Deciphering the demographic history of allochronic differentiation in the pine processionary moth Thaumetopoea pityocampa

Genome-wide patterns of genetic diversity, population structure and demographic history in mānuka (Leptospermum scoparium) growing on indigenous Māori land

Leptospermum scoparium J. R. Forst et G. Forst, known as mānuka by Māori, the indigenous people of Aotearoa (New Zealand), is a culturally and economically significant shrub species, native to New Zealand and Australia. Chemical, morphological and phylogenetic studies have indicated geographical variation of mānuka across its range in New Zealand, and genetic differentiation between New Zealand and Australia. We used pooled whole genome re-sequencing of 76 L. scoparium and outgroup populations from New Zealand and Australia to compile a dataset totalling ~2.5 million SNPs. We explored the genetic structure and relatedness of L. scoparium across New Zealand, and between populations in New Zealand and Australia, as well as the complex demographic history of this species. Our population genomic investigation suggests there are five geographically distinct mānuka gene pools within New Zealand, with evidence of gene flow occurring between these pools. Demographic modelling suggests three of these gene pools have undergone expansion events, whilst the evolutionary histories of the remaining two have been subjected to contractions. Furthermore, mānuka populations in New Zealand are genetically distinct from populations in Australia, with coalescent modelling suggesting these two clades diverged ~9-12 million years ago. We discuss the evolutionary history of this species and the benefits of using pool-seq for such studies. Our research will support the management and conservation of mānuka by landowners, particularly Māori, and the development of a provenance story for the branding of mānuka based products.

ƒ-statistics estimation and admixture graph construction with Pool-Seq or allele count data using the R package poolfstat

By capturing various patterns of the structuring of genetic variation across populations, f -statistics have proved highly effective for the inference of demographic history. Such statistics are defined as covariance of SNP allele frequency differences among sets of populations without requiring haplotype information and are hence particularly relevant for the analysis of pooled sequencing (Pool-Seq) data. We here propose a reinterpretation of the F (and D) parameters in terms of probability of gene identity and derive from this unified definition unbiased estimators for both Pool-Seq data and standard allele count data obtained from individual genotypes. We implemented these estimators in a new version of the R package poolfstat, which now includes a wide range of inference methods: (i) three-population test of admixture; (ii) four-population test of treeness; (iii) F4-ratio estimation of admixture rates; and (iv) fitting, visualization and (semi-automatic) construction of admixture graphs. A comprehensive evaluation of the methods implemented in poolfstat on both simulated Pool-Seq (with various sequencing coverages and error rates) and allele count data confirmed the accuracy of these approaches, even for the most cost-effective Pool-Seq design involving relatively low sequencing coverages. We further analyzed a real Pool-Seq data made of 14 populations of the invasive species Drosophila suzukii which allowed refining both the demographic history of native populations and the invasion routes followed by this emblematic pest. Our new package poolfstat provides the community with a user-friendly and efficient all-in-one tool to unravel complex population genetic histories from large-size Pool-Seq or allele count SNP data.

Extending approximate Bayesian computation with supervised machine learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest

Simulation-based methods such as approximate Bayesian computation (ABC) are well-adapted to the analysis of complex scenarios of populations and species genetic history. In this context, supervised machine learning (SML) methods provide attractive statistical solutions to conduct efficient inferences about scenario choice and parameter estimation. The Random Forest methodology (RF) is a powerful ensemble of SML algorithms used for classification or regression problems. Random Forest allows conducting inferences at a low computational cost, without preliminary selection of the relevant components of the ABC summary statistics, and bypassing the derivation of ABC tolerance levels. We have implemented a set of RF algorithms to process inferences using simulated data sets generated from an extended version of the population genetic simulator implemented in DIYABC v2.1.0. The resulting computer package, named DIYABC Random Forest v1.0, integrates two functionalities into a user-friendly interface: the simulation under custom evolutionary scenarios of different types of molecular data (microsatellites, DNA sequences or SNPs) and RF treatments including statistical tools to evaluate the power and accuracy of inferences. We illustrate the functionalities of DIYABC Random Forest v1.0 for both scenario choice and parameter estimation through the analysis of pseudo-observed and real data sets corresponding to pool-sequencing and individual-sequencing SNP data sets. Because of the properties inherent to the implemented RF methods and the large feature vector (including various summary statistics and their linear combinations) available for SNP data, DIYABC Random Forest v1.0 can efficiently contribute to the analysis of large SNP data sets to make inferences about complex population genetic histories.

Genomic divergence and differential gene expression between crustacean ecotypes across a marine thermal gradient

Environmental gradients between marine biogeographical provinces separate distinct faunal communities. However, the absence of absolute dispersal barriers allows numerous species to occur on both sides of such boundaries. While the regional populations of such widespread species are often morphologically indistinguishable from each other, genetic evidence suggests that they represent unique ecotypes, and likely even cryptic species, that may be uniquely adapted to their local environment. Here, we explored genomic divergence in four sympatric southern African decapod crustaceans whose ranges span the boundary between the cool-temperate west coast (south-eastern Atlantic) and the warm-temperate south coast (south-western Indian Ocean) near the southern tip of the African continent. Using genome-wide data, we found that all four species comprise distinct west coast and south coast ecotypes, with molecular dating suggesting divergence during the Pleistocene. Transcriptomic data from the hepatopancreas of twelve specimens of one of these species, the mudprawn Upogebia africana, which were exposed to either 10 °C or 20 °C, showed a clear difference in gene expression profiles between the west- and south coast ecotypes. This difference was particularly clear at 10 °C, where individuals from the south coast experienced a 'transcriptomic shock'. This low temperature is more typical of the west coast during upwelling events, and the physiological stress experienced by the south coast ecotype under such conditions may explain its absence from that coastline. Our results shed new light on the processes involved in driving genomic divergence and incipient speciation along coastlines with porous dispersal barriers.

Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species

BACKGROUND

As global change and anthropogenic pressures continue to increase, conservation and management increasingly needs to consider species' potential to adapt to novel environmental conditions. Therefore, it is imperative to characterise the main selective forces acting on ecosystems, and how these may influence the evolutionary potential of populations and species. Using a multi-model seascape genomics approach, we compare putative environmental drivers of selection in three sympatric southern African marine invertebrates with contrasting ecology and life histories: Cape urchin (Parechinus angulosus), Common shore crab (Cyclograpsus punctatus), and Granular limpet (Scutellastra granularis).

RESULTS

Using pooled (Pool-seq), restriction-site associated DNA sequencing (RAD-seq), and seven outlier detection methods, we characterise genomic variation between populations along a strong biogeographical gradient. Of the three species, only S. granularis showed significant isolation-by-distance, and isolation-by-environment driven by sea surface temperatures (SST). In contrast, sea surface salinity (SSS) and range in air temperature correlated more strongly with genomic variation in C. punctatus and P. angulosus. Differences were also found in genomic structuring between the three species, with outlier loci contributing to two clusters in the East and West Coasts for S. granularis and P. angulosus, but not for C. punctatus.

CONCLUSION

The findings illustrate distinct evolutionary potential across species, suggesting that species-specific habitat requirements and responses to environmental stresses may be better predictors of evolutionary patterns than the strong environmental gradients within the region. We also found large discrepancies between outlier detection methodologies, and thus offer a novel multi-model approach to identifying the principal environmental selection forces acting on species. Overall, this work highlights how adding a comparative approach to seascape genomics (both with multiple models and species) can elucidate the intricate evolutionary responses of ecosystems to global change.

Instability of natural selection at candidate barrier loci underlying speciation in wood ants

Speciation underlies the generation of novel biodiversity. Yet, there is much to learn about how natural selection shapes genomes during speciation. Selection is assumed to act against gene flow at barrier loci, promoting reproductive isolation. However, evidence for gene flow and selection is often indirect and we know very little about the temporal stability of barrier loci. Here we utilize haplodiploidy to identify candidate male barrier loci in hybrids between two wood ant species. As ant males are haploid, they are expected to reveal recessive barrier loci, which can be masked in diploid females if heterozygous. We then test for barrier stability in a sample collected 10 years later and use survival analysis to provide a direct measure of natural selection acting on candidate male barrier loci. We find multiple candidate male barrier loci scattered throughout the genome. Surprisingly, a proportion of them are not stable after 10 years, natural selection apparently switching from acting against to favouring introgression in the later sample. Instability of the barrier effect and natural selection for introgressed alleles could be due to environment-dependent selection, emphasizing the need to consider temporal variation in the strength of natural selection and the stability of the barrier effect at putative barrier loci in future speciation work.

From refugia to contact: Pine processionary moth hybrid zone in a complex biogeographic setting

Contact zones occur at the crossroad between specific dispersal routes and are facilitated by biogeographic discontinuities. Here, we focused on two Lepidoptera sister species that come in contact near the Turkish Straits System (TSS). We aimed to infer their phylogeographic histories in the Eastern Mediterranean and finely analyze their co-occurrence and hybridization patterns in this biogeographic context. We used molecular mitochondrial and nuclear markers to study 224 individuals from 42 localities. We used discordances between markers and complementary assignment methods to identify and map hybrids and parental individuals. We confirmed the parapatric distribution of Thaumetopoea pityocampa (Lepidoptera: Notodontidae) in the west and Thaumetopoea wilkinsoni in the east and identified a narrow contact zone. We identified several glacial refugia of T. wilkinsoni in southern Turkey with a strong east-west differentiation in this species. Unexpectedly, T. pityocampa crossed the TSS and occur in northern Aegean Turkey and some eastern Greek islands. We found robust evidence of introgression between the two species in a restricted zone in northwestern Turkey, but we did not identify any F1 individuals. The identified hybrid zone was mostly bimodal. The distributions and genetic patterns of the studied species were strongly influenced both by the Quaternary climatic oscillations and the complex geological history of the Aegean region. T. pityocampa and T. wilkinsoni survived the last glacial maximum in disjoint refugia and met in western Turkey at the edge of the recolonization routes. Expanding population of T. wilkinsoni constrained T. pityocampa to the western Turkish shore. Additionally, we found evidence of recurrent introgression by T. wilkinsoni males in several T. pityocampa populations. Our results suggest that some prezygotic isolation mechanisms, such as differences in timing of the adult emergences, might be a driver of the isolation between the sister species.

Comparing Pool-seq, Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost-effective sequencing approaches, namely Pool-seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping-by-sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool-seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool-seq data showed F ST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar F ST estimates, indicating that individual-based approaches provided more congruent results than Pool-seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost-effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.

Measuring Genetic Differentiation from Pool-seq Data

The advent of high throughput sequencing and genotyping technologies enables the comparison of patterns of polymorphisms at a very large number of markers. While the characterization of genetic structure from individual sequencing data remains expensive for many nonmodel species, it has been shown that sequencing pools of individual DNAs (Pool-seq) represents an attractive and cost-effective alternative. However, analyzing sequence read counts from a DNA pool instead of individual genotypes raises statistical challenges in deriving correct estimates of genetic differentiation. In this article, we provide a method-of-moments estimator of [Formula: see text] for Pool-seq data, based on an analysis-of-variance framework. We show, by means of simulations, that this new estimator is unbiased and outperforms previously proposed estimators. We evaluate the robustness of our estimator to model misspecification, such as sequencing errors and uneven contributions of individual DNAs to the pools. Finally, by reanalyzing published Pool-seq data of different ecotypes of the prickly sculpin Cottus asper, we show how the use of an unbiased [Formula: see text] estimator may question the interpretation of population structure inferred from previous analyses.

Identifying genomic hotspots of differentiation and candidate genes involved in the adaptive divergence of pea aphid host races

Identifying the genomic bases of adaptation to novel environments is a long-term objective in evolutionary biology. Because genetic differentiation is expected to increase between locally adapted populations at the genes targeted by selection, scanning the genome for elevated levels of differentiation is a first step towards deciphering the genomic architecture underlying adaptive divergence. The pea aphid Acyrthosiphon pisum is a model of choice to address this question, as it forms a large complex of plant-specialized races and cryptic species, resulting from recent adaptive radiation. Here, we characterized genomewide polymorphisms in three pea aphid races specialized on alfalfa, clover and pea crops, respectively, which we sequenced in pools (poolseq). Using a model-based approach that explicitly accounts for selection, we identified 392 genomic hotspots of differentiation spanning 47.3 Mb and 2,484 genes (respectively, 9.12% of the genome size and 8.10% of its genes). Most of these highly differentiated regions were located on the autosomes, and overall differentiation was weaker on the X chromosome. Within these hotspots, high levels of absolute divergence between races suggest that these regions experienced less gene flow than the rest of the genome, most likely by contributing to reproductive isolation. Moreover, population-specific analyses showed evidence of selection in every host race, depending on the hotspot considered. These hotspots were significantly enriched for candidate gene categories that control host-plant selection and use. These genes encode 48 salivary proteins, 14 gustatory receptors, 10 odorant receptors, five P450 cytochromes and one chemosensory protein, which represent promising candidates for the genetic basis of host-plant specialization and ecological isolation in the pea aphid complex. Altogether, our findings open new research directions towards functional studies, for validating the role of these genes on adaptive phenotypes.

Draft genome and reference transcriptomic resources for the urticating pine defoliator Thaumetopoea pityocampa (Lepidoptera: Notodontidae)

The pine processionary moth Thaumetopoea pityocampa (Lepidoptera: Notodontidae) is the main pine defoliator in the Mediterranean region. Its urticating larvae cause severe human and animal health concerns in the invaded areas. This species shows a high phenotypic variability for various traits, such as phenology, fecundity and tolerance to extreme temperatures. This study presents the construction and analysis of extensive genomic and transcriptomic resources, which are an obligate prerequisite to understand their underlying genetic architecture. Using a well-studied population from Portugal with peculiar phenological characteristics, the karyotype was first determined and a first draft genome of 537 Mb total length was assembled into 68,292 scaffolds (N50 = 164 kb). From this genome assembly, 29,415 coding genes were predicted. To circumvent some limitations for fine-scale physical mapping of genomic regions of interest, a 3X coverage BAC library was also developed. In particular, 11 BACs from this library were individually sequenced to assess the assembly quality. Additionally, de novo transcriptomic resources were generated from various developmental stages sequenced with HiSeq and MiSeq Illumina technologies. The reads were de novo assembled into 62,376 and 63,175 transcripts, respectively. Then, a robust subset of the genome-predicted coding genes, the de novo transcriptome assemblies and previously published 454/Sanger data were clustered to obtain a high-quality and comprehensive reference transcriptome consisting of 29,701 bona fide unigenes. These sequences covered 99% of the cegma and 88% of the busco highly conserved eukaryotic genes and 84% of the busco arthropod gene set. Moreover, 90% of these transcripts could be localized on the draft genome. The described information is available via a genome annotation portal (http://bipaa.genouest.org/sp/thaumetopoea_pityocampa/).