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


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.

SUBMITTER: Zhang R 

PROVIDER: S-EPMC9264592 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

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

Zhang Runxuan R   Kuo Richard R   Coulter Max M   Calixto Cristiane P G CPG   Entizne Juan Carlos JC   Guo Wenbin W   Marquez Yamile Y   Milne Linda L   Riegler Stefan S   Matsui Akihiro A   Tanaka Maho M   Harvey Sarah S   Gao Yubang Y   Wießner-Kroh Theresa T   Paniagua Alejandro A   Crespi Martin M   Denby Katherine K   Hur Asa Ben AB   Huq Enamul E   Jantsch Michael M   Jarmolowski Artur A   Koester Tino T   Laubinger Sascha S   Li Qingshun Quinn QQ   Gu Lianfeng L   Seki Motoaki M   Staiger Dorothee D   Sunkar Ramanjulu R   Szweykowska-Kulinska Zofia Z   Tu Shih-Long SL   Wachter Andreas A   Waugh Robbie R   Xiong Liming L   Zhang Xiao-Ning XN   Conesa Ana A   Reddy Anireddy S N ASN   Barta Andrea A   Kalyna Maria M   Brown John W S JWS  

Genome biology 20220707 1


<h4>Background</h4>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.<h4>Results</h4>We p  ...[more]

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