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Related Concept Videos

RNA-seq03:21

RNA-seq

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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Next-generation Sequencing03:00

Next-generation Sequencing

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
Although all next-generation methods use different technologies, they all share a set of standard features.
Transgenic Plants02:50

Transgenic Plants

Recombinant DNA technology called transgenesis is often used to add a foreign gene or remove a detrimental gene from an organism. Such genetically modified organisms are called transgenic organisms.
The first-ever transgenic plant was a tobacco plant developed in 1983 that showed resistance against the tobacco mosaic virus. Since then, many transgenic plants have been developed and commercialized for improving the agricultural, ornamental, and horticultural value of a crop plant. Transgenic...

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Related Experiment Video

Updated: May 23, 2026

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
07:18

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Published on: May 21, 2020

Exploring the switchgrass transcriptome using second-generation sequencing technology.

Yixing Wang1, Xin Zeng, Niranjani J Iyer

  • 1Department of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, Oklahoma, United States of America.

Plos One
|April 6, 2012
PubMed
Summary
This summary is machine-generated.

This study used next-generation sequencing to analyze switchgrass (Panicum virgatum L.) gene space, generating extensive expressed sequence tag (EST) data. This research significantly enhances genomic resources for this important bioenergy crop.

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Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
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Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
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Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

Area of Science:

  • Plant Genomics
  • Bioenergy Crops
  • Transcriptomics

Background:

  • Switchgrass (Panicum virgatum L.) is a key C4 perennial bioenergy grass.
  • Developing high-yielding cultivars requires robust genomic resources.
  • Large genome size and polyploidy complicate whole-genome sequencing.

Purpose of the Study:

  • To explore the transcriptional landscape of switchgrass as an alternative to whole-genome sequencing.
  • To generate and analyze expressed sequence tag (EST) data for switchgrass.
  • To expand genomic resources for switchgrass breeding and research.

Main Methods:

  • Sequencing of switchgrass cDNA libraries from four distinct tissues using Roche 454 GS-FLX Titanium technology.
  • De novo assembly of expressed sequence tags (ESTs).
  • Comparative analysis with other monocot genomes (foxtail millet, Brachypodium, sorghum, rice, maize) and in silico identification of EST-Simple Sequence Repeats (SSRs).

Main Results:

  • Generated nearly one million reads, assembled into over 240,000 contigs.
  • Utilized foxtail millet as a reference to improve assembly and annotation.
  • Identified unique transcriptional signatures across tissues and discovered over 24,000 ESTs in dormant seeds, with over 2000 potential EST-SSRs.

Conclusions:

  • Estimated coverage of approximately 90% of the switchgrass gene space.
  • Nearly doubled the available EST information for switchgrass in public databases.
  • Demonstrated the efficiency of second-generation sequencing for complex genomes and the utility of related species like Setaria viridis as proxies.