scholarly journals Identification of microRNAs in the West Nile virus vector Culex tarsalis

2021 ◽  
Author(s):  
Sultan Asad ◽  
Ahmed M Mehdi ◽  
Sujit Pujhari ◽  
Claudia Rueckert ◽  
Gregory D Ebel ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Cell Line ◽  
Rna Sequencing ◽  
Small Rna ◽  
The United States ◽  
Small Rna Sequencing ◽  
Culex Tarsalis ◽  
Sequencing Data ◽  
West Nile

Background: microRNAs (miRNAs) represent a group of small non-coding RNAs that are crucial gene regulators of important biological functions including development and pathogen defense in most living organisms. Presently, there is a lack of availability of information regarding the miRNAs in the mosquito Culex tarsalis, which is one of the most important vectors of West Nile virus (WNV) in the United States. We used small RNA sequencing data and in vitro and in vivo experiments to identify and validate the presence of a repertoire of miRNAs in Cx. tarsalis mosquitoes. Results: Using bioinformatic approaches we analyzed small RNA sequencing data from the Cx. tarsalis CT embryonic cell line to discover 86 miRNAs. Consistent with other mosquitoes such as Aedes albopictus and Cx. quinquefasciatus, mi-184 was found to be the most abundant miRNA in Cx tarsalis. We also identified an additional 20 novel miRNAs from the recently sequenced Cx. tarsalis genome, for a total of 106 miRNAs identified in this study. The presence of selected miRNAs was biologically validated in both cell line and adult Cx. tarsalis mosquitoes using RT-qPCR and sequencing. Conclusions: Cx. tarsalis is an important vector of many medically important pathogens including WNV and Western Equine encephalitis. Here we report a detailed insight into the miRNA population in Cx. tarsalis mosquitoes. These results will open new avenues of research deciphering the role of miRNAs in different Cx. tarsalis biological events such as development, metabolism, immunity and pathogen infection.

scholarly journals Characterizing the cancer-associated microbiome with small RNA sequencing data

2020 ◽  
Vol 522 (3) ◽  
pp. 776-782
Author(s):  
Wei-Hao Lee ◽  
Kai-Pu Chen ◽  
Kai Wang ◽  
Hsuan-Cheng Huang ◽  
Hsueh-Fen Juan
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Small Rna Sequencing ◽  
Sequencing Data

scholarly journals miRquant 2.0: an Expanded Tool for Accurate Annotation and Quantification of MicroRNAs and their isomiRs from Small RNA-Sequencing Data

2016 ◽  
Vol 13 (5) ◽  
Author(s):  
Matthew Kanke ◽  
Jeanette Baran-Gale ◽  
Jonathan Villanueva ◽  
Praveen Sethupathy
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Cell Types ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Sequencing Technology ◽  
Additional Information ◽  
Disease States ◽  
Non Coding Rnas ◽  
The Rich

SummarySmall non-coding RNAs, in particular microRNAs, are critical for normal physiology and are candidate biomarkers, regulators, and therapeutic targets for a wide variety of diseases. There is an ever-growing interest in the comprehensive and accurate annotation of microRNAs across diverse cell types, conditions, species, and disease states. Highthroughput sequencing technology has emerged as the method of choice for profiling microRNAs. Specialized bioinformatic strategies are required to mine as much meaningful information as possible from the sequencing data to provide a comprehensive view of the microRNA landscape. Here we present miRquant 2.0, an expanded bioinformatics tool for accurate annotation and quantification of microRNAs and their isoforms (termed isomiRs) from small RNA-sequencing data. We anticipate that miRquant 2.0 will be useful for researchers interested not only in quantifying known microRNAs but also mining the rich well of additional information embedded in small RNA-sequencing data.

scholarly journals Evidence for human microRNA-offset RNAs in small RNA sequencing data

2009 ◽  
Vol 25 (18) ◽  
pp. 2298-2301 ◽  
Author(s):  
D. Langenberger ◽  
C. Bermudez-Santana ◽  
J. Hertel ◽  
S. Hoffmann ◽  
P. Khaitovich ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Small Rna Sequencing ◽  
Sequencing Data

scholarly journals In silico genome wide mining of conserved and novel miRNAs in the brain and pineal gland of Danio rerio using small RNA sequencing data

Genomics Data ◽  
2016 ◽  
Vol 7 ◽  
pp. 46-53 ◽  
Author(s):  
Suyash Agarwal ◽  
Naresh Sahebrao Nagpure ◽  
Prachi Srivastava ◽  
Basdeo Kushwaha ◽  
Ravindra Kumar ◽  
...  
Keyword(s):  
Pineal Gland ◽  
Rna Sequencing ◽  
Danio Rerio ◽  
Small Rna ◽  
In Silico ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Genome Wide ◽  
The Brain

Traces of post-transcriptional RNA modifications in deep sequencing data

2011 ◽  
Vol 392 (4) ◽  
Author(s):  
Sven Findeiß ◽  
David Langenberger ◽  
Peter F. Stadler ◽  
Steve Hoffmann
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Small Rna Sequencing ◽  
Data Sets ◽  
Sequencing Data ◽  
Rna Modifications ◽  
Deep Sequencing Data ◽  
Complex Processes ◽  
Mature Micrornas ◽  
Rna Maturation

Abstract Many aspects of the RNA maturation leave traces in RNA sequencing data in the form of deviations from the reference genomic DNA. This includes, in particular, genomically non-encoded nucleotides and chemical modifications. The latter leave their signatures in the form of mismatches and conspicuous patterns of sequencing reads. Modified mapping procedures focusing on particular types of deviations can help to unravel post-transcriptional modification, maturation and degradation processes. Here, we focus on small RNA sequencing data that is produced in large quantities aimed at the analysis of microRNA expression. Starting from the recovery of many well known modified sites in tRNAs, we provide evidence that modified nucleotides are a pervasive phenomenon in these data sets. Regarding non-encoded nucleotides we concentrate on CCA tails, which surprisingly can be found in a diverse collection of transcripts including sub-populations of mature microRNAs. Although small RNA sequencing libraries alone are insufficient to obtain a complete picture, they can inform on many aspects of the complex processes of RNA maturation.

scholarly journals Paired-end small RNA sequencing reveals a possible overestimation in the isomiR sequence repertoire previously reported from conventional single read data analysis

2021 ◽  
Author(s):  
Jose Francisco Sanchez-Herrero ◽  
Raquel Pluvinet ◽  
Antonio Luna-de Haro ◽  
Lauro Sumoy
Keyword(s):  
Data Analysis ◽  
Rna Sequencing ◽  
Small Rna ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Technical Noise ◽  
Sequencing Errors ◽  
Abundance And Diversity ◽  
Template Dna ◽  
Generation Sequencing

Abstract Background Next generation sequencing has allowed the discovery of miRNA isoforms, termed isomirs. Some isomirs are derived from imprecise processing of pre-miRNA precursors, leading to length variants. Additional variability is introduced by non-templated addition of bases at the ends or editing of internal bases, resulting in base differences relative to the template DNA sequence. We hypothesized that some component of the isomir variation reported so far could be due to systematic technical noise and not real. Results We have developed the XICRA pipeline to analyze small RNA sequencing data at the isomir level. We exploited its ability to use single or merged reads to compare isomir results derived from paired-end (PE) reads with those from single reads (SR) to address whether detectable sequence differences relative to canonical miRNAs found in isomirs are true biological variations or the result of errors in sequencing. We have detected non-negligible systematic differences between SR and PE data which primarily affect putative internally edited isomirs, and at a much smaller frequency terminal length changing isomirs. This is relevant for the identification of true isomirs in small RNA sequencing datasets. Conclusions We conclude that potential artifacts derived from sequencing errors and/or data processing could result in an overestimation of abundance and diversity of miRNA isoforms. Efforts in annotating the isomirnome should take this into account.

scholarly journals Long-term surveillance defines spatial and temporal patterns implicating Culex tarsalis as the primary vector of West Nile virus in Iowa, USA

2018 ◽  
Author(s):  
Brendan M. Dunphy ◽  
Kristofer B. Kovach ◽  
Ella J. Gehrke ◽  
Eleanor N. Field ◽  
Wayne A. Rowley ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Disease Transmission ◽  
Climatic Factors ◽  
Strong Support ◽  
The United States ◽  
Culex Tarsalis ◽  
Mosquito Vectors ◽  
Spatial And Temporal Patterns ◽  
West Nile

AbstractWest Nile virus (WNV) has become the most epidemiologically important mosquito-borne disease in the United States, causing ∼50,000 cases since its introduction in 1999. Transmitted primarily by Culex species, WNV transmission requires the complex interplay between bird reservoirs and mosquito vectors, with human cases the result of epizootic spillover. To better understand the intrinsic factors that drive these interactions, we have compiled infection data from sentinel chickens, mosquito vectors, and human cases in Iowa over a 15 year period (2002-2016) to better understand the spatial and temporal components that drive WNV transmission. Supplementing these findings with mosquito abundance, distribution, and host preferences data, we provide strong support that Culex tarsalis is the most important vector of human WNV infections in the region. Finally, we identify underlying climatic factors (temperature and drought) that are associated with inter-annual trends in WNV intensity. Together, our analysis provides new insights into WNV infection patterns in multiple hosts and highlights the importance of long-term surveillance to understand the dynamics of mosquito-borne-disease transmission.

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