Evidence map›Paper›PMID 18522722›Full record

ArticleBMC genomics2008

The RHNumtS compilation: features and bioinformatics approaches to locate and quantify Human NumtS.

Daniela Lascaro, Stefano Castellana, Giuseppe Gasparre, Giovanni Romeo, Cecilia Saccone, Marcella Attimonelli

Abstract readComparative StudyValidation Study
In one paragraph

Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Daniela LascaroDipartimento di Biochimica e Biologia Molecolare E, Quagliariello, Università di Bari, Via E, Orabona 4, 70126 Bari, Italy. daniela.lascaro@biologia.uniba.it
Stefano Castellana
Giuseppe Gasparre
Giovanni Romeo
Cecilia Saccone
Marcella Attimonelli

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo 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.

resultsLocation 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.

conclusionThe 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.

Indexed as

Genome, HumanCell NucleusChromosome MappingComputational BiologyDatabases, Nucleic AcidDNA, MitochondrialGenome, MitochondrialGenomicsHumansIsochoresPolymerase Chain ReactionReference ValuesSequence AlignmentSequence Analysis, DNADNA, MitochondrialIsochores

Identifiers

PMID18522722
PMCPMC2447851

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.