Best practices on the differential expression analysis of multi-species RNA-seq

Genome Biol. 2021 Apr 29;22(1):121. doi: 10.1186/s13059-021-02337-8.


Advances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

Keywords: Best practices; Differential gene expression; RNA-Seq; Transcriptomics.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Animals
  • Eukaryota / genetics
  • Gene Expression Profiling / methods*
  • Gene Expression Profiling / standards
  • Gene Expression Regulation
  • High-Throughput Nucleotide Sequencing*
  • Humans
  • Organ Specificity
  • Prokaryotic Cells / metabolism
  • RNA / genetics
  • RNA-Seq / methods*
  • RNA-Seq / standards
  • ROC Curve
  • Sequence Alignment
  • Sequence Analysis, RNA / methods
  • Single-Cell Analysis / methods
  • Transcriptome*
  • Workflow


  • RNA