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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...

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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Haplotype and isoform specific expression estimation using multi-mapping RNA-seq reads.

Ernest Turro1, Shu-Yi Su, Ângela Gonçalves

  • 1Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, W2 1PG, UK. ernest.turro@ic.ac.uk

Genome Biology
|February 12, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a new RNA-seq method to simultaneously measure gene isoform expression and allelic imbalance in diploid organisms. The approach models haplotype-specific isoforms, enabling accurate analysis even with unknown parental sequences.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Accurate estimation of isoform expression and allelic imbalance is crucial for understanding gene regulation and genetic variation.
  • Existing methods often struggle to simultaneously resolve these two complex aspects from RNA-seq data.

Purpose of the Study:

  • To develop a novel computational pipeline and statistical methodology for the simultaneous estimation of isoform expression and allelic imbalance.
  • To enable the reconstruction of parental isoform sequences when unknown.
  • To provide a robust software tool for analyzing RNA-seq data.

Main Methods:

  • Development of a novel pipeline integrating statistical modeling for RNA-seq data analysis.
  • Implementation of a statistical method, MMSEQ, to deconvolve read mapping to multiple transcripts, including haplotype-specific isoforms.
  • Modeling of haplotype-specific isoform expression.
  • Reconstruction of parental isoform sequences when they are not initially known.
  • Incorporation of non-uniform read generation and paired-end read support.

Main Results:

  • A new methodology and software pipeline for simultaneous estimation of isoform expression and allelic imbalance.
  • The ability to reconstruct parental isoform sequences.
  • The MMSEQ method effectively deconvolves read mapping in complex transcriptomic scenarios.
  • The software accommodates advanced sequencing features like non-uniform read generation and paired-end reads.

Conclusions:

  • The presented pipeline offers a significant advancement in analyzing complex transcriptomic data.
  • Simultaneous estimation of isoform expression and allelic imbalance is feasible and valuable.
  • The MMSEQ method provides a powerful tool for researchers studying gene expression and genetic variation in diploid organisms.