Multiple organism algorithm for finding ultraconserved elements
<p>Abstract</p> <p>Background</p> <p>Ultraconserved elements are nucleotide or protein sequences with 100% identity (no mismatches, insertions, or deletions) in the same organism or between two or more organisms. Studies indicate that these conserved regions are associa...
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| Format: | Article |
| Language: | English |
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BMC
2008-01-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/9/15 |
| _version_ | 1818497677835370496 |
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| author | Lobo Neil F Christley Scott Madey Greg |
| author_facet | Lobo Neil F Christley Scott Madey Greg |
| author_sort | Lobo Neil F |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>Ultraconserved elements are nucleotide or protein sequences with 100% identity (no mismatches, insertions, or deletions) in the same organism or between two or more organisms. Studies indicate that these conserved regions are associated with micro RNAs, mRNA processing, development and transcription regulation. The identification and characterization of these elements among genomes is necessary for the further understanding of their functionality.</p> <p>Results</p> <p>We describe an algorithm and provide freely available software which can find all of the ultraconserved sequences between genomes of multiple organisms. Our algorithm takes a combinatorial approach that finds all sequences without requiring the genomes to be aligned. The algorithm is significantly faster than BLAST and is designed to handle very large genomes efficiently. We ran our algorithm on several large comparative analyses to evaluate its effectiveness; one compared 17 vertebrate genomes where we find 123 ultraconserved elements longer than 40 bps shared by all of the organisms, and another compared the human body louse, <it>Pediculus humanus humanus</it>, against itself and select insects to find thousands of non-coding, potentially functional sequences.</p> <p>Conclusion</p> <p>Whole genome comparative analysis for multiple organisms is both feasible and desirable in our search for biological knowledge. We argue that bioinformatic programs should be forward thinking by assuming analysis on multiple (and possibly large) genomes in the design and implementation of algorithms. Our algorithm shows how a compromise design with a trade-off of disk space versus memory space allows for efficient computation while only requiring modest computer resources, and at the same time providing benefits not available with other software.</p> |
| first_indexed | 2024-12-10T18:48:14Z |
| format | Article |
| id | doaj.art-527c001669af45b5a0a819fe7796d4d6 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-10T18:48:14Z |
| publishDate | 2008-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-527c001669af45b5a0a819fe7796d4d62022-12-22T01:37:25ZengBMCBMC Bioinformatics1471-21052008-01-01911510.1186/1471-2105-9-15Multiple organism algorithm for finding ultraconserved elementsLobo Neil FChristley ScottMadey Greg<p>Abstract</p> <p>Background</p> <p>Ultraconserved elements are nucleotide or protein sequences with 100% identity (no mismatches, insertions, or deletions) in the same organism or between two or more organisms. Studies indicate that these conserved regions are associated with micro RNAs, mRNA processing, development and transcription regulation. The identification and characterization of these elements among genomes is necessary for the further understanding of their functionality.</p> <p>Results</p> <p>We describe an algorithm and provide freely available software which can find all of the ultraconserved sequences between genomes of multiple organisms. Our algorithm takes a combinatorial approach that finds all sequences without requiring the genomes to be aligned. The algorithm is significantly faster than BLAST and is designed to handle very large genomes efficiently. We ran our algorithm on several large comparative analyses to evaluate its effectiveness; one compared 17 vertebrate genomes where we find 123 ultraconserved elements longer than 40 bps shared by all of the organisms, and another compared the human body louse, <it>Pediculus humanus humanus</it>, against itself and select insects to find thousands of non-coding, potentially functional sequences.</p> <p>Conclusion</p> <p>Whole genome comparative analysis for multiple organisms is both feasible and desirable in our search for biological knowledge. We argue that bioinformatic programs should be forward thinking by assuming analysis on multiple (and possibly large) genomes in the design and implementation of algorithms. Our algorithm shows how a compromise design with a trade-off of disk space versus memory space allows for efficient computation while only requiring modest computer resources, and at the same time providing benefits not available with other software.</p>http://www.biomedcentral.com/1471-2105/9/15 |
| spellingShingle | Lobo Neil F Christley Scott Madey Greg Multiple organism algorithm for finding ultraconserved elements BMC Bioinformatics |
| title | Multiple organism algorithm for finding ultraconserved elements |
| title_full | Multiple organism algorithm for finding ultraconserved elements |
| title_fullStr | Multiple organism algorithm for finding ultraconserved elements |
| title_full_unstemmed | Multiple organism algorithm for finding ultraconserved elements |
| title_short | Multiple organism algorithm for finding ultraconserved elements |
| title_sort | multiple organism algorithm for finding ultraconserved elements |
| url | http://www.biomedcentral.com/1471-2105/9/15 |
| work_keys_str_mv | AT loboneilf multipleorganismalgorithmforfindingultraconservedelements AT christleyscott multipleorganismalgorithmforfindingultraconservedelements AT madeygreg multipleorganismalgorithmforfindingultraconservedelements |