Linguistic Groups

2017 ◽  
Author(s):  
Manjil Hazarika
Keyword(s):  
Population Genetic ◽  
Northeast India ◽  
Detailed Account ◽  
Racial Composition ◽  
Genetic Studies ◽  
Close Proximity ◽  
Races Of Mankind ◽  
Linguistic Groups ◽  
Modern Population

An old-fashioned somatological analysis of the racial composition of the present-day populations of Northeast India suggested that this area was home to two major races of mankind, the Caucasoid and the Mongoloid, and modern population genetic studies now provide us with an even more fine-meshed and complex view of population prehistory. Close proximity of these populations in terms of settlements has led to exchange of genes between the two groups. This chapter provides a detailed account of the linguistic situation in Northeast India, which is relevant to our understanding of the prehistoric dispersals of linguistic groups. Various linguistic hypotheses and feasible archaeological links are discussed in this chapter. Probable routes of migration are also discussed on the basis of linguistic, ethnographical, historical, and folkloristic data.

scholarly journals Cultural factors that affected the spatial and temporal epidemiology of kuru

2017 ◽  
Vol 4 (1) ◽  
pp. 160789 ◽  
Author(s):  
J. T. Whitfield ◽  
W. H. Pako ◽  
J. Collinge ◽  
M. P. Alpers
Keyword(s):  
Papua New Guinea ◽  
Cultural Practices ◽  
Mortuary Practices ◽  
Cultural Group ◽  
Genetic Studies ◽  
Linguistic Group ◽  
Epidemiological Changes ◽  
Spatio Temporal ◽  
Linguistic Groups ◽  
Initial Pattern

Kuru is a prion disease which became epidemic among the Fore and surrounding linguistic groups in Papua New Guinea, peaking in the late 1950s. It was transmitted during the transumption (endocannibalism) of dead family members at mortuary feasts. In this study, we aimed to explain the historical spread and the changing epidemiological patterns of kuru by analysing factors that affected its transmission. We also examined what cultural group principally determined a family's behaviour during mortuary rituals. Our investigations showed that differences in mortuary practices were responsible for the initial pattern of the spread of kuru and the ultimate shape of the epidemic, and for subsequent spatio-temporal differences in the epidemiology of kuru. Before transumption stopped altogether, the South Fore continued to eat the bodies of those who had died of kuru, whereas other linguistic groups, sooner or later, stopped doing so. The linguistic group was the primary cultural group that determined behaviour but at linguistic boundaries the neighbouring group's cultural practices were often adopted. The epidemiological changes were not explained by genetic differences, but genetic studies led to an understanding of genetic susceptibility to kuru and the selection pressure imposed by kuru, and provided new insights into human history and evolution.

scholarly journals MIC16 gene represents a potential novel genetic marker for population genetic studies of Toxoplasma gondii

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Wen-Ge Liu ◽  
Xiao-Pei Xu ◽  
Jia Chen ◽  
Qian-Ming Xu ◽  
Si-Long Luo ◽  
...  
Keyword(s):  
Toxoplasma Gondii ◽  
Genetic Marker ◽  
Population Genetic ◽  
Genetic Studies

scholarly journals The first set of universal nuclear protein-coding loci markers for avian phylogenetic and population genetic studies

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Yang Liu ◽  
Simin Liu ◽  
Chia-Fen Yeh ◽  
Nan Zhang ◽  
Guoling Chen ◽  
...  
Keyword(s):  
Population Genetic ◽  
Nuclear Protein ◽  
Genetic Studies ◽  
Protein Coding

scholarly journals Population genetic studies on indigenous conifers in Korea

2006 ◽  
Vol 2 (2) ◽  
pp. 137-148
Author(s):  
S. W. Lee ◽  
Y. P. Hong ◽  
H. Y. Kwon ◽  
Z. S. Kim
Keyword(s):  
Population Genetic ◽  
Genetic Studies

scholarly journals Why most Principal Component Analyses (PCA) in population genetic studies are wrong

2021 ◽  
Author(s):  
Eran Elhaik
Keyword(s):  
Population Genetics ◽  
Population Genetic ◽  
Genetic Model ◽  
Principal Component ◽  
Population Data ◽  
Test Cases ◽  
Validity Of Results ◽  
Genetic Studies ◽  
Minimal Loss ◽  
Admixture Population

Principal Component Analysis (PCA) is a multivariate analysis that allows reduction of the complexity of datasets while preserving data's covariance and visualizing the information on colorful scatterplots, ideally with only a minimal loss of information. PCA applications are extensively used as the foremost analyses in population genetics and related fields (e.g., animal and plant or medical genetics), implemented in well-cited packages like EIGENSOFT and PLINK. PCA outcomes are used to shape study design, identify and characterize individuals and populations, and draw historical and ethnobiological conclusions on origins, evolution, whereabouts, and relatedness. The replicability crisis in science has prompted us to evaluate whether PCA results are reliable, robust, and replicable. We employed an intuitive color-based model alongside human population data for eleven common test cases. We demonstrate that PCA results are artifacts of the data and that they can be easily manipulated to generate desired outcomes. PCA results may not be reliable, robust, or replicable as the field assumes. Our findings raise concerns on the validity of results reported in the literature of population genetics and related fields that place a disproportionate reliance upon PCA outcomes and the insights derived from them. We conclude that PCA may have a biasing role in genetic investigations. An alternative mixed-admixture population genetic model is discussed.

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