-bindingproteins. Nat Biotechnol,2009.27(7):p.667-70.
8. Licatalosi, D.D. and R.B. Darnell, RNA processing and its regulation:global insights into biological networks. Nat Rev Genet,2010.11(1):p.75-87.
9. Legendre, M. and D. Gautheret, Sequence determinants in human polyadenylation site selection. BMC Genomics,2003.4(1):p.7.
10. Beaudoing, E., et al., Patterns of variant polyadenylation signal usage in human genes. Genome Res,2000.10(7):p.1001-10.
11. Cheng, Y, R.M. Miura, and B. Tian, Prediction of mRNA polyadenylation sites by support vector machine. Bioinformatics,2006.22(19):p.2320-5.
12. Akhtar, M.N., et al., POLLYAR, a new computer program for prediction of poly(A) sites in human sequences. BMC Genomics,2010.11:p.646.
13. Lambert, A., et al., The ERPINserver:an interface to profile-based RNA motif identification. Nucleic acids research,2004.32(Web Server issue):p. W160-5.
14. Lee, J.Y., et al., PolyA_DB2:mRNA polyadenylation sites in vertebrate genes. Nucleic Acids Res,2007.35(Database issue):p. D165-8.
15. Zhang, H., et al., PolyA_DB:a database for mammalian mRNA polyadenylation. Nucleic Acids Res,2005.33(Database issue):p. D116-20.
16. Tian, B., et al., A large-scale analysis of mRNA polyadenylation of human and mouse genes. Nucleic Acids Res,2005.33(1):p.201-12.
17. Zhang, H., J.Y. Lee, and B. Tian, Biased alternative polyadenylation in human tissues. Genome Biol,2005.6(12):p. R100.
18. Sandberg, R., et al., Proliferating cells express mRNAs with shortened 3'untranslated regions and fewer microRNA target sites. Science,2008.320(5883):p.1643-7.
19. Singh, P., et al., Global Changes in Processing of mRNA 3'Untranslated Regions Characterize Clinically Distinct Cancer Subtypes. Cancer Res,2009.
20. Mayr, C. and D.P. Bartel, Widespread shortening of 3'UTRs by alternative cleavage and polyadenylation activates oncogenes in cancer cells. Cell,2009.138(4):p.673-84.
21. Fu, Y, et al., Differential genome-wide profiling of tandem 3' UTRs among human breast cancer and normal cells by high-throughput sequencing. Genome research,2011.
22. Ramskold, D., et al., An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS Comput Biol,2009.5(12):p. e1000598.
23. Lau, A.G., et al., Distinct 3' UTRs differentially regulate activity-dependent translation of brain-derived neurotrophic factor (BDNF). Proc Natl Acad Sci U S A,2010.
24. An, J.J., et al., Distinct role of long 3' UTR BDNF mRNA in spine morphology and synaptic plasticity in hippocampal neurons. Cell,2008.134(1):p.175-87.
25. Ji, Z., et al., Progressive lengthening of 3'untranslated regions of mRNAs by alternative polyadenylation during mouse embryonic development. Proc Natl Acad Sci U S A,2009.
26. Flavell, S.W., et al., Genome-wide analysis ofMEF2 transcriptional program reveals synaptic target genes and neuronal activity-dependent polyadenylation site selection. Neuron,2008. 60(6):p.1022-38.
27. Yoon, K.., et al., Over-represented sequences located on 3' UTRs are potentially involved in regulatory functions. RNA Biol,2008.5(4):p.255-62.
28. Shibata, T., et al., A polymorphism in the 3'-utr of cyclooxygenase-2 and the risk of gastric cancer. Molecular medicine reports,2008.1(4):p.561-4.
29. Sun, C., et al., Differential allelic expression ofc.1568C＞A at UGT2B15 is due to variation in a novel cis-regulatory element in the 3' UTR. Gene,2011.
30. Lecuyer, E., et al., Global analysis of mRNA localization reveals a prominent role in organizing cellular architecture and function. Cell,2007.131(1):p.174-87.
31. Gonzalez, I., et al., ASH1 mRNA localization in yeast involves multiple secondary structural elements and Ash1 protein translation. Curr Biol,1999.9(6):p.337-40.
32. Chartrand, P., et al., Structural elements required for the localization ofASHl mRNA and of a green fluorescent protein reporter particle in vivo. Curr Biol,1999.9(6):p.333-6.
33. Macdonald, P.M. and G. Struhl, cis-acting sequences responsible for anterior localization of bicoid mRNA in Drosophila embryos. Nature,1988.336(6199):p.595-8.
34. Macdonald, P.M. and K. Kerr, Redundant RNA recognition events in bicoid mRNA localization. RNA,1997.3(12):p.1413-20.
35. Ferrandon, D., et al., RNA-RNA interaction is required for the formation of specific bicoid mRNA 3' UTR-STAUFENribonucleoprotein particles. EMBO J,1997.16(7):p.1751-8.
36. Simmonds, A.J., et al., Apical localization of wingless transcripts is required for wingless signaling. Cell,2001.105(2):p.197-207.
37. Najand, N. and A.J. Simmonds, A minimal WLE2 element is not sufficient to direct apical localization in the absence of RNAs containing the full length wingless 3'UTR RNA Biol, 2007.4(3):p.138-46.
38. Mowry, K.L. and D.A. Melton,Vegetal messenger RNA localization directed by a 340-nt RNA sequence element in Xenopus oocytes. Science,1992.255(5047):p.991-4.
39. Lewis, R.A., et al., Conserved and clustered RNA recognition sequences are a critical feature of signals directing RNA localization in Xenopus oocytes. Mechanisms of development,2004. 121(1):p.101-9.
40. Ross, A.F., et al., Characterization of a beta-actin mRNA zipcode-binding protein. Mol Cell Biol,1997.17(4):p.2158-65.
41. Munro, T.P., et al., Mutational analysis of a heterogeneous nuclear ribonucleoprotein A2 response element for RNA trafficking. J Biol Chem,1999.274(48):p.34389-95.
42. Shan, J., et al., A molecular mechanism for mRNA trafficking in neuronal dendrites. J Neurosci,2003.23(26):p.8859-66.
43. Ainger, K., et al., Transport and localization elements in myelin basic protein mRNA J Cell Biol,1997.138(5):p.1077-87.
44. Raju, C.S., et al., In neurons, activity-dependent association of dendritically transported mRNA transcripts with the transacting factor CBF-A is mediated by A2RE/RTS elements. Mol Biol Cell,2011.22(11):p.1864-77.
45. Jacobsen, A., et al., Signatures of RNA binding proteins globally coupled to effective microRNA target sites. Genome Res,2010.20(8):p.1010-9.
46. Chen, C.Y. and A.B. Shyu, AU-rich elements:characterization and importance in mRNA degradation. Trends Biochem Sci,1995.20(11):p.465-70.
47. Gruber, A.R., et al., AREsite:a database for the comprehensive investigation of AU-rich elements. Nucleic Acids Res,2011.39(Database issue):p. D66-9.
48. Bakheet, T., B.R. Williams, and K.S. Khabar, ARED 3.0:the large and diverse AU-rich transcriptome. Nucleic Acids Res,2006.34(Database issue):p. D111-4.
49. Yang, E., et al., Decay rates of human mRNAs:correlation with functional characteristics and sequence attributes. Genome Res,2003.13(8):p.1863-72.
50. Oh-Hashi, K., Y. Hirata, and K. Kiuchi, Characterization of 3'-untranslated region of the mouse GDNFgene. BMC Mol Biol,2012.13(1):p.2.
51. Vlasova, I.A. and P.R. Bohjanen, Posttranscriptional regulation of gene networks by GU-rich elements and CELF proteins. RNA Biol,2008.5(4):p.201-7.
52. Vlasova, I.A., et al., Conserved GU-rich elements mediate mRNA decay by binding to CUG-bindingprotein 1. Mol Cell,2008.29(2):p.263-70.
53. Rattenbacher, B., et al., Analysis of CUGBP1 targets identifies GU-repeat sequences that mediate rapid mRNA decay. Mol Cell Biol,2010.30(16):p.3970-80.
54. Irier, H.A., et al., Translational regulation of GluR2 mRNAs in rat hippocampus by alternative 3'untranslated regions. J Neurochem,2009.109(2):p.584-94.
55. Irier, H.A., et al., Control of glutamate receptor 2 (GluR2) translational initiation by its alternative 3'untranslated regions. Mol Pharmacol,2009.76(6):p.1145-9.
56. Subramaniam, K., et al., The 3'-untranslated region of the beta2-adrenergic receptor mRNA regulates receptor synthesis. J Biol Chem,2004.279(26):p.27108-15.
57. Otero, L.J., A. Devaux, and N. Standart, A 250-nucleotide UA-rich element in the 3' untranslated region of Xenopus laevis Vg1 mRNA represses translation both in vivo and in vitro. RNA,2001.7(12):p.1753-67.
58. Smibert, C.A., et al., smaug protein represses translation of unlocalized nanos mRNA in the Drosophila embryo. Genes Dev,1996.10(20):p.2600-9.
59. Dahanukar, A. and R.P. Wharton, The Nanos gradient in Drosophila embryos is generated by translational regulation. Genes Dev,1996.10(20):p.2610-20.
60. Oberstrass, F.C., et al., Shape-specific recognition in the structure of the Vts1p SAM domain with RNA Nat Struct Mol Biol,2006.13(2):p.160-7.
61. Aviv, T., et al., Sequence-specific recognition of RNA hairpins by the SAM domain of Vts1p. Nat Struct Mol Biol,2006.13(2):p.168-76.
62. Grillo, G., et al., UTRdb and UTRsite (RELEASE 2010):a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs. Nucleic Acids Res,2010. 38(Database issue):p. D75-80.
63. Jacobs, G.H., et al., Transterm:a database to aid the analysis of regulatory sequences in mRNAs. Nucleic Acids Res,2009.37(Database issue):p. D72-6.
64. Huang, H.Y., et al., RegRNA: an integrated web server for identifying regulatory RNA motifs and elements. Nucleic acids research,2006.34(Web Server issue):p. W429-34.
65. Bailey, T.L., et al., MEME SUITE:tools for motif discovery and searching. Nucleic Acids Res, 2009.37(Web Server issue):p. W202-8.
66. Hiller, M., et al., Using RNA secondary structures to guide sequence motif finding towards single-stranded regions. Nucleic Acids Res,2006.34(17):p. e117.
67. Hofacker, I.L., Vienna RNA secondary structure server. Nucleic acids research,2003.31(13): p.3429-31.
68. Pavesi, G., et al., RNAProfile:an algorithm for finding conserved secondary structure motifs in unalignedRNA sequences. Nucleic Acids Res,2004.32(10):p.3258-69.
69. Yao, Z., Z. Weinberg, and W.L. Ruzzo, CMfinder--a covariance model based RNA motif finding algorithm. Bioinformatics,2006.22(4):p.445-52.
70. Xu, X., Y. Ji, and G.D. Stormo, RNA Sampler:a new sampling based algorithm for common RNA secondary structure prediction and structural alignment. Bioinformatics,2007.23(15):p. 1883-91.
71. Foat, B.C. and G.D. Stormo, Discovering structural cis-regulatory elements by modeling the behaviors of mRNAs. Mol Syst Biol,2009.5:p.268.
72. Cook, K.B., et al., RBPDB:a database ofRNA-binding specificities. Nucleic Acids Res,2010.
73. Clery, A., M. Blatter, and F.H. Allain, RNA recognition motifs:boring? Not quite. Curr Opin Struct Biol,2008.18(3):p.290-8.
74. Galante, P.A., et al., A comprehensive in silico expression analysis of RNA binding proteins in normal and tumor tissue:Identification of potential players in tumor formation. RNA Biol, 2009.6(4):p.426-33.
75. St Johnston, D., D. Beuchle, and C. Nusslein-Volhard, Staufen, a gene required to localize maternal RNAs in the Drosophila egg. Cell,1991.66(1):p.51-63.
76. Ferrandon, D., et al., Staufen protein associates with the 3'UTR of bicoid mRNA to form particles that move in a microtubule-dependent manner: Cell,1994.79(7):p.1221-32.
77. Kiebler, M.A., et al., The mammalian staufen protein localizes to the somatodendritic domain of cultured hippocampal neurons:implications for its involvement in mRNA transport. J Neurosci,1999.19(1):p.288-97.
78. Tang, S.J., et al., A role for a rat homolog of staufen in the transport of RNA to neuronal dendrites. Neuron,2001.32(3):p.463-75.
79. Farina, K.L., et al., Two ZBP1 KH domains facilitate beta-actin mRNA localization, granule formation, and cytoskeletal attachment. J Cell Biol,2003.160(1):p.77-87.
80. Deshler, J.O., M.I. Highett, and B.J. Schnapp, Localization of Xenopus Vgl mRNA by Vera protein and the endoplasmic reticulum. Science,1997.276(5315):p.1128-31.
81. Lin, A.C. and C.E. Holt, Local translation and directional steering in axons. EMBO J,2007. 26(16):p.3729-36.
82. Zhang, H.L., et al., Neurotrophin-induced transport of a beta-actin mRNP complex increases beta-actin levels and stimulates growth cone motility. Neuron,2001.31(2):p.261-75.
83. Pan, F., et al., ZBP2 facilitates binding ofZBP1 to beta-actin mRNA during transcription. Mol Cell Biol,2007.27(23):p.8340-51.
84. Rehbein, M., et al., Two trans-acting rat-brain proteins, MARTA1 and MARTA2, interact specifically with the dendritic targeting element in MAP2 mRNAs. Brain Res Mol Brain Res, 2000.79(1-2):p.192-201.
85. Kroll, T.T., et al., A homolog of FBP2/KSRP binds to localized mRNAs in Xenopus oocytes. Development,2002.129(24):p.5609-19.
86. Meisner, N.C., et al., mRNA openers and closers:modulating AU-rich element-controlled mRNA stability by a molecular switch in mRNA secondary structure. Chembiochem,2004. 5(10):p.1432-47.
87. Zhou, C., C.Z. Vignere, and E.S. Levitan, AUF1 is upregulated by angiotensin Ⅱto destabilize cardiac Kv4.3 channel mRNA Journal of molecular and cellular cardiology,2008.45(6):p. 832-8.
88. Ishimaru, D., et al., Mechanism of regulation of bcl-2 mRNA by nucleolin and A+U-rich element-binding factor 1 (AUF1). The Journal of biological chemistry,2010.285(35):p. 27182-91.
89. McGray, A.J., et al., Regulation of thrombospondin-1 expression through AU-rich elements in the 3'UTR of the mRNA Cellular & molecular biology letters,2011.16(1):p.55-68.
90. Gouble, A., et al., A new player in oncogenesis:AUF1/hnRNPD overexpression leads to tumorigenesis in transgenic mice. Cancer research,2002.62(5):p.1489-95.
91. Zhang, J., G. Tsaprailis, and G.T. Bowden, Nucleolin stabilizes Bcl-X L messenger RNA in response to UVA irradiation. Cancer research,2008.68(4):p.1046-54.
92. Otake, Y., et al., Overexpression of nucleolin in chronic lymphocytic leukemia cells induces stabilization of bcl2 mRNA Blood,2007.109(7):p.3069-75.
93. Westmark, C.J. and J.S. Malter, Extracellular-regulated kinase controls beta-amyloid precursor protein mRNA decay. Brain Res Mol Brain Res,2001.90(2):p.193-201.
94. Imai, T., et al., The neural RNA-binding protein Musashil translationally regulates mammalian numb gene expression by interacting with its mRNA Mol Cell Biol,2001.21(12): p.3888-900.
95. Horisawa, K., et al.,3'-Untranslated region of doublecortin mRNA is a binding target of the Musashil RNA-binding protein. FEBS letters,2009.583(14):p.2429-34.
96. Chritton, J.J. and M. Wickens, Translational repression by PUF proteins in vitro:RNA,2010. 16(6):p.1217-25.
97. Backlund, M., et al., Posttranscriptional regulation of angiotensin Ⅱ type 1 receptor expression byglyceraldehyde 3-phosphate dehydrogenase. Nucleic Acids Res,2009.37(7):p. 2346-58.
98. Ben-Tabou de-Leon, S. and E.H. Davidson, Modeling the dynamics of transcriptional gene regulatory networks for animal development. Dev Biol,2009.325(2):p.317-28.
99. Tennyson, C.N., H.J. Klamut, and R.G. Worton, The human dystrophin gene requires 16 hours to be transcribed and is cotranscriptionally spliced. Nat Genet,1995.9(2):p.184-90.
100. Barreau, C., L. Paillard, and H.B. Osborne, AU-rich elements and associated factors:are there unifying principles?Nucleic acids research,2005.33(22):p.7138-50.
101. Lal, A., et al., Concurrent versus individual binding of HuR and AUF1 to common labile target mRNAs. EMBO J,2004.23(15):p.3092-102.
102. Pan, Y.X., H. Chen, and M.S. Kilberg, Interaction of RNA-binding proteins HuR and AUF1 with the human ATF3 mRNA 3'-untranslated region regulates its amino acid limitation-induced stabilization. J Biol Chem,2005.280(41):p.34609-16.
103. Young, L.E., et al., The mRNA binding proteins HuR and tristetraprolin regulate cyclooxygenase 2 expression during colon carcinogenesis. Gastroenterology,2009.136(5):p. 1669-79.
104. Kedde, M., et al., A Pumilio-induced RNA structure switch in p27-3' UTR controls miR-221 andmiR-222 accessibility. Nature cell biology,2010.12(10):p.1014-20.
105. Tominaga, K., et al., Competitive regulation of nucleolin expression by HuR and miR-494. Mol Cell Biol,2011.31(20):p.4219-31.
106. Epis, M.R., et al., The RNA-binding Protein HuR Opposes the Repression of ERBB-2 Gene Expression by MicroRNAmiR-331-3p in Prostate Cancer Cells. J Biol Chem,2011.286(48): p.41442-54.
107. Bhattacharyya, S.N., et al., Relief of microRNA-mediated translational repression in human cells subjected to stress. Cell,2006.125(6):p.1111-24.
108. Young, L.E., et al., The mRNA stability factor HuR inhibits microRNA-16 targeting of COX-2. Mol Cancer Res,2012.10(1):p.167-80.
109. Ellington, A.D. and J.W. Szostak, In vitro selection of RNA molecules that bind specific ligands. Nature,1990.346(6287):p.818-22.
110. Tuerk, C. and L. Gold, Systematic evolution of ligands by exponential enrichment:RNA ligands to bacteriophage T4 DNApolymerase. Science,1990.249(4968):p.505-10.
111. Garner, M.M. and A. Revzin, A gel electrophoresis method for quantifying the binding of proteins to specific DNA regions:application to components of the Escherichia coli lactose operon regulatory system. Nucleic Acids Res,1981.9(13):p.3047-60.
112. Keene, J.D., J.M. Komisarow, and M.B. Friedersdorf, RIP-Chip:the isolation and identification of mRNAs, microRNAs and protein components ofribonucleoprotein complexes from cell extracts. Nature protocols,2006.1(1):p.302-7.
113. Baroni, T.E., et al., Advances in RIP-chip analysis:RNA-binding protein immunoprecipitation-microarrayproling. Methods Mol Biol,2008.419:p.93-108.
114. Hafner, M., et al., Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell,2010.141(1):p.129-41.
115. Licatalosi, D.D., et al., HITS-CLIP yields genome-wide insights into brain alternative RNA processing. Nature,2008.456(7221):p.464-9.
116. Hafner, M., et al., PAR-CliP--a method to identify transcriptome-wide the binding sites of RNA binding proteins. Journal of visualized experiments:JoVE,2010(41).
117. Konig, J., et al., iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution. Nat Struct Mol Biol,2010.17(7):p.909-15.
118. Cheung, P., et al., Specific interaction ofHeLa cell proteins with coxsackievirus B3 3'UTR:La autoantigen binds the 3'and 5'UTR independently of the poly(A) tail. Cell Microbiol,2007. 9(7):p.1705-15.
119. Rabani, M., M. Kertesz, and E. Segal, Computational prediction of RNA structural motifs involved in posttranscriptional regulatory processes. Proc Natl Acad Sci U S A,2008.105(39): p.14885-90.
120. Ding, Y. and C.E. Lawrence, A statistical sampling algorithm for RNA secondary structure prediction. Nucleic Acids Res,2003.31(24):p.7280-301.
121. Kazan, H., et al., RNAcontext:a new method for learning the sequence and structure binding preferences ofRNA-bindingproteins. PLoS Comput Biol,2010.6:p.e1000832.
122. Nordlund, J., et al., Digital gene expression profiling of primary acute lymphoblastic leukemia cells. Leukemia,2011.
123. Shen, Y., et al., Transcriptome dynamics through alternative polyadenylation in developmental and environmental responses in plants revealed by deep sequencing. Genome Res,2011.21(9): p.1478-86.
124. Shepard, P.J., et al., Complex and dynamic landscape of RNA polyadenylation revealed by PAS-Seq. RNA,2011.17(4):p.761-72.
125. Boutet, S.C., et al., Alternative Polyadenylation Mediates MicroRNA Regulation of Muscle Stem Cell Function. Cell Stem Cell,2012.10(3):p.327-36.
126. Lin, B., et al., Massively parallel signature sequencing and bioinformatics analysis identifies up-regulation of TGFBI and SOX4 in human glioblastoma. PLoS ONE,2010.5(4):p.e10210.
127. Reinartz, J., et al., Massively parallel signature sequencing (MPSS) as a tool for in-depth quantitative gene expression profiling in all organisms. Briefings in functional genomics & proteomics,2002.1(1):p.95-104.
128. Brenner, S., et al., Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nat Biotechnol,2000.18(6):p.630-4.
129. Anders, S. and W. Huber, Differential expression analysis for sequence count data. Genome biology,2010.11(10):p. R106.
130. Blahnik, K.R., et al., Sole-Search:an integrated analysis program for peak detection and functional annotation using ChIP-seq data. Nucleic Acids Res,2010.38(3):p. e13.
131. Koscielny, G., et al., ASTD:The Alternative Splicing and Transcript Diversity database. Genomics,2009.93(3):p.213-20.
132. Elkon, R., et al., E2F mediates enhanced alternative polyadenylation in proliferation. Genome Biol,2012.13(7):p. R59.
133. Hoque, M., et al., Analysis of alternative cleavage and polyadenylation by 3'region extraction and deep sequencing. Nat Methods,2013.10(2):p.133-9.
134. Wilkening, S., et al., An efficient method for genome-wide polyadenylation site mapping and RNA quantification. Nucleic Acids Res,2013.41(5):p. e65.
135. Wang, L., R.D. Dowell, and R. Yi, Genome-wide maps of polyadenylation reveal dynamic mRNA 3'-end formation in mammalian cell lineages. RNA,2013.19(3):p.413-25.
136. Potthoff, M.J. and E.N. Olson, MEF2:a central regulator of diverse developmental programs. Development,2007.134(23):p.4131-40.
137. Lam, B.Y. and S. Chawla, MEF2D expression increases during neuronal differentiation of neural progenitor cells and correlates with neurite length. Neuroscience letters,2007.427(3): p.153-8.
138. Souza, A.P., et al., HspBP1 levels are elevated in breast tumor tissue and inversely related to tumor aggressiveness. Cell stress & chaperones,2009.14(3):p.301-10.
139. Sanchez-Beato, M., et al., Variability in the expression of polycomb proteins in different normal and tumoral tissues. A pilot study using tissue microarrays. Modern pathology:an official journal of the United States and Canadian Academy of Pathology, Inc,2006.19(5):p. 684-94.
140. Scotto-Lavino, E., G. Du, and M.A. Frohman,3'end cDNA amplification using classic RACE. Nature protocols,2006.1(6):p.2742-5.
141. Rozen, S. and H. Skaletsky, Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol,2000.132:p.365-86.
142. Huang, Y., et al., A study of miRNAs targets prediction and experimental validation. Protein Cell,2010.1(11):p.979-86.
143. Nicolas, F.E., Experimental validation ofmicroRNA targets using a luciferase reporter system. Methods Mol Biol,2011.732:p.139-52.
144. Hofacker, I.L., M. Fekete, and P.F. Stadler, Secondary structure prediction for aligned RNA sequences. Journal of molecular biology,2002.319(5):p.1059-66.
145. Gautheret, D. and A. Lambert, Direct RNA motif definition and identification from multiple sequence alignments using secondary structure profiles. J Mol Biol,2001.313(5):p.1003-11.
146. Giegerich, R., B. Voss, and M. Rehmsmeier, Abstract shapes of RNA. Nucleic Acids Res,2004. 32(16):p.4843-51.
147. Mathews, D.H. and D.H. Turner, Dynalign:an algorithm for finding the secondary structure common to two RNA sequences. J Mol Biol,2002.317(2):p.191-203.
148. Mathews, D., Predicting the secondary structure common to two RNA sequences with Dynalign. Curr Protoc Bioinformatics,2004. Chapter 12:p. Unit 124.
149. Harmanci, A.O., G. Sharma, and D.H. Mathews, Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign. BMC Bioinformatics,2007.8:p.130.
150. Will, S., et al., Inferring noncoding RNA families and classes by means of genome-scale structure-based clustering. PLoS Comput Biol,2007.3(4):p. e65.
151. Havgaard, J.H., R.B. Lyngso, and J. Gorodkin, The FOLDALIGN web server for pairwise structural RNA alignment and mutual motif search. Nucleic acids research,2005.33(Web Server issue):p. W650-3.
152. Do, C.B., C.S. Foo, and S. Batzoglou, A max-margin model for efficient simultaneous alignment and folding of RNA sequences. Bioinformatics,2008.24(13):p. i68-76.
153. Ji, Y., X. Xu, and G.D. Stormo, A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences. Bioinformatics, 2004.20(10):p.1591-602.
154. Hamada, M., et al., Mining frequent stem patterns from unaligned RNA sequences. Bioinformatics,2006.22(20):p.2480-7.
155. Wei, D., L.V. Alpert, and C.E. Lawrence, RNAG:a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences. Bioinformatics,2011.27(18):p.2486-93.
156. Liu, J., et al., A method for aligning RNA secondary structures and its application to RNA motifdetection. BMC Bioinformatics,2005.6:p.89.
157. Filippova, N., et al., The Rna-Binding Protein Hur Promotes Glioma Growth and Treatment Resistance. Molecular cancer research:MCR,2011.
158. Calaluce, R., et al., The RNA binding protein HuR differentially regulates unique subsets of mRNAs in estrogen receptor negative and estrogen receptor positive breast cancer. BMC Cancer,2010.10:p.126.
159. Heinonen, M., et al., Role of RNA binding protein HuR in ductal carcinoma in situ of the breast. The Journal of pathology,2011.
160. Mazan-Mamczarz, K., et al., Identification of transformation-related pathways in a breast epithelial cell model using a ribonomics approach. Cancer Res,2008.68(19):p.7730-5.
161. Saunus, J.M., et al., Posttranscriptional regulation of the breast cancer susceptibility gene BRCA1 by the RNA binding protein HuR. Cancer Res,2008.68(22):p.9469-78.
162. Gubin, M.M., et al., Overexpression of the RNA binding protein HuR impairs tumor growth in triple negative breast cancer associated with deficient angiogenesis. Cell Cycle,2010.9(16): p.3337-46.
163. Denkert, C., et al., Expression of the ELAV-like protein HuR is associated with higher tumor grade and increased cyclooxygenase-2 expression in human breast carcinoma. Clinical cancer research:an official journal of the American Association for Cancer Research,2004.10(16): p.5580-6.
164. Fay, J., et al., Increased expression of cellular RNA-binding proteins in HPV-induced neoplasia and cervical cancer. J Med Virol,2009.81(5):p.897-907.
165. Lopez de Silanes, I., et al., Role of the RNA-binding protein HuR in colon carcinogenesis. Oncogene,2003.22(46):p.7146-54.
166. Abdelmohsen, K. and M. Gorospe, Posttranscriptional regulation of cancer traits by HuR Wiley Interdiscip Rev RNA,2010.1(2):p.214-29.
167. Okano, H., T. Imai, and M. Okabe, Musashi:a translational regulator of cell fate. Journal of cell science,2002.115(Pt 7):p.1355-9.
168. MacNicol, M.C., C.E. Cragle, and A.M. MacNicol, Context-dependent regulation of Musashi-mediated mRNA translation and cell cycle regulation. Cell Cycle,2011.10(1):p. 39-44.
169. Toda, M., et al., Expression of the neural RNA-binding protein Musashi1 in human gliomas. Glia,2001.34(1):p.1-7.
170. Wang, X.Y., et al., Musashi1 regulates breast tumor cell proliferation and is a prognostic indicator of poor survival. Molecular cancer,2010.9:p.221.
171. Padmanabhan, K. and J.D. Richter, Regulated Pumilio-2 binding controls RINGO/Spy mRNA translation and CPEBactivation. Genes & development,2006.20(2):p.199-209.
172. Iervolino, A., et al., hnRNP Al nucleocytoplasmic shuttling activity is required for normal myelopoiesis and BCR/ABL leukemogenesis. Mol Cell Biol,2002.22(7):p.2255-66.
173. Sommer, G., et al., Implication of RNA-binding protein La in proliferation, migration and invasion of lymph node-metastasized hypopharyngeal SCC cells. PLoS ONE,2011.6(10):p. e25402.
174. Al-Ejeh, F., J.M. Darby, and M.P. Brown, The La autoantigen is a malignancy-associated cell death target that is induced by DNA-damaging drugs. Clinical cancer research:an official journal of the American Association for Cancer Research,2007.13(18 Pt 2):p.5509s-5518s.
175. Trotta, R., et al., BCR/ABL activates mdm2 mRNA translation via the La antigen. Cancer Cell, 2003.3(2):p.145-60.
176. Sommer, G., et al., The RNA-binding protein La contributes to cell proliferation and CCND1 expression. Oncogene,2011.30(4):p.434-44.
177. Shi, Y., et al., IL-6-induced enhancement of c-Myc translation in multiple myeloma cells: critical role of cytoplasmic localization of the rna-binding protein hnRNP Al. J Biol Chem, 2011.286(1):p.67-78.
178. Guil, S., J.C. Long, and J.F. Caceres, hnRNP Al relocalization to the stress granules reflects a role in the stress response. Mol Cell Biol,2006.26(15):p.5744-58.
179. Hope, N.R. and G.I. Murray, The expression profile of RNA-binding proteins in primary and metastatic colorectal cancer:relationship of heterogeneous nuclear ribonucleoproteins with prognosis. Hum Pathol, 2011. 42(3): p. 393-402.
180. Ma, Y.L., et al., Heterogeneous nuclear ribonucleoprotein Al is identified as a potentialbiomarker for colorectal cancer based on differential proteomics technology. J Proteome Res,2009. 8(10): p. 4525-35.
181. Mukherjee, N., et al., Coordinated posttranscriptional mRNA population dynamics duringT-cell activation. Mol Syst Biol, 2009. 5: p. 288.
182. Mazan-Mamczarz, K., et al., Identification of a signature motif in target mRNAs ofRNA-bindingprotein AUF1. Nucleic Acids Res, 2009. 37(1): p. 204-14.
183. de Sousa Abreu, R., et al., Genomic analyses of musashil downstream targets show a strongassociation with cancer-related processes. J Biol Chem, 2009. 284(18): p. 12125-35.
184. Eiring, A.M., et al., Identification of novel posttranscriptional targets of the BCR/ABLoncoprotein by ribonomics: requirement of E2F3 for BCR/ABL leukemogenesis. Blood, 2008.111(2): p. 816-28.
185. Yang, C, D.A. Maiguel, and F. Carrier, Identification of nucleolin and nucleophosmin asgenotoxic stress-responsive RNA-binding proteins. Nucleic acids research, 2002. 30(10): p.2251-60.
186. Galgano, A., et al., Comparative analysis of mRNA targets for human PUF-family proteinssuggests extensive interaction with the miRNA regulatory system. PLoS ONE, 2008. 3(9): p.e3164.
187. Kishore, S., et al., A quantitative analysis of CLIP methods for identifying binding sites ofRNA-binding proteins. Nature methods, 2011.
188. Mukherjee, N., et al., Integrative regulatory mapping indicates that the RNA-binding proteinHuR couples pre-mRNA processing and mRNA stability. Mol Cell, 2011. 43(3): p. 327-39.
189. Lebedeva, S., et al., Transcriptome-wide analysis of regulatory interactions of theRNA-binding protein HuR Mol Cell, 2011.43(3): p. 340-52.
190. Tollervey, J.R., et al., Characterizing the RNA targets and position-dependent splicingregulation by TDP-43. Nat Neurosci, 2011.14(4): p. 452-8.
191. Wang, Z., et al., iCLIP predicts the dual splicing effects of TIA-RNA interactions. PLoS Biol,2010. 8(10): p. el000530.
192. Eddy, S.R. and R. Durbin, RNA sequence analysis using covariance models. Nucleic AcidsRes, 1994. 22(11): p. 2079-88.
193. Nawrocki, E.P., D.L. Kolbe, and S.R. Eddy, Infernal 1.0: inference of RNA alignments.Bioinformatics, 2009. 25(10): p. 1335-7.
194. Weinberg, Z. and R.R. Breaker, R2R--software to speed the depiction of aesthetic consensusRNA secondary structures. BMC Bioinformatics, 2011.12: p. 3.
195. Enright, A.J., et al., MicroRNA targets in Drosophila. Genome Biol, 2003. 5(1): p. R1.
196. Krek, A., et al., Combinatorial microRNA target predictions. Nat Genet, 2005. 37(5): p.495-500.
197. Grimson, A., et al., MicroRNA targeting specificity in mammals: determinants beyond seedpairing. Mol Cell, 2007. 27(1): p. 91-105.
198. Rehmsmeier, M., et al., Fast and effective prediction of microRNA/target duplexes. RNA,2004.10(10): p. 1507-17.
199. Legendre, M., et al., Differential repression of alternative transcripts: a screen for miRNAtargets. PLoS Comput Biol, 2006. 2(5): p. e43.
200. Thomas, L.F. and P. Saetrom, Single nucleotide polymorphisms can create alternative polyadenylation signals and affect gene expression through loss of microRNA-reguiation. PLoS Comput Biol,2012.8(8):p. e1002621.
201. Al Rayyan, N., et al., Two single nucleotide polymorphisms in the human nescient helix-loop-helix 2 (NHLH2) gene reduce mRNA stability and DNA binding. Gene,2013. 512(1):p.134-42.
202. Keller, A., et al., Identification of novel SNPs in glioblastoma using targeted resequencing. PLoS One,2011.6(6):p. e18158.
203. Li, H. and R. Durbin, Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics,2009.25(14):p.1754-60.
204. Li, H., et al., The Sequence Alignment/Map format and SAMtools. Bioinformatics,2009. 25(16):p.2078-9.
205. Wang, K., M. Li, and H. Hakonarson, ANNOVAR:functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res,2010.38(16):p. e164.
206. Rajaraman, P., et al., Genome-wide association study of glioma and meta-analysis. Hum Genet,2012.131(12):p.1877-88.
207. Nicoloso, M.S., et al., Single-nucleotide polymorphisms inside microRNA target sites influence tumor susceptibility. Cancer Res,2010.70(7):p.2789-98.
208. Haas, U., G. Sczakiel, and S.D. Laufer, MicroRNA-mediated regulation of gene expression is affected by disease-associated SNPs within the 3'-UTR via altered RNA structure. RNA Biol, 2012.9(6):p.924-37.
209. Bruno, A.E., et al., miRdSNP:a database of disease-associated SNPs and microRNA target sites on 3'UTRs of human genes. BMC Genomics,2012.13:p.44.
210. Brockmann, R., et al., Posttranscriptional expression regulation:what determines translation rates? PLoS Comput Biol,2007.3(3):p. e57.
211. Tian, Q., et al., Integrated genomic and proteomic analyses of gene expression in Mammalian cells. Molecular & cellular proteomics:MCP,2004.3(10):p.960-9.
212. Nie, L., G. Wu, and W. Zhang, Correlation between mRNA and protein abundance in Desulfovibrio vulgaris:a multiple regression to identify sources of variations. Biochemical and biophysical research communications,2006.339(2):p.603-10.
213. Andreassi, C. and A. Riccio, To localize or not to localize:mRNA fate is in 3'UTR ends. Trends Cell Biol,2009.19(9):p.465-74.
214. Shi, Y., et al., Molecular architecture of the human pre-mRNA 3'processing complex. Mol Cell,2009.33(3):p.365-76.
215. Mapendano, C.K., et al., Crosstalk between mRNA 3' end processing and transcription initiation. Mol Cell,2010.40(3):p.410-22.
216. Ji, Z., et al., Transcriptional activity regulates alternative cleavage and polyadenylation. Mol Syst Biol,2011.7:p.534.
2. McKee, A.E. and P.A. Silver, Systems perspectives on mRNA processing. Cell Res,2007. 17(7):p.581-90.
3. Chatterjee, S. and J.K. Pal, Role of 5'- and 3'-untranslated regions of mRNAs in human diseases. Biol Cell,2009.101(5):p.251-62.
4. Triboulet, R. and R.I. Gregory, Pumilio turns on microRNA function. Nature cell biology,2010. 12(10):p.928-9.
5. Lutz, C.S. and A. Moreira, Alternative mRNA polyadenylation in eukaryotes:an effective regulator of gene expression. WIREs RNA,2011.2(1):p.23-31.
6. Morris, A.R., N. Mukherjee, and J.D. Keene, Systematic analysis of posttranscriptional gene expression. Wiley Interdiscip Rev Syst Biol Med,2010.2(2):p.162-80.
7. Ray, D., et al., Rapid and systematic analysis of the RNA recognition specificities of RNA-bindingproteins. Nat Biotechnol,2009.27(7):p.667-70.
8. Licatalosi, D.D. and R.B. Darnell, RNA processing and its regulation:global insights into biological networks. Nat Rev Genet,2010.11(1):p.75-87.
9. Legendre, M. and D. Gautheret, Sequence determinants in human polyadenylation site selection. BMC Genomics,2003.4(1):p.7.
10. Beaudoing, E., et al., Patterns of variant polyadenylation signal usage in human genes. Genome Res,2000.10(7):p.1001-10.
11. Cheng, Y, R.M. Miura, and B. Tian, Prediction of mRNA polyadenylation sites by support vector machine. Bioinformatics,2006.22(19):p.2320-5.
12. Akhtar, M.N., et al., POLLYAR, a new computer program for prediction of poly(A) sites in human sequences. BMC Genomics,2010.11:p.646.
13. Lambert, A., et al., The ERPINserver:an interface to profile-based RNA motif identification. Nucleic acids research,2004.32(Web Server issue):p. W160-5.
14. Lee, J.Y., et al., PolyA_DB2:mRNA polyadenylation sites in vertebrate genes. Nucleic Acids Res,2007.35(Database issue):p. D165-8.
15. Zhang, H., et al., PolyA_DB:a database for mammalian mRNA polyadenylation. Nucleic Acids Res,2005.33(Database issue):p. D116-20.
16. Tian, B., et al., A large-scale analysis of mRNA polyadenylation of human and mouse genes. Nucleic Acids Res,2005.33(1):p.201-12.
17. Zhang, H., J.Y. Lee, and B. Tian, Biased alternative polyadenylation in human tissues. Genome Biol,2005.6(12):p. R100.
18. Sandberg, R., et al., Proliferating cells express mRNAs with shortened 3'untranslated regions and fewer microRNA target sites. Science,2008.320(5883):p.1643-7.
19. Singh, P., et al., Global Changes in Processing of mRNA 3'Untranslated Regions Characterize Clinically Distinct Cancer Subtypes. Cancer Res,2009.
20. Mayr, C. and D.P. Bartel, Widespread shortening of 3'UTRs by alternative cleavage and polyadenylation activates oncogenes in cancer cells. Cell,2009.138(4):p.673-84.
21. Fu, Y, et al., Differential genome-wide profiling of tandem 3' UTRs among human breast cancer and normal cells by high-throughput sequencing. Genome research,2011.
22. Ramskold, D., et al., An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS Comput Biol,2009.5(12):p. e1000598.
23. Lau, A.G., et al., Distinct 3' UTRs differentially regulate activity-dependent translation of brain-derived neurotrophic factor (BDNF). Proc Natl Acad Sci U S A,2010.
24. An, J.J., et al., Distinct role of long 3' UTR BDNF mRNA in spine morphology and synaptic plasticity in hippocampal neurons. Cell,2008.134(1):p.175-87.
25. Ji, Z., et al., Progressive lengthening of 3'untranslated regions of mRNAs by alternative polyadenylation during mouse embryonic development. Proc Natl Acad Sci U S A,2009.
26. Flavell, S.W., et al., Genome-wide analysis ofMEF2 transcriptional program reveals synaptic target genes and neuronal activity-dependent polyadenylation site selection. Neuron,2008. 60(6):p.1022-38.
27. Yoon, K.., et al., Over-represented sequences located on 3' UTRs are potentially involved in regulatory functions. RNA Biol,2008.5(4):p.255-62.
28. Shibata, T., et al., A polymorphism in the 3'-utr of cyclooxygenase-2 and the risk of gastric cancer. Molecular medicine reports,2008.1(4):p.561-4.
29. Sun, C., et al., Differential allelic expression ofc.1568C＞A at UGT2B15 is due to variation in a novel cis-regulatory element in the 3' UTR. Gene,2011.
30. Lecuyer, E., et al., Global analysis of mRNA localization reveals a prominent role in organizing cellular architecture and function. Cell,2007.131(1):p.174-87.
31. Gonzalez, I., et al., ASH1 mRNA localization in yeast involves multiple secondary structural elements and Ash1 protein translation. Curr Biol,1999.9(6):p.337-40.
32. Chartrand, P., et al., Structural elements required for the localization ofASHl mRNA and of a green fluorescent protein reporter particle in vivo. Curr Biol,1999.9(6):p.333-6.
33. Macdonald, P.M. and G. Struhl, cis-acting sequences responsible for anterior localization of bicoid mRNA in Drosophila embryos. Nature,1988.336(6199):p.595-8.
34. Macdonald, P.M. and K. Kerr, Redundant RNA recognition events in bicoid mRNA localization. RNA,1997.3(12):p.1413-20.
35. Ferrandon, D., et al., RNA-RNA interaction is required for the formation of specific bicoid mRNA 3' UTR-STAUFENribonucleoprotein particles. EMBO J,1997.16(7):p.1751-8.
36. Simmonds, A.J., et al., Apical localization of wingless transcripts is required for wingless signaling. Cell,2001.105(2):p.197-207.
37. Najand, N. and A.J. Simmonds, A minimal WLE2 element is not sufficient to direct apical localization in the absence of RNAs containing the full length wingless 3'UTR RNA Biol, 2007.4(3):p.138-46.
38. Mowry, K.L. and D.A. Melton,Vegetal messenger RNA localization directed by a 340-nt RNA sequence element in Xenopus oocytes. Science,1992.255(5047):p.991-4.
39. Lewis, R.A., et al., Conserved and clustered RNA recognition sequences are a critical feature of signals directing RNA localization in Xenopus oocytes. Mechanisms of development,2004. 121(1):p.101-9.
40. Ross, A.F., et al., Characterization of a beta-actin mRNA zipcode-binding protein. Mol Cell Biol,1997.17(4):p.2158-65.
41. Munro, T.P., et al., Mutational analysis of a heterogeneous nuclear ribonucleoprotein A2 response element for RNA trafficking. J Biol Chem,1999.274(48):p.34389-95.
42. Shan, J., et al., A molecular mechanism for mRNA trafficking in neuronal dendrites. J Neurosci,2003.23(26):p.8859-66.
43. Ainger, K., et al., Transport and localization elements in myelin basic protein mRNA J Cell Biol,1997.138(5):p.1077-87.
44. Raju, C.S., et al., In neurons, activity-dependent association of dendritically transported mRNA transcripts with the transacting factor CBF-A is mediated by A2RE/RTS elements. Mol Biol Cell,2011.22(11):p.1864-77.
45. Jacobsen, A., et al., Signatures of RNA binding proteins globally coupled to effective microRNA target sites. Genome Res,2010.20(8):p.1010-9.
46. Chen, C.Y. and A.B. Shyu, AU-rich elements:characterization and importance in mRNA degradation. Trends Biochem Sci,1995.20(11):p.465-70.
47. Gruber, A.R., et al., AREsite:a database for the comprehensive investigation of AU-rich elements. Nucleic Acids Res,2011.39(Database issue):p. D66-9.
48. Bakheet, T., B.R. Williams, and K.S. Khabar, ARED 3.0:the large and diverse AU-rich transcriptome. Nucleic Acids Res,2006.34(Database issue):p. D111-4.
49. Yang, E., et al., Decay rates of human mRNAs:correlation with functional characteristics and sequence attributes. Genome Res,2003.13(8):p.1863-72.
50. Oh-Hashi, K., Y. Hirata, and K. Kiuchi, Characterization of 3'-untranslated region of the mouse GDNFgene. BMC Mol Biol,2012.13(1):p.2.
51. Vlasova, I.A. and P.R. Bohjanen, Posttranscriptional regulation of gene networks by GU-rich elements and CELF proteins. RNA Biol,2008.5(4):p.201-7.
52. Vlasova, I.A., et al., Conserved GU-rich elements mediate mRNA decay by binding to CUG-bindingprotein 1. Mol Cell,2008.29(2):p.263-70.
53. Rattenbacher, B., et al., Analysis of CUGBP1 targets identifies GU-repeat sequences that mediate rapid mRNA decay. Mol Cell Biol,2010.30(16):p.3970-80.
54. Irier, H.A., et al., Translational regulation of GluR2 mRNAs in rat hippocampus by alternative 3'untranslated regions. J Neurochem,2009.109(2):p.584-94.
55. Irier, H.A., et al., Control of glutamate receptor 2 (GluR2) translational initiation by its alternative 3'untranslated regions. Mol Pharmacol,2009.76(6):p.1145-9.
56. Subramaniam, K., et al., The 3'-untranslated region of the beta2-adrenergic receptor mRNA regulates receptor synthesis. J Biol Chem,2004.279(26):p.27108-15.
57. Otero, L.J., A. Devaux, and N. Standart, A 250-nucleotide UA-rich element in the 3' untranslated region of Xenopus laevis Vg1 mRNA represses translation both in vivo and in vitro. RNA,2001.7(12):p.1753-67.
58. Smibert, C.A., et al., smaug protein represses translation of unlocalized nanos mRNA in the Drosophila embryo. Genes Dev,1996.10(20):p.2600-9.
59. Dahanukar, A. and R.P. Wharton, The Nanos gradient in Drosophila embryos is generated by translational regulation. Genes Dev,1996.10(20):p.2610-20.
60. Oberstrass, F.C., et al., Shape-specific recognition in the structure of the Vts1p SAM domain with RNA Nat Struct Mol Biol,2006.13(2):p.160-7.
61. Aviv, T., et al., Sequence-specific recognition of RNA hairpins by the SAM domain of Vts1p. Nat Struct Mol Biol,2006.13(2):p.168-76.
62. Grillo, G., et al., UTRdb and UTRsite (RELEASE 2010):a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs. Nucleic Acids Res,2010. 38(Database issue):p. D75-80.
63. Jacobs, G.H., et al., Transterm:a database to aid the analysis of regulatory sequences in mRNAs. Nucleic Acids Res,2009.37(Database issue):p. D72-6.
64. Huang, H.Y., et al., RegRNA: an integrated web server for identifying regulatory RNA motifs and elements. Nucleic acids research,2006.34(Web Server issue):p. W429-34.
65. Bailey, T.L., et al., MEME SUITE:tools for motif discovery and searching. Nucleic Acids Res, 2009.37(Web Server issue):p. W202-8.
66. Hiller, M., et al., Using RNA secondary structures to guide sequence motif finding towards single-stranded regions. Nucleic Acids Res,2006.34(17):p. e117.
67. Hofacker, I.L., Vienna RNA secondary structure server. Nucleic acids research,2003.31(13): p.3429-31.
68. Pavesi, G., et al., RNAProfile:an algorithm for finding conserved secondary structure motifs in unalignedRNA sequences. Nucleic Acids Res,2004.32(10):p.3258-69.
69. Yao, Z., Z. Weinberg, and W.L. Ruzzo, CMfinder--a covariance model based RNA motif finding algorithm. Bioinformatics,2006.22(4):p.445-52.
70. Xu, X., Y. Ji, and G.D. Stormo, RNA Sampler:a new sampling based algorithm for common RNA secondary structure prediction and structural alignment. Bioinformatics,2007.23(15):p. 1883-91.
71. Foat, B.C. and G.D. Stormo, Discovering structural cis-regulatory elements by modeling the behaviors of mRNAs. Mol Syst Biol,2009.5:p.268.
72. Cook, K.B., et al., RBPDB:a database ofRNA-binding specificities. Nucleic Acids Res,2010.
73. Clery, A., M. Blatter, and F.H. Allain, RNA recognition motifs:boring? Not quite. Curr Opin Struct Biol,2008.18(3):p.290-8.
74. Galante, P.A., et al., A comprehensive in silico expression analysis of RNA binding proteins in normal and tumor tissue:Identification of potential players in tumor formation. RNA Biol, 2009.6(4):p.426-33.
75. St Johnston, D., D. Beuchle, and C. Nusslein-Volhard, Staufen, a gene required to localize maternal RNAs in the Drosophila egg. Cell,1991.66(1):p.51-63.
76. Ferrandon, D., et al., Staufen protein associates with the 3'UTR of bicoid mRNA to form particles that move in a microtubule-dependent manner: Cell,1994.79(7):p.1221-32.
77. Kiebler, M.A., et al., The mammalian staufen protein localizes to the somatodendritic domain of cultured hippocampal neurons:implications for its involvement in mRNA transport. J Neurosci,1999.19(1):p.288-97.
78. Tang, S.J., et al., A role for a rat homolog of staufen in the transport of RNA to neuronal dendrites. Neuron,2001.32(3):p.463-75.
79. Farina, K.L., et al., Two ZBP1 KH domains facilitate beta-actin mRNA localization, granule formation, and cytoskeletal attachment. J Cell Biol,2003.160(1):p.77-87.
80. Deshler, J.O., M.I. Highett, and B.J. Schnapp, Localization of Xenopus Vgl mRNA by Vera protein and the endoplasmic reticulum. Science,1997.276(5315):p.1128-31.
81. Lin, A.C. and C.E. Holt, Local translation and directional steering in axons. EMBO J,2007. 26(16):p.3729-36.
82. Zhang, H.L., et al., Neurotrophin-induced transport of a beta-actin mRNP complex increases beta-actin levels and stimulates growth cone motility. Neuron,2001.31(2):p.261-75.
83. Pan, F., et al., ZBP2 facilitates binding ofZBP1 to beta-actin mRNA during transcription. Mol Cell Biol,2007.27(23):p.8340-51.
84. Rehbein, M., et al., Two trans-acting rat-brain proteins, MARTA1 and MARTA2, interact specifically with the dendritic targeting element in MAP2 mRNAs. Brain Res Mol Brain Res, 2000.79(1-2):p.192-201.
85. Kroll, T.T., et al., A homolog of FBP2/KSRP binds to localized mRNAs in Xenopus oocytes. Development,2002.129(24):p.5609-19.
86. Meisner, N.C., et al., mRNA openers and closers:modulating AU-rich element-controlled mRNA stability by a molecular switch in mRNA secondary structure. Chembiochem,2004. 5(10):p.1432-47.
87. Zhou, C., C.Z. Vignere, and E.S. Levitan, AUF1 is upregulated by angiotensin Ⅱto destabilize cardiac Kv4.3 channel mRNA Journal of molecular and cellular cardiology,2008.45(6):p. 832-8.
88. Ishimaru, D., et al., Mechanism of regulation of bcl-2 mRNA by nucleolin and A+U-rich element-binding factor 1 (AUF1). The Journal of biological chemistry,2010.285(35):p. 27182-91.
89. McGray, A.J., et al., Regulation of thrombospondin-1 expression through AU-rich elements in the 3'UTR of the mRNA Cellular & molecular biology letters,2011.16(1):p.55-68.
90. Gouble, A., et al., A new player in oncogenesis:AUF1/hnRNPD overexpression leads to tumorigenesis in transgenic mice. Cancer research,2002.62(5):p.1489-95.
91. Zhang, J., G. Tsaprailis, and G.T. Bowden, Nucleolin stabilizes Bcl-X L messenger RNA in response to UVA irradiation. Cancer research,2008.68(4):p.1046-54.
92. Otake, Y., et al., Overexpression of nucleolin in chronic lymphocytic leukemia cells induces stabilization of bcl2 mRNA Blood,2007.109(7):p.3069-75.
93. Westmark, C.J. and J.S. Malter, Extracellular-regulated kinase controls beta-amyloid precursor protein mRNA decay. Brain Res Mol Brain Res,2001.90(2):p.193-201.
94. Imai, T., et al., The neural RNA-binding protein Musashil translationally regulates mammalian numb gene expression by interacting with its mRNA Mol Cell Biol,2001.21(12): p.3888-900.
95. Horisawa, K., et al.,3'-Untranslated region of doublecortin mRNA is a binding target of the Musashil RNA-binding protein. FEBS letters,2009.583(14):p.2429-34.
96. Chritton, J.J. and M. Wickens, Translational repression by PUF proteins in vitro:RNA,2010. 16(6):p.1217-25.
97. Backlund, M., et al., Posttranscriptional regulation of angiotensin Ⅱ type 1 receptor expression byglyceraldehyde 3-phosphate dehydrogenase. Nucleic Acids Res,2009.37(7):p. 2346-58.
98. Ben-Tabou de-Leon, S. and E.H. Davidson, Modeling the dynamics of transcriptional gene regulatory networks for animal development. Dev Biol,2009.325(2):p.317-28.
99. Tennyson, C.N., H.J. Klamut, and R.G. Worton, The human dystrophin gene requires 16 hours to be transcribed and is cotranscriptionally spliced. Nat Genet,1995.9(2):p.184-90.
100. Barreau, C., L. Paillard, and H.B. Osborne, AU-rich elements and associated factors:are there unifying principles?Nucleic acids research,2005.33(22):p.7138-50.
101. Lal, A., et al., Concurrent versus individual binding of HuR and AUF1 to common labile target mRNAs. EMBO J,2004.23(15):p.3092-102.
102. Pan, Y.X., H. Chen, and M.S. Kilberg, Interaction of RNA-binding proteins HuR and AUF1 with the human ATF3 mRNA 3'-untranslated region regulates its amino acid limitation-induced stabilization. J Biol Chem,2005.280(41):p.34609-16.
103. Young, L.E., et al., The mRNA binding proteins HuR and tristetraprolin regulate cyclooxygenase 2 expression during colon carcinogenesis. Gastroenterology,2009.136(5):p. 1669-79.
104. Kedde, M., et al., A Pumilio-induced RNA structure switch in p27-3' UTR controls miR-221 andmiR-222 accessibility. Nature cell biology,2010.12(10):p.1014-20.
105. Tominaga, K., et al., Competitive regulation of nucleolin expression by HuR and miR-494. Mol Cell Biol,2011.31(20):p.4219-31.
106. Epis, M.R., et al., The RNA-binding Protein HuR Opposes the Repression of ERBB-2 Gene Expression by MicroRNAmiR-331-3p in Prostate Cancer Cells. J Biol Chem,2011.286(48): p.41442-54.
107. Bhattacharyya, S.N., et al., Relief of microRNA-mediated translational repression in human cells subjected to stress. Cell,2006.125(6):p.1111-24.
108. Young, L.E., et al., The mRNA stability factor HuR inhibits microRNA-16 targeting of COX-2. Mol Cancer Res,2012.10(1):p.167-80.
109. Ellington, A.D. and J.W. Szostak, In vitro selection of RNA molecules that bind specific ligands. Nature,1990.346(6287):p.818-22.
110. Tuerk, C. and L. Gold, Systematic evolution of ligands by exponential enrichment:RNA ligands to bacteriophage T4 DNApolymerase. Science,1990.249(4968):p.505-10.
111. Garner, M.M. and A. Revzin, A gel electrophoresis method for quantifying the binding of proteins to specific DNA regions:application to components of the Escherichia coli lactose operon regulatory system. Nucleic Acids Res,1981.9(13):p.3047-60.
112. Keene, J.D., J.M. Komisarow, and M.B. Friedersdorf, RIP-Chip:the isolation and identification of mRNAs, microRNAs and protein components ofribonucleoprotein complexes from cell extracts. Nature protocols,2006.1(1):p.302-7.
113. Baroni, T.E., et al., Advances in RIP-chip analysis:RNA-binding protein immunoprecipitation-microarrayproling. Methods Mol Biol,2008.419:p.93-108.
114. Hafner, M., et al., Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell,2010.141(1):p.129-41.
115. Licatalosi, D.D., et al., HITS-CLIP yields genome-wide insights into brain alternative RNA processing. Nature,2008.456(7221):p.464-9.
116. Hafner, M., et al., PAR-CliP--a method to identify transcriptome-wide the binding sites of RNA binding proteins. Journal of visualized experiments:JoVE,2010(41).
117. Konig, J., et al., iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution. Nat Struct Mol Biol,2010.17(7):p.909-15.
118. Cheung, P., et al., Specific interaction ofHeLa cell proteins with coxsackievirus B3 3'UTR:La autoantigen binds the 3'and 5'UTR independently of the poly(A) tail. Cell Microbiol,2007. 9(7):p.1705-15.
119. Rabani, M., M. Kertesz, and E. Segal, Computational prediction of RNA structural motifs involved in posttranscriptional regulatory processes. Proc Natl Acad Sci U S A,2008.105(39): p.14885-90.
120. Ding, Y. and C.E. Lawrence, A statistical sampling algorithm for RNA secondary structure prediction. Nucleic Acids Res,2003.31(24):p.7280-301.
121. Kazan, H., et al., RNAcontext:a new method for learning the sequence and structure binding preferences ofRNA-bindingproteins. PLoS Comput Biol,2010.6:p.e1000832.
122. Nordlund, J., et al., Digital gene expression profiling of primary acute lymphoblastic leukemia cells. Leukemia,2011.
123. Shen, Y., et al., Transcriptome dynamics through alternative polyadenylation in developmental and environmental responses in plants revealed by deep sequencing. Genome Res,2011.21(9): p.1478-86.
124. Shepard, P.J., et al., Complex and dynamic landscape of RNA polyadenylation revealed by PAS-Seq. RNA,2011.17(4):p.761-72.
125. Boutet, S.C., et al., Alternative Polyadenylation Mediates MicroRNA Regulation of Muscle Stem Cell Function. Cell Stem Cell,2012.10(3):p.327-36.
126. Lin, B., et al., Massively parallel signature sequencing and bioinformatics analysis identifies up-regulation of TGFBI and SOX4 in human glioblastoma. PLoS ONE,2010.5(4):p.e10210.
127. Reinartz, J., et al., Massively parallel signature sequencing (MPSS) as a tool for in-depth quantitative gene expression profiling in all organisms. Briefings in functional genomics & proteomics,2002.1(1):p.95-104.
128. Brenner, S., et al., Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nat Biotechnol,2000.18(6):p.630-4.
129. Anders, S. and W. Huber, Differential expression analysis for sequence count data. Genome biology,2010.11(10):p. R106.
130. Blahnik, K.R., et al., Sole-Search:an integrated analysis program for peak detection and functional annotation using ChIP-seq data. Nucleic Acids Res,2010.38(3):p. e13.
131. Koscielny, G., et al., ASTD:The Alternative Splicing and Transcript Diversity database. Genomics,2009.93(3):p.213-20.
132. Elkon, R., et al., E2F mediates enhanced alternative polyadenylation in proliferation. Genome Biol,2012.13(7):p. R59.
133. Hoque, M., et al., Analysis of alternative cleavage and polyadenylation by 3'region extraction and deep sequencing. Nat Methods,2013.10(2):p.133-9.
134. Wilkening, S., et al., An efficient method for genome-wide polyadenylation site mapping and RNA quantification. Nucleic Acids Res,2013.41(5):p. e65.
135. Wang, L., R.D. Dowell, and R. Yi, Genome-wide maps of polyadenylation reveal dynamic mRNA 3'-end formation in mammalian cell lineages. RNA,2013.19(3):p.413-25.
136. Potthoff, M.J. and E.N. Olson, MEF2:a central regulator of diverse developmental programs. Development,2007.134(23):p.4131-40.
137. Lam, B.Y. and S. Chawla, MEF2D expression increases during neuronal differentiation of neural progenitor cells and correlates with neurite length. Neuroscience letters,2007.427(3): p.153-8.
138. Souza, A.P., et al., HspBP1 levels are elevated in breast tumor tissue and inversely related to tumor aggressiveness. Cell stress & chaperones,2009.14(3):p.301-10.
139. Sanchez-Beato, M., et al., Variability in the expression of polycomb proteins in different normal and tumoral tissues. A pilot study using tissue microarrays. Modern pathology:an official journal of the United States and Canadian Academy of Pathology, Inc,2006.19(5):p. 684-94.
140. Scotto-Lavino, E., G. Du, and M.A. Frohman,3'end cDNA amplification using classic RACE. Nature protocols,2006.1(6):p.2742-5.
141. Rozen, S. and H. Skaletsky, Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol,2000.132:p.365-86.
142. Huang, Y., et al., A study of miRNAs targets prediction and experimental validation. Protein Cell,2010.1(11):p.979-86.
143. Nicolas, F.E., Experimental validation ofmicroRNA targets using a luciferase reporter system. Methods Mol Biol,2011.732:p.139-52.
144. Hofacker, I.L., M. Fekete, and P.F. Stadler, Secondary structure prediction for aligned RNA sequences. Journal of molecular biology,2002.319(5):p.1059-66.
145. Gautheret, D. and A. Lambert, Direct RNA motif definition and identification from multiple sequence alignments using secondary structure profiles. J Mol Biol,2001.313(5):p.1003-11.
146. Giegerich, R., B. Voss, and M. Rehmsmeier, Abstract shapes of RNA. Nucleic Acids Res,2004. 32(16):p.4843-51.
147. Mathews, D.H. and D.H. Turner, Dynalign:an algorithm for finding the secondary structure common to two RNA sequences. J Mol Biol,2002.317(2):p.191-203.
148. Mathews, D., Predicting the secondary structure common to two RNA sequences with Dynalign. Curr Protoc Bioinformatics,2004. Chapter 12:p. Unit 124.
149. Harmanci, A.O., G. Sharma, and D.H. Mathews, Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign. BMC Bioinformatics,2007.8:p.130.
150. Will, S., et al., Inferring noncoding RNA families and classes by means of genome-scale structure-based clustering. PLoS Comput Biol,2007.3(4):p. e65.
151. Havgaard, J.H., R.B. Lyngso, and J. Gorodkin, The FOLDALIGN web server for pairwise structural RNA alignment and mutual motif search. Nucleic acids research,2005.33(Web Server issue):p. W650-3.
152. Do, C.B., C.S. Foo, and S. Batzoglou, A max-margin model for efficient simultaneous alignment and folding of RNA sequences. Bioinformatics,2008.24(13):p. i68-76.
153. Ji, Y., X. Xu, and G.D. Stormo, A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences. Bioinformatics, 2004.20(10):p.1591-602.
154. Hamada, M., et al., Mining frequent stem patterns from unaligned RNA sequences. Bioinformatics,2006.22(20):p.2480-7.
155. Wei, D., L.V. Alpert, and C.E. Lawrence, RNAG:a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences. Bioinformatics,2011.27(18):p.2486-93.
156. Liu, J., et al., A method for aligning RNA secondary structures and its application to RNA motifdetection. BMC Bioinformatics,2005.6:p.89.
157. Filippova, N., et al., The Rna-Binding Protein Hur Promotes Glioma Growth and Treatment Resistance. Molecular cancer research:MCR,2011.
158. Calaluce, R., et al., The RNA binding protein HuR differentially regulates unique subsets of mRNAs in estrogen receptor negative and estrogen receptor positive breast cancer. BMC Cancer,2010.10:p.126.
159. Heinonen, M., et al., Role of RNA binding protein HuR in ductal carcinoma in situ of the breast. The Journal of pathology,2011.
160. Mazan-Mamczarz, K., et al., Identification of transformation-related pathways in a breast epithelial cell model using a ribonomics approach. Cancer Res,2008.68(19):p.7730-5.
161. Saunus, J.M., et al., Posttranscriptional regulation of the breast cancer susceptibility gene BRCA1 by the RNA binding protein HuR. Cancer Res,2008.68(22):p.9469-78.
162. Gubin, M.M., et al., Overexpression of the RNA binding protein HuR impairs tumor growth in triple negative breast cancer associated with deficient angiogenesis. Cell Cycle,2010.9(16): p.3337-46.
163. Denkert, C., et al., Expression of the ELAV-like protein HuR is associated with higher tumor grade and increased cyclooxygenase-2 expression in human breast carcinoma. Clinical cancer research:an official journal of the American Association for Cancer Research,2004.10(16): p.5580-6.
164. Fay, J., et al., Increased expression of cellular RNA-binding proteins in HPV-induced neoplasia and cervical cancer. J Med Virol,2009.81(5):p.897-907.
165. Lopez de Silanes, I., et al., Role of the RNA-binding protein HuR in colon carcinogenesis. Oncogene,2003.22(46):p.7146-54.
166. Abdelmohsen, K. and M. Gorospe, Posttranscriptional regulation of cancer traits by HuR Wiley Interdiscip Rev RNA,2010.1(2):p.214-29.
167. Okano, H., T. Imai, and M. Okabe, Musashi:a translational regulator of cell fate. Journal of cell science,2002.115(Pt 7):p.1355-9.
168. MacNicol, M.C., C.E. Cragle, and A.M. MacNicol, Context-dependent regulation of Musashi-mediated mRNA translation and cell cycle regulation. Cell Cycle,2011.10(1):p. 39-44.
169. Toda, M., et al., Expression of the neural RNA-binding protein Musashi1 in human gliomas. Glia,2001.34(1):p.1-7.
170. Wang, X.Y., et al., Musashi1 regulates breast tumor cell proliferation and is a prognostic indicator of poor survival. Molecular cancer,2010.9:p.221.
171. Padmanabhan, K. and J.D. Richter, Regulated Pumilio-2 binding controls RINGO/Spy mRNA translation and CPEBactivation. Genes & development,2006.20(2):p.199-209.
172. Iervolino, A., et al., hnRNP Al nucleocytoplasmic shuttling activity is required for normal myelopoiesis and BCR/ABL leukemogenesis. Mol Cell Biol,2002.22(7):p.2255-66.
173. Sommer, G., et al., Implication of RNA-binding protein La in proliferation, migration and invasion of lymph node-metastasized hypopharyngeal SCC cells. PLoS ONE,2011.6(10):p. e25402.
174. Al-Ejeh, F., J.M. Darby, and M.P. Brown, The La autoantigen is a malignancy-associated cell death target that is induced by DNA-damaging drugs. Clinical cancer research:an official journal of the American Association for Cancer Research,2007.13(18 Pt 2):p.5509s-5518s.
175. Trotta, R., et al., BCR/ABL activates mdm2 mRNA translation via the La antigen. Cancer Cell, 2003.3(2):p.145-60.
176. Sommer, G., et al., The RNA-binding protein La contributes to cell proliferation and CCND1 expression. Oncogene,2011.30(4):p.434-44.
177. Shi, Y., et al., IL-6-induced enhancement of c-Myc translation in multiple myeloma cells: critical role of cytoplasmic localization of the rna-binding protein hnRNP Al. J Biol Chem, 2011.286(1):p.67-78.
178. Guil, S., J.C. Long, and J.F. Caceres, hnRNP Al relocalization to the stress granules reflects a role in the stress response. Mol Cell Biol,2006.26(15):p.5744-58.
179. Hope, N.R. and G.I. Murray, The expression profile of RNA-binding proteins in primary and metastatic colorectal cancer:relationship of heterogeneous nuclear ribonucleoproteins with prognosis. Hum Pathol, 2011. 42(3): p. 393-402.
180. Ma, Y.L., et al., Heterogeneous nuclear ribonucleoprotein Al is identified as a potentialbiomarker for colorectal cancer based on differential proteomics technology. J Proteome Res,2009. 8(10): p. 4525-35.
181. Mukherjee, N., et al., Coordinated posttranscriptional mRNA population dynamics duringT-cell activation. Mol Syst Biol, 2009. 5: p. 288.
182. Mazan-Mamczarz, K., et al., Identification of a signature motif in target mRNAs ofRNA-bindingprotein AUF1. Nucleic Acids Res, 2009. 37(1): p. 204-14.
183. de Sousa Abreu, R., et al., Genomic analyses of musashil downstream targets show a strongassociation with cancer-related processes. J Biol Chem, 2009. 284(18): p. 12125-35.
184. Eiring, A.M., et al., Identification of novel posttranscriptional targets of the BCR/ABLoncoprotein by ribonomics: requirement of E2F3 for BCR/ABL leukemogenesis. Blood, 2008.111(2): p. 816-28.
185. Yang, C, D.A. Maiguel, and F. Carrier, Identification of nucleolin and nucleophosmin asgenotoxic stress-responsive RNA-binding proteins. Nucleic acids research, 2002. 30(10): p.2251-60.
186. Galgano, A., et al., Comparative analysis of mRNA targets for human PUF-family proteinssuggests extensive interaction with the miRNA regulatory system. PLoS ONE, 2008. 3(9): p.e3164.
187. Kishore, S., et al., A quantitative analysis of CLIP methods for identifying binding sites ofRNA-binding proteins. Nature methods, 2011.
188. Mukherjee, N., et al., Integrative regulatory mapping indicates that the RNA-binding proteinHuR couples pre-mRNA processing and mRNA stability. Mol Cell, 2011. 43(3): p. 327-39.
189. Lebedeva, S., et al., Transcriptome-wide analysis of regulatory interactions of theRNA-binding protein HuR Mol Cell, 2011.43(3): p. 340-52.
190. Tollervey, J.R., et al., Characterizing the RNA targets and position-dependent splicingregulation by TDP-43. Nat Neurosci, 2011.14(4): p. 452-8.
191. Wang, Z., et al., iCLIP predicts the dual splicing effects of TIA-RNA interactions. PLoS Biol,2010. 8(10): p. el000530.
192. Eddy, S.R. and R. Durbin, RNA sequence analysis using covariance models. Nucleic AcidsRes, 1994. 22(11): p. 2079-88.
193. Nawrocki, E.P., D.L. Kolbe, and S.R. Eddy, Infernal 1.0: inference of RNA alignments.Bioinformatics, 2009. 25(10): p. 1335-7.
194. Weinberg, Z. and R.R. Breaker, R2R--software to speed the depiction of aesthetic consensusRNA secondary structures. BMC Bioinformatics, 2011.12: p. 3.
195. Enright, A.J., et al., MicroRNA targets in Drosophila. Genome Biol, 2003. 5(1): p. R1.
196. Krek, A., et al., Combinatorial microRNA target predictions. Nat Genet, 2005. 37(5): p.495-500.
197. Grimson, A., et al., MicroRNA targeting specificity in mammals: determinants beyond seedpairing. Mol Cell, 2007. 27(1): p. 91-105.
198. Rehmsmeier, M., et al., Fast and effective prediction of microRNA/target duplexes. RNA,2004.10(10): p. 1507-17.
199. Legendre, M., et al., Differential repression of alternative transcripts: a screen for miRNAtargets. PLoS Comput Biol, 2006. 2(5): p. e43.
200. Thomas, L.F. and P. Saetrom, Single nucleotide polymorphisms can create alternative polyadenylation signals and affect gene expression through loss of microRNA-reguiation. PLoS Comput Biol,2012.8(8):p. e1002621.
201. Al Rayyan, N., et al., Two single nucleotide polymorphisms in the human nescient helix-loop-helix 2 (NHLH2) gene reduce mRNA stability and DNA binding. Gene,2013. 512(1):p.134-42.
202. Keller, A., et al., Identification of novel SNPs in glioblastoma using targeted resequencing. PLoS One,2011.6(6):p. e18158.
203. Li, H. and R. Durbin, Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics,2009.25(14):p.1754-60.
204. Li, H., et al., The Sequence Alignment/Map format and SAMtools. Bioinformatics,2009. 25(16):p.2078-9.
205. Wang, K., M. Li, and H. Hakonarson, ANNOVAR:functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res,2010.38(16):p. e164.
206. Rajaraman, P., et al., Genome-wide association study of glioma and meta-analysis. Hum Genet,2012.131(12):p.1877-88.
207. Nicoloso, M.S., et al., Single-nucleotide polymorphisms inside microRNA target sites influence tumor susceptibility. Cancer Res,2010.70(7):p.2789-98.
208. Haas, U., G. Sczakiel, and S.D. Laufer, MicroRNA-mediated regulation of gene expression is affected by disease-associated SNPs within the 3'-UTR via altered RNA structure. RNA Biol, 2012.9(6):p.924-37.
209. Bruno, A.E., et al., miRdSNP:a database of disease-associated SNPs and microRNA target sites on 3'UTRs of human genes. BMC Genomics,2012.13:p.44.
210. Brockmann, R., et al., Posttranscriptional expression regulation:what determines translation rates? PLoS Comput Biol,2007.3(3):p. e57.
211. Tian, Q., et al., Integrated genomic and proteomic analyses of gene expression in Mammalian cells. Molecular & cellular proteomics:MCP,2004.3(10):p.960-9.
212. Nie, L., G. Wu, and W. Zhang, Correlation between mRNA and protein abundance in Desulfovibrio vulgaris:a multiple regression to identify sources of variations. Biochemical and biophysical research communications,2006.339(2):p.603-10.
213. Andreassi, C. and A. Riccio, To localize or not to localize:mRNA fate is in 3'UTR ends. Trends Cell Biol,2009.19(9):p.465-74.
214. Shi, Y., et al., Molecular architecture of the human pre-mRNA 3'processing complex. Mol Cell,2009.33(3):p.365-76.
215. Mapendano, C.K., et al., Crosstalk between mRNA 3' end processing and transcription initiation. Mol Cell,2010.40(3):p.410-22.
216. Ji, Z., et al., Transcriptional activity regulates alternative cleavage and polyadenylation. Mol Syst Biol,2011.7:p.534.