RESUMEN
Accurate quantification of gene and transcript-specific expression, with the underlying knowledge of precise transcript isoforms, is crucial to understanding many biological processes. Analysis of RNA sequencing data has benefited from the development of alignment-free algorithms which enhance the precision and speed of expression analysis. However, such algorithms require a reference transcriptome. Here we generate a reference transcript dataset (LsRTDv1) for lettuce (cv. Saladin), combining long- and short-read sequencing with publicly available transcriptome annotations, and filtering to keep only transcripts with high-confidence splice junctions and transcriptional start and end sites. LsRTDv1 identifies novel genes (mostly long non-coding RNAs) and increases the number of transcript isoforms per gene in the lettuce genome from 1.4 to 2.7. We show that LsRTDv1 significantly increases the mapping rate of RNA-seq data from a lettuce time-series experiment (mock- and Botrytis cinerea-inoculated) and enables detection of genes that are differentially alternatively spliced in response to infection as well as transcript-specific expression changes. LsRTDv1 is a valuable resource for investigation of transcriptional and alternative splicing regulation in lettuce.
