Single, Rapid Coastal Settlement of Asia Revealed by Analysis of Complete Mitochondrial Genomes

Macaulay, Vincent; Hill, Catherine; Achilli, Alessandro; Rengo, Chiara; Clarke, D.W.; Meehan, William J.; Blackburn, James E.; Semino, Ornella; Scozzari, Rosaria; Cruciani, Fulvio; Taha, Adi; Shaari, Norazila Kassim; Raja, Joseph Maripa; Ismail, Patimah; Zafarina, Zainuddin; Goodwin, William; Bulbeck, David; Bandelt, Hans Jürgen; Oppenheimer, Stephen; Torroni, Antonio; Richards, Martin B.

doi:10.1126/science.1109792

Cited by 674 publications

(591 citation statements)

References 29 publications

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“…1,18 Mutations are recorded by comparing with the revised Cambridge reference sequence (rCRS). 19 All the individuals were allocated into specific haplogroup based on their control-region information; the assignments were further confirmed by typing additional diagnostic coding-region mutations according to the reconstructed phylogenetic trees of East Asian, 1,20-25 South Asian 5,7,12,[26][27][28][29][30][31][32][33] and Southeast Asian [34][35][36][37][38] (Supplementary Table S1, Supplementary Material online). For the mtDNA sample of interest, entire genome was amplified and sequenced as described elsewhere.…”

Section: Dna Amplification Sequencing and Quality Controlmentioning

confidence: 99%

Revisiting the role of the Himalayas in peopling Nepal: insights from mitochondrial genomes

Wang

Sun

et al. 2012

J Hum Genet

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Himalayas was believed to be a formidably geographical barrier between South and East Asia. The observed high frequency of the East Eurasian paternal lineages in Nepal led some researchers to suggest that these lineages were introduced into Nepal from Tibet directly; however, it is also possible that the East Eurasian genetic components might trace their origins to northeast India where abundant East Eurasian maternal lineages have been detected. To trace the origin of the Nepalese maternal genetic components, especially those of East Eurasian ancestry, and then to better understand the role of the Himalayas in peopling Nepal, we have studied the matenal genetic composition extensively, especially the East Eurasian lineages, in Nepalese and its surrounding populations. Our results revealed the closer affinity between the Nepalese and the Tibetans, specifically, the Nepalese lineages of the East Eurasian ancestry generally are phylogenetically closer with the ones from Tibet, albeit a few mitochondrial DNA haplotypes, likely resulted from recent gene flow, were shared between the Nepalese and northeast Indians. It seems that Tibet was most likely to be the homeland for most of the East Eurasian in the Nepalese. Taking into account the previous observation on Y chromosome, now it is convincing that bearer of the East Eurasian genetic components had entered Nepal across the Himalayas around 6 kilo years ago (kya), a scenario in good agreement with the previous results from linguistics and archeology.

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Section: Dna Amplification Sequencing and Quality Controlmentioning

confidence: 99%

Revisiting the role of the Himalayas in peopling Nepal: insights from mitochondrial genomes

Wang

Sun

et al. 2012

J Hum Genet

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“…Ces analyses suggèrent qu'une population ancestrale située en Afrique de l'Est est plus vraisemblable qu'une origine Sud Africaine ou asiatique. L'âge de l'expansion a été estimé à environ 58 000 ans, une date en concordance parfaite avec les datations les plus récentes pour l'expansion de l'homme [1,2,5] …”

Section: L'exemple D'helicobacter Pyloriunclassified

“…Si de nombreux détails restent à clarifier, seule une minorité de chercheurs dans le domaine met en doute une origine africaine récente (~200 000 ans). Il y a 60 000 ans environ, une expansion démographique a entraîné une sortie hors de l'Afrique et la colonisation de tous les continents Ce scénario est fondé sur l'analyse de marqueurs géné-tiques haploïdes (ADN mitochondrial et chromosome Y) [1,2], de marqueurs autosomiques [3][4][5] ainsi que de données morphologiques [6] et archéolo-giques [7].…”

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Helicobacter pylori, notre fidèle compagnon gastrique

Balloux

2007

Med Sci (Paris)

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“…1,2 The availability of genome-wide data by technologies ranging from genotyping to next-generation sequencing provides the unprecedented opportunity to study the demographic changes and migration patterns of modern humans shaped by the environment and subsequent evolutionary process of genetic drift and natural selection. 3,4 Valuable new insights have been derived from large complete genome sequencing surveys of populations in Africa, 5,6 Asia, 7,8 Europe, 9 and the Americas. 10 Many of the existing population genetics inference and methodologies have been built on the foundation of the coalescent theory, [11][12][13] although these can be generally classified according to the type of genetic data used as input and the assumptions about population demography (Table 1).…”

Section: Introductionmentioning

confidence: 99%

Estimating time to the most recent common ancestor (TMRCA): comparison and application of eight methods

Zhou

Teo

2015

Eur J Hum Genet

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Investigating how an ancestral population diverges to give rise to distinct subpopulations remains a fundamental pursuit in population genetics. There is broad consensus for the 'Out-of-Africa' hypothesis that states that modern humans arose ∼ 200 000 years ago in Africa and spread throughout the continent ∼ 100 000 years ago. This was followed by several waves of major population dispersals across the globe, although the exact nature of the population divergence remains debatable. Existing methods to estimate population divergence time differ in their methodological frameworks and demographic assumptions, and require different types of genetic data as input. These fundamental differences often result in the methods producing inconsistent estimates of the population divergence time, further confounding attempts to robustly uncover the history of human migration, especially when most population genetic studies do not employ multiple methods to estimate the time to the most recent common ancestor (TMRCA). Here, we chose eight popular methods for estimating TMRCA and evaluated their robustness and accuracy in correctly identifying the true TMRCA through a series of simulations that mimicked different evolutionary scenarios. We subsequently applied all eight methods to estimate the population divergence time between Southeast Asian Malays and South Asian Indians using deep whole-genome sequencing data.

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Single, Rapid Coastal Settlement of Asia Revealed by Analysis of Complete Mitochondrial Genomes

Cited by 674 publications

References 29 publications

Revisiting the role of the Himalayas in peopling Nepal: insights from mitochondrial genomes

Revisiting the role of the Himalayas in peopling Nepal: insights from mitochondrial genomes

Helicobacter pylori, notre fidèle compagnon gastrique

Estimating time to the most recent common ancestor (TMRCA): comparison and application of eight methods

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