Genomics of Divergence along a Continuum of Parapatric Population Differentiation

MM received funding from the Max Planck innovation funds for this project. PGDF was supported by a Marie Curie European Reintegration Grant (proposal nr 270891). CE was supported by German Science Foundation grants (DFG, EI 841/4-1 and EI 841/6-1)

Individuals with obesity and COVID-19: A global perspective on the epidemiology and biological relationships

The linkage of individuals with obesity and COVID-19 is controversial and lacks systematic reviews. After a systematic search of the Chinese and English language literature on COVID-19, 75 studies were used to conduct a series of meta-analyses on the relationship of individuals with obesity–COVID-19 over the full spectrum from risk to mortality. A systematic review of the mechanistic pathways for COVID-19 and individuals with obesity is presented. Pooled analysis show individuals with obesity were more at risk for COVID-19 positive, >46.0% higher (OR = 1.46; 95% CI, 1.30–1.65; p < 0.0001); for hospitalization, 113% higher (OR = 2.13; 95% CI, 1.74–2.60; p < 0.0001); for ICU admission, 74% higher (OR = 1.74; 95% CI, 1.46–2.08); and for mortality, 48% increase in deaths (OR = 1.48; 95% CI, 1.22–1.80; p < 0.001). Mechanistic pathways for individuals with obesity are presented in depth for factors linked with COVID-19 risk, severity and their potential for diminished therapeutic and prophylactic treatments among these individuals. Individuals with obesity are linked with large significant increases in morbidity and mortality from COVID-19. There are many mechanisms that jointly explain this impact. A major concern is that vaccines will be less effective for the individuals with obesity

AWclust: point-and-click software for non-parametric population structure analysis

<p>Abstract</p> <p>Background</p> <p>Population structure analysis is important to genetic association studies and evolutionary investigations. Parametric approaches, e.g. STRUCTURE and L-POP, usually assume Hardy-Weinberg equilibrium (HWE) and linkage equilibrium among loci in sample population individuals. However, the assumptions may not hold and allele frequency estimation may not be accurate in some data sets. The improved version of STRUCTURE (version 2.1) can incorporate linkage information among loci but is still sensitive to high background linkage disequilibrium. Nowadays, large-scale single nucleotide polymorphisms (SNPs) are becoming popular in genetic studies. Therefore, it is imperative to have software that makes full use of these genetic data to generate inference even when model assumptions do not hold or allele frequency estimation suffers from high variation.</p> <p>Results</p> <p>We have developed point-and-click software for non-parametric population structure analysis distributed as an R package. The software takes advantage of the large number of SNPs available to categorize individuals into ethnically similar clusters and it does not require assumptions about population models. Nor does it estimate allele frequencies. Moreover, this software can also infer the optimal number of populations.</p> <p>Conclusion</p> <p>Our software tool employs non-parametric approaches to assign individuals to clusters using SNPs. It provides efficient computation and an intuitive way for researchers to explore ethnic relationships among individuals. It can be complementary to parametric approaches in population structure analysis.</p

Assessing population genetic structure via the maximisation of genetic distance

<p>Abstract</p> <p>Background</p> <p>The inference of the hidden structure of a population is an essential issue in population genetics. Recently, several methods have been proposed to infer population structure in population genetics.</p> <p>Methods</p> <p>In this study, a new method to infer the number of clusters and to assign individuals to the inferred populations is proposed. This approach does not make any assumption on Hardy-Weinberg and linkage equilibrium. The implemented criterion is the maximisation (via a <it>simulated annealing </it>algorithm) of the averaged genetic distance between a predefined number of clusters. The performance of this method is compared with two Bayesian approaches: STRUCTURE and BAPS, using simulated data and also a real human data set.</p> <p>Results</p> <p>The simulations show that with a reduced number of markers, BAPS overestimates the number of clusters and presents a reduced proportion of correct groupings. The accuracy of the new method is approximately the same as for STRUCTURE. Also, in Hardy-Weinberg and linkage disequilibrium cases, BAPS performs incorrectly. In these situations, STRUCTURE and the new method show an equivalent behaviour with respect to the number of inferred clusters, although the proportion of correct groupings is slightly better with the new method. Re-establishing equilibrium with the randomisation procedures improves the precision of the Bayesian approaches. All methods have a good precision for <it>F</it>_{<it>ST </it>}≥ 0.03, but only STRUCTURE estimates the correct number of clusters for <it>F</it>_{<it>ST </it>}as low as 0.01. In situations with a high number of clusters or a more complex population structure, MGD performs better than STRUCTURE and BAPS. The results for a human data set analysed with the new method are congruent with the geographical regions previously found.</p> <p>Conclusion</p> <p>This new method used to infer the hidden structure in a population, based on the maximisation of the genetic distance and not taking into consideration any assumption about Hardy-Weinberg and linkage equilibrium, performs well under different simulated scenarios and with real data. Therefore, it could be a useful tool to determine genetically homogeneous groups, especially in those situations where the number of clusters is high, with complex population structure and where Hardy-Weinberg and/or linkage equilibrium are present.</p

Genome-Wide Genotype-Expression Relationships Reveal Both Copy Number and Single Nucleotide Differentiation Contribute to Differential Gene Expression between Stickleback Ecotypes

Repeated and independent emergence of trait divergence that matches habitat differences is a sign of parallel evolution by natural selection. Yet, the molecular underpinnings that are targeted by adaptive evolution often remain elusive. We investigate this question by combining genome-wide analyses of copy number variants (CNVs), single nucleotide polymorphisms (SNPs), and gene expression across four pairs of lake and river populations of the three-spined stickleback (Gasterosteus aculeatus). We tested whether CNVs that span entire genes and SNPs occurring in putative cis-regulatory regions contribute to gene expression differences between sticklebacks from lake and river origins. We found 135 gene CNVs that showed a significant positive association between gene copy number and gene expression, suggesting that CNVs result in dosage effects that can fuel phenotypic variation and serve as substrates for habitat-specific selection. Copy number differentiation between lake and river sticklebacks also contributed to expression differences of two immune-related genes in immune tissues, cathepsin A and GIMAP7. In addition, we identified SNPs in cis-regulatory regions (eSNPs) associated with the expression of 1,865 genes, including one eSNP upstream of a carboxypeptidase gene where both the SNP alleles differentiated and the gene was differentially expressed between lake and river populations. Our study highlights two types of mutations as important sources of genetic variation involved in the evolution of gene expression and in potentially facilitating repeated adaptation to novel environments

Repeated Lake-Stream Divergence in Stickleback Life History within a Central European Lake Basin

Life history divergence between populations inhabiting ecologically distinct habitats might be a potent source of reproductive isolation, but has received little attention in the context of speciation. We here test for life history divergence between threespine stickleback inhabiting Lake Constance (Central Europe) and multiple tributary streams. Otolith analysis shows that lake fish generally reproduce at two years of age, while their conspecifics in all streams have shifted to a primarily annual life cycle. This divergence is paralleled by a striking and consistent reduction in body size and fecundity in stream fish relative to lake fish. Stomach content analysis suggests that life history divergence might reflect a genetic or plastic response to pelagic versus benthic foraging modes in the lake and the streams. Microsatellite and mitochondrial markers further reveal that life history shifts in the different streams have occurred independently following the colonization by Lake Constance stickleback, and indicate the presence of strong barriers to gene flow across at least some of the lake-stream habitat transitions. Given that body size is known to strongly influence stickleback mating behavior, these barriers might well be related to life history divergence