scholarly journals Profiling and Characterization of Small RNAs in the Liverwort,Marchantia polymorpha, Belonging to the First Diverged Land Plants

2015 ◽  
Vol 57 (2) ◽  
pp. 359-372 ◽  
Author(s):  
Masayuki Tsuzuki ◽  
Ryuichi Nishihama ◽  
Kimitsune Ishizaki ◽  
Yukio Kurihara ◽  
Minami Matsui ◽  
...  
Keyword(s):  
Small Rnas ◽  
Land Plants ◽  
Marchantia Polymorpha

Characterization of small RNAs in early zebrafish PGCs

2021 ◽  
Author(s):  
Xiaoyuan Zhang ◽  
Yiping Li ◽  
Yunbin Zhang ◽  
Shifeng Li
Keyword(s):  
Small Rnas

scholarly journals Identification and characterization of two novel classes of small RNAs in the mouse germline: retrotransposon-derived siRNAs in oocytes and germline small RNAs in testes

2006 ◽  
Vol 20 (13) ◽  
pp. 1732-1743 ◽  
Author(s):  
Toshiaki Watanabe ◽  
Atsushi Takeda ◽  
Tomoyuki Tsukiyama ◽  
Kazuyuki Mise ◽  
Tetsuro Okuno ◽  
...  
Keyword(s):  
Small Rnas ◽  
Identification And Characterization

scholarly journals sRNA Target Prediction Organizing Tool (SPOT) Integrates Computational and Experimental Data To Facilitate Functional Characterization of Bacterial Small RNAs

mSphere ◽  
2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Alisa M. King ◽  
Carin K. Vanderpool ◽  
Patrick H. Degnan
Keyword(s):  
Experimental Data ◽  
Stress Responses ◽  
Small Rnas ◽  
Metabolic Regulation ◽  
Functional Characterization ◽  
Target Prediction ◽  
Structure Stability ◽  
Accurate Identification ◽  
Mrna Targets

Small RNAs (sRNAs) regulate gene expression in diverse bacteria by interacting with mRNAs to change their structure, stability, or translation. Hundreds of sRNAs have been identified in bacteria, but characterization of their regulatory functions is limited by difficulty with sensitive and accurate identification of mRNA targets. Thus, new robust methods of bacterial sRNA target identification are in demand. Here, we describe our small RNA target prediction organizing tool (SPOT), which streamlines the process of sRNA target prediction by providing a single pipeline that combines available computational prediction tools with customizable results filtering based on experimental data. SPOT allows the user to rapidly produce a prioritized list of predicted sRNA-target mRNA interactions that serves as a basis for further experimental characterization. This tool will facilitate elucidation of sRNA regulons in bacteria, allowing new discoveries regarding the roles of sRNAs in bacterial stress responses and metabolic regulation.

scholarly journals Plugging Small RNAs into the Network

mSystems ◽  
2020 ◽  
Vol 5 (3) ◽  
Author(s):  
Lars Barquist
Keyword(s):  
Small Rnas ◽  
Posttranscriptional Regulation ◽  
Network Inference ◽  
Functional Characterization ◽  
The State ◽  
Diverse Range ◽  
Regulatory Interactions ◽  
Link Type ◽  
Wide Range

ABSTRACT Small RNAs (sRNAs) have been discovered in every bacterium examined and have been shown to play important roles in the regulation of a diverse range of behaviors, from metabolism to infection. However, despite a wide range of available techniques for discovering and validating sRNA regulatory interactions, only a minority of these molecules have been well characterized. In part, this is due to the nature of posttranscriptional regulation: the activity of an sRNA depends on the state of the transcriptome as a whole, so characterization is best carried out under the conditions in which it is naturally active. In this issue of mSystems, Arrieta-Ortiz and colleagues (M. L. Arrieta-Ortiz, C. Hafemeister, B. Shuster, N. S. Baliga, et al., mSystems 5:e00057-20, 2020, https://doi.org/10.1128/mSystems.00057-20) present a network inference approach based on estimating sRNA activity across transcriptomic compendia. This shows promise not only for identifying new sRNA regulatory interactions but also for pinpointing the conditions in which these interactions occur, providing a new avenue toward functional characterization of sRNAs.

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