Literature DB >> 20053813

A combined immunoprecipitation, mass spectrometric and nucleic acid sequencing approach to determine microRNA-mediated post-transcriptional gene regulatory networks.

Jeffrey N Savas1, Naoko Tanese.   

Abstract

While initiation of transcription has attracted the most attention in the field of gene regulation, it has become clear that additional stages in the gene expression cascade including post-transcriptional events are under equally exquisite control. The seminal discovery that short RNAs (microRNA, small interfering RNA, Piwi-interacting RNA), play important roles in repressing gene expression has spurred a rush of new interest in post-transcriptional gene silencing mechanisms. The development of affinity tags and high-resolution tandem mass spectrometry (MS/MS) has greatly simplified the analysis of proteins that regulate gene expression. Further, the use of DNA microarrays and 'second generation' nucleic acid sequencing ('deep sequencing') technologies has facilitated the identification of their regulatory targets. These technological advancements mark a significant step towards a comprehensive understanding of gene regulatory networks. The purpose of this review is to highlight several recent reports that illustrate the value of affinity-purification (immunoprecipitation) followed by mass spectrometric protein analysis and nucleic acid analysis by deep sequencing (AP-MS/Seq) to examine mRNA after it has been transcribed. The ability to identify the direct nucleic acid targets of post-transcriptional gene regulatory machines is a critical first step towards understanding the contribution of post-transcriptional pathways on gene expression.

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Year:  2010        PMID: 20053813      PMCID: PMC3097100          DOI: 10.1093/bfgp/elp050

Source DB:  PubMed          Journal:  Brief Funct Genomics        ISSN: 2041-2649            Impact factor:   4.241


  40 in total

1.  Promoter-specific binding of Rap1 revealed by genome-wide maps of protein-DNA association.

Authors:  J D Lieb; X Liu; D Botstein; P O Brown
Journal:  Nat Genet       Date:  2001-08       Impact factor: 38.330

Review 2.  microRNA target predictions in animals.

Authors:  Nikolaus Rajewsky
Journal:  Nat Genet       Date:  2006-06       Impact factor: 38.330

3.  A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes.

Authors:  Kevin C Miranda; Tien Huynh; Yvonne Tay; Yen-Sin Ang; Wai-Leong Tam; Andrew M Thomson; Bing Lim; Isidore Rigoutsos
Journal:  Cell       Date:  2006-09-22       Impact factor: 41.582

Review 4.  Argonaute proteins: mediators of RNA silencing.

Authors:  Lasse Peters; Gunter Meister
Journal:  Mol Cell       Date:  2007-06-08       Impact factor: 17.970

5.  Zebrafish MiR-430 promotes deadenylation and clearance of maternal mRNAs.

Authors:  Antonio J Giraldez; Yuichiro Mishima; Jason Rihel; Russell J Grocock; Stijn Van Dongen; Kunio Inoue; Anton J Enright; Alexander F Schier
Journal:  Science       Date:  2006-02-16       Impact factor: 47.728

6.  Functional dissection of the human TNRC6 (GW182-related) family of proteins.

Authors:  David Baillat; Ramin Shiekhattar
Journal:  Mol Cell Biol       Date:  2009-05-26       Impact factor: 4.272

7.  MicroRNA silencing through RISC recruitment of eIF6.

Authors:  Thimmaiah P Chendrimada; Kenneth J Finn; Xinjun Ji; David Baillat; Richard I Gregory; Stephen A Liebhaber; Amy E Pasquinelli; Ramin Shiekhattar
Journal:  Nature       Date:  2007-05-16       Impact factor: 49.962

8.  Genome-wide mapping of in vivo protein-DNA interactions.

Authors:  David S Johnson; Ali Mortazavi; Richard M Myers; Barbara Wold
Journal:  Science       Date:  2007-05-31       Impact factor: 47.728

9.  Translation repression in human cells by microRNA-induced gene silencing requires RCK/p54.

Authors:  Chia-ying Chu; Tariq M Rana
Journal:  PLoS Biol       Date:  2006-07       Impact factor: 8.029

Review 10.  Yeast two-hybrid, a powerful tool for systems biology.

Authors:  Anna Brückner; Cécile Polge; Nicolas Lentze; Daniel Auerbach; Uwe Schlattner
Journal:  Int J Mol Sci       Date:  2009-06-18       Impact factor: 6.208

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  1 in total

1.  Mathematical modeling of combinatorial regulation suggests that apparent positive regulation of targets by miRNA could be an artifact resulting from competition for mRNA.

Authors:  Dimpal Nyayanit; Chetan J Gadgil
Journal:  RNA       Date:  2015-01-09       Impact factor: 4.942

  1 in total

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