scholarly journals Full-length genome sequence of segmented RNA virus from ticks was obtained using small RNA sequencing data

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaofeng Xu ◽  
Jinlong Bei ◽  
Yibo Xuan ◽  
Jiayuan Chen ◽  
Defu Chen ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Genome Sequence ◽  
Small Rna ◽  
Rna Viruses ◽  
Rna Virus ◽  
Full Length ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Geographical Regions ◽  
Full Length Genome

Abstract Background In 2014, a novel tick-borne virus of the Flaviviridae family was first reported in the Mogiana region of Brazil and named the Mogiana tick virus (MGTV). Thereafter, the Jingmen tick virus (JMTV), Kindia tick virus (KITV), and Guangxi tick virus (GXTV)—evolutionarily related to MGTV—were reported. Results In the present study, we used small RNA sequencing (sRNA-seq) to detect viruses in ticks and discovered a new MGTV strain in Amblyomma testudinarium ticks collected in China’s Yunnan Province in 2016. We obtained the full-length genome sequence of this MGTV strain Yunnan2016 (GenBank: MT080097, MT080098, MT080099 and MT080100) and recommended it for its inclusion in the NCBI RefSeq database for future studies on MGTV, JMTV, KITV and GXTV. Phylogenetic analysis showed that MGTV, JMTV, KITV and GXTV are monophyletic and belong to a MGTV group. Furthermore, this MGTV group of viruses may be phylogenetically related to geographical regions that were formerly part of the supercontinents Gondwana and Laurasia. Conclusions To the best of our knowledge, this is the first study in which 5′ and 3′ sRNAs were used to generate full-length genome sequences of, but not limited to, RNA viruses. We also demonstrated the feasibility of using the sRNA-seq based method for the detection of viruses in pooled two and even possible one small ticks. MGTV may preserve the characteristic of ancient RNA viruses, which can be used to study the origin and evolution of RNA viruses. In addition, MGTV can be used as novel species for studies in phylogeography.

scholarly journals Full-length genome sequence of segmented RNA virus from ticks was obtained using small RNA sequencing data

2020 ◽  
Author(s):  
Xiaofeng Xu ◽  
Jinlong Bei ◽  
Yibo Xuan ◽  
Jianyuan Chen ◽  
Defu Chen ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Genome Sequence ◽  
Small Rna ◽  
Rna Virus ◽  
Phylogenetic Analyses ◽  
Full Length ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Link Type ◽  
Full Length Genome

AbstractIn 2014, A novel tick-borne virus of the genus Flavivirus was first reported from the Mogiana region in Brazil. This virus was named the Mogiana tick virus (MGTV). Later, MGTV was also named as Jingmen tick virus (JMTV), Kindia tick virus (KDTV), Guangxi tick virus (GXTV) etc. In the present study, we used small RNA sequencing (sRNA-seq) to detect viruses in ticks and detected MGTV in Amblyomma testudinarium ticks, which had been captured in Yunnan province of China in the year of 2016. The full-length genome sequence of a new MGTV strain Yunnan2016 (GenBank: MT080097, MT080098, MT080099 and MT080100) was obtained and recommended to be included into the NCBI RefSeq database for the future studies of MGTV. Our phylogenetic analyses showed that viruses named MGTV, JMTV, KDTV and GXTV are monophyletic: the MGTV group (lineage) of viruses. We show, for the first time, that 5′ and 3′ sRNAs can be used to obtain full-length sequences of the 5’ and 3’ ends of, but not limited to genome sequences of RNA viruses. And we proved the feasibility of using the sRNA-seq based method for the detection of viruses in a sample containing miniscule RNA.

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.

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