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EASTR: Identifying and eliminating systematic alignment errors in multi-exon genes.

Ida Shinder1,2, Richard Hu3,4, Hyun Joo Ji3,4

  • 1Cross Disciplinary Graduate Program in Biomedical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA. ishinde1@jhmi.edu.

Nature Communications
|November 8, 2023
PubMed
Summary
This summary is machine-generated.

Widely used RNA sequencing tools can create false gene splice alignments. A new tool, EASTR (Emending Alignments of Spliced Transcript Reads), corrects these errors, improving gene expression analysis accuracy.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Accurate RNA-to-genome alignment is crucial for gene expression analysis in biomedical research.
  • Current splice-aware aligners like STAR and HISAT2 can produce erroneous spliced alignments, especially near repeated sequences.
  • These errors can lead to 'phantom' introns and falsely spliced transcripts, impacting downstream analyses and even genome annotations.

Purpose of the Study:

  • To address the issue of erroneous spliced alignments introduced by common RNA sequencing tools.
  • To present EASTR (Emending Alignments of Spliced Transcript Reads), a novel software tool for detecting and removing false splice alignments and transcripts.
  • To enhance the accuracy of RNA-seq data analysis and genome annotation.

Main Methods:

  • Development of EASTR, a software tool that identifies sequence similarity between intron-flanking regions to detect erroneous alignments.
  • Application of EASTR to alignment files generated by standard RNA sequencing workflows.
  • Utilizing EASTR on existing genome annotation databases to identify and correct mis-annotations.

Main Results:

  • EASTR effectively detects and removes falsely spliced alignments and transcripts caused by repeated sequences.
  • Application of EASTR improves the accuracy of spliced alignments across various species, including human, maize, and Arabidopsis thaliana.
  • Using EASTR before transcript assembly significantly reduces false positive introns, exons, and transcripts, leading to more accurate assembled transcripts.
  • EASTR successfully identified and corrected mis-annotated transcripts within reference genome annotation databases.

Conclusions:

  • EASTR is a valuable tool for improving the accuracy of RNA sequencing data analysis by correcting alignment errors.
  • The software enhances the reliability of gene expression studies and the quality of genome annotations.
  • EASTR's ability to detect sequence similarity provides a robust method for identifying artifactual splicing events.