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Towards an improved apple reference transcriptome using RNA-seq.

Yang Bai1, Laura Dougherty, Kenong Xu

  • 1Department of Horticulture, Cornell University, New York State Agricultural Experiment Station, Geneva, NY, 14456, USA.

Molecular Genetics and Genomics : MGG
|February 18, 2014
PubMed
Summary
This summary is machine-generated.

Researchers improved the apple reference transcriptome for better RNA sequencing analysis. This enhanced transcriptome significantly increases read mapping efficiency, advancing apple transcriptomic studies.

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Area of Science:

  • Plant genomics
  • Transcriptomics
  • Bioinformatics

Background:

  • The apple (Malus × domestica) reference genome, established in 2010, has limitations for RNA sequencing (RNA-seq) analysis.
  • Low coverage of the reference transcriptome hinders accurate read mapping in transcriptomic studies.

Purpose of the Study:

  • To enhance the apple reference transcriptome for improved RNA-seq analysis.
  • To increase the accuracy and efficiency of transcriptomic studies in apple.

Main Methods:

  • Generated 168.5 million strand-specific RNA-seq reads from Golden Delicious apple fruit across various developmental stages.
  • Employed a hybrid approach combining genome-guided and de novo assembly strategies.
  • Integrated original and newly identified transcripts to create an improved reference transcriptome.

Main Results:

  • Developed an improved apple reference transcriptome comprising 71,178 genes/transcripts, including 17,524 novel transcripts.
  • Achieved a significant increase in RNA-seq read mapping rates, from 37.4–46.6% with the original transcriptome to 62.5–82.3% with the improved version.
  • The novel transcripts were derived from both direct mapping and de novo assembly of unmapped reads.

Conclusions:

  • The enhanced apple reference transcriptome substantially improves RNA-seq data analysis.
  • This advancement represents a significant step towards a comprehensive apple reference transcriptome.
  • Facilitates more robust and complete transcriptomic profiling in apple research.