A popular strategy for studying alternative splicing in non-model organisms starts from sequencing the entire transcriptome, then assembling the reads by using de novo transcriptome assembly algorithms to obtain predicted transcripts. A similarity search algorithm is then applied to a related organism to infer possible function of these predicted transcripts. Although some of these predictions may be inaccurate and transcripts with low coverage are often missed, the current project observed that it is possible to obtain a more complete set of transcripts to facilitate possible functional assignments by starting the search from the intermediate de Bruijn graph that contains all branching possibilities. The researchers show that their developed algorithm is able to recover more similar transcripts than existing algorithms, with large improvements in obtaining longer transcripts and a finer resolution of isoforms. The algorithm was used to study salt and waterlogging tolerance in two Melilotus species by constructing new RNA-Seq libraries. This strategy bypasses the transcript prediction step in RNA-Seq data and makes use of support from evolutionary information. (publisher abstract modified)
Identifying Similar Transcripts in a Related Organism From de Bruijn Graphs of RNA-Seq Data, With Applications to the Study of Salt and Waterlogging Tolerance in Melilotus
NCJ Number
254254
Journal
BMC Genomics Volume: 20 Dated: 2019
Date Published
2019
Length
9 pages
Annotation
This project developed an algorithm to extract similar transcripts in a related organism by starting the search from the de Bruijn graph that represents the transcriptome instead of from predicted transcripts.
Abstract
Date Published: January 1, 2019