University of Regensburg
Publishes on MicroRNA in disease regulation, RNA Research and Splicing, Cancer-related Molecular Pathways. 20 papers and 2k citations.
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MicroRNAs (miRNAs) constitute a class of small non-coding RNAs that regulate gene expression on the level of translation and/or mRNA stability. Mammalian miRNAs associate with members of the Argonaute (Ago) protein family and bind to partially complementary sequences in the 3' untranslated region (UTR) of specific target mRNAs. Computer algorithms based on factors such as free binding energy or sequence conservation have been used to predict miRNA target mRNAs. Based on such predictions, up to one third of all mammalian mRNAs seem to be under miRNA regulation. However, due to the low degree of complementarity between the miRNA and its target, such computer programs are often imprecise and therefore not very reliable. Here we report the first biochemical identification approach of miRNA targets from human cells. Using highly specific monoclonal antibodies against members of the Ago protein family, we co-immunoprecipitate Ago-bound mRNAs and identify them by cloning. Interestingly, most of the identified targets are also predicted by different computer programs. Moreover, we randomly analyzed six different target candidates and were able to experimentally validate five as miRNA targets. Our data clearly indicate that miRNA targets can be experimentally identified from Ago complexes and therefore provide a new tool to directly analyze miRNA function.
Short interfering RNAs (siRNAs) are widely used as tool for gene inactivation in basic research and therapeutic applications. One of the major shortcomings of siRNA experiments are sequence-specific off-target effects. Such effects are largely unpredictable because siRNAs can affect partially complementary sequences and function like microRNAs (miRNAs), which inhibit gene expression on mRNA stability or translational levels. Here we demonstrate that novel, enzymatically generated siRNA pools-referred to as siPools-containing up to 60 accurately defined siRNAs eliminate off-target effects. This is achieved by the low concentration of each individual siRNA diluting sequence-specific off-target effects below detection limits. In fact, whole transcriptome analyses reveal that single siRNA transfections can severely affect global gene expression. However, when complex siRNA pools are transfected, almost no transcriptome alterations are observed. Taken together, we present enzymatically produced complex but accurately defined siRNA pools with potent on-target silencing but without detectable off-target effects.