A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

Runxuan Zhang*, Richard Kuo, Max Coulter, Cristiane P. G. Calixto, Juan Carlos Entizne, Wenbin Guo, Yamile Marquez, Linda Milne, Stefan Riegler, Akihiro Matsui, Maho Tanaka, Sarah Harvey, Yubang Gao, Theresa Wießner-Kroh, Alejandro Paniagua, Martin Crespi, Katherine Denby, Asa ben Hur, Enamul Huq, Michael JantschArtur Jarmolowski, Tino Koester, Sascha Laubinger, Qingshun Quinn Li, Lianfeng Gu, Motoaki Seki, Dorothee Staiger, Ramanjulu Sunkar, Zofia Szweykowska-Kulinska, Shih Long Tu, Andreas Wachter, Robbie Waugh, Liming Xiong, Xiao Ning Zhang, Ana Conesa, Anireddy S. N. Reddy, Andrea Barta, Maria Kalyna, John W. S. Brown

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

39 Citations (Scopus)

Abstract

Background: Accurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis.

Results: We present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 169,000 transcripts—twice that of the best current Arabidopsis transcriptome and including over 1500 novel genes. Seventy-eight percent of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We develop novel methods to determine splice junctions and transcription start and end sites accurately. Mismatch profiles around splice junctions provide a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identify high-confidence transcription start and end sites and remove fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provides higher resolution of transcript expression profiling and identifies cold-induced differential transcription start and polyadenylation site usage.

Conclusions: AtRTD3 is the most comprehensive Arabidopsis transcriptome currently. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage analysis from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single-molecule sequencing analysis from any species.

Original languageEnglish
Article number149
JournalGenome Biology
Volume23
Early online date7 Jul 2022
DOIs
Publication statusPublished - Dec 2022

Scopus Subject Areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

User-Defined Keywords

  • Alternative polyadenylation
  • Alternative splicing
  • Arabidopsis
  • Iso-seq
  • Reference transcript dataset
  • Splice junction
  • Transcription start and end sites

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