Efficient learning in ABC algorithms

Approximate Bayesian Computation has been successfully used in population genetics to bypass the calculation of the likelihood. These methods provide accurate estimates of the posterior distribution by comparing the observed dataset to a sample of datasets simulated from the model. Although parallelization is easily achieved, computation times for ensuring a suitable approximation quality of the posterior distribution are still high. To alleviate the computational burden, we propose an adaptive, sequential algorithm that runs faster than other ABC algorithms but maintains accuracy of the approximation. This proposal relies on the sequential Monte Carlo sampler of Del Moral et al. (2012) but is calibrated to reduce the number of simulations from the model. The paper concludes with numerical experiments on a toy example and on a population genetic study of Apis mellifera, where our algorithm was shown to be faster than traditional ABC schemes

Reliable ABC model choice via random forests

Approximate Bayesian computation (ABC) methods provide an elaborate approach to Bayesian inference on complex models, including model choice. Both theoretical arguments and simulation experiments indicate, however, that model posterior probabilities may be poorly evaluated by standard ABC techniques. We propose a novel approach based on a machine learning tool named random forests to conduct selection among the highly complex models covered by ABC algorithms. We thus modify the way Bayesian model selection is both understood and operated, in that we rephrase the inferential goal as a classification problem, first predicting the model that best fits the data with random forests and postponing the approximation of the posterior probability of the predicted MAP for a second stage also relying on random forests. Compared with earlier implementations of ABC model choice, the ABC random forest approach offers several potential improvements: (i) it often has a larger discriminative power among the competing models, (ii) it is more robust against the number and choice of statistics summarizing the data, (iii) the computing effort is drastically reduced (with a gain in computation efficiency of at least fifty), and (iv) it includes an approximation of the posterior probability of the selected model. The call to random forests will undoubtedly extend the range of size of datasets and complexity of models that ABC can handle. We illustrate the power of this novel methodology by analyzing controlled experiments as well as genuine population genetics datasets. The proposed methodologies are implemented in the R package abcrf available on the CRAN.Comment: 39 pages, 15 figures, 6 table

Gene-flow between populations of cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) is highly variable between years

Both large and small scale migrations of Helicoverpa armigera Hübner in Australia were investigated using AMOVA analysis and genetic assignment tests. Five microsatellite loci were screened across 3142 individuals from 16 localities in eight major cotton and grain growing regions within Australia, over a 38-month period (November 1999 to January 2003). From November 1999 to March 2001 relatively low levels of migration were characterized between growing regions. Substantially higher than average gene-flow rates and limited differentiation between cropping regions characterized the period from April 2001 to March 2002. A reduced migration rate in the year from April 2002 to March 2003 resulted in significant genetic structuring between cropping regions. This differentiation was established within two or three generations. Genetic drift alone is unlikely to drive genetic differentiation over such a small number of generations, unless it is accompanied by extreme bottlenecks and/or selection. Helicoverpa armigera in Australia demonstrated isolation by distance, so immigration into cropping regions is more likely to come from nearby regions than from afar. This effect was most pronounced in years with limited migration. However, there is evidence of long distance dispersal events in periods of high migration (April 2001–March 2002). The implications of highly variable migration patterns for resistance management are considered.K.D. Scott, K.S. Wilkinson, N. Lawrence, C.L. Lange, L.J. Scott, M.A. Merritt, A.J. Lowe and G.C Graha

Population history, gene flow, and bottlenecks in island populations of a secondary seed disperser, the southern grey shrike (Lanius meridionalis koenigi)

Studying the population history and demography of organisms with important ecological roles can aid understanding of evolutionary processes at the community level and inform conservation. We screened genetic variation (mtDNA and microsatellite) across the populations of the southern grey shrike (Lanius meridionalis koenigi) in the Canary Islands, where it is an endemic subspecies and an important secondary seed disperser. We show that the Canarian subspecies is polyphyletic with L. meridionalis elegans from North Africa and that shrikes have colonized the Canary Islands from North Africa multiple times. Substantial differences in genetic diversity exist across islands, which are most likely the product of a combination of historical colonization events and recent bottlenecks. The Eastern Canary Islands had the highest overall levels of genetic diversity and have probably been most recently and/or frequently colonized from Africa. Recent or ongoing bottlenecks were detected in three of the islands and are consistent with anecdotal evidence of population declines due to human disturbance. These findings are troubling given the shrike's key ecological role in the Canary Islands, and further research is needed to understand the community-level consequences of declines in shrike populations. Finally, we found moderate genetic differentiation among populations, which largely reflected the shrike's bottleneck history; however, a significant pattern of isolation-by-distance indicated that some gene flow occurs between islands. This study is a useful first step toward understanding how secondary seed dispersal operates over broad spatial scales

Reliability assessment of null allele detection: inconsistencies between and within different methods

Microsatellite loci are widely used in population genetic studies, but the presence of null alleles may lead to biased results. Here we assessed five methods that indirectly detect null alleles, and found large inconsistencies among them. Our analysis was based on 20 microsatellite loci genotyped in a natural population of Microtus oeconomus sampled during 8 years, together with 1200 simulated populations without null alleles, but experiencing bottlenecks of varying duration and intensity, and 120 simulated populations with known null alleles. In the natural population, 29% of positive results were consistent between the methods in pairwise comparisons, and in the simulated dataset this proportion was 14%. The positive results were also inconsistent between different years in the natural population. In the null-allele-free simulated dataset, the number of false positives increased with increased bottleneck intensity and duration. We also found a low concordance in null allele detection between the original simulated populations and their 20% random subsets. In the populations simulated to include null alleles, between 22% and 42% of true null alleles remained undetected, which highlighted that detection errors are not restricted to false positives. None of the evaluated methods clearly outperformed the others when both false positive and false negative rates were considered. Accepting only the positive results consistent between at least two methods should considerably reduce the false positive rate, but this approach may increase the false negative rate. Our study demonstrates the need for novel null allele detection methods that could be reliably applied to natural population

Museum DNA reveals the demographic history of the endangered Seychelles warbler

The importance of evolutionary conservation – how understanding evolutionary forces can help guide conservation decisions – is widely recognized. However, the historical demography of many endangered species is unknown, despite the fact that this can have important implications for contemporary ecological processes and for extinction risk. Here, we reconstruct the population history of the Seychelles warbler (Acrocephalus sechellensis) – an ecological model species. By the 1960s, this species was on the brink of extinction, but its previous history is unknown. We used DNA samples from contemporary and museum specimens spanning 140 years to reconstruct bottleneck history. We found a 25% reduction in genetic diversity between museum and contemporary populations, and strong genetic structure. Simulations indicate that the Seychelles warbler was bottlenecked from a large population, with an ancestral Ne of several thousands falling to <50 within the last century. Such a rapid decline, due to anthropogenic factors, has important implications for extinction risk in the Seychelles warbler, and our results will inform conservation practices. Reconstructing the population history of this species also allows us to better understand patterns of genetic diversity, inbreeding and promiscuity in the contemporary populations. Our approaches can be applied across species to test ecological hypotheses and inform conservation

Russian wheat aphids (Diuraphis noxia) in China: Native range expansion or recent introduction?

In this study, we explore the population genetics of the Russian wheat aphid (RWA) (Diuraphis noxia), one of the world’s most invasive agricultural pests, in north-western China. We have analysed the data of 10 microsatellite loci and mitochondrial sequences from 27 populations sampled over 2 years in China. The results confirm that the RWAs are holocyclic in China with high genetic diversity indicating widespread sexual reproduction. Distinct differences in microsatellite genetic diversity and distribution revealed clear geographic isolation between RWA populations in northern and southern Xinjiang, China, with gene flow interrupted across extensive desert regions. Despite frequent grain transportation from north to south in this region, little evidence for RWA translocation as a result of human agricultural activities was found. Consequently, frequent gene flow among northern populations most likely resulted from natural dispersal, potentially facilitated by wind currents. We also found evidence for the longterm existence and expansion of RWAs in China, despite local opinion that it is an exotic species only present in China since 1975. Our estimated date of RWA expansion throughout China coincides with the debut of wheat domestication and cultivation practices in western Asia in the Holocene. We conclude that western China represents the limit of the far eastern native range of this species. This study is the most comprehensive molecular genetic investigation of the RWA in its native range undertaken to date and provides valuable insights into the history of the association of this aphid with domesticated cereals and wild grasses

Tgf-β1 Inhibits Cftr Biogenesis and Prevents Functional Rescue of ΔF508-Cftr in Primary Differentiated Human Bronchial Epithelial Cells

CFTR is an integral transmembrane glycoprotein and a cAMP-activated Cl- channel. Mutations in the CFTR gene lead to Cystic Fibrosis (CF)-an autosomal recessive disease with majority of the morbidity and mortality resulting from airway infection, inflammation, and fibrosis. The most common disease-associated mutation in the CFTR gene-deletion of Phe508 (ΔF508) leads to a biosynthetic processing defect of CFTR. Correction of the defect and delivery of ΔF508-CFTR to the cell surface has been highly anticipated as a disease modifying therapy. Compared to promising results in cultured cell this approach was much less effective in CF patients in an early clinical trial. Although the cause of failure to rescue ΔF508-CFTR in the clinical trial has not been determined, presence of factor(s) that interfere with the rescue in vivo could be considered. The cytokine TGF-β1 is frequently elevated in CF patients. TGF-β1 has pleiotropic effects in different disease models and genetic backgrounds and little is known about TGF-β1 effects on CFTR in human airway epithelial cells. Moreover, there are no published studies examining TGF-β1 effects on the functional rescue of ΔF508-CFTR. Here we found that TGF-β1 inhibits CFTR biogenesis by reducing mRNA levels and protein abundance in primary differentiated human bronchial epithelial (HBE) cells from non-CF individuals. TGF-β1 inhibits CFTR biogenesis without compromising the epithelial phenotype or integrity of HBE cells. TGF-β1 also inhibits biogenesis and impairs the functional rescue of ΔF508-CFTR in HBE cells from patients homozygous for the ΔF508 mutation. Our data indicate that activation of TGF-β1 signaling may inhibit CFTR function in non-CF individuals and may interfere with therapies directed at correcting the processing defect of ΔF508-CFTR in CF patients. © 2013 Snodgrass et al

European wildcat populations are subdivided into five main biogeographic groups: consequences of Pleistocene climate changes or recent anthropogenic fragmentation?

Extant populations of the European wildcat are fragmented across the continent, the likely consequence of recent extirpations due to habitat loss and over-hunting. However, their underlying phylogeographic history has never been reconstructed. For testing the hypothesis that the European wildcat survived the Ice Age fragmented in Mediterranean refuges, we assayed the genetic variation at 31 microsatellites in 668 presumptive European wildcats sampled in 15 European countries. Moreover, to evaluate the extent of subspecies/population divergence and identify eventual wild × domestic cat hybrids, we genotyped 26 African wildcats from Sardinia and North Africa and 294 random-bred domestic cats. Results of multivariate analyses and Bayesian clustering confirmed that the European wild and the domestic cats (plus the African wildcats) belong to two well-differentiated clusters (average Ф ST = 0.159, r st = 0.392, P &gt; 0.001; Analysis of molecular variance [AMOVA]). We identified from c. 5% to 10% cryptic hybrids in southern and central European populations. In contrast, wild-living cats in Hungary and Scotland showed deep signatures of genetic admixture and introgression with domestic cats. The European wildcats are subdivided into five main genetic clusters (average Ф ST = 0.103, r st = 0.143, P &gt; 0.001; AMOVA) corresponding to five biogeographic groups, respectively, distributed in the Iberian Peninsula, central Europe, central Germany, Italian Peninsula and the island of Sicily, and in north-eastern Italy and northern Balkan regions (Dinaric Alps). Approximate Bayesian Computation simulations supported late Pleistocene-early Holocene population splittings (from c. 60 k to 10 k years ago), contemporary to the last Ice Age climatic changes. These results provide evidences for wildcat Mediterranean refuges in southwestern Europe, but the evolution history of eastern wildcat populations remains to be clarified. Historical genetic subdivisions suggest conservation strategies aimed at enhancing gene flow through the restoration of ecological corridors within each biogeographic units. Concomitantly, the risk of hybridization with free-ranging domestic cats along corridor edges should be carefully monitored