SNF1-RELATED KINASE 1 and TARGET OF RAPAMYCIN control light-responsive splicing events and developmental characteristics in etiolated Arabidopsis seedlings.

The kinases SNF1-RELATED KINASE 1 (SnRK1) and TARGET OF RAPAMYCIN (TOR) are central sensors of the energy status, linking this information via diverse regulatory mechanisms to plant development and stress responses. Despite the well-studied functions of SnRK1 and TOR under conditions of limited or ample energy availability, respectively, little is known about the extent to which the 2 sensor systems function and how they are integrated in the same molecular process or physiological context. Here, we demonstrate that both SnRK1 and TOR are required for proper skotomorphogenesis in etiolated Arabidopsis (Arabidopsis thaliana) seedlings, light-induced cotyledon opening, and regular development in light. Furthermore, we identify SnRK1 and TOR as signaling components acting upstream of light- and sugar-regulated alternative splicing events, expanding the known action spectra for these 2 key players in energy signaling. Our findings imply that concurring SnRK1 and TOR activities are required throughout various phases of plant development. Based on the current knowledge and our findings, we hypothesize that turning points in the activities of these sensor kinases, as expected to occur upon illumination of etiolated seedlings, instead of signaling thresholds reflecting the nutritional status may modulate developmental programs in response to altered energy availability.

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

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.