Dataset Information

Orthology between genomes of Brachypodium, wheat and rice.

ABSTRACT:

Background

In the past, rice genome served as a good model for studies involving comparative genomics of grass species. More recently, however, Brachypodium distachyon genome has emerged as a better model system for genomes of temperate cereals including wheat. During the present study, Brachypodium EST contigs were utilized to resolve orthologous relationships among the genomes of Brachypodium, wheat and rice.

Findings

Comparative sequence analysis of 3,818 Brachypodium EST (bEST) contigs and 3,792 physically mapped wheat EST (wEST) contigs revealed that as many as 449 bEST contigs were orthologous to 1,154 wEST loci that were bin-mapped on all the 21 wheat chromosomes. Similarly 743 bEST contigs were orthologous to specific rice genome sequences distributed on all the 12 rice chromosomes. As many as 183 bEST contigs were orthologous to both wheat and rice genome sequences, which harbored as many as 17 SSRs conserved across the three species. Primers developed for 12 of these 17 conserved SSRs were used for a wet-lab experiment, which resolved relatively high level of conservation among the genomes of Brachypodium, wheat and rice.

Conclusion

The present study confirmed that Brachypodium is a better model than rice for analysis of the genomes of temperate cereals like wheat and barley. The whole genome sequence of Brachypodium, which should become available in the near future, will further facilitate greatly the studies involving comparative genomics of cereals.

SUBMITTER: Kumar S

PROVIDER: S-EPMC2695472 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

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Publications

Orthology between genomes of Brachypodium, wheat and rice.

Kumar Sachin S Mohan Amita A Balyan Harindra S HS Gupta Pushpendra K PK

BMC research notes 20090527

<h4>Background</h4>In the past, rice genome served as a good model for studies involving comparative genomics of grass species. More recently, however, Brachypodium distachyon genome has emerged as a better model system for genomes of temperate cereals including wheat. During the present study, Brachypodium EST contigs were utilized to resolve orthologous relationships among the genomes of Brachypodium, wheat and rice.<h4>Findings</h4>Comparative sequence analysis of 3,818 Brachypodium EST (bEST ...[more]

PMID: 19470185

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Project description:Orthology detection is critically important for accurate functional annotation, and has been widely used to facilitate studies on comparative and evolutionary genomics. Although various methods are now available, there has been no comprehensive analysis of performance, due to the lack of a genomic-scale 'gold standard' orthology dataset. Even in the absence of such datasets, the comparison of results from alternative methodologies contains useful information, as agreement enhances confidence and disagreement indicates possible errors. Latent Class Analysis (LCA) is a statistical technique that can exploit this information to reasonably infer sensitivities and specificities, and is applied here to evaluate the performance of various orthology detection methods on a eukaryotic dataset. Overall, we observe a trade-off between sensitivity and specificity in orthology detection, with BLAST-based methods characterized by high sensitivity, and tree-based methods by high specificity. Two algorithms exhibit the best overall balance, with both sensitivity and specificity>80%: INPARANOID identifies orthologs across two species while OrthoMCL clusters orthologs from multiple species. Among methods that permit clustering of ortholog groups spanning multiple genomes, the (automated) OrthoMCL algorithm exhibits better within-group consistency with respect to protein function and domain architecture than the (manually curated) KOG database, and the homolog clustering algorithm TribeMCL as well. By way of using LCA, we are also able to comprehensively assess similarities and statistical dependence between various strategies, and evaluate the effects of parameter settings on performance. In summary, we present a comprehensive evaluation of orthology detection on a divergent set of eukaryotic genomes, thus providing insights and guides for method selection, tuning and development for different applications. Many biological questions have been addressed by multiple tests yielding binary (yes/no) outcomes but no clear definition of truth, making LCA an attractive approach for computational biology.

Dataset Information

Orthology between genomes of Brachypodium, wheat and rice.

Background

Findings

Conclusion

Publications

Orthology between genomes of Brachypodium, wheat and rice.

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