The miRNA profiles of mouse neuroblastoma were in keeping with their human counterpart, except for the presence of the mouse-specific cluster of mir-297a-1(46) (12

Human Leukocyte Elastase 0 Comments

The miRNA profiles of mouse neuroblastoma were in keeping with their human counterpart, except for the presence of the mouse-specific cluster of mir-297a-1(46) (12.3% average cloning frequency), which was not expressed in normal mouse brain. 29. NIHMS26851-supplement-29.xls (112K) GUID:?6BB7BEDE-CB61-40EF-9E55-1BB028B9F497 30. NIHMS26851-supplement-30.xls (218K) GUID:?A620CB16-CAE8-4CB4-813D-C3BF5D0EB6DD 31. NIHMS26851-supplement-31.xls (149K) GUID:?7A0FB6D6-A721-4D6F-B61C-E67DC96B2142 32. NIHMS26851-supplement-32.doc (4.3M) GUID:?94583EC0-4E5A-45A8-A904-CE234BC65883 33. NIHMS26851-supplement-33.xls (18K) GUID:?277D9975-3247-4E0F-A9F8-B76373A2CED4 34. NIHMS26851-supplement-34.xls (1.4M) GUID:?CE2F5C69-10B3-4598-A21D-0DAE8033B853 35. NIHMS26851-supplement-35.xls (547K) GUID:?66E5AA26-78A0-4028-B01F-3FB28A8543B1 36. NIHMS26851-supplement-36.xls (188K) GUID:?475C27BD-E419-47BE-ADD8-178A6B3D6E50 37. NIHMS26851-supplement-37.xls (14K) GUID:?92C4C453-4E5E-4C3D-8BB0-08104485A0CF 38. NIHMS26851-supplement-38.xls (1.0M) GUID:?E27A6861-09C7-4192-84E3-2A2642B34091 Summary MicroRNAs (miRNAs) are small non-coding regulatory RNAs that reduce stability and/or translation of fully or partially sequence-complementary target mRNAs. In order to identify miRNAs and to assess their expression patterns, we sequenced over 250 small RNA libraries from 26 different organ systems and cell types of human and rodents, enriched in neuronal as well as normal and malignant hematopoietic cells and tissues. We present expression profiles derived from clone count data and provide novel computational tools for their analysis. Unexpectedly, a relatively small set of miRNAs, many of which are ubiquitously expressed, account for most of the difference in miRNA profiles between cell lineages and tissues. This broad survey also provides detailed and accurate information about mature sequences, precursors, genome locations, maturation processes, inferred transcriptional units and conservation patterns. We also propose a subclassification scheme for miRNAs for assisting future experimental and computational functional analyses. Introduction MicroRNAs (miRNAs) are small (~22-nucleotide) non-coding regulatory RNA molecules encoded by plants, animals and some viruses (reviewed in Bartel, 2004; Berezikov and Plasterk, 2005; Cullen, 2006; Mallory and Vaucheret, 2006). They were first discovered in and were shown to regulate expression of partially complementary mRNAs (Lee et al., 1993; Wightman et al., 1993; Moss et al., 1997). Most miRNAs are evolutionary conserved in related species and some even show conservation between invertebrates and vertebrates (Pasquinelli et al., 2000; Lagos-Quintana et al., 2001; Lau et al., 2001; Lee and Ambros, 2001). Many miRNAs have well-defined developmental and cell-type specific expression patterns (reviewed in Wienholds and Plasterk, 2005). However, for most mammalian miRNAs FRAX486 the relative abundance and specificity of expression remain to be investigated. miRNAs regulate a variety of developmental and physiological processes (reviewed in Cao et al., 2006; Plasterk, 2006; Shivdasani, 2006). The analysis of miRNA function in animals CD3G is either performed genetically or by delivery of synthetic miRNA precursors or antisense oligonucleotides (antagomirs) (reviewed recently in Krtzfeldt et al., 2006). Such analysis revealed that 100 to 200 target mRNAs are repressed and destabilized by a single miRNA (Krtzfeldt et al., 2005; Lim et al., 2005; Linsley et al., 2007). Other mRNAs appear to be under selective pressure to avoid complementarity to co-expressed highly-abundant miRNAs (Farh et al., 2005; Stark et al., 2005; Sood et al., 2006). Many computational studies have been conducted to define miRNA regulatory networks (reviewed in Rajewsky, 2006), yet most molecular targets of miRNAs remain experimentally undefined. Posttranscriptional editing of some double-stranded precursor miRNAs by adenosine deamination (Luciano et al., 2004; Pfeffer et al., 2005; Blow et al., 2006; Kawahara et al., 2007) can further control targeting specificity as well as modulate the stability and processing of miRNA precursor transcripts (Gottwein et al., 2006; Yang et al., FRAX486 2006). Polymorphic sequence variation identified in some other pre-miRNA sequences, in contrast, had no effect on miRNA processing (Iwai and Naraba, 2005; Diederichs and Haber, 2006). Regulated processing of miRNA precursor transcripts has also been reported in the context of cell-type and stage-specific expression (Obernosterer et al., 2006; Thomson et al., 2006). The increasing number of studies addressing the role of miRNAs in development and in various diseases including cancer emphasizes the need for a comprehensive catalogue of accurate sequence, expression and conservation information for the large number FRAX486 of recently proposed miRNAs. Here we present a database and analysis of over 250 small RNA cDNA libraries obtained by cloning and sequencing. We have developed interactive analysis tools, and illustrate their utility in.