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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...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Related Experiment Video

Updated: Jun 11, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

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Function annotation of the rice transcriptome at single-nucleotide resolution by RNA-seq.

Tingting Lu1, Guojun Lu, Danlin Fan

  • 1National Center for Gene Research & Institute of Plant Physiology and Ecology, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Shanghai 200233, China.

Genome Research
|July 15, 2010
PubMed
Summary

RNA sequencing (RNA-seq) reveals extensive novel transcripts and alternative splicing in rice subspecies. This study provides a high-resolution view of the rice transcriptional landscape, uncovering new gene models and expression patterns.

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iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution
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iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution

Published on: April 30, 2011

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Last Updated: Jun 11, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

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Published on: November 7, 2025

iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution
10:45

iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution

Published on: April 30, 2011

Area of Science:

  • Genomics
  • Transcriptomics
  • Plant Biology

Background:

  • The rice transcriptome's functional complexity remains incompletely understood.
  • Previous studies relied on DNA microarrays, limiting comprehensive analysis.
  • Next-generation sequencing, specifically RNA sequencing (RNA-seq), offers advanced capabilities for transcriptome mapping and quantification.

Purpose of the Study:

  • To globally sample and analyze the transcripts of cultivated rice (Oryza sativa) subspecies (indica and japonica) using RNA-seq.
  • To resolve whole-genome transcription profiles and identify novel transcriptional active regions (nTARs).
  • To compare transcriptomes between the two rice subspecies for a comprehensive understanding of the transcriptional landscape.

Main Methods:

  • Application of RNA sequencing (RNA-seq) to globally sample rice transcripts.
  • Identification and characterization of novel transcriptional active regions (nTARs).
  • Validation and extension of existing rice gene models based on RNA-seq data.

Main Results:

  • Identification of 15,708 novel transcriptional active regions (nTARs), with over 51% lacking homology to public protein data.
  • Discovery that approximately 48% of rice genes exhibit alternative splicing, a higher percentage than previously estimated.
  • Validation of 83.1% of current rice gene models and identification of 6228 extended gene models.
  • Detection of differential expression patterns in 3464 genes between rice subspecies.
  • Analysis of single nucleotide polymorphisms (SNPs) revealing a nonsynonymous/synonymous mutation ratio of approximately 1:1.06.

Conclusions:

  • RNA-seq provides a high-resolution view of the rice transcriptional landscape, revealing significant complexity.
  • A substantial number of novel transcripts and extensive alternative splicing were identified, expanding the known rice transcriptome.
  • Comparative analysis between indica and japonica subspecies highlights differences in gene expression and potential evolutionary insights.