From regionally predictable to locally complex population structure in a freshwater top predator: river systems are not always the unit of connectivity in Northern PikeEsox lucius

2014 ◽  
Vol 24 (2) ◽  
pp. 305-316 ◽  
Author(s):  
Dorte Bekkevold ◽  
Lene Jacobsen ◽  
Jakob Hemmer-Hansen ◽  
Søren Berg ◽  
Christian Skov
Keyword(s):  
Population Structure ◽  
Top Predator ◽  
River Systems ◽  
Complex Population

Genetic population structure of a highly migratory Hilsa Shad, Tenualosa ilisha, in three river systems, inferred from four mitochondrial genes analysis

2019 ◽  
Vol 102 (7) ◽  
pp. 939-954 ◽  
Author(s):  
Vindhya Mohindra ◽  
B. K. Divya ◽  
Rajesh Kumar ◽  
Rajeev K. Singh ◽  
Arvind Kumar Dwivedi ◽  
...  
Keyword(s):  
Population Structure ◽  
Mitochondrial Genes ◽  
Genetic Population Structure ◽  
River Systems ◽  
Genetic Population ◽  
Tenualosa Ilisha

scholarly journals Complex population structure in African village dogs and its implications for inferring dog domestication history

2009 ◽  
Vol 106 (33) ◽  
pp. 13903-13908 ◽  
Author(s):  
A. R. Boyko ◽  
R. H. Boyko ◽  
C. M. Boyko ◽  
H. G. Parker ◽  
M. Castelhano ◽  
...  
Keyword(s):  
Population Structure ◽  
Complex Population ◽  
Dog Domestication

scholarly journals Scaling probabilistic models of genetic variation to millions of humans

2014 ◽  
Author(s):  
Prem Gopalan ◽  
Wei Hao ◽  
David M. Blei ◽  
John D. Storey
Keyword(s):  
Population Genetics ◽  
Population Structure ◽  
Genetic Variation ◽  
Probabilistic Models ◽  
Simulated Data ◽  
Genomic Data ◽  
Human Populations ◽  
Data Sets ◽  
Complex Population ◽  
Simulated Data Sets

One of the major goals of population genetics is to quantitatively understand variation of genetic polymorphisms among individuals. To this end, researchers have developed sophisticated statistical methods to capture the complex population structure that underlies observed genotypes in humans, and such methods have been effective for analyzing modestly sized genomic data sets. However, the number of genotyped humans has grown significantly in recent years, and it is accelerating. In aggregate about 1M individuals have been genotyped to date. Analyzing these data will bring us closer to a nearly complete picture of human genetic variation; but existing methods for population genetics analysis do not scale to data of this size. To solve this problem we developed TeraStructure. TeraStructure is a new algorithm to fit Bayesian models of genetic variation in human populations on tera-sample-sized data sets (1012observed genotypes, e.g., 1M individuals at 1M SNPs). It is a principled approach to Bayesian inference that iterates between subsampling locations of the genome and updating an estimate of the latent population structure of the individuals. On data sets of up to 2K individuals, TeraStructure matches the existing state of the art in terms of both speed and accuracy. On simulated data sets of up to 10K individuals, TeraStructure is twice as fast as existing methods and has higher accuracy in recovering the latent population structure. On genomic data simulated at the tera-sample-size scales, TeraStructure continues to be accurate and is the only method that can complete its analysis.

scholarly journals Mycelial biomass and concentration of loline alkaloids driven by complex population structure in Epichloë uncinata and meadow fescue (Schedonorus pratensis)

Mycologia ◽  
2020 ◽  
Vol 112 (3) ◽  
pp. 474-490 ◽  
Author(s):  
G. Cagnano ◽  
I. Lenk ◽  
N. Roulund ◽  
C. S. Jensen ◽  
M. P. Cox ◽  
...  
Keyword(s):  
Population Structure ◽  
Mycelial Biomass ◽  
Meadow Fescue ◽  
Complex Population ◽  
Loline Alkaloids

scholarly journals Population structure and geographic segregation of Cryptosporidium parvum IId subtypes in cattle in China

2020 ◽  
Author(s):  
Zhenjie Zhang ◽  
Suhui Hu ◽  
Wentao Zhao ◽  
Yaqiong Guo ◽  
Na Li ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Cryptosporidium Parvum ◽  
Population Genetic ◽  
Principal Component ◽  
Farm Animals ◽  
Industrialized Countries ◽  
Genetic Characteristics ◽  
Distance Analysis ◽  
Complex Population

Abstract Background: Cryptosporidium parvum is a zoonotic pathogen worldwide. Extensive genetic diversity and complex population structures exist in C. parvum in different geographic regions and hosts. Unlike the IIa subtype family, which is responsible for most zoonotic C. parvum infections in industrialized countries, IId is identified as the dominant subtype family in farm animals, rodents, and humans in China. Thus far, the population genetic characteristics of IId subtypes in calves in China are not clear.Methods: In the present study, 46 C. parvum isolates from cattle in China were characterized using multilocus sequenceanalysis of eight genetic loci. They belonged to three IId subtypes in the 60 kDa glycoprotein (gp60) gene, including IIdA20G1 (n = 17), IIdA19G1 (n = 24) and IIdA15G1 (n = 5). The data generated were analyzed for population genetic structures of C. parvum using various tools.Results: Seventeen multilocus genotypes were identified. The results of linkage disequilibrium analysis indicated the presence of an epidemic genetic structure in the C. parvum IId population. When isolates of various geographical areas were treated as individual subpopulations, maximum likelihood inference of phylogeny, pairwise genetic distance analysis, sub-structure analysis, principal component analysis and network analysis all provided evidence for geographic segregation of subpopulations in Heilongjiang, Hebei, and Xinjiang. In contrast, isolates from Guangdong, Shanghai, and Jiangsu were genetically similar to each other.Conclusions: Data from the multilocus analysis have revealed a much higher genetic diversity of C. parvum than gp60 sequence analysis. Despite an epidemic population structure, there is apparent geographic segregation in C. parvum subpopulations within China.

scholarly journals netview p: a network visualization tool to unravel complex population structure using genome-wide SNPs

2015 ◽  
Vol 16 (1) ◽  
pp. 216-227 ◽  
Author(s):  
Eike J. Steinig ◽  
Markus Neuditschko ◽  
Mehar S. Khatkar ◽  
Herman W. Raadsma ◽  
Kyall R. Zenger
Keyword(s):  
Population Structure ◽  
Network Visualization ◽  
Visualization Tool ◽  
Genome Wide ◽  
Complex Population

Conservation implications of complex population structure: lessons from the loggerhead turtle (Caretta caretta)

2005 ◽  
Vol 14 (8) ◽  
pp. 2389-2402 ◽  
Author(s):  
B. W. BOWEN ◽  
A. L. BASS ◽  
L. SOARES ◽  
R. J. TOONEN
Keyword(s):  
Population Structure ◽  
Loggerhead Turtle ◽  
Caretta Caretta ◽  
Conservation Implications ◽  
Complex Population

scholarly journals Complex population structure of the Atlantic puffin revealed by whole genome analyses

2020 ◽  
Author(s):  
Oliver Kersten ◽  
Bastiaan Star ◽  
Deborah M. Leigh ◽  
Tycho Anker-Nilssen ◽  
Hallvard Strøm ◽  
...  
Keyword(s):  
Population Structure ◽  
Gene Flow ◽  
Isolation By Distance ◽  
Spatial Scales ◽  
Secondary Contact ◽  
Whole Genome ◽  
Genome Data ◽  
Complex Population ◽  
Genome Analyses ◽  
Atlantic Puffin

AbstractThe factors underlying gene flow and genomic population structure in vagile seabirds are notoriously difficult to understand due to their complex ecology with diverse dispersal barriers and extensive periods at sea. Yet, such understanding is vital for conservation management of seabirds that are globally declining at alarming rates. Here, we elucidate the population structure of the Atlantic puffin (Fratercula arctica) by assembling its reference genome and analyzing genome-wide resequencing data of 72 individuals from 12 colonies. We identify four large, genetically distinct clusters, observe isolation-by-distance between colonies within these clusters, and obtain evidence for a secondary contact zone. These observations disagree with the current taxonomy, and show that a complex set of contemporary biotic factors impede gene flow over different spatial scales. Our results highlight the power of whole genome data to reveal unexpected population structure in vagile marine seabirds and its value for seabird taxonomy, evolution and conservation.

scholarly journals New kinship and FST estimates reveal higher levels of differentiation in the global human population

2019 ◽  
Author(s):  
Alejandro Ochoa ◽  
John D. Storey
Keyword(s):  
Population Structure ◽  
Genetic Relatedness ◽  
Genetic Distances ◽  
Recent Common Ancestor ◽  
Human Populations ◽  
Population Genetic Analysis ◽  
Most Recent Common Ancestor ◽  
Complex Population ◽  
Population Structures ◽  
Modern Population

Kinship coefficients and FST, which measure genetic relatedness and the overall population structure, respectively, have important biomedical applications. However, existing estimators are only accurate under restrictive conditions that most natural population structures do not satisfy. We recently derived new kinship and FST estimators for arbitrary population structures [1, 2]. Our estimates on human datasets reveal a complex population structure driven by founder effects due to dispersal from Africa and admixture. Notably, our new approach estimates larger FST values of 26% for native worldwide human populations and 23% for admixed Hispanic individuals, whereas the existing approach estimates 9.8% and 2.6%, respectively. While previous work correctly measured FST between subpopulation pairs, our generalized FST measures genetic distances among all individuals and their most recent common ancestor (MRCA) population, revealing that genetic differentiation is greater than previously appreciated. This analysis demonstrates that estimating kinship and FST under more realistic assumptions is important for modern population genetic analysis.

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