scholarly journals Population Genomic Evidence Reveals Subtle Patterns of Differentiation in the Trophically Polymorphic Cuatro Ciénegas Cichlid, Herichthys minckleyi

2019 ◽  
Vol 110 (3) ◽  
pp. 361-369 ◽  
Author(s):  
Katherine L Bell ◽  
Chris C Nice ◽  
Darrin Hulsey
Keyword(s):  
Gene Flow ◽  
Biological Diversity ◽  
Molecular Genetic ◽  
Molecular Ecology ◽  
Cichlid Fish ◽  
Genome Wide ◽  
A Genome ◽  
The Face ◽  
Or Gene ◽  
Herichthys Minckleyi

Abstract In recent decades, an increased understanding of molecular ecology has led to a reinterpretation of the role of gene flow during the evolution of reproductive isolation and biological novelty. For example, even in the face of ongoing gene flow strong selection may maintain divergent polymorphisms, or gene flow may introduce novel biological diversity via hybridization and introgression from a divergent species. Herein, we elucidate the evolutionary history and genomic basis of a trophically polymorphic trait in a species of cichlid fish, Herichthys minckleyi. We explored genetic variation at 3 hierarchical levels; between H. minckleyi (n = 69) and a closely related species Herichthys cyanoguttatus (n = 10), between H. minckleyi individuals from 2 geographic locations, and finally between individuals with alternate morphotypes at both a genome-wide and locus-specific scale. We found limited support for the hypothesis that the H. minckleyi polymorphism is the result of ongoing hybridization between the 2 species. Within H. minckleyi we found evidence of geographic genetic structure, and using traditional population genetic analyses found that individuals of alternate morphotypes within a pool appear to be panmictic. However, when we used a locus-specific approach to examine the relationship between multi-locus genotype, tooth size, and geographic sampling, we found the first evidence for molecular genetic differences between the H. minckleyi morphotypes.

scholarly journals Comparative transcriptome analysis of mule uncovered several heterosis-related genes for improving muscular endurance and cognition

2019 ◽  
Author(s):  
Shan Gao
Keyword(s):  
Alternative Splicing ◽  
Molecular Genetic ◽  
Hybrid Vigor ◽  
Neuronal System ◽  
Future Studies ◽  
Genome Wide ◽  
A Genome ◽  
Genetic Mechanisms ◽  
Productive Traits ◽  
Genome Wide Gene Expression

AbstractHeterosis has been widely exploited in animal and plant breeding to enhance the productive traits of hybrid progeny of two breeds or two species. Although, there were multiple models for explaining the hybrid vigor, such as dominance and over-dominance hypothesis, its underlying molecular genetic mechanisms remain equivocal. The aim of this study is through comparing the different expression genes (DEGs) and different alternative splicing (DAS) genes to explore the mechanism of heterosis. Here, we performed a genome-wide gene expression and alternative splicing analysis of two heterotic crosses between donkey and horse in three tissues. The results showed that the DAS genes influenced the heterosis-related phenotypes in a unique than DEGs and about 10% DEGs are DAS genes. In addition, over 69.7% DEGs and 87.2% DAS genes showed over-dominance or dominance, respectively. Furthermore, the “Muscle Contraction” and “Neuronal System” pathways were significantly enriched both for the DEGs and DAS genes in muscle. TNNC2 and RYR1 genes may contribute to mule’s great endurance while GRIA2 and GRIN1 genes may be related with mule’s cognition. Together, these DEGs and DAS genes provide the candidates for future studies of the genetic and molecular mechanism of heterosis in mule.

scholarly journals Admixture into and within sub-Saharan Africa

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
George BJ Busby ◽  
Gavin Band ◽  
Quang Si Le ◽  
Muminatou Jallow ◽  
Edith Bougama ◽  
...  
Keyword(s):  
Gene Flow ◽  
Geographic Region ◽  
Sub Saharan Africa ◽  
Genome Wide ◽  
A Genome ◽  
Depth Analysis ◽  
Shared Ancestry ◽  
Sub Saharan ◽  
Linguistic Groups ◽  
Insight Into

Similarity between two individuals in the combination of genetic markers along their chromosomes indicates shared ancestry and can be used to identify historical connections between different population groups due to admixture. We use a genome-wide, haplotype-based, analysis to characterise the structure of genetic diversity and gene-flow in a collection of 48 sub-Saharan African groups. We show that coastal populations experienced an influx of Eurasian haplotypes over the last 7000 years, and that Eastern and Southern Niger-Congo speaking groups share ancestry with Central West Africans as a result of recent population expansions. In fact, most sub-Saharan populations share ancestry with groups from outside of their current geographic region as a result of gene-flow within the last 4000 years. Our in-depth analysis provides insight into haplotype sharing across different ethno-linguistic groups and the recent movement of alleles into new environments, both of which are relevant to studies of genetic epidemiology.

scholarly journals Predicting the Landscape of Recombination Using Deep Learning

2020 ◽  
Vol 37 (6) ◽  
pp. 1790-1808 ◽  
Author(s):  
Jeffrey R Adrion ◽  
Jared G Galloway ◽  
Andrew D Kern
Keyword(s):  
Deep Learning ◽  
Evolutionary History ◽  
Model Misspecification ◽  
Natural Populations ◽  
High Accuracy ◽  
Demographic Model ◽  
Recombination Rates ◽  
Genome Wide ◽  
A Genome ◽  
The Face

Abstract Accurately inferring the genome-wide landscape of recombination rates in natural populations is a central aim in genomics, as patterns of linkage influence everything from genetic mapping to understanding evolutionary history. Here, we describe recombination landscape estimation using recurrent neural networks (ReLERNN), a deep learning method for estimating a genome-wide recombination map that is accurate even with small numbers of pooled or individually sequenced genomes. Rather than use summaries of linkage disequilibrium as its input, ReLERNN takes columns from a genotype alignment, which are then modeled as a sequence across the genome using a recurrent neural network. We demonstrate that ReLERNN improves accuracy and reduces bias relative to existing methods and maintains high accuracy in the face of demographic model misspecification, missing genotype calls, and genome inaccessibility. We apply ReLERNN to natural populations of African Drosophila melanogaster and show that genome-wide recombination landscapes, although largely correlated among populations, exhibit important population-specific differences. Lastly, we connect the inferred patterns of recombination with the frequencies of major inversions segregating in natural Drosophila populations.

scholarly journals The genomic impact of European colonization of the Americas

2019 ◽  
Author(s):  
Linda Ongaro ◽  
Marilia O. Scliar ◽  
Rodrigo Flores ◽  
Alessandro Raveane ◽  
Davide Marnetto ◽  
...  
Keyword(s):  
Gene Flow ◽  
Demographic History ◽  
Colonial Era ◽  
Genome Wide ◽  
A Genome ◽  
European Colonization ◽  
High Degree ◽  
The Impact ◽  
North And South America ◽  
North And South

AbstractThe human genetic diversity of the Americas has been shaped by several events of gene flow that have continued since the Colonial Era and the Atlantic slave trade. Moreover, multiple waves of migration followed by local admixture occurred in the last two centuries, the impact of which has been largely unexplored.Here we compiled a genome-wide dataset of ∼12,000 individuals from twelve American countries and ∼6,000 individuals from worldwide populations and applied haplotype-based methods to investigate how historical movements from outside the New World affected i) the genetic structure, ii) the admixture profile, iii) the demographic history and iv) sex-biased gene-flow dynamics, of the Americas.We revealed a high degree of complexity underlying the genetic contribution of European and African populations in North and South America, from both geographic and temporal perspectives, identifying previously unreported sources related to Italy, the Middle East and to specific regions of Africa.

scholarly journals Japan COVID-19 Task Force: a nation-wide consortium to elucidate host genetics of COVID-19 pandemic in Japan

2021 ◽  
Author(s):  
Ho Namkoong ◽  
Ryuya Edahiro ◽  
Koichi Fukunaga ◽  
Yuya Shirai ◽  
Kyuto Sonehara ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Risk Allele ◽  
Task Force ◽  
European Population ◽  
P Value ◽  
Host Genetics ◽  
Risk Variants ◽  
Genome Wide ◽  
A Genome ◽  
The Face

To elucidate the host genetic loci affecting severity of SARS-CoV-2 infection, or Coronavirus disease 2019 (COVID-19), is an emerging issue in the face of the current devastating pandemic. Here, we report a genome-wide association study (GWAS) of COVID-19 in a Japanese population led by the Japan COVID-19 Task Force, as one of the initial discovery GWAS studies performed on a non-European population. Enrolling a total of 2,393 cases and 3,289 controls, we not only replicated previously reported COVID-19 risk variants (e.g., LZTFL1, FOXP4, ABO, and IFNAR2), but also found a variant on 5p35 (rs60200309-A at DOCK2) that was significantly associated with severe COVID-19 in younger (<65 years of age) patients with a genome-wide significant p-value of 1.2 × 10-8 (odds ratio = 2.01, 95% confidence interval = 1.58-2.55). This risk allele was prevalent in East Asians, including Japanese (minor allele frequency [MAF] = 0.097), but rarely found in Europeans. Cross-population Mendelian randomization analysis made a causal inference of a number of complex human traits on COVID-19. In particular, obesity had a significant impact on severe COVID-19. The presence of the population-specific risk allele underscores the need of non-European studies of COVID-19 host genetics.

scholarly journals A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence

2015 ◽  
Vol 21 (8) ◽  
pp. 1145-1151 ◽  
Author(s):  
S L Spain ◽  
I Pedroso ◽  
N Kadeva ◽  
M B Miller ◽  
W G Iacono ◽  
...  
Keyword(s):  
Population Distribution ◽  
Genetic Model ◽  
Molecular Genetic ◽  
Heritability Estimate ◽  
Population Based ◽  
Functional Protein ◽  
Genome Wide ◽  
A Genome ◽  
Rare Alleles ◽  
High Intelligence

Abstract Although individual differences in intelligence (general cognitive ability) are highly heritable, molecular genetic analyses to date have had limited success in identifying specific loci responsible for its heritability. This study is the first to investigate exome variation in individuals of extremely high intelligence. Under the quantitative genetic model, sampling from the high extreme of the distribution should provide increased power to detect associations. We therefore performed a case–control association analysis with 1409 individuals drawn from the top 0.0003 (IQ >170) of the population distribution of intelligence and 3253 unselected population-based controls. Our analysis focused on putative functional exonic variants assayed on the Illumina HumanExome BeadChip. We did not observe any individual protein-altering variants that are reproducibly associated with extremely high intelligence and within the entire distribution of intelligence. Moreover, no significant associations were found for multiple rare alleles within individual genes. However, analyses using genome-wide similarity between unrelated individuals (genome-wide complex trait analysis) indicate that the genotyped functional protein-altering variation yields a heritability estimate of 17.4% (s.e. 1.7%) based on a liability model. In addition, investigation of nominally significant associations revealed fewer rare alleles associated with extremely high intelligence than would be expected under the null hypothesis. This observation is consistent with the hypothesis that rare functional alleles are more frequently detrimental than beneficial to intelligence.

scholarly journals Heritability and molecular genetic basis of antisaccade eye tracking error rate: A genome-wide association study

2014 ◽  
Vol 51 (12) ◽  
pp. 1272-1284 ◽  
Author(s):  
Uma Vaidyanathan ◽  
Stephen M. Malone ◽  
Jennifer M. Donnelly ◽  
Micah A. Hammer ◽  
Michael B. Miller ◽  
...  
Keyword(s):  
Association Study ◽  
Error Rate ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Molecular Genetic ◽  
Tracking Error ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Molecular Genetic Basis ◽  
A Genome

scholarly journals Heritability and molecular-genetic basis of resting EEG activity: A genome-wide association study

2014 ◽  
Vol 51 (12) ◽  
pp. 1225-1245 ◽  
Author(s):  
Stephen M. Malone ◽  
Scott J. Burwell ◽  
Uma Vaidyanathan ◽  
Michael B. Miller ◽  
Matt MCGUE ◽  
...  
Keyword(s):  
Association Study ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Molecular Genetic ◽  
Genome Wide Association ◽  
Eeg Activity ◽  
Genome Wide ◽  
Molecular Genetic Basis ◽  
A Genome

scholarly journals Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps

Genetics ◽  
2001 ◽  
Vol 157 (4) ◽  
pp. 1819-1829 ◽  
Author(s):  
T H E Meuwissen ◽  
B J Hayes ◽  
M E Goddard
Keyword(s):  
Molecular Genetic ◽  
Linear Unbiased Prediction ◽  
Genome Wide ◽  
A Genome ◽  
Reproductive Techniques ◽  
Genetic Techniques ◽  
Best Linear Unbiased ◽  
Genetic Value ◽  
Dense Marker ◽  
Marker Spacing

Abstract Recent advances in molecular genetic techniques will make dense marker maps available and genotyping many individuals for these markers feasible. Here we attempted to estimate the effects of ∼50,000 marker haplotypes simultaneously from a limited number of phenotypic records. A genome of 1000 cM was simulated with a marker spacing of 1 cM. The markers surrounding every 1-cM region were combined into marker haplotypes. Due to finite population size (Ne = 100), the marker haplotypes were in linkage disequilibrium with the QTL located between the markers. Using least squares, all haplotype effects could not be estimated simultaneously. When only the biggest effects were included, they were overestimated and the accuracy of predicting genetic values of the offspring of the recorded animals was only 0.32. Best linear unbiased prediction of haplotype effects assumed equal variances associated to each 1-cM chromosomal segment, which yielded an accuracy of 0.73, although this assumption was far from true. Bayesian methods that assumed a prior distribution of the variance associated with each chromosome segment increased this accuracy to 0.85, even when the prior was not correct. It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.

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