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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
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RNA-seq03:21

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Related Experiment Video

Updated: Feb 19, 2026

Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes
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Viral Diagnostics in Plants Using Next Generation Sequencing: Computational Analysis in Practice.

Susan Jones1, Amanda Baizan-Edge2, Stuart MacFarlane3

  • 1Information and Computational Science Group, The James Hutton Institute, Dundee, United Kingdom.

Frontiers in Plant Science
|November 11, 2017
PubMed
Summary
This summary is machine-generated.

Next-generation sequencing (NGS) offers unbiased virus detection in crops, overcoming limitations of traditional methods. This review highlights RNA-sequencing and bioinformatics approaches for identifying known and unknown plant viruses, crucial for food security.

Keywords:
bioinformatics & computational biologycrop protectionfood securitynext generation sequencing (NGS)viral diagnostic

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Area of Science:

  • Plant Pathology
  • Virology
  • Bioinformatics
  • Genomics

Background:

  • Viral diseases cause substantial crop yield and quality losses, impacting global food security.
  • Current molecular diagnostic techniques like RT-PCR are specific to known viruses, potentially missing novel or multiple infections.
  • The need for rapid, accurate, and comprehensive viral detection in diverse plant materials is critical.

Purpose of the Study:

  • To review recent advancements in using RNA-sequencing (RNA-seq) for unbiased virus detection in crop plants.
  • To emphasize the computational methods and bioinformatics workflows essential for analyzing next-generation sequencing (NGS) data for viral identification.
  • To discuss challenges and future directions in applying RNA-seq for plant virus diagnostics.

Main Methods:

  • RNA-sequencing (RNA-seq) of plant material to capture all RNA transcripts, including viral sequences.
  • Development and application of bioinformatics pipelines for efficient host sequence removal and virus classification from NGS data.
  • Review of recent studies employing RNA-seq for detecting known and emergent viruses in various crop species.

Main Results:

  • RNA-seq enables hypothesis-free detection of multiple known and unknown viruses simultaneously in plant samples.
  • Specific bioinformatics workflows are crucial for processing large NGS datasets and accurately identifying viral agents.
  • The adoption of these advanced techniques is currently limited, necessitating further development and accessibility.

Conclusions:

  • RNA-seq, coupled with robust bioinformatics, represents a significant advance in plant virus diagnostics, essential for crop protection and food security.
  • Future directions include the integration of cloud computing for enhanced accessibility and deployment of bioinformatics tools in analytical environments.
  • Overcoming current limitations will facilitate wider adoption, improving our ability to manage viral threats in agriculture.