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Cited by 1,073

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Mitochondrial portraits of human populations using median networks.

Open access
Bandelt, H J, Forster, P, Sykes, B C, Richards, M B·1995·Genetics

Abstract

Analysis of variation in the hypervariable region of mitochondrial DNA (mtDNA) has emerged as an important tool for studying human evolution and migration. However, attempts to reconstruct optimal intraspecific mtDNA phylogenies frequently fail because parallel mutation events partly obscure the true evolutionary pathways. This makes it inadvisable to present a single phylogenetic tree at the expense of neglecting equally acceptable ones. As an alternative, we propose a novel network approach for portraying mtDNA relationships. For small sample sizes (< approximately 50), an unmodified median network contains all most parsimonious trees, displays graphically the full information content of the sequence data, and can easily be generated by hand. For larger sample sizes, we reduce the complexity of the network by identifying parallelisms. This reduction procedure is guided by a compatibility argument and an additional source of phylogenetic information: the frequencies of the mitochondrial haplotypes. As a spin-off, our approach can also assist in identifying sequencing errors, which manifest themselves in implausible network substructures. We illustrate the advantages of our approach with several examples from existing data sets.

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Metadata

Authors
Bandelt, H. J., Forster, P., Sykes, B. C., & Richards, M. B.
Venue
Genetics
Published
1995-10-01
Volume
141
Issue
2
Pages
743-753
ISSN
  • 0016-6731 (ISSN-L)
  • 1943-2631
OpenAlex
W1834060250
Cited by
1,073
References
1
FWCI
7.10
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Mitochondrial portraits of human populations using median networks. https://app.cochat.ai/papers/10.1093/genetics/141.2.743
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Bandelt, H. J., Forster, P., Sykes, B. C., & Richards, M. B. (1995). Mitochondrial portraits of human populations using median networks. Genetics. https://doi.org/10.1093/genetics/141.2.743

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