XSAnno: a framework for building ortholog models in cross-species transcriptome comparisons

BMC Genomics. 2014 May 7;15(1):343. doi: 10.1186/1471-2164-15-343.

Abstract

Background: The accurate characterization of RNA transcripts and expression levels across species is critical for understanding transcriptome evolution. As available RNA-seq data accumulate rapidly, there is a great demand for tools that build gene annotations for cross-species RNA-seq analysis. However, prevailing methods of ortholog annotation for RNA-seq analysis between closely-related species do not take inter-species variation in mappability into consideration.

Results: Here we present XSAnno, a computational framework that integrates previous approaches with multiple filters to improve the accuracy of inter-species transcriptome comparisons. The implementation of this approach in comparing RNA-seq data of human, chimpanzee, and rhesus macaque brain transcriptomes has reduced the false discovery of differentially expressed genes, while maintaining a low false negative rate.

Conclusion: The present study demonstrates the utility of the XSAnno pipeline in building ortholog annotations and improving the accuracy of cross-species transcriptome comparisons.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Brain / metabolism
  • Gene Expression
  • Gene Expression Profiling / methods*
  • Gene Library
  • Genome
  • Genome, Human
  • Humans
  • Macaca mulatta / genetics
  • Models, Genetic*
  • Pan troglodytes / genetics
  • Prefrontal Cortex / metabolism
  • Sequence Alignment
  • Sequence Analysis, RNA
  • Species Specificity