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Linking crop traits to transcriptome differences in a progeny population of tetraploid potato.

Erik AlexanderssonSandeep KushwahaAastha SubediDeborah WeighillSharlee ClimerDaniel JacobsonErik Andreasson
Published in: BMC plant biology (2020)
In our study, we identify 100's of transcripts, putatively linked based on expression with 17 traits of potato, representing both well-known and novel associations. This approach can be used to link the transcriptome to traits. We explore the possibility of associating the level of transcript expression from controlled, optimal environments to traits in a progeny population with different methods introducing the application of DUO for the first time on transcriptome data. We verify the expression pattern for five of the putative transcript markers in another progeny population.
Keyphrases
  • genome wide
  • rna seq
  • poor prognosis
  • single cell
  • gene expression
  • dna methylation
  • binding protein
  • machine learning
  • electronic health record
  • artificial intelligence