Performance of gene expression analyses using de novo assembled transcripts in polyploid species

Ling Yun Chen, Diego F. Morales-Briones, Courtney N. Passow, Ya Yang, Bonnie Berger

Research output: Contribution to journalArticlepeer-review

Abstract

Motivation: Quality of gene expression analyses using de novo assembled transcripts in species that experienced recent polyploidization remains unexplored. Results: Differential gene expression (DGE) analyses using putative genes inferred by Trinity, Corset and Grouper performed slightly differently across five plant species that experienced various polyploidy histories. In species that lack recent polyploidy events that occurred in the past several millions of years, DGE analyses using de novo assembled transcriptomes identified 54-82% of the differentially expressed genes recovered by mapping reads to the reference genes. However, in species that experienced more recent polyploidy events, the percentage decreased to 21-65%. Gene co-expression network analyses using de novo assemblies versus mapping to the reference genes recovered the same module that significantly correlated with treatment in one species that lacks recent polyploidization. Availability and implementation: Commands and scripts used in this study are available at https://bitbucket.org/lychen83/chen-et-al-2018-benchmark-dge/; Analysis files are available at Dryad doi: 10.5061/dryad.4p6n481. Supplementary information: Supplementary data are available at Bioinformatics online.

Original languageEnglish (US)
Pages (from-to)4314-4320
Number of pages7
JournalBioinformatics
Volume35
Issue number21
DOIs
StatePublished - Nov 1 2019

Bibliographical note

Funding Information:
This work was supported by the University of Minnesota, Twin Cities.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

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