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Identification of high confidence human poly(A) RNA isoform scaffolds using nanopore sequencing.

Logan MulroneyMadalee G WulfIra SchildkrautGeorge TzertzinisJohn BuswellMiten JainHugh E OlsenMark E DiekhansIvan R CorrêaMark AkesonLaurence M Ettwiller
Published in: RNA (New York, N.Y.) (2021)
Nanopore sequencing devices read individual RNA strands directly. This facilitates identification of exon linkages and nucleotide modifications; however, using conventional methods the 5' and 3' ends of poly(A) RNA cannot be identified unambiguously. This is due in part to the architecture of the nanopore/enzyme-motor complex, and in part to RNA degradation in vivo and in vitro that can obscure transcription start and end sites. In this study, we aimed to identify individual full-length human RNA isoform scaffolds among ~4 million nanopore poly(A)-selected RNA reads. First, to identify RNA strands bearing 5' m7G caps, we exchanged the biological cap for a modified cap attached to a 45-nucleotide oligomer. This oligomer adaptation method improved 5' end sequencing and ensured correct identification of the 5' m7G capped ends. Second, among these 5'-capped nanopore reads, we screened for ionic current signatures consistent with a 3' polyadenylation site. Combining these two steps, we identified 294,107 individual high-confidence full-length RNA scaffolds, most of which (257,721) aligned to protein-coding genes. Of these, 4,876 scaffolds indicated unannotated isoforms that were often internal to longer, previously identified RNA isoforms. Orthogonal data confirmed the validity of these high-confidence RNA scaffolds.
Keyphrases
  • single molecule
  • nucleic acid
  • tissue engineering
  • small molecule
  • solid state
  • artificial intelligence
  • binding protein
  • big data