Literature DB >> 34495505

Guiding RNAi Design Through Characterization of Endogenous Small RNA Pathways.

Jacob O Peter1, Yulica Santos-Ortega1, Alex Flynt2.   

Abstract

RNA interference (RNAi) is a common eukaryotic gene regulation process driven by small RNA effectors. Mechanisms that govern regulatory small noncoding RNA behavior have been extensively described in only a handful of organisms, which suggests that the most effective RNAi approach in many organisms, such as insect pests, remains to be determined. Taking advantage of advances in high-throughput sequencing, characterization of small RNA molecules can be achieved through bioinformatic approaches without the need for genetic experiments. This chapter describes pipelines for characterizing three main classes of small RNAs (microRNAs, small-interfering RNAs, and piwi-associated RNAs) using computationally determined small RNA biogenesis signatures. Obtaining information regarding the abundance of different small RNA classes through these pipelines will lead to a better-informed RNAi strategy, thereby identifying the most efficacious approach for RNAi.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Bioinformatics; Cloning; Pests; RNAi; dsRNA; small-RNAs

Mesh:

Substances:

Year:  2022        PMID: 34495505      PMCID: PMC8959004          DOI: 10.1007/978-1-0716-1633-8_4

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  21 in total

1.  Evaluation of SmartStax and SmartStax PRO maize against western corn rootworm and northern corn rootworm: efficacy and resistance management.

Authors:  Graham P Head; Matthew W Carroll; Sean P Evans; Dwain M Rule; Alan R Willse; Thomas L Clark; Nicholas P Storer; Ronald D Flannagan; Luke W Samuel; Lance J Meinke
Journal:  Pest Manag Sci       Date:  2017-03-17       Impact factor: 4.845

2.  Computing siRNA and piRNA overlap signatures.

Authors:  Christophe Antoniewski
Journal:  Methods Mol Biol       Date:  2014

Review 3.  Insecticidal RNA interference, thinking beyond long dsRNA.

Authors:  Alex S Flynt
Journal:  Pest Manag Sci       Date:  2020-11-04       Impact factor: 4.845

4.  Tissue-dependence and sensitivity of the systemic RNA interference response in the desert locust, Schistocerca gregaria.

Authors:  Niels Wynant; Heleen Verlinden; Bert Breugelmans; Gert Simonet; Jozef Vanden Broeck
Journal:  Insect Biochem Mol Biol       Date:  2012-09-26       Impact factor: 4.714

Review 5.  Epigenetics in alternative pre-mRNA splicing.

Authors:  Reini F Luco; Mariano Allo; Ignacio E Schor; Alberto R Kornblihtt; Tom Misteli
Journal:  Cell       Date:  2011-01-07       Impact factor: 41.582

6.  Discrete small RNA-generating loci as master regulators of transposon activity in Drosophila.

Authors:  Julius Brennecke; Alexei A Aravin; Alexander Stark; Monica Dus; Manolis Kellis; Ravi Sachidanandam; Gregory J Hannon
Journal:  Cell       Date:  2007-03-08       Impact factor: 41.582

7.  PRG-1 and 21U-RNAs interact to form the piRNA complex required for fertility in C. elegans.

Authors:  Pedro J Batista; J Graham Ruby; Julie M Claycomb; Rosaria Chiang; Noah Fahlgren; Kristin D Kasschau; Daniel A Chaves; Weifeng Gu; Jessica J Vasale; Shenghua Duan; Darryl Conte; Shujun Luo; Gary P Schroth; James C Carrington; David P Bartel; Craig C Mello
Journal:  Mol Cell       Date:  2008-06-19       Impact factor: 17.970

8.  miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades.

Authors:  Marc R Friedländer; Sebastian D Mackowiak; Na Li; Wei Chen; Nikolaus Rajewsky
Journal:  Nucleic Acids Res       Date:  2011-09-12       Impact factor: 16.971

9.  piPipes: a set of pipelines for piRNA and transposon analysis via small RNA-seq, RNA-seq, degradome- and CAGE-seq, ChIP-seq and genomic DNA sequencing.

Authors:  Bo W Han; Wei Wang; Phillip D Zamore; Zhiping Weng
Journal:  Bioinformatics       Date:  2014-10-17       Impact factor: 6.937

10.  miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments.

Authors:  Michael Hackenberg; Martin Sturm; David Langenberger; Juan Manuel Falcón-Pérez; Ana M Aransay
Journal:  Nucleic Acids Res       Date:  2009-05-11       Impact factor: 16.971

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