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Entizne, J. C.

Publications and source records attributed to Entizne, J. C..

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Rapid and dynamic alternative splicing impacts the Arabidopsis cold response transcriptome

BackgroundPlants have adapted to tolerate and survive constantly changing environmental conditions by re-programming gene expression. The scale of the contribution of alternative splicing (AS) to stress responses has been underestimated due to limitations in RNA-seq analysis programs and poor representation of AS transcripts in plant databases. Significantly, the dynamics of the AS response have not been investigated but this is now possible with accurate transcript quantification programs and AtRTD2, a new, comprehensive transcriptome for Arabidopsis.\n\nResultsUsing ultra-deep RNA-sequencing of a time-course of Arabidopsis thaliana plants exposed to cold treatment, we identified 8,949 genes with altered expression of which 2,442 showed significant differential alternative splicing (DAS) and 1,647 genes were regulated only at the level of AS (DAS-only). The high temporal resolution demonstrated the rapid induction of both transcription and AS resulting in coincident waves of differential expression (transcription) and differential alternative splicing in the first 6-9 hours of cold. The differentially expressed and DAS gene sets were largely non-overlapping, each comprising thousands of genes. The dynamic analysis of AS identified genes with rapid and sensitive AS within 3 h of transfer to the cold (early AS genes), which were enriched for splicing and transcription factors. A detailed investigation of the novel cold-response DAS-only gene, U2B\"-LIKE, suggested that it regulates AS and is required for tolerance to freezing.\n\nConclusionsOur data indicate that transcription and AS are the major regulators of transcriptome reprogramming that together govern the physiological and survival responses of plants to low temperature.

genomics

Fast and accurate differential splicing analysis across multiple conditions with replicates

Multiple approaches have been proposed to study differential splicing from RNA sequencing (RNA-seq) data1, including the analysis of transcript isoforms2,3, clusters of splice-junctions4,5, alternative splicing events6-8 and exonic regions9. However, many challenges remain unsolved, including the limitation in speed, the computing capacity and storage requirements, the constraints in the number of reads needed to achieve sufficient accuracy, and the lack of robust methods to account for variability between replicates and for analyses across multiple conditions. We present here a significant extension of SUPPA8 to enable streamlined analysis of differential splicing across multiple conditions, taking into account biological variability. We show that SUPPA differential splicing analysis achieves high accuracy using extensive experimental and simulated data compared to other methods; and shows higher accuracy at low sequencing depth, with short read lengths, and using replicas with unbalanced depth, which has important implications for the cost-effective use of RNA-seq data for splicing analysis. We also validate the analysis of multiple conditions with SUPPA by studying differential splicing during iPS-cell to neuron differentiation and during erythroblast differentiation, providing support for the applicability of SUPPA for the robust analysis of differential splicing beyond binary comparisons.

bioinformatics