Glisovic, T, Bachorik, JL, Yong, J, Dreyfuss, G. RNA‐binding proteins and post‐transcriptional gene regulation. FEBS Lett 2008, 582:1977–1986.
Galante, PA, Sandhu, D, de Sousa, AR, Gradassi, M, Slager, N, Vogel, C, de Souza, SJ, Penalva, LO. 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, 6:426–433.
Esteller, M. Non‐coding RNAs in human disease. Nat Rev Genet 2011, 12:861–874.
Tenenbaum, SA, Carson, CC, Lager, PJ, Keene, JD. Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays. Proc Natl Acad Sci U S A 2000, 97:14085–14090.
Arava, Y, Wang, Y, Storey, JD, Liu, CL, Brown, PO, Herschlag, D. Genome‐wide analysis of mRNA translation profiles in Saccharomyces cerevisiae. Proc Natl Acad Sci 2003, 100:3889–3894.
Ingolia, NT, Ghaemmaghami, S, Newman, JRS, Weissman, JS. Genome‐wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 2009, 324:218–223.
Ozsolak, F, Milos, PM. RNA sequencing: advances, challenges and opportunities. Nat Rev Genet 2011, 12:87–98.
Garber, M, Grabherr, MG, Guttman, M, Trapnell, C. Computational methods for transcriptome annotation and quantification using RNA‐seq. Nat Methods 2011, 8:469–477.
Wang, Z, Gerstein, M, Snyder, M. RNA‐Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 2009, 10:57–63.
Oshlack, A, Robinson, MD, Young, MD. From RNA‐seq reads to differential expression results. Genome Biol 2010, 11:220.
Granneman, S, Kudla, G, Petfalski, E, Tollervey, D. Identification of protein binding sites on U3 snoRNA and pre‐rRNA by UV cross‐linking and high‐throughput analysis of cDNAs. Proc Natl Acad Sci 2009, 106:9613–9618.
Ule, J, Jensen, KB, Ruggiu, M, Mele, A, Ule, A, Darnell, RB. CLIP identifies Nova‐regulated RNA networks in the brain. Science 2003, 302:1212–1215.
Licatalosi, DD, Mele, A, Fak, JJ, Ule, J, Kayikci, M, Chi, SW, Clark, TA, Schweitzer, AC, Blume, JE, Wang, X, et al. HITS‐CLIP yields genome‐wide insights into brain alternative RNA processing. Nature 2008, 456:464–469.
Konig, J, Zarnack, K, Rot, G, Curk, T, Kayikci, M, Zupan, B, Turner, DJ, Luscombe, NM, Ule, J. iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution. Nat Struct Mol Biol 2010, 17:909–915.
Hafner, M, Landthaler, M, Burger, L, Khorshid, M, Hausser, J, Berninger, P, Rothballer, A, Ascano, M Jr, Jungkamp, A‐C, Munschauer, M. Transcriptome‐wide identification of RNA‐binding protein and microRNA target sites by PAR‐CLIP. Cell 2010, 141:129–141.
Uren, PJ, Bahrami‐Samani, E, Burns, SC, Qiao, M, Karginov, FV, Hodges, E, Hannon, GJ, Sanford, JR, Penalva, LOF, Smith, AD. Site identification in high‐throughput RNA‐protein interaction data. Bioinformatics 2012, 28:3013–3020.
Mili, S, Steitz, JA. Evidence for reassociation of RNA‐binding proteins after cell lysis: implications for the interpretation of immunoprecipitation analyses. RNA 2004, 10:1692–1694.
Roy, PJ, Stuart, JM, Lund, J, Kim, SK. Chromosomal clustering of muscle‐expressed genes in Caenorhabditis elegans. Nature 2002, 418:975–979.
Penalva, LO, Burdick, MD, Lin, SM, Sutterluety, H, Keene, JD. RNA‐binding proteins to assess gene expression states of co‐cultivated cells in response to tumor cells. Mol Cancer 2004, 3:24.
Doyle, JP, Dougherty, JD, Heiman, M, Schmidt, EF, Stevens, TR, Ma, G, Bupp, S, Shrestha, P, Shah, RD, Doughty, ML, et al. Application of a translational profiling approach for the comparative analysis of CNS cell types. Cell 2008, 135:749–762.
Baltz, AG, Munschauer, M, Schwanhäusser, B, Vasile, A, Murakawa, Y, Schueler, M, Youngs, N, Penfold‐Brown, D, Drew, K, Milek, M. The mRNA‐bound proteome and its global occupancy profile on protein‐coding transcripts. Mol Cell 2012, 46:674–690.
Castello, A, Fischer, B, Eichelbaum, K, Horos, R, Beckmann, BM, Strein, C, Davey, NE, Humphreys, DT, Preiss, T, Steinmetz, LM. Insights into RNA biology from an atlas of mammalian mRNA‐binding proteins. Cell 2012, 149:1393–1406.
Tome, JM, Ozer, A, Pagano, JM, Gheba, D, Schroth, G, Lis, JT. Comprehensive analysis of RNA‐protein interactions by high‐throughput sequencing‐RNA affinity profiling. Nat Methods 2014, 11:683–688.
Nutiu, R, Friedman, RC, Luo, S, Khrebtukova, I, Silva, D, Li, R, Zhang, L, Schroth, GP, Burge, CB. Direct measurement of DNA affinity landscapes on a high‐throughput sequencing instrument. Nat Biotechnol 2011, 29:659–664.
Fonseca, NA, Rung, J, Brazma, A, Marioni, JC. Tools for mapping high‐throughput sequencing data. Bioinformatics 2012, 28:3169–3177.
Mukherjee, N, Corcoran, DL, Nusbaum, JD, Reid, DW, Georgiev, S, Hafner, M, Ascano, M Jr, Tuschl, T, Ohler, U, Keene, JD. Integrative regulatory mapping indicates that the RNA‐binding protein HuR couples pre‐mRNA processing and mRNA stability. Mol Cell 2011, 43:327–339.
Lebedeva, S, Jens, M, Theil, K, Schwanhäusser, B, Selbach, M, Landthaler, M, Rajewsky, N. Transcriptome‐wide analysis of regulatory interactions of the RNA‐binding protein HuR. Mol Cell 2011, 43:340–352.
Ascano, M, Mukherjee, N, Bandaru, P, Miller, JB, Nusbaum, JD, Corcoran, DL, Langlois, C, Munschauer, M, Dewell, S, Hafner, M. FMRP targets distinct mRNA sequence elements to regulate protein expression. Nature 2012, 492:382–386.
Erhard, F, Dölken, L, Zimmer, R. RIP‐chip enrichment analysis. Bioinformatics 2013, 29:77–83.
Sugimoto, Y, König, J, Hussain, S, Zupan, B, Curk, T, Frye, M, Ule, J. Analysis of CLIP and iCLIP methods for nucleotide‐resolution studies of protein‐RNA interactions, 2012.
Friedersdorf, MB, Keene, JD. Advancing the functional utility of PAR‐CLIP by quantifying background binding to mRNAs and lncRNAs. Genome Biol 2014, 15:16.
Freeberg, MA, Han, T, Moresco, JJ, Kong, A, Yang, Y‐C, Lu, ZJ, Yates, JR, Kim, JK. Pervasive and dynamic protein binding sites of the mRNA transcriptome in Saccharomyces cerevisiae, 2013.
Klass, DM, Scheibe, M, Butter, F, Hogan, GJ, Mann, M, Brown, PO. Quantitative proteomic analysis reveals concurrent RNA–protein interactions and identifies new RNA‐binding proteins in Saccharomyces cerevisiae. Genome Res 2013, 23:1028–1038.
Li, Y, Zhao, DY, Greenblatt, JF, Zhang, ZL. RIPSeeker: a statistical package for identifying protein‐associated transcripts from RIP‐seq experiments. Nucleic Acids Res 2013, 41:18.
Wang, T, Xie, Y, Xiao, GH. dCLIP: a computational approach for comparative CLIP‐seq analyses. Genome Biol 2014, 15:13.
Wang, T, Chen, B, Kim, M, Xie, Y, Xiao, G. A model‐based approach to identify binding sites in CLIP‐seq data. PLoS One 2014, 9:e93248.
Kucukural, A, Ozadam, H, Singh, G, Moore, MJ, Cenik, C. ASPeak: an abundance sensitive peak detection algorithm for RIP‐Seq. Bioinformatics 2013, 29:2485–2486.
Zhang, C, Darnell, RB. Mapping in vivo protein‐RNA interactions at single‐nucleotide resolution from HITS‐CLIP data. Nat Biotechnol 2011, 29:607–614.
Corcoran, DL, Georgiev, S, Mukherjee, N, Gottwein, E, Skalsky, RL, Keene, JD, Ohler, U. PARalyzer: definition of RNA binding sites from PAR‐CLIP short‐read sequence data. Genome Biol 2011, 12:16.
Loeb, GB, Khan, AA, Canner, D, Hiatt, JB, Shendure, J, Darnell, RB, Leslie, CS, Rudensky, AY. Transcriptome‐wide miR‐155 binding map reveals widespread noncanonical microRNA targeting. Mol Cell 2012, 48:760–770.
Zarnack, K, König, J, Tajnik, M, Martincorena, I, Eustermann, S, Stévant, I, Reyes, A, Anders, S, Luscombe, NM, Ule, J. Direct competition between hnrnp c and u2af65 protects the transcriptome from the exonization of alu elements. Cell 2013, 152:453–466.
Xue, Y, Ouyang, K, Huang, J, Zhou, Y, Ouyang, H, Li, H, Wang, G, Wu, Q, Wei, C, Bi, Y. Direct conversion of fibroblasts to neurons by reprogramming PTB‐regulated microRNA circuits. Cell 2013, 152:82–96.
Mukherjee, N, Lager, PJ, Friedersdorf, MB, Thompson, MA, Keene, JD. Coordinated posttranscriptional mRNA population dynamics during T‐cell activation. Mol Syst Biol 2009, 5:288.
Chen, BB, Yun, J, Kim, MS, Mendell, JT, Xie, Y. PIPE‐CLIP: a comprehensive online tool for CLIP‐seq data analysis. Genome Biol 2014, 15:10.
Webb, S, Hector, RD, Kudla, G, Granneman, S. PAR‐CLIP data indicate that Nrd1‐Nab3‐dependent transcription termination regulates expression of hundreds of protein coding genes in yeast. Genome Biol 2014, 15:R8–22.
Goecks, J, Nekrutenko, A, Taylor, J. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences, Genome Biology 2010, 11:R86–98.
Liu, JS, Neuwald, AF, Lawrence, CE. Bayesian models for multiple local sequence alignment and Gibbs sampling strategies. J Am Stat Assoc 1995, 90:1156–1170.
Ray, D, Kazan, H, Cook, KB, Weirauch, MT, Najafabadi, HS, Li, X, Gueroussov, S, Albu, M, Zheng, H, Yang, A. A compendium of RNA‐binding motifs for decoding gene regulation. Nature 2013, 499:172–177.
Perez‐Canadillas, JM, Varani, G. Recent advances in RNA‐protein recognition. Curr Opin Struct Biol 2001, 11:53–58.
Sanchez‐Diaz, P, Penalva, LO. Review Post‐Transcription Meets Post‐Genomic. RNA Biol 2006, 3:101–109.
Klug, SJ, Famulok, M. All you wanted to know about selex. Mol Biol Rep 1994, 20:97–107.
Tuerk, C. Using the SELEX combinatorial chemistry process to find high affinity nucleic acid ligands to target molecules. Methods Mol Biol 1997, 67:219–230.
Ray, D, Kazan, H, Chan, ET, Castillo, LP, Chaudhry, S, Talukder, S, Blencowe, BJ, Morris, Q, Hughes, TR. Rapid and systematic analysis of the RNA recognition specificities of RNA‐binding proteins. Nat Biotechnol 2009, 27:667–670.
Stormo, GD, Schneider, TD, Gold, L, Ehrenfeucht, A. Use of the ‘Perceptron’ algorithm to distinguish translational initiation sites in E. coli. Nucleic Acids Res 1982, 10:2997–3011.
Cardon, LR, Stormo, GD. Expectation maximization algorithm for identifying protein‐binding sites with variable lengths from unaligned DNA fragments. J Mol Biol 1992, 223:159–170.
Lawrence, CE, Reilly, AA. An expectation maximization (EM) algorithm for the identification and characterization of common sites in unaligned biopolymer sequences. Proteins Struct Funct Bioinform 1990, 7:41–51.
Liu, JS. The collapsed Gibbs sampler in Bayesian computations with applications to a gene regulation problem. J Am Stat Assoc 1994, 89:958–966.
Abdullah, SLS, Hussin, NM, Harun, H, Khalid, NEA. Comparative study of random‐PSO and Linear‐PSO algorithms. In: 2012 International Conference on Computer & Information Science (ICCIS), IEEE; 2012.
Bailey, TL, Elkan, C. Unsupervised learning of multiple motifs in biopolymers using expectation maximization. Mach Learn 1995, 21:51–80.
Liu, XS, Brutlag, DL, Liu, JS. An algorithm for finding protein–DNA binding sites with applications to chromatin‐immunoprecipitation microarray experiments. Nat Biotechnol 2002, 20:835–839.
Roth, FP, Hughes, JD, Estep, PW, Church, GM. Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole‐genome mRNA quantitation. Nat Biotechnol 1998, 16:939–945.
Smith, AD, Sumazin, P, Zhang, MQ. Identifying tissue‐selective transcription factor binding sites in vertebrate promoters. Proc Natl Acad Sci U S A 2005, 102:1560–1565.
Das, MK, Dai, H‐K. A survey of DNA motif finding algorithms. BMC Bioinform 2007, 8:S21.
Hu, J, Li, B, Kihara, D. Limitations and potentials of current motif discovery algorithms. Nucleic Acids Res 2005, 33:4899–4913.
Gardina, PJ, Clark, TA, Shimada, B, Staples, MK, Yang, Q, Veitch, J, Schweitzer, A, Awad, T, Sugnet, C, Dee, S, et al. Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array. BMC Genomics 2006, 7:325–342.
Qiu, P. Recent advances in computational promoter analysis in understanding the transcriptional regulatory network. Biochem Biophys Res Commun 2003, 309:495–501.
Stormo, GD. DNA binding sites: representation and discovery. Bioinformatics 2000, 16:16–23.
Akerman, M, David‐Eden, H, Pinter, RY, Mandel‐Gutfreund, Y. A computational approach for genome‐wide mapping of splicing factor binding sites. Genome Biol 2009, 10:R30.
Zhang, C, Lee, K‐Y, Swanson, MS, Darnell, RB. Prediction of clustered RNA‐binding protein motif sites in the mammalian genome. Nucleic Acids Res 2013, 41:6793–6807.
Li, X, Kazan, H, Lipshitz, HD, Morris, QD. Finding the target sites of RNA‐binding proteins. WIREs RNA 2014, 5:111–130.
Eddy, SR, Durbin, R. RNA sequence analysis using covariance models. Nucleic Acids Res 1994, 22:2079–2088.
Yao, Z, Weinberg, Z, Ruzzo, WL. CMfinder—a covariance model based RNA motif finding algorithm. Bioinformatics 2006, 22:445–452.
Mathews, DH, Turner, DH. Dynalign: an algorithm for finding the secondary structure common to two RNA sequences. J Mol Biol 2002, 317:191–203.
Fogel, GB, Porto, VW, Weekes, DG, Fogel, DB, Griffey, RH, McNeil, JA, Lesnik, E, Ecker, DJ, Sampath, R. Discovery of RNA structural elements using evolutionary computation. Nucleic Acids Res 2002, 30:5310–5317.
Mauri, G, Pavesi, G. %22Pattern discovery in RNA secondary structure using affix trees%22. In: Combinatorial Pattern Matching. Lecture Notes in Computer Science, Springer, 2003, 2676:278–294.
Hiller, M, Pudimat, R, Busch, A, Backofen, R. Using RNA secondary structures to guide sequence motif finding towards single‐stranded regions. Nucleic Acids Res 2006, 34:e117–117.
Kazan, H, Ray, D, Chan, ET, Hughes, TR, Morris, Q. RNAcontext: a new method for learning the sequence and structure binding preferences of RNA‐binding proteins. PLoS Comput Biol 2010, 6:e1000832.
Maticzka, D, Lange, SJ, Costa, F, Backofen, R. GraphProt: modeling binding preferences of RNA‐binding proteins. Genome Biol 2014, 15:R17.
Chou, CH, Lin, FM, Chou, MT, Hsu, SD, Chang, TH, Weng, SL, Shrestha, S, Hsiao, CC, Hung, JH, Huang, HD. A computational approach for identifying microRNA‐target interactions using high‐throughput CLIP and PAR‐CLIP sequencing. BMC Genomics 2013, 14:11.
Moore, MJ, Zhang, C, Gantman, EC, Mele, A, Darnell, JC, Darnell, RB. Mapping Argonaute and conventional RNA‐binding protein interactions with RNA at single‐nucleotide resolution using HITS‐CLIP and CIMS analysis. Nat Protoc 2014, 9:263–293.
Zheng, H, Fu, R, Wang, J‐T, Liu, Q, Chen, H, Jiang, S‐W. Advances in the techniques for the prediction of microRNA targets. Int J Mol Sci 2013, 14:8179–8187.
Grimson, A, Farh, KK‐H, Johnston, WK, Garrett‐Engele, P, Lim, LP, Bartel, DP. MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell 2007, 27:91–105.
Kertesz, M, Iovino, N, Unnerstall, U, Gaul, U, Segal, E. The role of site accessibility in microRNA target recognition. Nat Genet 2007, 39:1278–1284.
Cook, KB, Kazan, H, Zuberi, K, Morris, Q, Hughes, TR. RBPDB: a database of RNA‐binding specificities. Nucleic Acids Res 2011, 39:D301–308.
Khorshid, M, Rodak, C, Zavolan, M. CLIPZ: a database and analysis environment for experimentally determined binding sites of RNA‐binding proteins. Nucleic Acids Res 2011, 39:D245–252.
Paz, I, Kosti, I, Ares, M, Cline, M, Mandel‐Gutfreund, Y. RBPmap: a web server for mapping binding sites of RNA‐binding proteins. Nucleic Acids Res 2014, 42: W361–367.
Vo, DT, Subramaniam, D, Remke, M, Burton, TL, Uren, PJ, Gelfond, JA, de Sousa, AR, Burns, SC, Qiao, M, Suresh, U. The RNA‐binding protein Musashi1 affects medulloblastoma growth via a network of cancer‐related genes and is an indicator of poor prognosis. Am J Pathol 2012, 181:1762–1772.
Scheibe, M, Butter, F, Hafner, M, Tuschl, T, Mann, M. Quantitative mass spectrometry and PAR‐CLIP to identify RNA‐protein interactions. Nucleic Acids Res 2012, 40:9897–9902.
Maatz, H, Jens, M, Liss, M, Schafer, S, Heinig, M, Kirchner, M, Adami, E, Rintisch, C, Dauksaite, V, Radke, MH. RNA‐binding protein RBM20 represses splicing to orchestrate cardiac pre‐mRNA processing. J Clin Invest 2014, 124:3419.
Hendrickson, DG, Hogan, DJ, McCullough, HL, Myers, JW, Herschlag, D, Ferrell, JE, Brown, PO. Concordant regulation of translation and mRNA abundance for hundreds of targets of a human microRNA. PLoS Biol 2009, 7:e1000238.
Selbach, M, Schwanhäusser, B, Thierfelder, N, Fang, Z, Khanin, R, Rajewsky, N. Widespread changes in protein synthesis induced by microRNAs. Nature 2008, 455:58–63.
Baek, D, Villén, J, Shin, C, Camargo, FD, Gygi, SP, Bartel, DP. The impact of microRNAs on protein output. Nature 2008, 455:64–71.
Tamim, S, Vo, DT, Uren, PJ, Qiao, M, Bindewald, E, Kasprzak, WK, Shapiro, BA, Nakaya, HI, Burns, SC, Araujo, PR. Genomic analyses reveal broad impact of miR‐137 on genes associated with malignant transformation and neuronal differentiation in glioblastoma cells. PLoS One 2014, 9:e85591.
Mortazavi, A, Williams, BA, McCue, K, Schaeffer, L, Wold, B. Mapping and quantifying mammalian transcriptomes by RNA‐Seq. Nat Methods 2008, 5:621–628.
Trapnell, C, Williams, BA, Pertea, G, Mortazavi, A, Kwan, G, van Baren, MJ, Salzberg, SL, Wold, BJ, Pachter, L. Transcript assembly and quantification by RNA‐Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 2010, 28:U511–174.
Wagner, GP, Kin, K, Lynch, VJ. Measurement of mRNA abundance using RNA‐seq data: RPKM measure is inconsistent among samples. Theory Biosci 2012, 131:281–285.
Dillies, M‐A, Rau, A, Aubert, J, Hennequet‐Antier, C, Jeanmougin, M, Servant, N, Keime, C, Marot, G, Castel, D, Estelle, J. A comprehensive evaluation of normalization methods for Illumina high‐throughput RNA sequencing data analysis. Brief Bioinform 2013, 14:671–683.
Robinson, MD, McCarthy, DJ, Smyth, GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26:139–140.
Anders, S, Huber, W. Differential expression analysis for sequence count data. Genome Biol 2010, 11:12.
Nookaew, I, Papini, M, Pornputtapong, N, Scalcinati, G, Fagerberg, L, Uhlen, M, Nielsen, J. A comprehensive comparison of RNA‐Seq‐based transcriptome analysis from reads to differential gene expression and cross‐comparison with microarrays: a case study in Saccharomyces cerevisiae. Nucleic Acids Res 2012, 40:10084–10097.
Nakaya, T, Alexiou, P, Maragkakis, M, Chang, A, Mourelatos, Z. FUS regulates genes coding for RNA‐binding proteins in neurons by binding to their highly conserved introns. RNA 2013, 19:498–509.
Beadle, GW, Tatum, EL. Genetic control of biochemical reactions in Neurospora. Proc Natl Acad Sci U S A 1941, 27:499.
Valdivia, HH. One gene, many proteins – alternative splicing of the ryanodine receptor gene adds novel functions to an already complex channel protein. Circ Res 2007, 100:761–763.
Brett, D, Pospisil, H, Valcarcel, J, Reich, J, Bork, P. Alternative splicing and genome complexity. Nat Genet 2002, 30:29–30.
Pan, Q, Shai, O, Lee, LJ, Frey, BJ, Blencowe, BJ. Deep surveying of alternative splicing complexity in the human transcriptome by high‐throughput sequencing (vol 40, pg 1413, 2008). Nat Genet 2009, 41:762–762.
Wang, ET, Sandberg, R, Luo, SJ, Khrebtukova, I, Zhang, L, Mayr, C, Kingsmore, SF, Schroth, GP, Burge, CB. Alternative isoform regulation in human tissue transcriptomes. Nature 2008, 456:470–476.
Schweingruber, C, Rufener, SC, Zünd, D, Yamashita, A, Mühlemann, O. Nonsense‐mediated mRNA decay—mechanisms of substrate mRNA recognition and degradation in mammalian cells. Biochim Biophys Acta Gene Regul Mech 2013, 1829:612–623.
Kalyna, M, Simpson, CG, Syed, NH, Lewandowska, D, Marquez, Y, Kusenda, B, Marshall, J, Fuller, J, Cardle, L, McNicol, J, et al. Alternative splicing and nonsense‐mediated decay modulate expression of important regulatory genes in Arabidopsis. Nucleic Acids Res 2012, 40:2454–2469.
Ali, GS, Reddy, ASN. Regulation of alternative splicing of pre‐mRNAs by stresses. Nucl Pre‐Mrna Proces Plants 2008, 326:257–275.
Yu, P, Zhou, L, Ke, W, Li, K. Clinical significance of pAKT and CD44v6 overexpression with breast cancer. J Cancer Res Clin Oncol 2010, 136:1283–1292.
Todaro, M, Gaggianesi, M, Catalano, V, Benfante, A, Iovino, F, Biffoni, M, Apuzzo, T, Sperduti, I, Volpe, S, Cocorullo, G. CD44v6 is a marker of constitutive and reprogrammed cancer stem cells driving colon cancer metastasis. Cell Stem Cell 2014, 14:342–356.
Shi, J, Zhou, Z, Di, W, Li, N. Correlation of CD44v6 expression with ovarian cancer progression and recurrence. BMC Cancer 2013, 13:182.
Liang, Y, Fang, T, Xu, H, Zhuo, Z. Expression of CD44v6 and Livin in gastric cancer tissue. Chin Med J (Engl) 2012, 125:3161–3165.
Hagiwara, M. Alternative splicing: a new drug target of the post‐genome era. Biochim Biophys Acta Proteins Proteomics 2005, 1754:324–331.
Trapnell, C, Hendrickson, DG, Sauvageau, M, Goff, L, Rinn, JL, Pachter, L. Differential analysis of gene regulation at transcript resolution with RNA‐seq. Nat Biotechnol 2013, 31:46.
Katz, Y, Wang, ET, Airoldi, EM, Burge, CB. Analysis and design of RNA sequencing experiments for identifying isoform regulation. Nat Methods 2010, 7:U1009–1101.
Anders, S, Reyes, A, Huber, W. Detecting differential usage of exons from RNA‐seq data. Genome Res 2012, 22:2008–2017.
Wang, WC, Qin, ZY, Feng, ZX, Wang, X, Zhang, XG. Identifying differentially spliced genes from two groups of RNA‐seq samples. Gene 2013, 518:164–170.
Shen, SH, Park, JW, Huang, J, Dittmar, KA, Lu, ZX, Zhou, Q, Carstens, RP, Xing, Y. MATS: a Bayesian framework for flexible detection of differential alternative splicing from RNA‐Seq data. Nucleic Acids Res 2012, 40:13.
Hu, Y, Huang, Y, Du, Y, Orellana, CF, Singh, D, Johnson, AR, Monroy, A, Kuan, PF, Hammond, SM, Makowski, L, et al. DiffSplice: the genome‐wide detection of differential splicing events with RNA‐seq. Nucleic Acids Res 2013, 41:18.
Aschoff, M, Hotz‐Wagenblatt, A, Glatting, KH, Fischer, M, Eils, R, Konig, R. Splicing compass: differential splicing detection using RNA‐Seq data. Bioinformatics 2013, 29:1141–1148.
Langmead, B, Trapnell, C, Pop, M, Salzberg, SL. Ultrafast and memory‐efficient alignment of short DNA sequences to the human genome. Genome Biol 2009, 10:10.
Trapnell, C, Pachter, L, Salzberg, SL. TopHat: discovering splice junctions with RNA‐Seq. Bioinformatics 2009, 25:1105–1111.
Dobin, A, Davis, CA, Schlesinger, F, Drenkow, J, Zaleski, C, Jha, S, Batut, P, Chaisson, M, Gingeras, TR. STAR: ultrafast universal RNA‐seq aligner. Bioinformatics 2013, 29:15–21.
Huang, S, Zhang, J, Li, R, Zhang, W, He, Z, Lam, T‐W, Peng, Z, Yiu, S‐M. SOAPsplice: genome‐wide ab initio detection of splice junctions from RNA‐Seq data. Front Genet 2011, 2:46.
Hoffmann, S, Otto, C, Doose, G, Tanzer, A, Langenberger, D, Christ, S, Kunz, M, Holdt, L, Teupser, D, Hackermüller, J. A multi‐split mapping algorithm for circular RNA, splicing, trans‐splicing, and fusion detection. Genome Biol 2014, 15:R34.
Wang, K, Singh, D, Zeng, Z, Coleman, SJ, Huang, Y, Savich, GL, He, XP, Mieczkowski, P, Grimm, SA, Perou, CM, et al. MapSplice: accurate mapping of RNA‐seq reads for splice junction discovery. Nucleic Acids Res 2010, 38:14.
Ameur, A, Wetterbom, A, Feuk, L, Gyllensten, U. Global and unbiased detection of splice junctions from RNA‐seq data. Genome Biol 2010, 11:9.
Hoffmann, S, Otto, C, Kurtz, S, Sharma, CM, Khaitovich, P, Vogel, J, Stadler, PF, Hackermuller, J. Fast mapping of short sequences with mismatches, insertions and deletions using index structures. Plos Comput Biol 2009, 5:10.
Wu, TD, Nacu, S. Fast and SNP‐tolerant detection of complex variants and splicing in short reads. Bioinformatics 2010, 26:873–881.
Au, KF, Jiang, H, Lin, L, Xing, Y, Wong, WH. Detection of splice junctions from paired‐end RNA‐seq data by SpliceMap. Nucleic Acids Res 2010, 38:4570–4578.
Jean, G, Kahles, A, Sreedharan, VT, Bona, FD, Rätsch, G. RNA‐Seq read alignments with PALMapper. Curr Protoc Bioinformatics 2010, Unit 11.6.
Hooper, JE. A survey of software for genome‐wide discovery of differential splicing in RNA‐Seq data. Hum Genomics 2014, 8:3.
EURASNET. Alternative Splicing Databases. Available at: http://www.eurasnet.info/tools/asdatabases, Accessed Nov. 24, 2014.
Hung, LH, Heiner, M, Hui, JY, Schreiner, S, Benes, V, Bindereif, A. Diverse roles of hnRNP L in mammalian mRNA processing: a combined microarray and RNAi analysis. Rna‐a Publ RNA Soc 2008, 14:284–296.
Huelga, SC, Vu, AQ, Arnold, JD, Liang, TY, Donohue, JP, Shiue, L, Hoon, S, Brenner, S, Ares, M, Yeo, GW. Integrative genome‐wide analysis reveals cooperative regulation of alternative splicing by hnRNP proteins. FASEB J 2012, 26:1.
Tollervey, JR, Curk, T, Rogelj, B, Briese, M, Cereda, M, Kayikci, M, Konig, J, Hortobagyi, T, Nishimura, AL, Zupunski, V, et al. Characterizing the RNA targets and position‐dependent splicing regulation by TDP‐43. Nat Neurosci 2011, 14:U452–580.
Yeo, GW, Coufal, NG, Liang, TY, Peng, GE, Fu, XD, Gage, FH. An RNA code for the FOX2 splicing regulator revealed by mapping RNA‐protein interactions in stem cells. Nat Struct Mol Biol 2009, 16:130–137.
Zhang, CL, Zhang, Z, Castle, J, Sun, SY, Johnson, J, Krainer, AR, Zhang, MQ. Defining the regulatory network of the tissue‐specific splicing factors Fox‐1 and Fox‐2. Genes Dev 2008, 22:2550–2563.
Llorian, M, Schwartz, S, Clark, TA, Hollander, D, Tan, LY, Spellman, R, Gordon, A, Schweitzer, AC, la Grange, P, Ast, G, et al. Position‐dependent alternative splicing activity revealed by global profiling of alternative splicing events regulated by PTB. Nat Struct Mol Biol 2010, 17:1114–U1112.
Xue, YC, Zhou, Y, Wu, TB, Zhu, T, Ji, X, Kwon, YS, Zhang, C, Yeo, G, Black, DL, Sun, H, et al. Genome‐wide analysis of PTB‐RNA interactions reveals a strategy used by the general splicing repressor to modulate exon inclusion or skipping. Mol Cell 2009, 36:996–1006.
Du, HQ, Cline, MS, Osborne, RJ, Tuttle, DL, Clark, TA, Donohue, JP, Hall, MP, Shiue, L, Swanson, MS, Thornton, CA, et al. Aberrant alternative splicing and extracellular matrix gene expression in mouse models of myotonic dystrophy. Nat Struct Mol Biol 2010, 17:187–188.
Wang, Z, Kayikci, M, Briese, M, Zarnack, K, Luscombe, NM, Rot, G, Zupan, B, Curk, T, Ule, J. iCLIP predicts the dual splicing effects of TIA‐RNA interactions. Plos Biol 2010, 8:16.
Elkon, R, Ugalde, AP, Agami, R. Alternative cleavage and polyadenylation: extent, regulation and function. Nat Rev Genet 2013, 14:496–506.
Hoque, M, Ji, Z, Zheng, D, Luo, W, Li, W, You, B, Park, JY, Yehia, G, Tian, B. Analysis of alternative cleavage and polyadenylation by 3 [prime] region extraction and deep sequencing. Nat Methods 2013, 10:133–139.
Smibert, P, Miura, P, Westholm, JO, Shenker, S, May, G, Duff, MO, Zhang, DY, Eads, BD, Carlson, J, Brown, JB, et al. Global patterns of tissue‐specific alternative polyadenylation in Drosophila. Cell Rep 2012, 1:277–289.
Alt, FW, Bothwell, AL, Knapp, M, Siden, E, Mather, E, Koshland, M, Baltimore, D. Synthesis of secreted and membrane‐bound immunoglobulin mu heavy chains is directed by mRNAs that differ at their 3′ ends. Cell 1980, 20:293–301.
Setzer, DR, McGrogan, M, Nunberg, JH, Schimke, RT. Size heterogeneity in the 3′ end of dihydrofolate reductase messenger RNAs in mouse cells. Cell 1980, 22:361–370.
Beaudoing, E, Freier, S, Wyatt, JR, Claverie, JM, Gautheret, D. Patterns of variant polyadenylation signal usage in human genes. Genome Res 2000, 10:1001–1010.
Gautheret, D, Poirot, O, Lopez, F, Audic, S, Claverie, JM. Alternate polyadenylation in human mRNAs: a large‐scale analysis by EST clustering. Genome Res 1998, 8:524–530.
Gruber, AR, Martin, G, Keller, W, Zavolan, M. Means to an end: mechanisms of alternative polyadenylation of messenger RNA precursors. WIREs RNA 2014, 5:183–196.
Haenni, S, Ji, Z, Hoque, M, Rust, N, Sharpe, H, Eberhard, R, Browne, C, Hengartner, MO, Mellor, J, Tian, B, et al. Analysis of C. elegans intestinal gene expression and polyadenylation by fluorescence‐activated nuclei sorting and 3′‐end‐seq. Nucleic Acids Res 2012, 40:6304–6318.
Derti, A, Garrett‐Engele, P, MacIsaac, KD, Stevens, RC, Sriram, S, Chen, R, Rohl, CA, Johnson, JM, Babak, T. A quantitative atlas of polyadenylation in five mammals. Genome Res 2012, 22:1173–1183.
Mueller, AA, Cheung, TH, Rando, TA. All`s well that ends well: alternative polyadenylation and its implications for stem cell biology. Curr Opin Cell Biol 2013, 25:222–232.
Sandberg, R, Neilson, JR, Sarma, A, Sharp, PA, Burge, CB. Proliferating cells express mRNAs with shortened 3′ untranslated regions and fewer microRNA target sites. Science 2008, 320:1643–1647.
Mayr, C, Bartel, DP. Widespread shortening of 3′ UTRs by alternative cleavage and polyadenylation activates oncogenes in cancer cells. Cell 2009, 138:673–684.
Ozsolak, F, Kapranov, P, Foissac, S, Kim, SW, Fishilevich, E, Monaghan, AP, John, B, Milos, PM. Comprehensive polyadenylation site maps in yeast and human reveal pervasive alternative polyadenylation. Cell 2010, 143:1018–1029.
Lembo, A, Di Cunto, F, Provero, P. Shortening of 3′ UTRs correlates with poor prognosis in breast and lung cancer. PLoS One 2012, 7:e31129.
Lin, Y, Li, Z, Ozsolak, F, Kim, SW, Arango‐Argoty, G, Liu, TT, Tenenbaum, SA, Bailey, T, Monaghan, AP, Milos, PM, et al. An in‐depth map of polyadenylation sites in cancer. Nucleic Acids Res 2012, 40:8460–8471.
Cheng, YM, Miura, RM, Tian, B. Prediction of mRNA polyadenylation sites by support vector machine. Bioinformatics 2006, 22:2320–2325.
Brockman, JM, Singh, P, Liu, DL, Quinlan, S, Salisbury, J, Graber, JH. PACdb: PolyA cleavage site and 3′‐UTR database. Bioinformatics 2005, 21:3691–3693.
Lee, JY, Yeh, I, Park, JY, Tian, B. PolyA_DB 2: mRNA polyadenylation sites in vertebrate genes. Nucleic Acids Res 2007, 35:D165–168.
Eberhardt, R, Anantham, D, Herth, F, Feller‐Kopman, D, Ernst, A. Electromagnetic navigation diagnostic bronchoscopy in peripheral lung lesions. Chest J 2007, 131:1800–1805.
Kervestin, S, Jacobson, A. NMD: a multifaceted response to premature translational termination. Nat Rev Mol Cell Biol 2012, 13:700–712.
Bakheet, T, Williams, BR, Khabar, KS. ARED 3.0: the large and diverse AU‐rich transcriptome. Nucleic Acids Res 2006, 34:D111–114.
Brennan, SE, Kuwano, Y, Alkharouf, N, Blackshear, PJ, Gorospe, M, Wilson, GM. The mRNA‐destabilizing protein tristetraprolin is suppressed in many cancers, altering tumorigenic phenotypes and patient prognosis. Cancer Res 2009, 69:5168–5176.
Uren, PJ, Burns, SC, Ruan, J, Singh, KK, Smith, AD, Penalva, LO. Genomic analyses of the RNA‐binding protein Hu antigen R (HuR) identify a complex network of target genes and novel characteristics of its binding sites. J Biol Chem 2011, 286:37063–37066.
Barreau, C, Paillard, L, Méreau, A, Osborne, HB. Mammalian CELF/Bruno‐like RNA‐binding proteins: molecular characteristics and biological functions. Biochimie 2006, 88:515–525.
Gruber, AR, Fallmann, J, Kratochvill, F, Kovarik, P, Hofacker, IL. AREsite: a database for the comprehensive investigation of AU‐rich elements. Nucleic Acids Res 2011, 39:D66–69.
Schoenberg, DR, Maquat, LE. Regulation of cytoplasmic mRNA decay. Nat Rev Genet 2012, 13:246–259.
Wang, Y, Liu, CL, Storey, JD, Tibshirani, RJ, Herschlag, D, Brown, PO. Precision and functional specificity in mRNA decay. Proc Natl Acad Sci 2002, 99:5860–5865.
Alic, A, Pérez‐Ortín, JE, Moreno, J, Arnau, V. mRNAStab—a web application for mRNA stability analysis. Bioinformatics 2013, 29:813–814.
Dölken, L, Ruzsics, Z, Rädle, B, Friedel, CC, Zimmer, R, Mages, J, Hoffmann, R, Dickinson, P, Forster, T, Ghazal, P. High‐resolution gene expression profiling for simultaneous kinetic parameter analysis of RNA synthesis and decay. RNA 2008, 14:1959–1972.
Miller, C, Schwalb, B, Maier, K, Schulz, D, Dümcke, S, Zacher, B, Mayer, A, Sydow, J, Marcinowski, L, Dölken, L. Dynamic transcriptome analysis measures rates of mRNA synthesis and decay in yeast. Mol Syst Biol 2011, 7:458.
Schwalb, B, Schulz, D, Sun, M, Zacher, B, Dümcke, S, Martin, DE, Cramer, P, Tresch, A. Measurement of genome‐wide RNA synthesis and decay rates with dynamic transcriptome analysis (DTA). Bioinformatics 2012, 28:884–885.
Dieterich, C, Stadler, PF. Computational biology of RNA interactions. WIREs RNA 2013, 4:107–120.
Goodarzi, H, Najafabadi, HS, Oikonomou, P, Greco, TM, Fish, L, Salavati, R, Cristea, IM, Tavazoie, S. Systematic discovery of structural elements governing stability of mammalian messenger RNAs. Nature 2012, 485:264–268.
Gupta, I, Clauder‐Münster, S, Klaus, B, Järvelin, AI, Aiyar, RS, Benes, V, Wilkening, S, Huber, W, Pelechano, V, Steinmetz, LM. Alternative polyadenylation diversifies post‐transcriptional regulation by selective RNA–protein interactions. Mol Syst Biol 2014, 10:719.
Geisberg, JV, Moqtaderi, Z, Fan, X, Ozsolak, F, Struhl, K. Global analysis of mRNA isoform half‐lives reveals stabilizing and destabilizing elements in yeast. Cell 2014, 156:812–824.
Bartel, DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004, 116:281–297.
Zhang, H, Kolb, FA, Brondani, V, Billy, E, Filipowicz, W. Human Dicer preferentially cleaves dsRNAs at their termini without a requirement for ATP. EMBO J 2002, 21:5875–5885.
Provost, P, Dishart, D, Doucet, J, Frendewey, D, Samuelsson, B, Radmark, O. Ribonuclease activity and RNA binding of recombinant human Dicer. EMBO J 2002, 21:5864–5874.
Chendrimada, TP, Gregory, RI, Kumaraswamy, E, Norman, J, Cooch, N, Nishikura, K, Shiekhattar, R. TRBP recruits the Dicer complex to Ago2 for microRNA processing and gene silencing. Nature 2005, 436:740–744.
Gregory, RI, Chendrimada, TP, Cooch, N, Shiekhattar, R. Human RISC couples microRNA biogenesis and posttranscriptional gene silencing. Cell 2005, 123:631–640.
Hammond, SM, Boettcher, S, Caudy, AA, Kobayashi, R, Hannon, GJ. Argonaute2, a link between genetic and biochemical analyses of RNAi. Science 2001, 293:1146–1150.
Pfaff, J, Hennig, J, Herzog, F, Aebersold, R, Sattler, M, Niessing, D, Meister, G. Structural features of Argonaute–GW182 protein interactions. Proc Natl Acad Sci 2013, 110:E3770–3779.
Song, JJ, Smith, SK, Hannon, GJ, Joshua‐Tor, L. Crystal structure of Argonaute and its implications for RISC slicer activity. Science 2004, 305:1434–1437.
Huntzinger, E, Izaurralde, E. Gene silencing by microRNAs: contributions of translational repression and mRNA decay. Nat Rev Genet 2011, 12:99–110.
Enright, AJ, John, B, Gaul, U, Tuschl, T, Sander, C, Marks, DS. MicroRNA targets in Drosophila. Genome Biol 2003, 5:R1.
Lewis, BP, Burge, CB, Bartel, DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 2005, 120:15–20.
Krek, A, Grün, D, Poy, MN, Wolf, R, Rosenberg, L, Epstein, EJ, MacMenamin, P, da Piedade, I, Gunsalus, KC, Stoffel, M. Combinatorial microRNA target predictions. Nat Genet 2005, 37:495–500.
Rajewsky, N, Vergassola, M, Gaul, U, Siggia, ED. Computational detection of genomic cis‐regulatory modules applied to body patterning in the early Drosophila embryo. BMC Bioinform 2002, 3:30.
Schroeder, MD, Pearce, M, Fak, J, Fan, H, Unnerstall, U, Emberly, E, Rajewsky, N, Siggia, ED, Gaul, U. Transcriptional control in the segmentation gene network of Drosophila. PLoS Biol 2004, 2:e271.
Gamazon, ER, Im, H‐K, Duan, S, Lussier, YA, Cox, NJ, Dolan, ME, Zhang, W. Exprtarget: an integrative approach to predicting human microRNA targets. PLoS One 2010, 5:e13534.
Kozomara, A, Griffiths‐Jones, S. miRBase: integrating microRNA annotation and deep‐sequencing data. Nucleic Acids Res 2011, 39:D152–157.
Vergoulis, T, Vlachos, IS, Alexiou, P, Georgakilas, G, Maragkakis, M, Reczko, M, Gerangelos, S, Koziris, N, Dalamagas, T, Hatzigeorgiou, AG. TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res 2012, 40:D222–229.
Rennie, W, Liu, C, Carmack, CS, Wolenc, A, Kanoria, S, Lu, J, Long, D, Ding, Y. STarMir: a web server for prediction of microRNA binding sites. Nucl Acids Res 2014, 42:W114–118.
Yang, J‐H, Li, J‐H, Shao, P, Zhou, H, Chen, Y‐Q, Qu, L‐H. starBase: a database for exploring microRNA–mRNA interaction maps from Argonaute CLIP‐Seq and Degradome‐Seq data. Nucleic Acids Res 2011, 39:D202–209.
Anders, G, Mackowiak, SD, Jens, M, Maaskola, J, Kuntzagk, A, Rajewsky, N, Landthaler, M, Dieterich, C. doRiNA: a database of RNA interactions in post‐transcriptional regulation. Nucleic Acids Res 2012, 40:D180–186.
Bazzini, AA, Lee, MT, Giraldez, AJ. Ribosome profiling shows that miR‐430 reduces translation before causing mRNA decay in zebrafish. Science 2012, 336:233–237.
Loayza‐Puch, F, Drost, J, Rooijers, K, Lopes, R, Elkon, R, Agami, R. p53 induces transcriptional and translational programs to suppress cell proliferation and growth. Genome Biol 2013, 14:12.
Sonenberg, N, Hinnebusch, AG. New modes of translational control in development, behavior, and disease. Mol Cell 2007, 28:721–729.
Lu, P, Vogel, C, Wang, R, Yao, X, Marcotte, EM. Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nat Biotechnol 2007, 25:117–124.
Vogel, C, Abreu, RD, Ko, DJ, Le, SY, Shapiro, BA, Burns, SC, Sandhu, D, Boutz, DR, Marcotte, EM, Penalva, LO. Sequence signatures and mRNA concentration can explain two‐thirds of protein abundance variation in a human cell line. Mol Syst Biol 2010, 6:9.
Bettegowda, A, Wilkinson, MF. Transcription and post‐transcriptional regulation of spermatogenesis. Philos Trans R Soc B Biol Sci 2010, 365:1637–1651.
Brown, GT, McIntyre, TM. Lipopolysaccharide signaling without a nucleus: Kinase cascades stimulate platelet shedding of proinflammatory IL‐1β‐rich microparticles. J Immunol 2011, 186:5489–5496.
Kuersten, S, Goodwin, EB. The power of the 3` UTR: translational control and development. Nat Rev Genet 2003, 4:626–637.
Bilanges, B, Stokoe, D. Mechanisms of translational deregulation in human tumors and therapeutic intervention strategies. Oncogene 2007, 26:5973–5990.
Lazaris‐Karatzas, A, Montine, KS, Sonenberg, N. Malignant transformation by a eukaryotic initiation factor subunit that binds to mRNA 5`cap, 1990.
Kozak, M, Evans, M, Gardner, PD, Flores, I, Mariano, TM, Pestka, S, Phelps, A, Wohlrab, H, Zushi, M, Gomi, K. Structural features in eukaryotic mRNAs that mod. Biol Chem 1991, 266:19867–19870.
Schwanhäusser, B, Busse, D, Li, N, Dittmar, G, Schuchhardt, J, Wolf, J, Chen, W, Selbach, M. Global quantification of mammalian gene expression control. Nature 2011, 473:337–342.
Kapeli, K, Yeo, GW. Genome‐wide approaches to dissect the roles of RNA binding proteins in translational control: implications for neurological diseases. Front Neurosci 2012, 6:144.
Zong, Q, Schummer, M, Hood, L, Morris, DR. Messenger RNA translation state: the second dimension of high‐throughput expression screening. Proc Natl Acad Sci 1999, 96:10632–10636.
Freeberg, L, Kuersten, S, Syed, F. Isolate and sequence ribosome‐protected mRNA fragments using size‐exclusion chromatography. Nat Methods 2013, 10 (Advertising feature).
ARTSeq Ribosome Profiling Kits from Epicentre. http://www.epibio.com/applications/rna‐sequencing/ribosome‐profiling/artseq‐ribosome‐profiling‐kits?protocols, 2014, Accessed Nov. 24, 2014.
Hsieh, AC, Liu, Y, Edlind, MP, Ingolia, NT, Janes, MR, Sher, A, Shi, EY, Stumpf, CR, Christensen, C, Bonham, MJ, et al. The translational landscape of mTOR signalling steers cancer initiation and metastasis. Nature 2012, 485:U55–196.
Kuersten, S, Radek, A, Vogel, C, Penalva, LOF. Translation regulation gets its ‘omics’ moment. WIREs RNA 2013, 4:617–630.
Jackson, RJ, Hellen, CU, Pestova, TV. The mechanism of eukaryotic translation initiation and principles of its regulation. Nat Rev Mol Cell Biol 2010, 11:113–127.
Staden, R. Measurements of the effects that coding for a protein has on a DNA sequence and their use for finding genes. Nucleic Acids Res 1984, 12:551–567.
Krogh, A, Brown, M, Mian, IS, Sjölander, K, Haussler, D. Hidden Markov models in computational biology: applications to protein modeling. J Mol Biol 1994, 235:1501–1531.
Burge, C, Karlin, S. Prediction of complete gene structures in human genomic DNA. J Mol Biol 1997, 268:78–94.
Crappé, J, Van Criekinge, W, Trooskens, G, Hayakawa, E, Luyten, W, Baggerman, G, Menschaert, G. Combining in silico prediction and ribosome profiling in a genome‐wide search for novel putatively coding sORFs. BMC Genomics 2013, 14:648.
Fritsch, C, Herrmann, A, Nothnagel, M, Szafranski, K, Huse, K, Schumann, F, Schreiber, S, Platzer, M, Krawczak, M, Hampe, J, et al. Genome‐wide search for novel human uORFs and N‐terminal protein extensions using ribosomal footprinting. Genome Res 2012, 22:2208–2218.
Ingolia, NT, Lareau, LF, Weissman, JS. Ribosome Profiling of Mouse Embryonic Stem Cells Reveals the Complexity and Dynamics of Mammalian Proteomes. Cell 2011, 147:789–802.
Lee, S, Liu, BT, Huang, SX, Shen, B, Qian, SB. Global mapping of translation initiation sites in mammalian cells at single‐nucleotide resolution. Proc Natl Acad Sci U S A 2012, 109:E2424–2432.
Guo, H, Ingolia, NT, Weissman, JS, Bartel, DP. Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature 2010, 466:835–840.
Stern‐Ginossar, N, Weisburd, B, Michalski, A, Vu, TKL, Hein, MY, Huang, SX, Ma, M, Shen, B, Qian, SB, Hengel, H, et al. Decoding Human Cytomegalovirus. Science 2012, 338:1088–1093.
Chew, G‐L, Pauli, A, Rinn, JL, Regev, A, Schier, AF, Valen, E. Ribosome profiling reveals resemblance between long non‐coding RNAs and 5′ leaders of coding RNAs. Development 2013, 140:2828–2834.
Reid, DW, Nicchitta, CV. Genome‐scale ribosome footprinting identifies a primary role for endoplasmic reticulum‐bound ribosomes in the translation of the mRNA transcriptome. J Biol Chem 2011, 287:5518–5536.
Barbosa, C, Peixeiro, I, Romão, L. Gene expression regulation by upstream open reading frames and human disease. PLoS Genet 2013, 9:e1003529.
Calvo, SE, Pagliarini, DJ, Mootha, VK. Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans. Proc Natl Acad Sci 2009, 106:7507–7512.
Hood, HM, Neafsey, DE, Galagan, J, Sachs, MS. Evolutionary roles of upstream open reading frames in mediating gene regulation in fungi. Annu Rev Microbiol 2009, 63:385–409.
Morris, DR, Geballe, AP. Upstream open reading frames as regulators of mRNA translation. Mol Cell Biol 2000, 20:8635–8642.
Howden, AJ, Geoghegan, V, Katsch, K, Efstathiou, G, Bhushan, B, Boutureira, O, Thomas, B, Trudgian, DC, Kessler, BM, Dieterich, DC. QuaNCAT: quantitating proteome dynamics in primary cells. Nat Methods 2013, 10:343–346.
Varenne, S, Buc, J, Lloubes, R, Lazdunski, C. Translation is a non‐uniform process: effect of tRNA availability on the rate of elongation of nascent polypeptide chains. J Mol Biol 1984, 180:549–576.
Shalgi, R, Lindquist, S, Burge, CB. Widespread regulation of translation by elongation pausing in heat shock. FASEB J 2013, 27:1.
Mukherjee, N, Jacobs, NC, Hafner, M, Kennington, EA, Nusbaum, JD, Tuschl, T, Blackshear, PJ, Ohler, U. Global target mRNA specification and regulation by the RNA‐binding protein ZFP36, 2014.