Project description:MicroRNAs are small RNAs that regulate protein levels. It is commonly assumed that the expression level of a microRNA is directly correlated with its repressive activity M-bM-^@M-^S that is, highly expressed microRNAs will repress their target mRNAs more. Here we investigate the quantitative relationship between endogenous microRNA expression and repression for 32 mature microRNAs in Drosophila melanogaster S2 cells. In general, we find that more abundant microRNAs repress their targets to a greater degree. However, the relationship between expression and repression is nonlinear, such that a 10-fold greater microRNA concentration produces only a 10% increase in target repression. The expression/repression relationship is the same for both dominant guide microRNAs and minor mature products (so-called passenger strands/microRNA* sequences). However, we find examples of microRNAs whose cellular concentrations differ by several orders of magnitude, yet induce similar repression of target mRNAs. Likewise, microRNAs with similar expression can have very different repressive abilities. We show that the association of microRNAs with Argonaute proteins does not explain this variation in repression. The observed relationship is consistent with the limiting step in target repression being the association of the microRNA/RISC complex with the target site. These findings argue that modest changes in cellular microRNA concentration will have minor effects on repression of targets. Two replicates of S2-DRSC cells under normal conditions
Project description:MicroRNAs are a class of small (~22nt) endogenous RNAs that regulate target transcript expression post-transcriptionally. Previous studies characterized age-related changes in diurnal transcript expression but it is not understood how these changes are regulated, and whether they may be attributed in part to changes in microRNA expression or activity with age. Diurnal small RNA expression changes with age were not previously studied. To interrogate changes in small RNA expression with age, we collected young (5 day) and old (55 day) Drosophila melanogaster around-the-clock and performed deep sequencing on size-selected RNA from whole heads. We find several microRNAs with changes in rhythmicity after aging, and we investigate microRNAs which are differentially expressed with age. We find that predicted targets of differentially expressed microRNAs have RNA-binding and transcription factor activity. We use a previously published method to identify mRNA transcripts which show evidence of microRNA targeting that is altered after aging, and find several that are involved in muscle development and maintenance. Finally, we identify novel microRNAs using the random-forest-based method miRWoods, which surprisingly also discovered transfer RNA-derived fragments.
Project description:MicroRNAs are small RNAs that regulate protein levels. It is commonly assumed that the expression level of a microRNA is directly correlated with its repressive activity – that is, highly expressed microRNAs will repress their target mRNAs more. Here we investigate the quantitative relationship between endogenous microRNA expression and repression for 32 mature microRNAs in Drosophila melanogaster S2 cells. In general, we find that more abundant microRNAs repress their targets to a greater degree. However, the relationship between expression and repression is nonlinear, such that a 10-fold greater microRNA concentration produces only a 10% increase in target repression. The expression/repression relationship is the same for both dominant guide microRNAs and minor mature products (so-called passenger strands/microRNA* sequences). However, we find examples of microRNAs whose cellular concentrations differ by several orders of magnitude, yet induce similar repression of target mRNAs. Likewise, microRNAs with similar expression can have very different repressive abilities. We show that the association of microRNAs with Argonaute proteins does not explain this variation in repression. The observed relationship is consistent with the limiting step in target repression being the association of the microRNA/RISC complex with the target site. These findings argue that modest changes in cellular microRNA concentration will have minor effects on repression of targets.
Project description:Drosophila melanogaster is a well-studied genetic model organism with several large-scale transcriptome resources. Here we investigate 7,952 proteins during the fly life cycle from embryo to adult and also provide a high-resolution temporal time course proteome of 5,458 proteins during embryogenesis. We use our large scale data set to compare transcript/protein expression, uncovering examples of extreme differences between mRNA and protein abundance. In the embryogenesis proteome, the time delay in protein synthesis after transcript expression was determined. For some proteins, including the transcription factor lola, we monitor isoform specific expression levels during early fly development. Furthermore, we obtained firm evidence of 268 small proteins, which are hard to predict by bioinformatics. We observe peptides originating from non-coding regions of the genome and identified Cyp9f3psi as a protein-coding gene. As a powerful resource to the community, we additionally created an interactive web interface (http://www.butterlab.org) advancing the access to our data.
Project description:modENCODE_submission_755 This submission comes from a modENCODE project of Eric Lai. For full list of modENCODE projects, see http://www.genome.gov/26524648 Project Goal: We plan to generate a comprehensive catalog of expressed and functional microRNAs, and generate biological evidence for their regulatory activity. We plan also to delineate the primary transcription units of microRNA genes. Finally, we plan to annotate other classes of non-miRNA expressed small RNAs, as least some of which may define novel classes of small RNA genes. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf