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Alternative RNA Splicing02:18

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Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
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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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Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
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LeafCutterMD: an algorithm for outlier splicing detection in rare diseases.

Garrett Jenkinson1,2, Yang I Li3,4, Shubham Basu1,2

  • 1Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55902, USA.

Bioinformatics (Oxford, England)
|April 22, 2020
PubMed
Summary
This summary is machine-generated.

LeafCutterMD enhances RNA sequencing analysis to identify aberrant splicing events in rare Mendelian diseases. This new method improves diagnostic power for identifying disease-causing genes when other sequencing methods fail.

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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Area of Science:

  • Genomics
  • Computational Biology
  • Rare Disease Diagnostics

Background:

  • Next-generation sequencing (NGS) improves rare Mendelian disease diagnosis but leaves many cases unsolved.
  • RNA sequencing (RNA-Seq) is increasingly used to identify disease-causing variants, particularly aberrant splicing events.
  • Statistical methods for detecting splicing outliers are currently limited.

Purpose of the Study:

  • To develop and validate LeafCutterMD, a novel statistical framework for detecting outlier splicing events.
  • To improve upon existing methods for identifying aberrant splicing in rare disease patients.
  • To enhance diagnostic yield for Mendelian diseases through advanced RNA-Seq analysis.

Main Methods:

  • LeafCutterMD was developed as an enhancement to the LeafCutter statistical framework.
  • The method's performance was evaluated using simulations and real patient data.
  • LeafCutterMD was applied to a cohort of disease-affected individuals.

Main Results:

  • LeafCutterMD demonstrated superior power in detecting outlier splicing events compared to state-of-the-art methods.
  • The framework effectively controlled false-positive rates.
  • LeafCutterMD successfully identified all previously manually curated aberrantly spliced genes in a patient cohort.

Conclusions:

  • LeafCutterMD is a powerful statistical tool for identifying aberrant splicing in rare Mendelian diseases.
  • The method significantly improves the diagnostic potential of RNA sequencing for unsolved cases.
  • LeafCutterMD offers a robust approach to discovering novel disease-associated genes through splicing analysis.