A Reduced Number of mtSNPs Saturates Mitochondrial DNA Haplotype Diversity of Worldwide Population Groups
A Reduced Number of mtSNPs Saturates Mitochondrial DNA Haplotype Diversity of Worldwide Population Groups
The high levels of variation characterising the mitochondrial DNA (mtDNA) molecule are due ultimately to its high average mutation rate; moreover, mtDNA variation is deeply structured in different populations and ethnic groups. There is growing interest in selecting a reduced number of mtDNA single nucleotide polymorphisms (mtSNPs) that account for the maximum level of discrimination power in a given population. Applications of the selected mtSNP panel range from anthropologic and medical studies to forensic genetic casework.This study proposes a new simulation-based method that explores the ability of different mtSNP panels to yield the maximum levels of discrimination power. The method explores subsets of mtSNPs of different sizes randomly chosen from a preselected panel of mtSNPs based on frequency. More than 2,000 complete genomes representing three main continental human population groups (Africa, Europe, and Asia) and two admixed populations ("African-Americans" and "Hispanics") were collected from GenBank and the literature, and were used as training sets. Haplotype diversity was measured for each combination of mtSNP and compared with existing mtSNP panels available in the literature. The data indicates that only a reduced number of mtSNPs ranging from six to 22 are needed to account for 95% of the maximum haplotype diversity of a given population sample. However, only a small proportion of the best mtSNPs are shared between populations, indicating that there is not a perfect set of "universal" mtSNPs suitable for all population contexts. The discrimination power provided by these mtSNPs is much higher than the power of the mtSNP panels proposed in the literature to date. Some mtSNP combinations also yield high diversity values in admixed populations.The proposed computational approach for exploring combinations of mtSNPs that optimise the discrimination power of a given set of mtSNPs is more efficient than previous empirical approaches. In contrast to precedent findings, the results seem to indicate that only few mtSNPs are needed to reach high levels of discrimination power in a population, independently of its ancestral background.
Internationality, Science, Q, R, Computational Biology, Genetic Variation, DNA, Mitochondrial, Polymorphism, Single Nucleotide, Evolution, Molecular, Genetics, Population, Haplotypes, Population Groups, Medicine, Humans, Computer Simulation, Research Article
Internationality, Science, Q, R, Computational Biology, Genetic Variation, DNA, Mitochondrial, Polymorphism, Single Nucleotide, Evolution, Molecular, Genetics, Population, Haplotypes, Population Groups, Medicine, Humans, Computer Simulation, Research Article
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