Characterization of tRNAs and tRNA-derived Small RNAs in Human Cerebral Cortical Organoids

2020 ◽  
Author(s):  
Alex Bagi
Keyword(s):  
Small Rnas

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.

scholarly journals Characterization of Hypovirus-Derived Small RNAs Generated in the Chestnut Blight Fungus by an Inducible DCL-2-Dependent Pathway

2008 ◽  
Vol 82 (6) ◽  
pp. 2613-2619 ◽  
Author(s):  
Xuemin Zhang ◽  
Gert C. Segers ◽  
Qihong Sun ◽  
Fuyou Deng ◽  
Donald L. Nuss
Keyword(s):  
Small Rnas ◽  
Rna Silencing ◽  
Cryphonectria Parasitica ◽  
Chestnut Blight ◽  
Fungal Host ◽  
Chestnut Blight Fungus ◽  
Mutant Strains ◽  
Suppressor Of Rna Silencing ◽  
Dependent Pathway

ABSTRACT The disruption of one of two dicer genes, dcl-2, of the chestnut blight fungus Cryphonectria parasitica was recently shown to increase susceptibility to mycovirus infection (G. C. Segers, X. Zhang, F. Deng, Q. Sun, and D. L. Nuss, Proc. Natl. Acad. Sci. USA 104:12902-12906, 2007). We now report the accumulation of virus-derived small RNAs (vsRNAs) in hypovirus CHV1-EP713-infected wild-type and dicer gene dcl-1 mutant C. parasitica strains but not in hypovirus-infected dcl-2 mutant and dcl-1 dcl-2 double-mutant strains. The CHV1-EP713 vsRNAs were produced from both the positive and negative viral RNA strands at a ratio of 3:2 in a nonrandom distribution along the viral genome. We also show that C. parasitica responds to hypovirus and mycoreovirus infections with a significant increase (12- to 20-fold) in dcl-2 expression while the expression of dcl-1 is increased only modestly (2-fold). The expression of dcl-2 is further increased (∼35-fold) following infection with a hypovirus CHV1-EP713 mutant that lacks the p29 suppressor of RNA silencing. The combined results demonstrate the biogenesis of mycovirus-derived small RNAs in a fungal host through the action of a specific dicer gene, dcl-2. They also reveal that dcl-2 expression is significantly induced in response to mycovirus infection by a mechanism that appears to be repressed by the hypovirus-encoded p29 suppressor of RNA silencing.

scholarly journals Identification and characterization of small RNAs inYersinia pestis

RNA Biology ◽  
2013 ◽  
Vol 10 (3) ◽  
pp. 397-405 ◽  
Author(s):  
Arthur Beauregard ◽  
Eric Smith ◽  
Brianna Petrone ◽  
Navjot Singh ◽  
Christopher Karch ◽  
...  
Keyword(s):  
Small Rnas ◽  
Identification And Characterization
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