scholarly journals Y Chromosome Sequences Reveal a Short Beringian Standstill, Rapid Expansion, and early Population structure of Native American Founders

2019 ◽  
Vol 29 (1) ◽  
pp. 149-157.e3 ◽  
Author(s):  
Thomaz Pinotti ◽  
Anders Bergström ◽  
Maria Geppert ◽  
Matt Bawn ◽  
Dominique Ohasi ◽  
...  
2002 ◽  
Vol 66 (4) ◽  
pp. 255-259 ◽  
Author(s):  
M.-C. BORTOLINI ◽  
F. M. SALZANO ◽  
C. H. D. BAU ◽  
Z. LAYRISSE ◽  
M. L. PETZL-ERLER ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rossana Santiago de Sousa Azulay ◽  
Luís Cristóvão Porto ◽  
Dayse Aparecida Silva ◽  
Maria da Glória Tavares ◽  
Roberta Maria Duailibe Ferreira Reis ◽  
...  

AbstractThis study aimed to investigate the relationship between genetic ancestry inferred from autosomal and Y chromosome markers and HLA genotypes in patients with Type 1 Diabetes from an admixed Brazilian population. Inference of autosomal ancestry; HLA-DRB1, -DQA1 and -DQB1 typifications; and Y chromosome analysis were performed. European autosomal ancestry was about 50%, followed by approximately 25% of African and Native American. The European Y chromosome was predominant. The HLA-DRB1*03 and DRB1*04 alleles presented risk association with T1D. When the Y chromosome was European, DRB1*03 and DRB1*04 homozygote and DRB1*03/DRB1*04 heterozygote genotypes were the most frequent. The results suggest that individuals from Maranhão have a European origin as their major component; and are patrilineal with greater frequency from the R1b haplogroup. The predominance of the HLA-DRB1*03 and DRB1*04 alleles conferring greater risk in our population and being more frequently related to the ancestry of the European Y chromosome suggests that in our population, the risk of T1D can be transmitted by European ancestors of our process miscegenation. However, the Y sample sizes of Africans and Native Americans were small, and further research should be conducted with large mixed sample sizes to clarify this possible association.


2018 ◽  
Vol 33 (2) ◽  
pp. 91-96
Author(s):  
Y. Y. Ashirbekov ◽  
A. V. Khrunin ◽  
D. M. Botbayev ◽  
A. M. Belkozhaev ◽  
A. O. Abaildayev ◽  
...  

2005 ◽  
Vol 128 (3) ◽  
pp. 670-677 ◽  
Author(s):  
Cheryl A. Wise ◽  
Sheena G. Sullivan ◽  
Michael L. Black ◽  
Wendy N. Erber ◽  
Alan H. Bittles

2010 ◽  
Vol 55 (9) ◽  
pp. 613-620 ◽  
Author(s):  
Efe Sezgin ◽  
Alyssa Drosdak ◽  
Carl McIntosh ◽  
Bailey Kessing ◽  
James A Lautenberger ◽  
...  

2017 ◽  
Vol 14 (128) ◽  
pp. 20170057 ◽  
Author(s):  
Luciana W. Zuccherato ◽  
Silvana Schneider ◽  
Eduardo Tarazona-Santos ◽  
Robert J. Hardwick ◽  
Douglas E. Berg ◽  
...  

While multiallelic copy number variation (mCNV) loci are a major component of genomic variation, quantifying the individual copy number of a locus and defining genotypes is challenging. Few methods exist to study how mCNV genetic diversity is apportioned within and between populations (i.e. to define the population genetic structure of mCNV). These inferences are critical in populations with a small effective size, such as Amerindians, that may not fit the Hardy–Weinberg model due to inbreeding, assortative mating, population subdivision, natural selection or a combination of these evolutionary factors. We propose a likelihood-based method that simultaneously infers mCNV allele frequencies and the population structure parameter f , which quantifies the departure of homozygosity from the Hardy–Weinberg expectation. This method is implemented in the freely available software CNVice, which also infers individual genotypes using information from both the population and from trios, if available. We studied the population genetics of five immune-related mCNV loci associated with complex diseases (beta-defensins, CCL3L1/CCL4L1 , FCGR3A , FCGR3B and FCGR2C ) in 12 traditional Native American populations and found that the population structure parameters inferred for these mCNVs are comparable to but lower than those for single nucleotide polymorphisms studied in the same populations.


2020 ◽  
Vol 69 (5) ◽  
pp. 884-896 ◽  
Author(s):  
Erik M Volz ◽  
Wiuf Carsten ◽  
Yonatan H Grad ◽  
Simon D W Frost ◽  
Ann M Dennis ◽  
...  

Abstract Population structure influences genealogical patterns, however, data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealized genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with the appearance and expansion of mutations conferring antimicrobial resistance. [Antimicrobial resistance; coalescent; HIV; population structure.]


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