A universal genomic coordinate translator for comparative genomics

BMC Bioinformatics

Neda Zamani²  Görel Sundström²  Jennifer RS Meadows²  Marc P Höppner²  Jacques Dainat²  Henrik Lantz²  Brian J Haas¹  Manfred G Grabherr¹ 

[1] Broad Institute of MIT and Harvard, Cambridge, MA, USA

[2] Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden

关键词: Cross-species gene expression analysis;    Genomic duplication;    Genomic coordinate translation;    Comparative genomics;   

Others  :  818323
DOI  :  10.1186/1471-2105-15-227

 received in 2014-03-10, accepted in 2014-06-18,  发布年份 2014

【 摘 要 】

Background

Genomic duplications constitute major events in the evolution of species, allowing paralogous copies of genes to take on fine-tuned biological roles. Unambiguously identifying the orthology relationship between copies across multiple genomes can be resolved by synteny, i.e. the conserved order of genomic sequences. However, a comprehensive analysis of duplication events and their contributions to evolution would require all-to-all genome alignments, which increases at N² with the number of available genomes, N.

Results

Here, we introduce Kraken, software that omits the all-to-all requirement by recursively traversing a graph of pairwise alignments and dynamically re-computing orthology. Kraken scales linearly with the number of targeted genomes, N, which allows for including large numbers of genomes in analyses. We first evaluated the method on the set of 12 Drosophila genomes, finding that orthologous correspondence computed indirectly through a graph of multiple synteny maps comes at minimal cost in terms of sensitivity, but reduces overall computational runtime by an order of magnitude. We then used the method on three well-annotated mammalian genomes, human, mouse, and rat, and show that up to 93% of protein coding transcripts have unambiguous pairwise orthologous relationships across the genomes. On a nucleotide level, 70 to 83% of exons match exactly at both splice junctions, and up to 97% on at least one junction. We last applied Kraken to an RNA-sequencing dataset from multiple vertebrates and diverse tissues, where we confirmed that brain-specific gene family members, i.e. one-to-many or many-to-many homologs, are more highly correlated across species than single-copy (i.e. one-to-one homologous) genes. Not limited to protein coding genes, Kraken also identifies thousands of newly identified transcribed loci, likely non-coding RNAs that are consistently transcribed in human, chimpanzee and gorilla, and maintain significant correlation of expression levels across species.

Conclusions

Kraken is a computational genome coordinate translator that facilitates cross-species comparisons, distinguishes orthologs from paralogs, and does not require costly all-to-all whole genome mappings. Kraken is freely available under LPGL from http://github.com/nedaz/kraken webcite.

【 授权许可】

   
2014 Zamani et al.; licensee BioMed Central Ltd.

【 图 表 】

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