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Open Access Methodology article

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

Ying Zhu1, Mingfeng Li1, André MM Sousa12 and Nenad Šestan1*

Author Affiliations

1 Department of Neurobiology, Kavli Institute for Neuroscience, Yale School of Medicine, 06510 New Haven, CT, USA

2 Graduate Program in Areas of Basic and Applied Biology, Abel Salazar Biomedical Sciences Institute, University of Porto, 4099-003 Porto, Portugal

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BMC Genomics 2014, 15:343  doi:10.1186/1471-2164-15-343

Published: 7 May 2014



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.


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.


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

Comparative transcriptomics; Ortholog annotation; RNA-seq; Gene expression; Prefrontal cortex; Evolution; Human evolution; Primate; Macaque; Chimpanzee