Genome-Wide Patterns of Genetic Distances Reveal Candidate Loci Contributing to Human Population-Specific Traits

This study focused on the genomic differences between the Czechoslovakian wolfdog (CWD) and its ancestors, the Grey wolf (GW) and German Shepherd dog. The Saarloos wolfdog and Belgian Shepherd dog were also included to study the level of GW genetics retained in the genome of domesticated breeds. The dataset consisted of 131 animals and 143,593 single nucleotide polymorphisms (SNPs). The effects of demographic history on the overall genome structure were determined by screening the distribution of the homozygous segments. The genetic variance distributed within and between groups was quantified by genetic distances, the FST index, and discriminant analysis of principal components. Fine-scale population stratification due to specific morphological and behavioural traits was assessed by principal component and factorial analyses. In the CWD, a demographic history effect was manifested mainly in a high genome-wide proportion of short homozygous segments corresponding to a historical load of inbreeding derived from founders. The observed proportion of long homozygous segments indicated that the inbreeding events shaped the CWD genome relatively recently compared to other groups. Even if there was a significant increase in genetic similarity among wolf-like breeds, they were genetically separated from each other. Moreover, this study showed that the CWD genome carries private alleles that are not found in either wolves or other dog breeds analysed in this study.

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You Will Never Walk Alone: Codispersal of JC Polyomavirus with Human Populations

Molecular Biology and Evolution ◽

10.1093/molbev/msz227 ◽

2019 ◽

Vol 37 (2) ◽

pp. 442-454 ◽

Cited By ~ 1

Author(s):

Diego Forni ◽

Rachele Cagliani ◽

Mario Clerici ◽

Uberto Pozzoli ◽

Manuela Sironi

Keyword(s):

Geographic Distribution ◽

Human Population ◽

Strong Support ◽

Time Frame ◽

Genetic Distances ◽

The Philippines ◽

Molecular Dating ◽

Human Populations ◽

Jc Polyomavirus ◽

Reconciliation Analysis

Abstract JC polyomavirus (JCPyV) is one of the most prevalent human viruses. Findings based on the geographic distribution of viral subtypes suggested that JCPyV codiverged with human populations. This view was however challenged by data reporting a much more recent origin and expansion of JCPyV. We collected information on ∼1,100 worldwide strains and we show that their geographic distribution roughly corresponds to major human migratory routes. Bayesian phylogeographic analysis inferred a Subsaharan origin for JCPyV, although with low posterior probability. High confidence inference at internal nodes provided strong support for a long-standing association between the virus and human populations. In line with these data, pairwise FST values for JCPyV and human mtDNA sampled from the same areas showed a positive and significant correlation. Likewise, very strong relationships were found when node ages in the JCPyV phylogeny were correlated with human population genetic distances (nuclear-marker based FST). Reconciliation analysis detected a significant cophylogenetic signal for the human population and JCPyV trees. Notably, JCPyV also traced some relatively recent migration events such as the expansion of people from the Philippines/Taiwan area into Remote Oceania, the gene flow between North-Eastern Siberian and Ainus, and the Koryak contribution to Circum-Arctic Americans. Finally, different molecular dating approaches dated the origin of JCPyV in a time frame that precedes human out-of-Africa migration. Thus, JCPyV infected early human populations and accompanied our species during worldwide dispersal. JCPyV typing can provide reliable geographic information and the virus most likely adapted to the genetic background of human populations.

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An approach based on a genome-wide association study reveals candidate loci for narcolepsy

Human Genetics ◽

10.1007/s00439-010-0862-z ◽

2010 ◽

Vol 128 (4) ◽

pp. 433-441 ◽

Cited By ~ 24

Author(s):

Mihoko Shimada ◽

Taku Miyagawa ◽

Minae Kawashima ◽

Susumu Tanaka ◽

Yutaka Honda ◽

...

Keyword(s):

Association Study ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Genome Wide ◽

A Genome ◽

Candidate Loci

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Gene-Expression-Guided Selection of Candidate Loci and Molecular Phenotype Analyses Enhance Genetic Discovery in Systemic Lupus Erythematosus

Clinical and Developmental Immunology ◽

10.1155/2012/682018 ◽

2012 ◽

Vol 2012 ◽

pp. 1-9 ◽

Cited By ~ 10

Author(s):

Yelena Koldobskaya ◽

Kichul Ko ◽

Akaash A. Kumar ◽

Sandra Agik ◽

Jasmine Arrington ◽

...

Keyword(s):

Gene Expression ◽

Systemic Lupus Erythematosus ◽

Gene Expression Data ◽

Lupus Erythematosus ◽

Clinical Manifestations ◽

Control Analysis ◽

Expression Data ◽

Systemic Lupus ◽

Genome Wide ◽

Candidate Loci

Systemic lupus erythematosus (SLE) is a highly heterogeneous autoimmune disorder characterized by differences in autoantibody profiles, serum cytokines, and clinical manifestations. We have previously conducted a case-case genome-wide association study (GWAS) of SLE patients to detect associations with autoantibody profile and serum interferon alpha (IFN-α). In this study, we used public gene expression data sets to rationally select additional single nucleotide polymorphisms (SNPs) for validation. The top 200 GWAS SNPs were searched in a database which compares genome-wide expression data to genome-wide SNP genotype data in HapMap cell lines. SNPs were chosen for validation if they were associated with differential expression of 15 or more genes at a significance ofP<9×10−5. This resulted in 11 SNPs which were genotyped in 453 SLE patients and 418 matched controls. Three SNPs were associated with SLE-associated autoantibodies, and one of these SNPs was also associated with serum IFN-α(P<4.5×10−3for all). One additional SNP was associated exclusively with serum IFN-α. Case-control analysis was insensitive to these molecular subphenotype associations. This study illustrates the use of gene expression data to rationally select candidate loci in autoimmune disease, and the utility of stratification by molecular phenotypes in the discovery of additional genetic associations in SLE.

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Genome-wide association analysis with selective genotyping identifies candidate loci for adult height at 8q21.13 and 15q22.33-q23 in Mongolians

Human Genetics ◽

10.1007/s00439-008-0512-x ◽

2008 ◽

Vol 123 (6) ◽

pp. 655-660 ◽

Cited By ~ 10

Author(s):

Tetsuaki Kimura ◽

Terukazu Kobayashi ◽

Batmunkh Munkhbat ◽

Ganjuur Oyungerel ◽

Tsolmon Bilegtsaikhan ◽

...

Keyword(s):

Association Analysis ◽

Adult Height ◽

Selective Genotyping ◽

Genome Wide Association ◽

Genome Wide Association Analysis ◽

Genome Wide ◽

Candidate Loci

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Candidate loci for insulin sensitivity and disposition index from a genome-wide association analysis of Hispanic participants in the Insulin Resistance Atherosclerosis (IRAS) Family Study

Diabetologia ◽

10.1007/s00125-009-1586-2 ◽

2009 ◽

Vol 53 (2) ◽

pp. 281-289 ◽

Cited By ~ 20

Author(s):

N. D. Palmer ◽

C. D. Langefeld ◽

J. T. Ziegler ◽

F. Hsu ◽

S. M. Haffner ◽

...

Keyword(s):

Insulin Resistance ◽

Insulin Sensitivity ◽

Association Analysis ◽

Family Study ◽

Disposition Index ◽

Genome Wide Association ◽

Genome Wide Association Analysis ◽

Genome Wide ◽

A Genome ◽

Candidate Loci

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Rapid adaptation to malaria facilitated by admixture in the human population of Cabo Verde

10.1101/2020.09.01.278226 ◽

2020 ◽

Author(s):

Iman Hamid ◽

Katharine Korunes ◽

Sandra Beleza ◽

Amy Goldberg

Keyword(s):

Human Population ◽

Rapid Evolution ◽

Selection Coefficient ◽

Rapid Adaptation ◽

Cabo Verde ◽

Selective Pressures ◽

The Past ◽

Genome Wide ◽

Admixed Population ◽

Demographic Inference

Humans have undergone large migrations over the past hundreds to thousands of years, exposing ourselves to new environments and selective pressures. Yet, evidence of ongoing or recent selection in humans is difficult to detect. Many of these migrations also resulted in gene flow between previously separated populations. These recently admixed populations provide unique opportunities to study rapid evolution in humans. Developing methods based on distributions of local ancestry, we demonstrate that this sort of genetic exchange has facilitated detectable adaptation to a malaria parasite in the admixed population of Cabo Verde within the last ~22 generations. We estimate the selection coefficient is approximately 0.08, one of the highest inferred in humans. Notably, we show that this strong selection at a single locus has likely affected patterns of ancestry genome-wide, potentially biasing demographic inference. Our study provides evidence of adaptation in a human population on historical timescales.

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Not just methods: User expertise explains the variability of outcomes of genome-wide studies

10.1101/055046 ◽

2016 ◽

Cited By ~ 1

Author(s):

Katie E. Lotterhos ◽

Olivier François ◽

Michael G.B. Blum

Keyword(s):

Summer School ◽

Statistical Power ◽

A Priori ◽

Simulated Data ◽

Genome Scan ◽

Genome Wide ◽

The Difference ◽

Difficult Challenge ◽

Genomic Regions ◽

Candidate Loci

AbstractGenome scan approaches promise to map genomic regions involved in adaptation of individuals to their environment. Outcomes of genome scans have been shown to depend on several factors including the underlying demography, the adaptive scenario, and the software or method used. We took advantage of a pedagogical experiment carried out during a summer school to explore the effect of an unexplored source of variability, which is the degree of user expertise.Participants were asked to analyze three simulated data challenges with methods presented during the summer school. In addition to submitting lists, participants evaluated a priori their level of expertise. We measured the quality of each genome scan analysis by computing a score that depends on false discovery rate and statistical power. In an easy and a difficult challenge, less advanced participants obtained similar scores compared to advanced ones, demonstrating that participants with little background in genome scan methods were able to learn how to use complex software after short introductory tutorials. However, in a challenge ofintermediate difficulty, advanced participants obtained better scores. To explain the difference, we introduce a probabilistic model that shows that a larger variation in scores is expected for SNPs of intermediate difficulty of detection. We conclude that practitioners should develop their statistical and computational expertise to follow the development of complex methods. To encourage training, we release the website of the summer school where users can submit lists of candidate loci, which will be scored and compared to the scores obtained by previous users.

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