Header Leaderboard Ad


ESPRESSO: Quantifying transcript isoforms from long-read sequencing



No announcement yet.
  • Filter
  • Time
  • Show
Clear All
new posts

  • ESPRESSO: Quantifying transcript isoforms from long-read sequencing

    Eukaryotic genes commonly generate multiple transcript isoforms which are important for understanding many biological processes and human diseases. Identification of isoforms has traditionally been completed using short-read technologies that limit read length and hinder isoform discovery.

    The increased utilization of long-read sequencing has allowed researchers to sequence thousands of bases in a single read and has improved the quantification and discovery of spice junctions. However, deficiencies with current computational tools motivated researchers from the Children’s Hospital of Philadelphia (CHOP) to develop their own tool, ESPRESSO (Error Statistics PRomoted Evaluator of Splice Site Options).

    This new tool uses long-read sequencing data and processes the resulting alignments to improve splice junction accuracy and isoform quantification. ESPRESSO was designed to compare the long reads for each gene to its corresponding genomic DNA. Then the error patterns of the reads are analyzed to locate splice junctions and complete isoforms.

    The CHOP researchers tested ESPRESSO using data generated from native DNA and RNA sequenced on Oxford Nanopore Technologies devices, along with simulated sequencing data. Over 1 billion long reads were analyzed, covering 30 human tissue types and three human cell lines.

    Using long reads to cross-reference transcripts to the genomic DNA allowed them to identify undocumented isoforms and splice junctions. In addition, ESPRESSO was able to accurately discover RNA isoforms and quantify them better than several other contemporary tools designed for transcript isoform analysis

    This computational tool has demonstrated that it can be a useful resource for investigating RNA from eukaryotic transcriptomes. Researchers from CHOP believe using ESPRESSO with long-read RNA sequencing will aid in our understanding of RNA variation and its role in genetic diseases.

    More information about ESPRESSO can be found on its corresponding GitHub page or by reading the published manuscript.

Latest Articles


  • seqadmin
    A Brief Overview and Common Challenges in Single-cell Sequencing Analysis
    by seqadmin

    ​​​​​​The introduction of single-cell sequencing has advanced the ability to study cell-to-cell heterogeneity. Its use has improved our understanding of somatic mutations1, cell lineages2, cellular diversity and regulation3, and development in multicellular organisms4. Single-cell sequencing encompasses hundreds of techniques with different approaches to studying the genomes, transcriptomes, epigenomes, and other omics of individual cells. The analysis of single-cell sequencing data i...

    01-24-2023, 01:19 PM
  • seqadmin
    Introduction to Single-Cell Sequencing
    by seqadmin
    Single-cell sequencing is a technique used to investigate the genome, transcriptome, epigenome, and other omics of individual cells using high-throughput sequencing. This technology has provided many scientific breakthroughs and continues to be applied across many fields, including microbiology, oncology, immunology, neurobiology, precision medicine, and stem cell research.

    The advancement of single-cell sequencing began in 2009 when Tang et al. investigated the single-cell transcriptomes
    01-09-2023, 03:10 PM