Ecological genetics of isolated loach populations indicate compromised adaptive potential

Many endangered species live in fragmented and isolated populations with low genetic variability, signs of inbreeding, and small effective population sizes - all features elevating their extinction risk. The flat-headed loach (Oreonectes platycephalus), a small noemacheilid fish, is widely across southern China, but only in the headwaters of hillstreams; as a result, they are spatially isolated from conspecific populations. We surveyed single nucleotide polymorphisms in 16 Hong Kong populations of O. platycephalus to determine whether loach populations from different streams were genetically isolated from each other, showed low levels of genetic diversity, signs of inbreeding, and had small contemporary effective population sizes. Estimates of average observed heterozygosity (HO = 0.0473), average weighted nucleotide diversity (πw = 0.0546) and contemporary effective population sizes (Ne = 10.2 ~ 129.8) were very low, and several populations showed clear signs of inbreeding as judged from relatedness estimates. The degree of genetic differentiation among populations was very high (average FST = 0.668), even over short geographic distances (<1.5 km), with clear patterns of isolation by distance. These results suggest that Hong Kong populations of O. platycephalus have experienced strong genetic drift and loss of genetic variability because sea-level rise after the last glaciation reduced connectedness among paleodrainages, isolating populations in headwaters. All this, together with the fact that the levels of genetic diversity and contemporary effective population sizes within O. platycephalus populations are lower than most other freshwater fishes, suggests that they face high local extinction risk and have limited capacity for future adaptation.

Estimation of contemporary effective population size in plant populations: Limitations of genomic datasets

Effective population size (N e) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate N e have been preferred over demographic methods because they rely on genetic data rather than time-consuming ecological monitoring. Methods based on linkage disequilibrium (LD), in particular, have become popular in conservation as they require a single sampling and provide estimates that refer to recent generations. A software program based on the LD method, GONE, looks particularly promising to estimate contemporary and recent-historical N e (up to 200 generations in the past). Genomic datasets from non-model species, especially plants, may present some constraints to the use of GONE, as linkage maps and reference genomes are seldom available, and SNP genotyping is usually based on reduced-representation methods. In this study, we use empirical datasets from four plant species to explore the limitations of plant genomic datasets when estimating N e using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect N e estimation using the LD method, such as the occurrence of population structure. We show how accuracy and precision of N e estimates potentially change with the following factors: occurrence of missing data, limited number of SNPs/individuals sampled, and lack of information about the location of SNPs on chromosomes, with the latter producing a significant bias, previously unexplored with empirical data. We finally compare the N e estimates obtained with GONE for the last generations with the contemporary N e estimates obtained with the programs currentNe and NeEstimator.

Temporal genetic variation mediated by climate change-induced salinity decline, a study on Artemia (Crustacea: Anostraca) from Kyêbxang Co, a high altitude salt lake on the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau is one of the areas the richest in salt lakes and Artemia sites. As a result of climate warming and wetting, the areas of salt lakes on the plateau have been increasing, and the salinities have decreased considerably since 1990s. However, the impact of salinity change on the genetic diversity of Artemia is still unknown. Kyêbxang Co is the highest (4620 m above sea level) salt lake currently with commercial harvesting of Artemia resting eggs in the world, and harbors the largest Artemia population on the plateau. Its salinity had dropped from ∼67 ppt in 1998 to ∼39 ppt in 2019. Using 13 microsatellite markers and the mitochondrial cytochrome oxidase submit I (COI) gene, we analyzed the temporal changes of genetic diversity, effective population size and genetic structure of this Artemia population based on samples collected in 1998, 2007 and 2019. Our results revealed a steady decline of genetic diversity and significant genetic differentiation among the sampling years, which may be a consequence of genetic drift and the selection of decreased salinity. A decline of effective population size was also detected, which may be relative to the fluctuation in census population size, skewed sex ratio, and selection of the declined salinity. In 2007 and 2019, the Artemia population showed an excess of heterozygosity and significant deviation from Hardy-Weinberg Equilibrium (p < 0.001), which may be associated with the heterozygote advantage under low salinity. To comprehensively understand the impact of climate warming and wetting on Artemia populations on the plateau, further investigation with broad and intensive sampling are needed.

The genetic status and rescue measure for a geographically isolated population of Amur tigers

The Amur tiger is currently confronted with challenges of anthropogenic development, leading to its population becoming fragmented into two geographically isolated groups: smaller and larger ones. Small and isolated populations frequently face a greater extinction risk, yet the small tiger population's genetic status and survival potential have not been assessed. Here, a total of 210 samples of suspected Amur tiger feces were collected from this small population, and the genetic background and population survival potentials were assessed by using 14 microsatellite loci. Our results demonstrated that the mean number of alleles in all loci was 3.7 and expected heterozygosity was 0.6, indicating a comparatively lower level of population genetic diversity compared to previously reported studies on other subspecies. The genetic estimates of effective population size (Ne) and the Ne/N ratio were merely 7.6 and 0.152, respectively, representing lower values in comparison to the Amur tiger population in Sikhote-Alin (the larger group). However, multiple methods have indicated the possibility of genetic divergence within our isolated population under study. Meanwhile, the maximum kinship recorded was 0.441, and the mean inbreeding coefficient stood at 0.0868, both of which are higher than those observed in other endangered species, such as the African lion and the grey wolf. Additionally, we have identified a significant risk of future extinction if the lethal equivalents were to reach 6.26, which is higher than that of other large carnivores. Further, our simulation results indicated that an increase in the number of breeding females would enhance the prospects of this population. In summary, our findings provide a critical theoretical basis for further bailout strategies concerning Amur tigers.

Pitfalls and windfalls of detecting demographic declines using population genetics in long-lived species

Detecting recent demographic changes is a crucial component of species conservation and management, as many natural populations face declines due to anthropogenic habitat alteration and climate change. Genetic methods allow researchers to detect changes in effective population size (N e ) from sampling at a single timepoint. However, in species with long lifespans, there is a lag between the start of a decline in a population and the resulting decrease in genetic diversity. This lag slows the rate at which diversity is lost, and therefore makes it difficult to detect recent declines using genetic data. However, the genomes of old individuals can provide a window into the past, and can be compared to those of younger individuals, a contrast that may help reveal recent demographic declines. To test whether comparing the genomes of young and old individuals can help infer recent demographic bottlenecks, we use forward-time, individual-based simulations with varying mean individual lifespans and extents of generational overlap. We find that age information can be used to aid in the detection of demographic declines when the decline has been severe. When average lifespan is long, comparing young and old individuals from a single timepoint has greater power to detect a recent (within the last 50 years) bottleneck event than comparing individuals sampled at different points in time. Our results demonstrate how longevity and generational overlap can be both a hindrance and a boon to detecting recent demographic declines from population genomic data.

Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

Anthropogenic disturbance driving population decline of a dominant tree in East Asia evergreen broadleaved forests over the last 11,000 years

Current biodiversity loss is generally considered to have been caused by anthropogenic disturbance, but it is unclear when anthropogenic activities began to affect biodiversity loss. One hypothesis suggests it began with the Industrial Revolution, whereas others propose that anthropogenic disturbance has been associated with biodiversity decline since the early Holocene. To test these hypotheses, we examined the unique vegetation of evergreen broadleaved forests (EBLFs) in East Asia, where humans have affected landscapes since the early Holocene. We adopted a genomic approach to infer the demographic history of a dominant tree (Litsea elongata) of EBLFs. We used Holocene temperature and anthropogenic disturbance factors to calculate the correlation between these variables and the historical effective population size of L. elongata with Spearman statistics and integrated the maximum-entropy niche model to determine the impact of climate change and anthropogenic disturbance on fluctuation in its effective population size. We identified 9 well-defined geographic clades for the populations of L. elongata. Based on the estimated historical population sizes of these clades, all the populations contracted, indicating persistent population decline over the last 11,000 years. Demographic history of L. elongata and human population change, change in cropland use, and change in irrigated rice area were significantly negatively correlated, whereas climate change in the Holocene was not correlated with demographic history. Our results support the early human impact hypothesis and provide comprehensive evidence that early anthropogenic disturbance may contribute to the current biodiversity crisis in East Asia.

High germline mutation rates, but not extreme population outbreaks, influence genetic diversity in a keystone coral predator

Lewontin's paradox, the observation that levels of genetic diversity (π) do not scale linearly with census population size (Nc) variation, is an evolutionary conundrum. The most extreme mismatches between π and Nc are found for highly abundant marine invertebrates. Yet, the influences of new mutations on π relative to extrinsic processes such as Nc fluctuations are unknown. Here, we provide the first germline mutation rate (μ) estimate for a marine invertebrate in corallivorous crown-of-thorns sea stars (Acanthaster cf. solaris). We use high-coverage whole-genome sequencing of 14 parent-offspring trios alongside empirical estimates of Nc in Australia's Great Barrier Reef to jointly examine the determinants of π in populations undergoing extreme Nc fluctuations. The A. cf. solaris mean μ was 9.13 x 10-09 mutations per-site per-generation (95% CI: 6.51 x 10-09 to 1.18 x 10-08), exceeding estimates for other invertebrates and showing greater concordance with vertebrate mutation rates. Lower-than-expected Ne (~70,000-180,000) and low Ne/Nc values (0.0047-0.048) indicated weak influences of population outbreaks on long-term π. Our findings are consistent with elevated μ evolving in response to reduced Ne and generation time length, with important implications for explaining high mutational loads and the determinants of genetic diversity in marine invertebrate taxa.

Conservation genomics analysis reveals recent population decline and possible causes in bumblebee Bombus opulentus

Bumblebees are a genus of pollinators (Bombus) that play important roles in natural ecosystem and agricultural production. Several bumblebee species have been recorded as under population decline, and the proportion of species experiencing population decline within subgenus Thoracobombus is higher than average. Bombus opulentus is 1 species in Thoracobombus, but little is known about its recent population dynamics. Here, we employed conservation genomics methods to investigate the population dynamics of B. opulentus during the recent past and identify the likely environmental factors that may cause population decline. Firstly, we placed the scaffold-level of B. opulentus reference genome sequence onto chromosome-level using Hi-C technique. Then, based on this reference genome and whole-genome resequencing data for 51 B. opulentus samples, we reconstructed the population structure and effective population size (Ne ) trajectories of B. opulentus and identified genes that were under positive selection. Our results revealed that the collected B. opulentus samples could be divided into 2 populations, and 1 of them experienced a recent population decline; the declining population also exhibited lower genetic diversity and higher inbreeding levels. Genes related to high-temperature tolerance, immune response, and detoxication showed signals of positive selection in the declining population, suggesting that climate warming and pathogen/pesticide exposures may contribute to the decline of this B. opulentus population. Taken together, our study provided insights into the demography of B. opulentus populations and highlighted that populations of the same bumblebee species could have contrasting Ne trajectories and population decline could be caused by a combination of various stressors.

Challenges in estimating effective population sizes from metagenome-assembled genomes

Effective population size (Ne) plays a critical role in shaping the relative efficiency between natural selection and genetic drift, thereby serving as a cornerstone for understanding microbial ecological dynamics. Direct Ne estimation relies on neutral genetic diversity within closely related genomes, which is, however, often constrained by the culturing difficulties for the vast majority of prokaryotic lineages. Metagenome-assembled genomes (MAGs) offer a high-throughput alternative for genomic data acquisition, yet their accuracy in Ne estimation has not been fully verified. This study examines the Thermococcus genus, comprising 66 isolated strains and 29 MAGs, to evaluate the reliability of MAGs in Ne estimation. Despite the even distribution across the Thermococcus phylogeny and the comparable internal average nucleotide identity (ANI) between isolate populations and MAG populations, our results reveal consistently lower Ne estimates from MAG populations. This trend of underestimation is also observed in various MAG populations across three other bacterial genera. The underrepresentation of genetic variation in MAGs, including loss of allele frequency data and variable genomic segments, likely contributes to the underestimation of Ne. Our findings underscore the necessity for caution when employing MAGs for evolutionary studies, which often depend on high-quality genome assemblies and nucleotide-level diversity.

Impact of population structure in the estimation of recent historical effective population size by the software GONE

BACKGROUND

Effective population size (Ne) is a crucial parameter in conservation genetics and animal breeding. A recent method, implemented by the software GONE, has been shown to be rather accurate in estimating recent historical changes in Ne from a single sample of individuals. However, GONE estimations assume that the population being studied has remained isolated for a period of time, that is, without migration or confluence of other populations. If this occurs, the estimates of Ne can be heavily biased. In this paper, we evaluate the impact of migration and admixture on the estimates of historical Ne provided by GONE through a series of computer simulations considering several scenarios: (a) the mixture of two or more ancestral populations; (b) subpopulations that continuously exchange individuals through migration; (c) populations receiving migrants from a large source; and (d) populations with balanced systems of chromosomal inversions, which also generate genetic structure.

RESULTS

Our results indicate that the estimates of historical Ne provided by GONE may be substantially biased when there has been a recent mixture of populations that were previously separated for a long period of time. Similarly, biases may occur when the rate of continued migration between populations is low, or when chromosomal inversions are present at high frequencies. However, some biases due to population structuring can be eliminated by conducting population structure analyses and restricting the estimation to the differentiated groups. In addition, disregarding the genomic regions that are involved in inversions can also remove biases in the estimates of Ne.

CONCLUSIONS

Different kinds of deviations from isolation and panmixia of the populations can generate biases in the recent historical estimates of Ne. Therefore, estimation of past demography could benefit from performing population structure analyses beforehand, by mitigating the impact of these biases on historical Ne estimates.

Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations

AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).

Demographic reconstruction of the Western sheep expansion from whole-genome sequences

As one of the earliest livestock, sheep (Ovis aries) were domesticated in the Fertile Crescent about 12,000-10,000 years ago and have a nearly worldwide distribution today. Most of our knowledge about the timing of their expansions stems from archaeological data but it is unclear how the genetic diversity of modern sheep fits with these dates. We used whole-genome sequencing data of 63 domestic breeds and their wild relatives, the Asiatic mouflon (O. gmelini, previously known as O. orientalis), to explore the demographic history of sheep. On the global scale, our analysis revealed geographic structuring among breeds with unidirectional recent gene flow from domestics into Asiatic mouflons. We then selected 4 representative breeds from Spain, Morocco, the United Kingdom, and Iran to build a comprehensive demographic model of the Western sheep expansion. We inferred a single domestication event around 11,000 years ago. The subsequent westward expansion is dated to approximately 7,000 years ago, later than the original Neolithic expansion of sheep and slightly predating the Secondary Product Revolution associated with wooly sheep. We see some signals of recent gene flow from an ancestral population into Southern European breeds which could reflect admixture with feral European mouflon. Furthermore, our results indicate that many breeds experienced a reduction of their effective population size during the last centuries, probably associated with modern breed development. Our study provides insights into the complex demographic history of Western Eurasian sheep, highlighting interactions between breeds and their wild counterparts.

Population genomics reveals how 5 ka of human occupancy led the Lima leaf-toed gecko (Phyllodactylus sentosus) to the brink of extinction

Small species with high home fidelity, high ecological specialization or low vagility are particularly prone to suffer from habitat modification and fragmentation. The Lima leaf-toed gecko (Phyllodactylus sentosus) is a critically endangered Peruvian species that shelters mostly in pre-Incan archeological areas called huacas, where the original environmental conditions are maintained. We used genotyping by sequencing to understand the population genomic history of P. sentosus. We found low genetic diversity (He 0.0406-0.134 and nucleotide diversity 0.0812-0.145) and deviations of the observed heterozygosity relative to the expected heterozygosity in some populations (Fis - 0.0202 to 0.0187). In all analyses, a clear population structuring was observed that cannot be explained by isolation by distance alone. Also, low levels of historical gene flow were observed between most populations, which decreased as shown in contemporary migration rate analysis. Demographic inference suggests these populations experienced bottleneck events during the last 5 ka. These results indicate that habitat modification since pre-Incan civilizations severely affected these populations, which currently face even more drastic urbanization threats. Finally, our predictions show that this species could become extinct in a decade without further intervention, which calls for urgent conservation actions being undertaken.

Functional genomic diversity is correlated with neutral genomic diversity in populations of an endangered rattlesnake

Theory predicts that genetic erosion in small, isolated populations of endangered species can be assessed using estimates of neutral genetic variation, yet this widely used approach has recently been questioned in the genomics era. Here, we leverage a chromosome-level genome assembly of an endangered rattlesnake (Sistrurus catenatus) combined with whole genome resequencing data (N = 110 individuals) to evaluate the relationship between levels of genome-wide neutral and functional diversity over historical and future timescales. As predicted, we found positive correlations between genome-wide estimates of neutral genetic diversity (π) and inferred levels of adaptive variation and an estimate of inbreeding mutation load, and a negative relationship between neutral diversity and an estimate of drift mutation load. However, these correlations were half as strong for projected future levels of neutral diversity based on contemporary effective population sizes. Broadly, our results confirm that estimates of neutral genetic diversity provide an accurate measure of genetic erosion in populations of a threatened vertebrate. They also provide nuance to the neutral-functional diversity controversy by suggesting that while these correlations exist, anthropogenetic impacts may have weakened these associations in the recent past and into the future.

Genomic signatures of convergent shifts to plunge-diving behavior in birds

Understanding the genetic basis of convergence at broad phylogenetic scales remains a key challenge in biology. Kingfishers (Aves: Alcedinidae) are a cosmopolitan avian radiation with diverse colors, diets, and feeding behaviors-including the archetypal plunge-dive into water. Given the sensory and locomotor challenges associated with air-water transitions, kingfishers offer a powerful opportunity to explore the effects of convergent behaviors on the evolution of genomes and phenotypes, as well as direct comparisons between continental and island lineages. Here, we use whole-genome sequencing of 30 diverse kingfisher species to identify the genomic signatures associated with convergent feeding behaviors. We show that species with smaller ranges (i.e., on islands) have experienced stronger demographic fluctuations than those on continents, and that these differences have influenced the dynamics of molecular evolution. Comparative genomic analyses reveal positive selection and genomic convergence in brain and dietary genes in plunge-divers. These findings enhance our understanding of the connections between genotype and phenotype in a diverse avian radiation.

Genomics of plant speciation

Studies of plants have been instrumental for revealing how new species originate. For several decades, botanical research has complemented and, in some cases, challenged concepts on speciation developed via the study of other organisms while also revealing additional ways in which species can form. Now, the ability to sequence genomes at an unprecedented pace and scale has allowed biologists to settle decades-long debates and tackle other emerging challenges in speciation research. Here, we review these recent genome-enabled developments in plant speciation. We discuss complications related to identification of reproductive isolation (RI) loci using analyses of the landscape of genomic divergence and highlight the important role that structural variants have in speciation, as increasingly revealed by new sequencing technologies. Further, we review how genomics has advanced what we know of some routes to new species formation, like hybridization or whole-genome duplication, while casting doubt on others, like population bottlenecks and genetic drift. While genomics can fast-track identification of genes and mutations that confer RI, we emphasize that follow-up molecular and field experiments remain critical. Nonetheless, genomics has clarified the outsized role of ancient variants rather than new mutations, particularly early during speciation. We conclude by highlighting promising avenues of future study. These include expanding what we know so far about the role of epigenetic and structural changes during speciation, broadening the scope and taxonomic breadth of plant speciation genomics studies, and synthesizing information from extensive genomic data that have already been generated by the plant speciation community.

Assessment of the Global Variance Effective Size of Subdivided Populations, and Its Relation to Other Effective Sizes

The variance effective population size ([Formula: see text]) is frequently used to quantify the expected rate at which a population's allele frequencies change over time. The purpose of this paper is to find expressions for the global [Formula: see text] of a spatially structured population that are of interest for conservation of species. Since [Formula: see text] depends on allele frequency change, we start by dividing the cause of allele frequency change into genetic drift within subpopulations (I) and a second component mainly due to migration between subpopulations (II). We investigate in detail how these two components depend on the way in which subpopulations are weighted as well as their dependence on parameters of the model such a migration rates, and local effective and census sizes. It is shown that under certain conditions the impact of II is eliminated, and [Formula: see text] of the metapopulation is maximized, when subpopulations are weighted proportionally to their long term reproductive contributions. This maximal [Formula: see text] is the sought for global effective size, since it approximates the gene diversity effective size [Formula: see text], a quantifier of the rate of loss of genetic diversity that is relevant for conservation of species and populations. We also propose two novel versions of [Formula: see text], one of which (the backward version of [Formula: see text]) is most stable, exists for most populations, and is closer to [Formula: see text] than the classical notion of [Formula: see text]. Expressions for the optimal length of the time interval for measuring genetic change are developed, that make it possible to estimate any version of [Formula: see text] with maximal accuracy.

Strong Positive Selection Biases Identity-By-Descent-Based Inferences of Recent Demography and Population Structure in Plasmodium falciparum

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD). Yet, strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we utilized simulations, a true IBD inference algorithm, and empirical datasets from different malaria transmission settings to investigate the extent of such bias and explore potential correction strategies. We analyzed whole genome sequence data generated from 640 new and 4,026 publicly available Plasmodium falciparum clinical isolates. Our findings demonstrated that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discovered that the removal of IBD peak regions partially restored the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

Population Genomics for Insect Conservation

Insects constitute vital components of ecosystems. There is alarming evidence for global declines in insect species diversity, abundance, and biomass caused by anthropogenic drivers such as habitat degradation or loss, agricultural practices, climate change, and environmental pollution. This raises important concerns about human food security and ecosystem functionality and calls for more research to assess insect population trends and identify threatened species and the causes of declines to inform conservation strategies. Analysis of genetic diversity is a powerful tool to address these goals, but so far animal conservation genetics research has focused strongly on endangered vertebrates, devoting less attention to invertebrates, such as insects, that constitute most biodiversity. Insects' shorter generation times and larger population sizes likely necessitate different analytical methods and management strategies. The availability of high-quality reference genome assemblies enables population genomics to address several key issues. These include precise inference of past demographic fluctuations and recent declines, measurement of genetic load levels, delineation of evolutionarily significant units and cryptic species, and analysis of genetic adaptation to stressors. This enables identification of populations that are particularly vulnerable to future threats, considering their potential to adapt and evolve. We review the application of population genomics to insect conservation and the outlook for averting insect declines.

Population-genomic analyses reveal bottlenecks and asymmetric introgression from Persian into iron walnut during domestication

Background

Persian walnut, Juglans regia, occurs naturally from Greece to western China, while its closest relative, the iron walnut, Juglans sigillata, is endemic in southwest China; both species are cultivated for their nuts and wood. Here, we infer their demographic histories and the time and direction of possible hybridization and introgression between them.

Results

We use whole-genome resequencing data, different population-genetic approaches (PSMC and GONE), and isolation-with-migration models (IMa3) on individuals from Europe, Iran, Kazakhstan, Pakistan, and China. IMa3 analyses indicate that the two species diverged from each other by 0.85 million years ago, with unidirectional gene flow from eastern J. regia and its ancestor into J. sigillata, including the shell-thickness gene. Within J. regia, a western group, located from Europe to Iran, and an eastern group with individuals from northern China, experienced dramatically declining population sizes about 80 generations ago (roughly 2400 to 4000 years), followed by an expansion at about 40 generations, while J. sigillata had a constant population size from about 100 to 20 generations ago, followed by a rapid decline.

Conclusions

Both J. regia and J. sigillata appear to have suffered sudden population declines during their domestication, suggesting that the bottleneck scenario of plant domestication may well apply in at least some perennial crop species. Introgression from introduced J. regia appears to have played a role in the domestication of J. sigillata.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02720-z.

What is N e, anyway?

Few doubt that effective population size (Ne) is one of the most important parameters in evolutionary biology, but how many can say they really understand the concept? Ne is the evolutionary analogue of the number of individuals (or adults) in the population, N. Whereas ecological consequences of population size depend on N, evolutionary consequences (rates of loss of genetic diversity and increase in inbreeding; relative effectiveness of selection) depend on Ne. Formal definitions typically relate effective size to a key population genetic parameter, such as loss of heterozygosity or variance in allele frequency. However, for practical application to real populations, it is more useful to define Ne in terms of three demographic parameters: number of potential parents (adult N), and mean and variance in offspring number. Defined this way, Ne determines the rate of random genetic drift across the entire genome in the offspring generation. Other evolutionary forces (mutation, migration, selection)—together with factors such as variation in recombination rate—can also affect genetic variation, and this leads to heterogeneity across the genome in observed rates of genetic change. For some, it has been convenient to interpret this heterogeneity in terms of heterogeneity in Ne, but unfortunately this has muddled the concepts of genetic drift and effective population size. A commonly-repeated misconception is that Ne is the number of parents that actually contribute genes to the next generation (NP). In reality, NP can be smaller or larger than Ne, and the NP/Ne ratio depends on the sex ratio, the mean and variance in offspring number, and whether inbreeding or variance Ne is of interest.

Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well‐being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within‐species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (N_e). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large‐scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long‐term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

OUP accepted manuscript

The nearly neutral theory is a common framework to describe natural selection at the molecular level. This theory emphasizes the importance of slightly deleterious mutations by recognizing their ability to segregate and eventually get fixed due to genetic drift in spite of the presence of purifying selection. As genetic drift is stronger in smaller than in larger populations, a correlation between population size and molecular measures of natural selection is expected within the nearly neutral theory. However, this hypothesis was originally formulated under equilibrium conditions. As most natural populations are not in equilibrium, testing the relationship empirically may lead to confounded outcomes. Demographic nonequilibria, for instance following a change in population size, are common scenarios that are expected to push the selection–drift relationship off equilibrium. By explicitly modeling the effects of a change in population size on allele frequency trajectories in the Poisson random field framework, we obtain analytical solutions of the nonstationary allele frequency spectrum. This enables us to derive exact results of measures of natural selection and effective population size in a demographic nonequilibrium. The study of their time-dependent relationship reveals a substantial deviation from the equilibrium selection–drift balance after a change in population size. Moreover, we show that the deviation is sensitive to the combination of different measures. These results therefore constitute relevant tools for empirical studies to choose suitable measures for investigating the selection–drift relationship in natural populations. Additionally, our new modeling approach extends existing population genetics theory and can serve as foundation for methodological developments.