scholarly journals Frontiers Approaches to the Diagnosis of Thrips (Thysanoptera): How Effective Are the Molecular and Electronic Detection Platforms?

Insects ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 920
Author(s):  
Amalendu Ghosh ◽  
Sumit Jangra ◽  
Ralf G. Dietzgen ◽  
Wen-Bin Yeh
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Insect Pests ◽  
Automated Identification ◽  
Thrips Species ◽  
Electronic Detection ◽  
Rflp Rapd ◽  
Site Identification ◽  
Electronic Sensors

Thrips are insect pests of economically important agricultural, horticultural, and forest crops. They cause damage by sucking plant sap and by transmitting several tospoviruses, ilarviruses, carmoviruses, sobemoviruses, and machlomoviruses. Accurate and timely identification is the key to successful management of thrips species. However, their small size, cryptic nature, presence of color and reproductive morphs, and intraspecies genetic variability make the identification of thrips species challenging. The use of molecular and electronic detection platforms has made thrips identification rapid, precise, sensitive, high throughput, and independent of developmental stages. Multi-locus phylogeny based on mitochondrial, nuclear, and other markers has resolved ambiguities in morphologically indistinguishable thrips species. Microsatellite, RFLP, RAPD, AFLP, and CAPS markers have helped to explain population structure, gene flow, and intraspecies heterogeneity. Recent techniques such as LAMP and RPA have been employed for sensitive and on-site identification of thrips. Artificial neural networks and high throughput diagnostics facilitate automated identification. This review also discusses the potential of pyrosequencing, microarrays, high throughput sequencing, and electronic sensors in delimiting thrips species.

scholarly journals High-Throughput Sequencing is a Crucial Tool to Investigate the Contribution of Human Endogenous Retroviruses (HERVs) to Human Biology and Development

Viruses ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 633 ◽  
Author(s):  
Maria Paola Pisano ◽  
Nicole Grandi ◽  
Enzo Tramontano
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Large Fraction ◽  
Expression Patterns ◽  
Cell Types ◽  
Endogenous Retroviruses ◽  
Human Endogenous Retroviruses ◽  
Retroviral Infections ◽  
The Impact

Human Endogenous retroviruses (HERVs) are remnants of ancient retroviral infections that represent a large fraction of our genome. Their transcriptional activity is finely regulated in early developmental stages and their expression is modulated in different cell types and tissues. Such activity has an impact on human physiology and pathology that is only partially understood up to date. Novel high-throughput sequencing tools have recently allowed for a great advancement in elucidating the various HERV expression patterns in different tissues as well as the mechanisms controlling their transcription, and overall, have helped in gaining better insights in an all-inclusive understanding of the impact of HERVs in biology of the host.

scholarly journals fluff: exploratory analysis and visualization of high-throughput sequencing data

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2209 ◽  
Author(s):  
Georgios Georgiou ◽  
Simon J. van Heeringen
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Command Line ◽  
Clustering Methods ◽  
Sequencing Data ◽  
Link Type ◽  
High Throughput Sequencing Data ◽  
Genome Wide ◽  
Genome Wide Data

Summary.In this article we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available athttp://fluff.readthedocs.org.Availability.fluff is implemented in Python and runs on Linux. The source code is freely available for download athttps://github.com/simonvh/fluff.

The great spruce bark beetle (Dendroctonus micans Kug.) (Coleoptera: Scolytidae) in Lithuania: occurrence, phenology, morphology and communities of associated fungi

2016 ◽  
Vol 107 (4) ◽  
pp. 431-438
Author(s):  
A. Menkis ◽  
J. Lynikienė ◽  
A. Marčiulynas ◽  
A. Gedminas ◽  
A. Povilaitienė
Keyword(s):  
Bark Beetle ◽  
High Throughput ◽  
Plant Pathogens ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Seed Orchard ◽  
Negative Effects ◽  
Dendroctonus Micans ◽  
Blue Stain Fungi ◽  
Blue Stain

AbstractWe studied the occurrence, morphology and phenology of Dendroctonus micans in Lithuania and the fungi associated with the beetle at different developmental stages. The occurrence of D. micans was assessed in 19 seed orchards (at least 40 years old) of Picea abies (L. Karst.) situated in different parts of the country. Bark beetle phenology was studied in two sites: a seed orchard of P. abies and a plantation of Picea pungens (Engelm.). D. micans morphology was assessed under the dissection microscope using individuals at different developmental stages that were sampled during phenology observations. Communities of fungi associated with D. micans were studied using both fungal culturing methods and direct high-throughput sequencing from D. micans. Results showed that the incidence D. micans was relatively rare and D. micans was mainly detected in central and eastern Lithuania. The life cycle included the following stages: adult, egg, I–V developmental stage larvae and pupa. However, development of D. micans was quicker and its nests larger under the bark of P. pungens than of P. abies, indicating the effect of the host species. Fungal culturing and direct high-throughput sequencing revealed that D. micans associated fungi communities were species rich and dominated by yeasts from a class Saccharomycetes. In total, 319 fungal taxa were sequenced, among which Peterozyma toletana (37.5% of all fungal sequences), Yamadazyma scolyti (30.0%) and Kuraishia capsulate (17.7%) were the most common. Plant pathogens and blue stain fungi were also detected suggesting their potentially negative effects to both tree health and timber quality.

scholarly journals fluff: exploratory analysis and visualization of high-throughput sequencing data

2016 ◽  
Author(s):  
Georgios Georgiou ◽  
Simon J. van Heeringen
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Command Line ◽  
Clustering Methods ◽  
Sequencing Data ◽  
Link Type ◽  
High Throughput Sequencing Data ◽  
Genome Wide ◽  
Genome Wide Data

AbstractSummaryIn this application note we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available at http://fluff.readthedocs.org.Availabilityfluff is implemented in Python and runs on Linux. The source code is freely available for download at http://github.com/simonvh/[email protected]

scholarly journals QsRNA-seq: a method for high-throughput profiling and quantifying small RNAs

2018 ◽  
Author(s):  
Alla Fishman ◽  
Dean Light ◽  
Ayelet T. Lamm
Keyword(s):  
High Throughput ◽  
Small Rnas ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Biological Research ◽  
C Elegans ◽  
Cellular Processes ◽  
Repetitive Nature ◽  
Developmental Role ◽  
Non Coding Rnas

The finding that small non-coding RNAs (sRNAs) can affect cellular processes by regulating gene expression had a significant impact on biological research and clinical diagnosis. Yet, the ability to quantify and profile sRNAs, specifically miRNAs, using high-throughput sequencing is especially challenging because of their small size and repetitive nature. We developed QsRNA-seq, a method for preparation of sRNA libraries for high-throughput sequencing that overcomes this difficulty by enabling separation of fragments shorter than 100nt long that differ only by 20nt in length. The method supports using unique molecular identifiers for quantification. We show that QsRNA-seq gives very accurate, comprehensive and reproducible results. Using QsRNA-seq to study the miRNA repertoire in C. elegans embryo and L4 larval developmental stages, enabled extending the list of miRNAs that are expressed in a developmental-specific manner. Interestingly, we found that miRNAs 23nt long are predominantly expressed in developmental stage L4, suggesting a possible connection between the length of miRNA and its developmental role.

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