Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes.
Comparative genomics of multiple related species is a powerful methodology for the discovery of functional genomic elements, and its power should increase with the number of species compared. Here, we use 12 Drosophila genomes to study the power of comparative genomics metrics to distinguish between...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2008-04-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC2291194?pdf=render |
| _version_ | 1811223113189294080 |
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| author | Michael F Lin Ameya N Deoras Matthew D Rasmussen Manolis Kellis |
| author_facet | Michael F Lin Ameya N Deoras Matthew D Rasmussen Manolis Kellis |
| author_sort | Michael F Lin |
| collection | DOAJ |
| description | Comparative genomics of multiple related species is a powerful methodology for the discovery of functional genomic elements, and its power should increase with the number of species compared. Here, we use 12 Drosophila genomes to study the power of comparative genomics metrics to distinguish between protein-coding and non-coding regions. First, we study the relative power of different comparative metrics and their relationship to single-species metrics. We find that even relatively simple multi-species metrics robustly outperform advanced single-species metrics, especially for shorter exons (< or =240 nt), which are common in animal genomes. Moreover, the two capture largely independent features of protein-coding genes, with different sensitivity/specificity trade-offs, such that their combinations lead to even greater discriminatory power. In addition, we study how discovery power scales with the number and phylogenetic distance of the genomes compared. We find that species at a broad range of distances are comparably effective informants for pairwise comparative gene identification, but that these are surpassed by multi-species comparisons at similar evolutionary divergence. In particular, while pairwise discovery power plateaued at larger distances and never outperformed the most advanced single-species metrics, multi-species comparisons continued to benefit even from the most distant species with no apparent saturation. Last, we find that genes in functional categories typically considered fast-evolving can nonetheless be recovered at very high rates using comparative methods. Our results have implications for comparative genomics analyses in any species, including the human. |
| first_indexed | 2024-04-12T08:27:31Z |
| format | Article |
| id | doaj.art-7488ca7e74644f31871ab1e92bc3c4d0 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-04-12T08:27:31Z |
| publishDate | 2008-04-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-7488ca7e74644f31871ab1e92bc3c4d02022-12-22T03:40:19ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582008-04-0144e100006710.1371/journal.pcbi.1000067Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes.Michael F LinAmeya N DeorasMatthew D RasmussenManolis KellisComparative genomics of multiple related species is a powerful methodology for the discovery of functional genomic elements, and its power should increase with the number of species compared. Here, we use 12 Drosophila genomes to study the power of comparative genomics metrics to distinguish between protein-coding and non-coding regions. First, we study the relative power of different comparative metrics and their relationship to single-species metrics. We find that even relatively simple multi-species metrics robustly outperform advanced single-species metrics, especially for shorter exons (< or =240 nt), which are common in animal genomes. Moreover, the two capture largely independent features of protein-coding genes, with different sensitivity/specificity trade-offs, such that their combinations lead to even greater discriminatory power. In addition, we study how discovery power scales with the number and phylogenetic distance of the genomes compared. We find that species at a broad range of distances are comparably effective informants for pairwise comparative gene identification, but that these are surpassed by multi-species comparisons at similar evolutionary divergence. In particular, while pairwise discovery power plateaued at larger distances and never outperformed the most advanced single-species metrics, multi-species comparisons continued to benefit even from the most distant species with no apparent saturation. Last, we find that genes in functional categories typically considered fast-evolving can nonetheless be recovered at very high rates using comparative methods. Our results have implications for comparative genomics analyses in any species, including the human.http://europepmc.org/articles/PMC2291194?pdf=render |
| spellingShingle | Michael F Lin Ameya N Deoras Matthew D Rasmussen Manolis Kellis Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes. PLoS Computational Biology |
| title | Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes. |
| title_full | Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes. |
| title_fullStr | Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes. |
| title_full_unstemmed | Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes. |
| title_short | Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes. |
| title_sort | performance and scalability of discriminative metrics for comparative gene identification in 12 drosophila genomes |
| url | http://europepmc.org/articles/PMC2291194?pdf=render |
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