DMCA
A mammalian microRNA expression atlas based on small RNA library sequencing. (2007)
| Venue: | Cell, |
| Citations: | 417 - 4 self |
BibTeX
@ARTICLE{Landgraf07amammalian,
author = {Pablo Landgraf and Mirabela Rusu and Robert Sheridan and Alain Sewer and Nicola Iovino and Alexei Aravin and Sé Bastien Pfeffer and Amanda Rice and Alice O Kamphorst and Markus Landthaler and Carolina Lin and Nicholas D Socci and Leandro Hermida and Valerio Fulci and Sabina Chiaretti and Robin Foà and Julia Schliwka and Uta Fuchs and Astrid Novosel and Roman-Ulrich Mü and Bernhard Schermer and Ute Bissels and Jason Inman and Quang Phan and David B Weir and Ruchi Choksi and Gabriella De Vita and Daniela Frezzetti and Hans-Ingo Trompeter and Veit Hornung and Grace Teng and Gunther Hartmann and Miklos Palkovits and Roberto Di Lauro and Peter Wernet and Giuseppe Macino and Charles E Rogler and James W Nagle and Jingyue Ju and F Nina Papavasiliou and Thomas Benzing and Peter Lichter and Wayne Tam and Michael J Brownstein and Andreas Bosio and James J Russo and Chris Sander and Mihaela Zavolan and Thomas Tuschl},
title = {A mammalian microRNA expression atlas based on small RNA library sequencing.},
journal = {Cell,},
year = {2007},
pages = {1401--1414}
}
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Abstract
SUMMARY MicroRNAs (miRNAs) are small noncoding regulatory RNAs that reduce stability and/or translation of fully or partially sequencecomplementary 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 that were enriched in neuronal as well as normal and malignant hematopoietic cells and tissues. We present expression profiles derived from clone count data and provide computational tools for their analysis. Unexpectedly, a relatively small set of miRNAs, many of which are ubiquitously expressed, account for most of the differences 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.
