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Related Concept Videos

RNA-seq03:21

RNA-seq

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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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Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
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RNA Interference01:23

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RNA Structure01:23

RNA Structure

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Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
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RNA Stability01:53

RNA Stability

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Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
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RNA Splicing01:32

RNA Splicing

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Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...
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Updated: Feb 7, 2026

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing RIPiT-Seq
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Benchmarking RNA-seq Tools for Real-World Diagnostic Applications.

Sarah Silverstein1, Kaushik Ganapathy2, Sandra Donkervoort1

  • 1National Institutes of Health.

Research Square
|February 6, 2026
PubMed
Summary
This summary is machine-generated.

RNA-sequencing (RNA-seq) tools aid in diagnosing rare pediatric neuromuscular diseases by analyzing aberrant splicing and gene expression. While valuable, these computational tools complement, rather than replace, traditional DNA sequencing analysis for definitive diagnoses.

Keywords:
RNA-seqcomputational toolsdiagnosticspediatric neuromuscular diseaserare diseasetranscriptomicsvariant interpretation

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Area of Science:

  • Genomics
  • Computational Biology
  • Pediatric Neurology

Background:

  • Pediatric neuromuscular diseases exhibit significant genetic and clinical diversity.
  • Many cases remain undiagnosed despite advanced molecular testing.
  • RNA-sequencing (RNA-seq) offers potential to uncover functional impacts of genetic variants, but its systematic analysis is evolving.

Purpose of the Study:

  • To evaluate the performance of open-source computational tools for analyzing RNA-seq data in diagnosing pediatric neuromuscular diseases.
  • To establish best practices for utilizing RNA-seq analysis tools in a clinical diagnostic setting.
  • To identify novel diagnostic candidates in previously undiagnosed cases.

Main Methods:

  • Benchmarking of eight RNA-seq analysis tools (splicing, expression, allelic imbalance) using 97 diagnosed samples.
  • Development of a truth set to categorize pathogenic variants based on transcriptomic effects.
  • Application of optimized RNA-seq analysis strategies to 74 undiagnosed patient samples.

Main Results:

  • Computational tools identified 28 diagnoses in 68 previously diagnosed probands with aberrant RNA events.
  • Splicing analysis tools were most frequent contributors, while allelic imbalance tools provided unique diagnoses.
  • False positive rates varied, being highest for splicing and lowest for expression analysis tools.

Conclusions:

  • RNA-seq analysis tools can accelerate variant interpretation in genetic diagnostics for pediatric neuromuscular diseases.
  • These tools serve as a valuable complement to, not a replacement for, manual analysis of DNA sequencing data.
  • Further refinement of RNA-seq analysis strategies is needed to maximize diagnostic yield.