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The RHNumtS compilation: Features and bioinformatics approaches to locate and quantify Human NumtS
BACKGROUND: To a greater or lesser extent, eukaryotic nuclear genomes contain fragments of their mitochondrial genome counterpart, deriving from the random insertion of damaged mtDNA fragments. NumtS (Nuclear mt Sequences) are not equally abundant in all species, and are redundant and polymorphic in...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447851/ https://www.ncbi.nlm.nih.gov/pubmed/18522722 http://dx.doi.org/10.1186/1471-2164-9-267 |
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author | Lascaro, Daniela Castellana, Stefano Gasparre, Giuseppe Romeo, Giovanni Saccone, Cecilia Attimonelli, Marcella |
author_facet | Lascaro, Daniela Castellana, Stefano Gasparre, Giuseppe Romeo, Giovanni Saccone, Cecilia Attimonelli, Marcella |
author_sort | Lascaro, Daniela |
collection | PubMed |
description | BACKGROUND: To a greater or lesser extent, eukaryotic nuclear genomes contain fragments of their mitochondrial genome counterpart, deriving from the random insertion of damaged mtDNA fragments. NumtS (Nuclear mt Sequences) are not equally abundant in all species, and are redundant and polymorphic in terms of copy number. In population and clinical genetics, it is important to have a complete overview of NumtS quantity and location. Searching PubMed for NumtS or Mitochondrial pseudo-genes yields hundreds of papers reporting Human NumtS compilations produced by in silico or wet-lab approaches. A comparison of published compilations clearly shows significant discrepancies among data, due both to unwise application of Bioinformatics methods and to a not yet correctly assembled nuclear genome. To optimize quantification and location of NumtS, we produced a consensus compilation of Human NumtS by applying various bioinformatics approaches. RESULTS: Location and quantification of NumtS may be achieved by applying database similarity searching methods: we have applied various methods such as Blastn, MegaBlast and BLAT, changing both parameters and database; the results were compared, further analysed and checked against the already published compilations, thus producing the Reference Human Numt Sequences (RHNumtS) compilation. The resulting NumtS total 190. CONCLUSION: The RHNumtS compilation represents a highly reliable reference basis, which may allow designing a lab protocol to test the actual existence of each NumtS. Here we report preliminary results based on PCR amplification and sequencing on 41 NumtS selected from RHNumtS among those with lower score. In parallel, we are currently designing the RHNumtS database structure for implementation in the HmtDB resource. In the future, the same database will host NumtS compilations from other organisms, but these will be generated only when the nuclear genome of a specific organism has reached a high-quality level of assembly. |
format | Text |
id | pubmed-2447851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-24478512008-07-10 The RHNumtS compilation: Features and bioinformatics approaches to locate and quantify Human NumtS Lascaro, Daniela Castellana, Stefano Gasparre, Giuseppe Romeo, Giovanni Saccone, Cecilia Attimonelli, Marcella BMC Genomics Research Article BACKGROUND: To a greater or lesser extent, eukaryotic nuclear genomes contain fragments of their mitochondrial genome counterpart, deriving from the random insertion of damaged mtDNA fragments. NumtS (Nuclear mt Sequences) are not equally abundant in all species, and are redundant and polymorphic in terms of copy number. In population and clinical genetics, it is important to have a complete overview of NumtS quantity and location. Searching PubMed for NumtS or Mitochondrial pseudo-genes yields hundreds of papers reporting Human NumtS compilations produced by in silico or wet-lab approaches. A comparison of published compilations clearly shows significant discrepancies among data, due both to unwise application of Bioinformatics methods and to a not yet correctly assembled nuclear genome. To optimize quantification and location of NumtS, we produced a consensus compilation of Human NumtS by applying various bioinformatics approaches. RESULTS: Location and quantification of NumtS may be achieved by applying database similarity searching methods: we have applied various methods such as Blastn, MegaBlast and BLAT, changing both parameters and database; the results were compared, further analysed and checked against the already published compilations, thus producing the Reference Human Numt Sequences (RHNumtS) compilation. The resulting NumtS total 190. CONCLUSION: The RHNumtS compilation represents a highly reliable reference basis, which may allow designing a lab protocol to test the actual existence of each NumtS. Here we report preliminary results based on PCR amplification and sequencing on 41 NumtS selected from RHNumtS among those with lower score. In parallel, we are currently designing the RHNumtS database structure for implementation in the HmtDB resource. In the future, the same database will host NumtS compilations from other organisms, but these will be generated only when the nuclear genome of a specific organism has reached a high-quality level of assembly. BioMed Central 2008-06-03 /pmc/articles/PMC2447851/ /pubmed/18522722 http://dx.doi.org/10.1186/1471-2164-9-267 Text en Copyright © 2008 Lascaro et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Lascaro, Daniela Castellana, Stefano Gasparre, Giuseppe Romeo, Giovanni Saccone, Cecilia Attimonelli, Marcella The RHNumtS compilation: Features and bioinformatics approaches to locate and quantify Human NumtS |
title | The RHNumtS compilation: Features and bioinformatics approaches to locate and quantify Human NumtS |
title_full | The RHNumtS compilation: Features and bioinformatics approaches to locate and quantify Human NumtS |
title_fullStr | The RHNumtS compilation: Features and bioinformatics approaches to locate and quantify Human NumtS |
title_full_unstemmed | The RHNumtS compilation: Features and bioinformatics approaches to locate and quantify Human NumtS |
title_short | The RHNumtS compilation: Features and bioinformatics approaches to locate and quantify Human NumtS |
title_sort | rhnumts compilation: features and bioinformatics approaches to locate and quantify human numts |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447851/ https://www.ncbi.nlm.nih.gov/pubmed/18522722 http://dx.doi.org/10.1186/1471-2164-9-267 |
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