Direct full-length RNA sequencing reveals unexpected transcriptome complexity during Caenorhabditis elegans development

  1. Zhongying Zhao1,2
  1. 1Department of Biology, Hong Kong Baptist University, Hong Kong, 999077, China;
  2. 2State Key Laboratory of Environmental and Biological Analysis, Hong Kong Baptist University, Hong Kong, 999077, China
  1. 3 These authors contributed equally to this work.

  • Corresponding author: zyzhao{at}hkbu.edu.hk
  • Abstract

    Massively parallel sequencing of the polyadenylated RNAs has played a key role in delineating transcriptome complexity, including alternative use of an exon, promoter, 5′ or 3′ splice site or polyadenylation site, and RNA modification. However, reads derived from the current RNA-seq technologies are usually short and deprived of information on modification, compromising their potential in defining transcriptome complexity. Here, we applied a direct RNA sequencing method with ultralong reads using Oxford Nanopore Technologies to study the transcriptome complexity in Caenorhabditis elegans. We generated approximately six million reads using native poly(A)-tailed mRNAs from three developmental stages, with average read lengths ranging from 900 to 1100 nt. Around half of the reads represent full-length transcripts. To utilize the full-length transcripts in defining transcriptome complexity, we devised a method to classify the long reads as the same as existing transcripts or as a novel transcript using sequence mapping tracks rather than existing intron/exon structures, which allowed us to identify roughly 57,000 novel isoforms and recover at least 26,000 out of the 33,500 existing isoforms. The sets of genes with differential expression versus differential isoform usage over development are largely different, implying a fine-tuned regulation at isoform level. We also observed an unexpected increase in putative RNA modification in all bases in the coding region relative to the UTR, suggesting their possible roles in translation. The RNA reads and the method for read classification are expected to deliver new insights into RNA processing and modification and their underlying biology in the future.

    Footnotes

    • Received April 15, 2019.
    • Accepted December 18, 2019.

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