Genetic, geographic, and linguistic variation among south american indians: Possible sex influence

American Journal of Physical Anthropology

Volumn 117, Issue 1, 2002, Pages 68-78

  Fagundes, Nelson J R ^a   Bonatto, S L ^b   Callegari Jacques, S M ^a   Salzano, F M ^a  

^a FEDERAL UNIVERSITY OF RIO GRANDE DO SUL   (Brazil)

^b PONTIFICAL CATHOLIC UNIVERSITY OF RIO GRANDE DO SUL   (Brazil)

Author keywords

FST analyses; MtDNA; Protein polymorphisms; Spatial autocorrelation

Indexed keywords

IMMUNOGLOBULIN; MITOCHONDRIAL DNA;

ARTICLE; BLOOD GROUP; CORRELATION FUNCTION; GENETIC ANALYSIS; GENETIC POLYMORPHISM; GEOGRAPHIC DISTRIBUTION; HUMAN; INDIA; LANGUAGE; MIGRATION; MOLECULAR EVOLUTION; SEX DIFFERENCE; SOUTH AMERICA; STATISTICAL ANALYSIS;

DNA, MITOCHONDRIAL; EVOLUTION; FEMALE; GEOGRAPHY; HUMANS; INDIANS, NORTH AMERICAN; LINGUISTICS; MALE; SEX FACTORS; SOUTH AMERICA; VARIATION (GENETICS);

EID: 0036136640     PISSN: 00029483     EISSN: None     Source Type: Journal    
DOI: 10.1002/ajpa.10015     Document Type: Article

References (46)

1. Genetic population structure in Japan. I: Geographic patterns of gene frequencies
2. Reasons for failure of genetic classifications of South Amerind populations
3. Failure of linguistic relationships to predict genetic distances between the Walǎpi and other tribes of lower Amazonia
4. Genetic variation within two linguistic Amerindian groups-relationship to geography and population size
5. Gm haplotype distribution in Amerindians: Relationship with geography and language
6. Clinal variation in the nuclear DNA of Europeans
7. The effects of spatial autocorrelation in geographical modeling
8. Genetic structure of the indigenous populations of Siberia
9. Population substructure and isolation by distance in three continental regions
10. Spatial differentiation of Rh and Gm haplotype frequencies in Sub-Saharan Africa and its relation to linguistic affinities
11. Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitochondrial DNA data
12. Genetic relationships between Amerindian populations of Argentina
13. Genetic composition of Chilean aboriginal populations: HLA and other genetic marker variation
14. Genetic structure of Quechua-speakers of the central Andes and geographical patterns of gene frequencies in South Amerindian populations
15. Genes, tribes and African history
16. The detection of disease clustering and a generalized regression approach
17. Autosomal, mtDNA and Y-chromosome diversity in Amerinds: Pre-and post-Columbian patterns of gene flow in South America
18. Evolutionary relationships of human populations on a global scale
19. Assessing the significance of a spatial correlogram
20. Patterns and correlates of genetic variation in South Amerindians
21. Patterns of genetic variation in native America
22. A problem with synthetic maps: Reply to Sokal et al
23. Y-chromosomal diversity in Europe is clinal and influenced primarily by geography, rather than by language
24. Gradients of HLA diversity in South American Indians
25. Human polymorphic genes
26. Intraand intertribal genetic variation within a linguistic group: The Ge-speaking Indians of Brazil
27. Genetic variation within a linguistic group: Apalai-Wayana and other Carib tribes
28. Protein genetic studies among the Tupi-Mondé Indians of the Brazilian Amazonia
29. Amerindian mitochondrial DNAs have rare Asian mutations at high frequencies, suggesting they derived from four primary maternal lineages
30. Genetic evidence for a higher female migration rate in humans
31. Guidelines for human gene nomenclature: An international system for human gene nomenclature
32. Multiple regression and correlation extensions of the Mantel test of matrix correspondence
33. Ecological parameters inferred from spatial correlograms
34. Spatial autocorrelation analysis in biology I. Methodology
35. Spatial genetic structure of human populations in Japan
36. A test of spatial autocorrelation analysis using an isolation by distance model
37. Spatial autocorrelation analysis of migration and selection
38. A problem with synthetic maps