The estimates of effective population size based on linkage disequilibrium are virtually unaffected by natural selection

Consequences of domestication in eastern oyster: Insights from whole genomic analyses

Selective breeding for production traits has yielded relatively rapid successes with high-fecundity aquaculture species. Discovering the genetic changes associated with selection is an important goal for understanding adaptation and can also facilitate better predictions about the likely fitness of selected strains if they escape aquaculture farms. Here, we hypothesize domestication as a genetic change induced by inadvertent selection in culture. Our premise is that standardized culture protocols generate parallel domestication effects across independent strains. Using eastern oyster as a model and a newly developed 600K SNP array, this study tested for parallel domestication effects in multiple independent selection lines compared with their progenitor wild populations. A single contrast was made between pooled selected strains (1-17 generations in culture) and all wild progenitor samples combined. Population structure analysis indicated rank order levels of differentiation as [wild - wild] < [wild - cultured] < [cultured - cultured]. A genome scan for parallel adaptation to the captive environment applied two methodologically distinct outlier tests to the wild versus selected strain contrast and identified a total of 1174 candidate SNPs. Contrasting wild versus selected strains revealed the early evolutionary consequences of domestication in terms of genomic differentiation, standing genetic diversity, effective population size, relatedness, runs of homozygosity profiles, and genome-wide linkage disequilibrium patterns. Random Forest was used to identify 37 outlier SNPs that had the greatest discriminatory power between bulked wild and selected oysters. The outlier SNPs were in genes enriched for cytoskeletal functions, hinting at possible traits under inadvertent selection during larval culture or pediveliger setting at high density. This study documents rapid genomic changes stemming from hatchery-based cultivation of eastern oysters, identifies candidate loci responding to domestication in parallel among independent aquaculture strains, and provides potentially useful genomic resources for monitoring interbreeding between farm and wild oysters.

Global assessment of effective population sizes: Consistent taxonomic differences in meeting the 50/500 rule

Effective population size (Ne) is a particularly useful metric for conservation as it affects genetic drift, inbreeding and adaptive potential within populations. Current guidelines recommend a minimum Ne of 50 and 500 to avoid short-term inbreeding and to preserve long-term adaptive potential respectively. However, the extent to which wild populations reach these thresholds globally has not been investigated, nor has the relationship between Ne and human activities. Through a quantitative review, we generated a dataset with 4610 georeferenced Ne estimates from 3829 populations, extracted from 723 articles. These data show that certain taxonomic groups are less likely to meet 50/500 thresholds and are disproportionately impacted by human activities; plant, mammal and amphibian populations had a <54% probability of reachingN ̂ e = 50 and a <9% probability of reachingN ̂ e = 500. Populations listed as being of conservation concern according to the IUCN Red List had a smaller medianN ̂ e than unlisted populations, and this was consistent across all taxonomic groups.N ̂ e was reduced in areas with a greater Global Human Footprint, especially for amphibians, birds and mammals, however relationships varied between taxa. We also highlight several considerations for future works, including the role that gene flow and subpopulation structure plays in the estimation ofN ̂ e in wild populations, and the need for finer-scale taxonomic analyses. Our findings provide guidance for more specific thresholds based on Ne and help prioritise assessment of populations from taxa most at risk of failing to meet conservation thresholds.

Genomic diversity of the locally developed Latvian Darkheaded sheep breed

The Latvian Darkheaded is the only locally developed sheep breed. The breed was formed at the beginning of the 20th century by crossing local coarse-wooled sheep with the British Shropshire and Oxfordshire breeds. The breed was later improved by adding Ile-de-France, Texel, German blackheads, and Finnsheep to achieve higher prolificacy and better meat quality. Previous studies have reported the Latvian Darkheaded sheep to be closely related to Estonian and Lithuanian Blackface breeds, according to microsatellite data. To expand our knowledge of the genetic resources of the Latvian Darkheaded breed, we conducted a whole-genome resequencing analysis on 40 native sheep. The investigation showed that local sheep harbor genetic diversity levels similar to those observed among other improved breeds of European origin, including Charollais and Suffolk. Genome-wide nucleotide diversity (π) in Latvian Darkheaded sheep was 3.91 × 10-3, whereas the average observed heterozygosity among the 40 animals was 0.267 and 0.438 within the subsample of unrelated individuals. The Ne has rapidly decreased to 200 ten generations ago with a recent drop to Ne 73 four generations ago. However, inbreeding levels based on runs of homozygosity were, on average, low, with FROH ranging between 0.016 and 0.059. The analysis of the genomic composition of the breed confirmed shared ancestry with sheep of British origin, reflecting the history of the breed. Nevertheless, Latvian Darkheaded sheep were genetically separable. The contemporary Latvian Darkheaded sheep population is genetically diverse with a low inbreeding rate. However, further development of breed management programs is necessary to prevent an increase in inbreeding, loss of genetic diversity, and depletion of breed-specific genetic resources, ensuring the preservation of the native Latvian Darkheaded sheep.

Comparative assessment of the effective population size and linkage disequilibrium of Karan Fries cattle revealed viable population dynamics

OBJECTIVE

Karan Fries (KF), a high-producing composite cattle was developed through crossing indicine Tharparkar cows with taurine bulls (Holstein Friesian, Brown Swiss, and Jersey), to increase the milk yield across India. This composite cattle population must maintain sufficient genetic diversity for long-term development and breed improvement in the coming years. The level of linkage disequilibrium (LD) measures the influence of population genetic forces on the genomic structure and provides insights into the evolutionary history of populations, while the decay of LD is important in understanding the limits of genome-wide association studies for a population. Effective population size (Ne) which is genomically based on LD accumulated over the course of previous generations, is a valuable tool for e valuation of the genetic diversity and level of inbreeding. The present study was undertaken to understand KF population dynamics through the estimation of Ne and LD for the longterm sustainability of these breeds.

METHODS

The present study included 96 KF samples genotyped using Illumina HDBovine array to estimate the effective population and examine the LD pattern. The genotype data were also obtained for other crossbreds (Santa Gertrudis, Brangus, and Beefmaster) and Holstein Friesian cattle for comparison purposes.

RESULTS

The average LD between single nucleotide polymorphisms (SNPs) was r2 = 0.13 in the present study. LD decay (r2 = 0.2) was observed at 40 kb inter-marker distance, indicating a panel with 62,765 SNPs was sufficient for genomic breeding value estimation in KF cattle. The pedigree-based Ne of KF was determined to be 78, while the Ne estimates obtained using LD-based methods were 52 (SNeP) and 219 (genetic optimization for Ne estimation), respectively.

CONCLUSION

KF cattle have an Ne exceeding the FAO's minimum recommended level of 50, which was desirable. The study also revealed significant population dynamics of KF cattle and increased our understanding of devising suitable breeding strategies for longterm sustainable development.

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.

Practical application of the linkage disequilibrium method for estimating contemporary effective population size: A review

The method to estimate contemporary effective population size (Ne ) based on patterns of linkage disequilibrium (LD) at unlinked loci has been widely applied to natural and managed populations. The underlying model makes many simplifying assumptions, most of which have been evaluated in numerous studies published over the last two decades. Here, these performance evaluations are reviewed and summarized, with a focus on information that facilitates practical application to real populations in nature. Potential sources of bias that are discussed include calculation of r2 (a measure of LD), adjustments for sampling error, physical linkage, age structure, migration and spatial structure, mutation and selection, mating systems, changes in abundance, rare alleles, missing data, genotyping errors, data filtering choices and methods for combining multiple Ne estimates. Factors that affect precision are reviewed, including pseudoreplication that limits the information gained from large genomics datasets, constraints imposed by small samples of individuals, and the challenges in obtaining robust estimates for large populations. Topics that merit further research include the potential to weight r2 values by allele frequency, lump samples of individuals, use genotypic likelihoods rather than called genotypes, prune large LD values and apply the method to species practising partial monogamy.

Estimation of the contemporary effective population size from SNP data while accounting for mating structure

A new method is developed to estimate the contemporary effective population size (Ne ) from linkage disequilibrium (LD) between SNPs without information on their location, which is the usual scenario in non-model species. The general theory of linkage disequilibrium is extended to include the contribution of full-sibs to the measure of LD, leading naturally to the estimation of Ne in monogamous and polygamous mating systems, as well as in multiparous species, and with non-random distributions of full-sib family size due to selection or other causes. Prediction of confidence intervals for Ne estimates was solved using a small artificial neural network trained on a dataset of over 105 simulation results. The method, implemented in a user-friendly and fast software (currentNe), is able to estimate Ne even in problematic scenarios with large population sizes or small sample sizes and provides confidence intervals that are more consistent than resampling methods.

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.

An empirical test of the estimation of historical effective population size using Drosophila melanogaster

The availability of a large number of high-density markers (SNPs) allows the estimation of historical effective population size (Ne ) from linkage disequilibrium between loci. A recent refinement of methods to estimate historical Ne from the recent past has been shown to be rather accurate with simulation data. The method has also been applied to real data for numerous species. However, the simulation data cannot encompass all the complexities of real genomes, and the performance of any estimation method with real data is always uncertain, as the true demography of the populations is not known. Here, we carried out an experimental design with Drosophila melanogaster to test the method with real data following a known demographic history. We used a population maintained in the laboratory with a constant census size of about 2800 individuals and subjected the population to a drastic decline to a size of 100 individuals. After a few generations, the population was expanded back to the previous size and after a few further generations again expanded to twice the initial size. Estimates of historical Ne were obtained with the software GONE both for autosomal and X chromosomes from samples of 17 individuals sequenced for the whole genome. Estimates of the historical effective size were able to infer the patterns of changes that occurred in the populations showing generally good performance of the method. We discuss the limitations of the method and the application of the software carried out so far.

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.

Resurrection genomics provides molecular and phenotypic evidence of rapid adaptation to salinization in a keystone aquatic species

Ecologists and evolutionary biologists are increasingly cognizant of rapid adaptation in wild populations. Rapid adaptation to anthropogenic environmental change is critical for maintaining biodiversity and ecosystems services into the future. Anthropogenic salinization of freshwater ecosystems is quickly emerging as a primary threat, which is well documented in the northern temperate ecoregion. Specifically, many northern temperate lakes have undergone extensive salinization because of urbanization and the associated increase in impervious surfaces causing runoff, and the extensive use of road deicing salts (e.g., NaCl). It remains unclear whether increasing salinization will lead to extirpation of species from these systems. Using a "resurrection genomics" approach, we investigated whether the keystone aquatic herbivore, Daphnia pulicaria, has evolved increased salinity tolerance in a severely salinized lake located in Minnesota, USA. Whole-genome resequencing of 54 Daphnia clones from the lake and hatched from resting eggs that represent a 25-y temporal contrast demonstrates that many regions of the genome containing genes related to osmoregulation are under selection in the study population. Tolerance assays of clones revealed that the most recent clones are more tolerant to salinity than older clones; this pattern is concomitant with the temporal pattern of stabilizing salinity in this lake. Together, our results demonstrate that keystone species such as Daphnia can rapidly adapt to increasing freshwater salinization. Further, our results indicate that rapid adaptation to salinity may allow lake Daphnia populations to persist in the face of anthropogenic salinization maintaining the food webs and ecosystem services they support despite global environmental change.

Estimation of Linkage Disequilibrium, Effective Population Size, and Genetic Parameters of Phenotypic Traits in Dabieshan Cattle

Dabieshan cattle (DBSC) are a valuable genetic resource for indigenous cattle breeds in China. It is a small to medium-sized breed with slower growth, but with good meat quality and fat deposition. Genetic markers could be used for the estimation of population genetic structure and genetic parameters. In this work, we genotyped the DBSC breeding population (n = 235) with the GeneSeek Genomic Profiler (GGP) 100 k density genomic chip. Genotype data of 222 individuals and 81,579 SNPs were retained after quality control. The average minor allele frequency (MAF) was 0.20 and the average linkage disequilibrium (LD) level (r²) was 0.67 at a distance of 0-50 Kb. The estimated relationship coefficient and effective population size (Ne) were 0.023 and 86 for the current generation. In addition, we used genotype data to estimate the genetic parameters of the population's phenotypic traits. Among them, height at hip cross (HHC) and shin circumference (SC) were rather high heritability traits, with heritability of 0.41 and 0.54, respectively. The results reflected the current cattle population's extent of inbreeding and history. Through the principal breeding parameters, genomic breeding would significantly improve the genetic progress of breeding.

Population dynamics of Baltic herring since the Viking Age revealed by ancient DNA and genomics

The world's oceans are currently facing major stressors in the form of overexploitation and anthropogenic climate change. The Baltic Sea was home to the first "industrial" fishery ∼800 y ago targeting the Baltic herring, a species that is still economically and culturally important today. Yet, the early origins of marine industries and the long-term ecological consequences of historical and contemporary fisheries remain debated. Here, we study long-term population dynamics of Baltic herring to evaluate the past impacts of humans on the marine environment. We combine modern whole-genome data with ancient DNA (aDNA) to identify the earliest-known long-distance herring trade in the region, illustrating that extensive fish trade began during the Viking Age. We further resolve population structure within the Baltic and observe demographic independence for four local herring stocks over at least 200 generations. It has been suggested that overfishing at Øresund in the 16th century resulted in a demographic shift from autumn-spawning to spring-spawning herring dominance in the Baltic. We show that while the Øresund fishery had a negative impact on the western Baltic herring stock, the demographic shift to spring-spawning dominance did not occur until the 20th century. Instead, demographic reconstructions reveal population trajectories consistent with expected impacts of environmental change and historical reports on shifting fishing targets over time. This study illustrates the joint impact of climate change and human exploitation on marine species as well as the role historical ecology can play in conservation and management policies.

Conservation Genomic Analysis of the Asian Honeybee in China Reveals Climate Factors Underlying Its Population Decline

The Asian honeybee, Apis cerana, is one of the most important native pollinators in Asia. Asian honeybees were believed to be under significant decline in China based on a report in 2005. On the contrary, a recent survey revealed that Asian honeybee populations in China are stable and even slightly increased in some regions. Therefore, the declining status of A. cerana populations in China is still unclear. Taking advantage of the abundant, publicly available genomic data for Asian honeybees in China, we employed conservation genomics methods to understand if Asian honeybee populations in China are declining and what the underlying climate factors are. We reconstructed the changes of effective population size (Ne) within the recent past for 6 population groups of Asian honeybees and found out that only one of them (population in Bomi, Tibet) showed a consistently declining Ne from the last 100 generations to 25 generations. Selective sweep analysis suggests that genes related to the tolerance of low temperatures and strong ultraviolet radiation are under selection in the declining population, indicating that these two climate factors most likely underlie the decline of BM populations during the recent past. Our study provides insights into the dynamic changes of Asian honeybee populations in China and identifies climate factors that underlie its population decline, which is valuable for the conservation of this important pollinator.

Simulation-Based Evaluation of Methods, Data Types, and Temporal Sampling Schemes for Detecting Recent Population Declines

Understanding recent population trends is critical to quantifying species vulnerability and implementing effective management strategies. To evaluate the accuracy of genomic methods for quantifying recent declines (beginning <120 generations ago), we simulated genomic data using forward-time methods (SLiM) coupled with coalescent simulations (msprime) under a number of demographic scenarios. We evaluated both site frequency spectrum (SFS)-based methods (momi2, Stairway Plot) and methods that employ linkage disequilibrium information (NeEstimator, GONE) with a range of sampling schemes (contemporary-only samples, sampling two time points, and serial sampling) and data types (RAD-like data and whole-genome sequencing). GONE and momi2 performed best overall, with >80% power to detect severe declines with large sample sizes. Two-sample and serial sampling schemes could accurately reconstruct changes in population size, and serial sampling was particularly valuable for making accurate inferences when genotyping errors or minor allele frequency cutoffs distort the SFS or under model mis-specification. However, sampling only contemporary individuals provided reliable inferences about contemporary size and size change using either site frequency or linkage-based methods, especially when large sample sizes or whole genomes from contemporary populations were available. These findings provide a guide for researchers designing genomics studies to evaluate recent demographic declines.