Evolution of coadaptation in a subdivided population

A linkage disequilibrium-based statistical test for Genome-Wide Epistatic Selection Scans in structured populations

The quest for signatures of selection using single nucleotide polymorphism (SNP) data has proven efficient to uncover genes involved in conserved and/or adaptive molecular functions, but none of the statistical methods were designed to identify interacting alleles as targets of selective processes. Here, we propose a statistical test aimed at detecting epistatic selection, based on a linkage disequilibrium (LD) measure accounting for population structure and heterogeneous relatedness between individuals. SNP-based ([Formula: see text]) and window-based ([Formula: see text]) statistics fit a Student distribution, allowing to test the significance of correlation coefficients. As a proof of concept, we use SNP data from the Medicago truncatula symbiotic legume plant and uncover a previously unknown gene coadaptation between the MtSUNN (Super Numeric Nodule) receptor and the MtCLE02 (CLAVATA3-Like) signaling peptide. We also provide experimental evidence supporting a MtSUNN-dependent negative role of MtCLE02 in symbiotic root nodulation. Using human HGDP-CEPH SNP data, our new statistical test uncovers strong LD between SLC24A5 (skin pigmentation) and EDAR (hairs, teeth, sweat glands development) world-wide, which persists after correction for population structure and relatedness in Central South Asian populations. This result suggests that epistatic selection or coselection could have contributed to the phenotypic make-up in some human populations. Applying this approach to genome-wide SNP data will facilitate the identification of coadapted gene networks in model or non-model organisms.

Screening for epistatic selection signatures: A simulation study

Detecting combinations of alleles that diverged between subpopulations via selection signature statistics can contribute to decipher the phenomenon of epistasis. This research focused on the simulation of genomic data from subpopulations under divergent epistatic selection (ES). We used D’_IS² and F_ST statistics in pairs of loci to scan the whole-genome. The results showed the ability to identify loci under additive-by-additive ES (ES_aa) by reporting large statistical departures between subpopulations with a high level of divergence, while it did not show the same advantage in the other types of ES. Despite this, limitations such as the difficulty to distinguish between the quasi-complete fixation of one locus by ES_aa from other events were observed. However, D’_IS² can detect loci under ES_aa by defining a minimum boundary for the minor allele frequency on a multiple subpopulation analysis where ES only takes place in one subset. Even so, the major limitation was distinguishing between ES and single-locus selection (SS); therefore, we can conclude that divergent locus can be also a result of ES. The test conditions with D-statistics of both Ohta (1982a, 1982b) and Black and Krafsur (1985) did not provide evidence to differentiate ES in our simulation framework of isolated subpopulations.

Plasmodium falciparum produce lower infection intensities in local versus foreign Anopheles gambiae populations

Both Plasmodium falciparum and Anopheles gambiae show great diversity in Africa, in their own genetic makeup and population dynamics. The genetics of the individual mosquito and parasite are known to play a role in determining the outcome of infection in the vector, but whether differences in infection phenotype vary between populations remains to be investigated. Here we established two A. gambiae s.s. M molecular form colonies from Cameroon and Burkina Faso, representing a local and a foreign population for each of the geographical sites. Experimental infections of both colonies were conducted in Cameroon and Burkina Faso using local wild P. falciparum, giving a sympatric and allopatric vector-parasite combination in each site. Infection phenotype was determined in terms of oocyst prevalence and intensity for at least nine infections for each vector-parasite combination. Sympatric infections were found to produce 25% fewer oocysts per midgut than allopatric infections, while prevalence was not affected by local/foreign interactions. The reduction in oocyst numbers in sympatric couples may be the result of evolutionary processes where the mosquito populations have locally adapted to their parasite populations. Future research on vector-parasite interactions must take into account the geographic scale of adaptation revealed here by conducting experiments in natural sympatric populations to give epidemiologically meaningful results.

The dynamics of mutations associated with anti-malarial drug resistance in Plasmodium falciparum

The evolution of resistance in Plasmodium falciparum against safe and affordable drugs such as chloroquine (CQ) and sulfadoxine-pyrimethamine (SP) is a major global health threat. Investigating the dynamics of resistance against these antimalarial drugs will lead to approaches for addressing the problem of resistance in malarial parasites that are solidly based in evolutionary genetics and population biology. In this article, we discuss current developments in population biology modeling and evolutionary genetics. Despite great advancements achieved in the past decade, understanding the complex dynamics of mutations conferring drug resistance in P. falciparum requires approaches that consider the parasite population structure among other demographic processes.

Simulation of DNA sequence evolution under models of recent directional selection

Computer simulation is an essential tool in the analysis of DNA sequence variation for mapping events of recent adaptive evolution in the genome. Various simulation methods are employed to predict the signature of selection in sequence variation. The most informative and efficient method currently in use is coalescent simulation. However, this method is limited to simple models of directional selection. Whole-population forward-in-time simulations are the alternative to coalescent simulations for more complex models. The notorious problem of excessive computational cost in forward-in-time simulations can be overcome by various simplifying amendments. Overall, the success of simulations depends on the creative application of some population genetic theory to the simulation algorithm.

The joint effects of selection and dominance on the QST - FST contrast

Q(ST) measures the differentiation of quantitative traits between populations. It is often compared to F(ST), which measures population differentiation at neutral marker loci due to drift, migration, and mutation. When Q(ST) is different from F(ST), it is usually taken as evidence that selection has either restrained or accelerated the differentiation of the quantitative trait relative to neutral markers. However, a number of other factors such as inbreeding, dominance, and epistasis may also affect the Q(ST) - F(ST) contrast. In this study, we examine the effects of dominance, selection, and inbreeding on Q(ST) - F(ST). We compare Q(ST) with F(ST) at selected and neutral loci for populations at equilibrium between selection, drift, mutation, and migration using both analytic and simulation approaches. Interestingly, when divergent selection is acting on a locus, inbreeding and dominance generally inflate Q(ST) relative to F(ST) when they are both measured at the quantitative locus at equilibrium. As a consequence, dominance is unlikely to hide the signature of divergent selection on the Q(ST) - F(ST) contrast. However, although in theory dominance and inbreeding affect the expectation for Q(ST) - F(ST), of most concern is the very large variance in both Q(ST) and F(ST), suggesting that we should be cautious in attributing small differences between Q(ST) and F(ST) to selection.