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

BMC Genomics

Nenad Šestan¹  André MM Sousa²  Mingfeng Li¹  Ying Zhu¹ 

[1] Department of Neurobiology, Kavli Institute for Neuroscience, Yale School of Medicine, 06510 New Haven, CT, USA;Graduate Program in Areas of Basic and Applied Biology, Abel Salazar Biomedical Sciences Institute, University of Porto, 4099-003 Porto, Portugal

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

Others  :  1217255
DOI  :  10.1186/1471-2164-15-343

 received in 2014-01-17, accepted in 2014-04-24,  发布年份 2014

【 摘 要 】

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.

【 授权许可】

   
2014 Zhu et al.; licensee BioMed Central Ltd.

【 图 表 】

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