| Abstract MicroRNAs may be small, but these noncoding RNAs that regulate gene expression are creating a big stir. Finding differences in the expression of microRNAs between, say, healthy and diseased cells could potentially be used to diagnose diseases or to assess treatment effects. If researchers can understand how they work, microRNAs could provide tools for manipulating genes, not to mention help to untangle how genes are regulated.At first glance, studying microRNAs seems more manageable than studying the menagerie of other types of RNA. Typical expression profiling experiments for protein-coding genes examine thousands of molecules; those for microRNAs examine hundreds. But researchers are still figuring out the most reliable ways to measure these important molecules. The most common techniques for profiling microRNAs are deep sequencing, microarrays and quantitative real-time PCR (qPCR). All are supported by several commercial offerings. Though specific products and techniques vary, researchers generally agree on the relative strengths and weaknesses of the platforms. The best choice depends on the application, says Muneesh Tewari, who studies microRNAs at the Fred Hutchinson Cancer Research Center. “It's a balance of cost, precision, accuracy and sample quantity,” he says. “If the purpose is to screen a bunch of samples to find a few microRNAs that change and you can tolerate a false negative, then the microarray may be the best platform. If the purpose is to detect microRNAs where the sample amount is limiting, then qPCR has better sensitivity, and if you are trying to see different isoforms or very similar microRNAs, then sequencing is going to be the best approach.
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