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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...
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA (lncRNA)...
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA (lncRNA)...
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...
Ribosomal RNA Synthesis02:53

Ribosomal RNA Synthesis

Ribosome synthesis is a highly complex and coordinated process involving more than 200 assembly factors. The synthesis and processing of ribosomal components occurs not only in the nucleolus but also in the nucleoplasm and the cytoplasm of eukaryotic cells.
Ribosome biogenesis begins with the synthesis of 5S and 45S pre-rRNAs by distinct RNA polymerases. The primary transcripts are extensively processed and modified before they are bound and folded by ribosomal proteins and assembly factors,...
CRISPR and crRNAs02:53

CRISPR and crRNAs

Bacteria and archaea are susceptible to viral infections just like eukaryotes; therefore, they have developed a unique adaptive immune system to protect themselves. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) are present in more than 45% of known bacteria and 90% of known archaea.
The CRISPR-Cas system stores a copy of foreign DNA in the host genome and uses it to identify the foreign DNA upon reinfection. CRISPR-Cas has three different...

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Structure-based whole-genome realignment reveals many novel noncoding RNAs.

Sebastian Will1, Michael Yu, Bonnie Berger

  • 1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.

Genome Research
|January 9, 2013
PubMed
Summary

Researchers developed REAPR (RE-Alignment for Prediction of structural ncRNA), a new pipeline that efficiently realigns genomes using RNA structure. This method significantly increases the detection of structural noncoding RNAs (ncRNAs), finding twice as many candidates as previous tools.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide computational screens identify structural noncoding RNAs (ncRNAs) by analyzing conserved RNA secondary structures in whole-genome alignments (WGAs).
  • Existing methods using sequence-based WGAs have limited sensitivity because they often misalign structural ncRNAs, leading to undetected ncRNAs.
  • Structure-based alignment offers higher sensitivity but is computationally prohibitive for genome-wide screens.

Purpose of the Study:

  • To develop an efficient pipeline for structure-based whole-genome realignment to overcome the limitations of current ncRNA detection methods.
  • To enhance the performance of de novo ncRNA predictors by improving the accuracy of genome-wide alignments.
  • To increase the sensitivity and accuracy of identifying structural ncRNAs.

Main Methods:

  • Introduction of the REAPR (RE-Alignment for Prediction of structural ncRNA) pipeline, which realigns whole genomes based on both RNA sequence and structure.
  • Development of a novel banding technique for efficient multiple RNA alignment, crucial for the pipeline's computational feasibility.
  • Integration of REAPR with de novo ncRNA predictors like RNAz to boost their performance.

Main Results:

  • REAPR significantly outperforms existing genome-wide screen predictors such as RNAz and EvoFold in identifying structural ncRNAs.
  • In direct comparison to a recent RNAz screen on D. melanogaster, REAPR identified twice as many high-confidence ncRNA candidates.
  • Experimental validation using modENCODE RNA-seq data confirmed a substantial number of REAPR's predictions as actual transcripts.

Conclusions:

  • REAPR overcomes computational barriers, enabling efficient, structure-aware genome realignment for enhanced ncRNA discovery.
  • The pipeline substantially improves the detection of structural ncRNAs, complementing transcript identification from RNA-seq data.
  • REAPR represents a significant advancement in the de novo structural characterization and identification of ncRNAs.