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Long-read transcriptome data for improved gene prediction in Lentinula edodes.

Sin-Gi Park1, Seung Il Yoo1, Dong Sung Ryu1

  • 1Theragen Etex Bio Institute, Suwon 16229, Republic of Korea.

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|May 31, 2018
PubMed
Summary
This summary is machine-generated.

This study enhances gene prediction accuracy for the popular edible mushroom Lentinula edodes using long-read sequencing. It identified 16,610 protein-coding genes, improving genomic resources for mushroom research.

Keywords:
GFF, general feature formatGene modelGene predictionLentinula edodesPacBio Single-molecule real-time (SMRT) transcriptome sequencingRNA-Seq, whole transcriptome sequencing

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Area of Science:

  • Mycology
  • Genomics
  • Molecular Biology

Background:

  • Lentinula edodes (shiitake mushroom) is globally significant for food and medicine, containing compounds like lentinan.
  • Previous whole-genome sequencing aimed to identify agronomic trait genes but lacked experimental gene model verification.
  • Gene prediction accuracy is crucial for understanding mushroom genetics and improving cultivation.

Purpose of the Study:

  • To improve the accuracy of gene prediction in Lentinula edodes.
  • To generate a more reliable set of protein-coding genes for L. edodes.
  • To provide a foundation for discovering genes related to important mushroom traits.

Main Methods:

  • Generated 12.6 Gb of long-read transcriptome data using PacBio single-molecule real-time (SMRT) sequencing.
  • Performed evidence-driven gene prediction integrating long- and short-read RNA sequencing data.
  • Generated 36,946 transcript clusters with an average length of 2.2 kb.

Main Results:

  • Predicted 16,610 protein-coding genes with error correction, significantly improving accuracy.
  • Verified that 42.2% of predicted genes were covered by full-length transcript clusters.
  • Established a more accurate gene set for L. edodes.

Conclusions:

  • The enhanced gene prediction provides a more reliable genomic resource for Lentinula edodes.
  • This improved gene set facilitates future research into mushroom agronomic and medicinal traits.
  • The study highlights the value of long-read sequencing for accurate fungal genome annotation.