Abies nephrolepis (Trautv. ex Maxim.) Maxim. has its southernmost populations in South Korea and they are expected to decline under climate change. To establish a strategic conservation plan, this study aimed to investigate the spatial genetic structure and seed characteristics of A. nephrolepis. We used nine microsatellite markers on 165 individuals of A. nephrolepis and sampled seeds in a southernmost population at Mt. Hambaeksan, South Korea. We observed a high level of heterozygosity, and a simulation study found that sampling 20 individuals was enough to secure sufficient genetic diversity on average. Spatial autocorrelation analysis revealed that individuals had a positive genetic relationship until 30 m. Bayesian clustering models, STRUCTURE and GENELAND, failed to achieve a consensus in the optimal number of population (K), estimating K = 1 and K = 2, respectively. Principal coordinate analysis supported the absence of genetic substructure within the study population. There was a large variance in seed production among mother trees. On average, seeds of A. nephrolepis from Mt. Hambaeksan had a purity of 70.4% and a germination percentage of 32.2%. We found that seed weight was the most effective indicator of seed quality. Mother trees at higher altitudes had poorer purity which is threatening to A. nephrolepis considering the upslope retreat of subalpine species under climate change. Our results provide insights into the interactions among spatial processes, genetic structure, and seed quality within a population of A. nephrolepis. Understanding the spatial genetic structure (SGS) in a population is important because spatial structure influences genetic parameters including mating system, selection, and genetic drift2. Investigating and comparing the SGS through generations offers important clues about historical and demographic forces that have affected the population4. Spatial autocorrelation analysis offers information about the SGS by comparing the structure of a population to a random arrangement and has been applied to various studies5. Bayesian clustering models describe multi-locus genotypes as clines or clusters to infer the SGS or recently created genetic barrier7. Comparing multiple Bayesian clustering models, including both spatial and non-spatial, is informative with additional independent inference methods, such as principal component analysis (PCA) or principal coordinate analysis (PCoA)8. For the investigation of genetic variation, microsatellite markers are commonly used on trees. Microsatellites, also known as simple sequence repeats (SSRs), are highly reproducible, polymorphic, codominant markers9. Microsatellite markers are useful to estimate the relationship or relatedness among individuals of unknown ancestry10 and have an advantage of cost-effectiveness11.In forest trees, 90% or more of the total genetic diversity of a species is often found within individual populations13. Ex-situ conservation has a critical role in providing materials for restoration and preventing extinction, so it gets highly important when additional threats can lead the species to an extinction vortex14. The materials for ex-situ conservation need to be collected from distanced trees to avoid inbreeding and encompass the genetic variation that target populations have15. Typically, the goal of gene conservation is to capture at least one copy of 95% of the common alleles that occur in target populations at frequencies over 0.0515, and it is impractical to set the goal to include whole alleles because it requires a much larger sampling size1. The sampling size to reach this goal differs by species because of the distinct characteristics of each species, including the mating and pollination systems1. Therefore, to establish an appropriate sampling strategy for the target species, we need to understand the pattern and extent of the genetic variation among and within its populations.Integration of genetics into conservation is getting more important as genetic diversity critically contributes to the survival of a species17. Seed characteristics need to be understood to efficiently collect the germplasm for conservation. Seed quality is a major factor that affects the seed sampling strategy17. The important indicators of seed quality include purity, germination percentage, and viability. While germination percentage is more easily tested, some researchers18 argue that viability is more important. They noted that germination percentage can provide imprecise information because we lack knowledge on dormancy and germination. Genetic diversity or genetic structure of the population is another important factor for the establishment of a good seed sampling strategy. An increase in homozygosity leads to embryo death, more empty seeds, and lower viability in various species, including Abies19. Therefore, genetic diversity of the population is at the core of sustainable reproduction and regeneration.For the restoration and conservation of tree species, seeds are the primary source of propagation because most tree species rarely propagate asexually in natureAbies nephrolepis (Trautv. ex Maxim.) Maxim. is a wind-pollinating conifer belonging to the section Balsamea of Abies20. It is naturally distributed in the subalpine or boreal forests of eastern Russia, northeast China, and the Korean peninsula21. It was assessed as Least Concern (LC) in 2010 (published in 2013) according to IUCN Redlist22. The main threat to the species is known to be logging21, but recently, the populations in South Korea have been affected by climate change. The Korea Forest Service noted that A. nephrolepis showed a decline rate of 31% in 2019–2020, which was estimated to be caused by higher temperature and droughts23 It is expected that the potential habitats of A. nephrolepis on the Korean peninsula will decrease to 36.4% by 2070–2099, and most regions in South Korea were expected to be inhabitable24. Populations of A. nephrolepis in South Korea had a low level of genetic differentiation and only about 3–8% of total genetic variation resulted from the variation among populations27. These studies suggest that we could make the conservation more efficient by focusing on several populations.A. nephrolepis. For this, this study had two main objectives: (1) to understand the within-population genetic variation in A. nephrolepis by investigating the genetic diversity and SGS, and (2) to identify the characteristics of seeds in a population. The study was conducted at Mt. Hambaeksan, South Korea, which was the southernmost population having dominant mitochondrial DNA haplotypes of A. nephrolepis28. We will discuss the relationships among genetic variation, seed quality, and spatial process.Our goal was to produce insights that lead to the establishment of an effective conservation plan in a southernmost population of A. nephrolepis at Mt. Hambaeksan  . Genetic diversity indices were also calculated on two different diameter classes . When the values were calculated by the diameter group, BT had Sp = 0.0081 , which was higher than the value obtained from all individuals. However, ST had a lower value of Sp = 0.0021 , and it was not statistically significant. It indicated that the bigger trees had a greater level of SGS. Overall, SGS found in all individuals could have resulted from the SGS in the bigger trees.The FST of 0.009 (p = 0.001), which was a very low level of differentiation. Principal coordinate analysis (PCoA) failed to demonstrate a clear clustering that coincides with the GENELAND result  inferred by two Bayesian clustering models, GENELAND and STRUCTURE, was inconsistent. In 20 independent runs in GENELAND, all runs produced consistent results, K = 2  of 14.55 cm (± 3.86 cm) and the smallest tree had a DBH of 5.2 cm. The mother trees produced 55.77 (± 67.36) cones on average, and there was a huge variance among trees. The least productive tree only produced five cones, while the most productive one produced about 270 cones. Overall, the top 20% of the most productive mother trees produced 61% of the total cones, and 81% of the cones were produced by the top 42% of the mother trees.30. However, the purity was approximately 10% lower than the forest seed standard quality investigated by the Forestry Research Institute of South Korea31, which is now known as the National Institute of Forest Science.The cone and seed characteristics of the sampled mother trees Table  were simBenefiting from the long pre-chilling period, seeds germinated early  nor the number of trees within the distance of spatial autocorrelation (30 m)  was not significantly related to the seed quality.There were also several significant relationships between the mother tree characteristics. The DBH and cone abundance had a positive relationship (r = 0.6053***), and the geographic position was also related to seed quality and quantity . Although Evanno’s ΔK method was developed to improve the detection of the optimal number, it cannot calculate the value at K = 1, therefore Evanno’s ΔK method selects K = 2 more frequentlyA. nephrolepis at Mt. Hambaeksan was not significant and the estimated Sp value (0.0036) was relatively weak compared to the average of outcrossing species (0.0126) or wind-dispersed species (0.0064)39. However, it was akin to Sp values of other species in Abies42. While there was no significant SGS in ST, BT had a stronger SGS. Previous studies found that younger generations of outcrossing species can have a weaker SGS45. According to these studies, an increase in genetic structure towards older life-history stages can result from local selection, historical events, and demographic factors. In this study, BT showed a higher level of inbreeding coefficient (F = 0.036) compared to ST (F = − 0.011). Considering the existence of a transmitting station right near the study area, populations of A. nephrolepis in the study area could have experienced a bottleneck event caused by the anthropogenic disturbance, then slowly recovered the genetic diversity by active gene flow in younger generations. However, we could not observe a clear decrease in the number of alleles in BT : the average annual temperature was about 0.5℃ higher, and annual precipitation was about 100 mm less. There were several studies on the relationship between climate change and seed quality. They found that the increased temperature and moisture stress can reduce the seed yield and quality, causing shortened duration of stigma receptivity48. Temperature irregularity affects the flowering timing, which causes asynchronous flowering within a population49. Therefore, the increased temperature might have affected pollen production or pollination of A. nephrolepis. Especially, the genus Abies lacks pollination drop and uses rainwater as an alternative19. Therefore, decreased precipitation could have decreased pollination success.The seeds and cones of 50. The amount of pollen of A. nephrolepis was not measured in this study, therefore, further studies might offer interesting information about the relationship between age and strobili production. There was a positive correlation between seed weight and seed quality. With this result, prioritizing heavier seeds in propagation seems efficient. For sampling, direct evaluation of seed weight is impossible because it needs post-collection treatment, such as drying or cleaning. Cone weight can be used as a good alternative because it had the strongest correlation with the seed weight and also had a positive relationship with the purity.The correlation analysis between seed characteristics found that more cones existed in trees with bigger DBH. This result corresponds to the previous research that noted, for some species in Pinaceae, older trees produced more cones while younger trees produced more pollenA. nephrolepis under climate change. Several studies expected that the lower limit of subalpine or alpine conifers will retreat upward due to climate change and have a decrease in its central area. The lowest limit of regeneration of Abies georgei Orr had retreated upslope 31 m per decade51, and A. nephrolepis was expected to lose its lowlands habitats52. Considering a decrease in purity at higher altitudes of Mt.Hambaeksan, loss and upward-retreat of habitable areas will result in poor regeneration of A. nephrolepis in South Korea. Therefore, the need for ex-situ conservation gets more important to adapt to climate change.Among the geographic factors, altitude showed a relationship with purity and cone abundance. The decrease in purity along the altitude could have been caused by the decrease in pollen pool. As the study plot was located right below a transmitting station on the summit, the individuals at the high altitude were on margin, therefore had a decreased pollen pool, which leads to poor reproductive success. This leaves important implications in seed production and regeneration of Abies has developed a post-zygotic barrier, it was expected that mother trees having more genetically close pollen trees would have poorer seed quality than the opposite. The insignificance could be because of the sufficient gene exchange among the mother trees. A. nephrolepis was a dominant species in the study plot and occupied the upper canopy. As A. nephrolepis is a predominantly outcrossing wind-dispersed conifer, occupying the upper canopy allows active pollen dispersal.The correlation analysis failed to find a significant relationship between genetic relatedness and seed quality. Because the genus A. nephrolepis at Mt. Hambaeksan. For the ex-situ conservation of A. nephrolepis at Mt. Hambaeksan, materials need to be collected from distant individuals that are at least 30 m away to avoid genetic relatedness. To encompass sufficient genetic diversity, at least 20 individuals have to be sampled within the study population. However, to secure the common alleles at every locus, much more individuals need to be sampled. Keeping sampling individuals distant, over 30 m away, will help reduce the optimal number of sampling. In this study, the 31 mother trees, which were 35 m apart from each other on average, included all common alleles.With this study, we could establish several sampling and management strategies for We could also establish some strategies for seed collection. Although trees with bigger DBH had more cones in a tree, it did not ensure seed quality or genetic diversity. Therefore, cones must be collected from various distant trees, regardless of size. However, the geographical position of the mother trees should be considered. It is better to avoid mother trees on the margin because they could have less gene exchange and lower purity. Within a tree, collecting heavier cones would be effective, as heavier cones have a higher probability of good quality. After the seed cleaning, heavier seeds should be chosen, as they are more likely to germinate.Ex-situ conservation is more emphasized and important for the species under threat, however, for the effective conservation of A. nephroelpis, in-situ conservation should be carried out together. A previous study on the conservation of Taxus cuspidata Sieb. et Zuuc., a species with a similar genetic and geographical distribution pattern to A. nephrolepis, pointed that ex-situ gene conservation might reduce overall genetic diversity and population size53.A. nephrolepis. The flowering individuals had a positive genetic relationship until 30 m, so we concluded 30 m is the optimal sampling distance of A. nephrolepis at Mt. Hambaeksan. The overall extent of the SGS was weak, but it was stronger among individuals in a bigger diameter class. There was no cluster found within the study population, therefore we considered sampling 20 individuals over the site would be enough to secure the genetic diversity of the population. The cones and seeds had similar characteristics to other populations in South Korea. Correlation analysis revealed that the DBH was positively related to the cone abundance and the seed weight was the most effective indicator of the seed quality. The purity was relatively low, and it got lower as the altitude got higher. Mother trees that were genetically closer to other individuals seemed to have poorer seed quality, but it was insignificant.This study aimed to understand the genetic variation and seed characteristics in a southernmost population of A. nephrolepis. This study contributes to the establishment of an effective ex-situ conservation of A. nephrolepis in a southernmost population in South Korea. Further studies including demographic and historical factors, mating systems and pollen dispersal need to be continued for a better understanding of the species. The impact of climate change on the regeneration of A. nephrolepis needs to be studied, as we inferred that higher temperature and upward-shifting reduction of habitats could disturb the healthy seed production.This study investigated SGS and seed quality together in a population of A. nephrolepis at Mt. Hambaeksan, South Korea. The study area was about 5 ha, located on the northern aspect near the mountaintop . Within the plot, all mature flowering individuals were sampled. A. nephrolepis forms strobili and pollinates in April to May, and its seeds mature in September to October54. We defined a mature flowering tree as a tree with cones (strobili) at the time of sampling. We collected fresh needles from 165 individuals .Sampling was carried out in a natural population of DNA was extracted from the fresh needles using QIAGEN DNeasy Plant mini kit  and GeneAll Exgene Plant SV mini kit . We followed the protocol of each kit with slight modifications. The modifications included increasing the time of 65 ℃ incubation and ice incubation to 30 min. The concentration and quality of the genomic DNA were measured with NanoVue Plus .57, As13, and As2058 , 0.04 μM HEX/FAM M13(-19) primer, and 0.2 μM of each reverse and forward primer. PCR programs were performed as described in each reference.For genotyping, nine microsatellite markers, AK87, AK171, AK173, AK176, AK246, AK247, AK25259. Large allele dropout, stutter allele, and null allele were checked and adjusted using MICRO-CHECKER60 with the Oosterhout algorithm, 1000 permutations.Fragment analysis was performed with PCR products by the National Instrumentation Center for Environmental Management (NICEM) in Seoul National University, with GeneScan 500 ROX size standard and ABI 3730 XL DNA Analyzer . Genotypes were scored using Microsatellite 1.4.7 plugin in Geneious Prime 2022.1.161. The number of alleles (A), number of effective alleles (AE), observed heterozygosity (HO), expected heterozygosity (HE), and fixation index (F) were calculated. To identify the degree of isolation by distance (IBD), we performed a Mantel test with 999 permutations between genetic distance and geographic distance of individuals.Genetic diversity indices were calculated using GenAlEx 6.50362. Individuals were randomly sampled with a sampling size of 5–50 and checked whether they confirmed the goal (“success”). The random sampling was permuted 1000 times at each sampling size, and we counted the number of successes during 1000 permutations.A sampling simulation study was performed to find the minimal sampling size that can reach the genetic diversity. Here, the simulation goal was to secure over 95% of common alleles, which appear at over 0.05 frequency in the populations. If the simulated sampling reached the goal, we defined it as “success”. The sampling simulation study was carried out in Python 3.10.6Sp statistic and Bayesian clustering model. This study only sampled adult trees, but we checked whether SGS differs by diameter class within the same life-history stage. To group the individuals into two diameter classes, the median (15.3 cm) of the DBH was used as a criterion. Individuals bigger than the median were grouped into the bigger trees , and the others were grouped into the smaller trees .SGS was investigated by three methods: spatial autocorrelation analysis, 63 was used. The correlation coefficient was calculated using GenAlEx 6.50361. The analysis was performed on even distance classes . Correlograms were plotted at the end point of the distance interval. Statistical significance of r values and correlograms were determined using 999 permutations and 1000 bootstraps, respectively.For spatial autocorrelation analysis, the correlation coefficient (r) of Smouse and PeakallSp statistic, developed by Vekemans and Hardy39, enables the comparison of the extent of SGS among different populations or species. Sp statistic estimates SGS with regression slope of kinship coefficient (Fij) against spatial distance: bF is the regression slope of kinship coefficient on the log of distance and F1 is the mean of Fij between individuals belonging to a first distance interval. SPAGeDi 1.564 was used to calculate the Sp statistic. Fij of Loiselle et al.65 was used, with an even distance class (20 m). Statistical significance of bF and F1 was determined with 10,000 permutations.66 and STRUCTURE67. GENELAND 4.9.2 was performed in R 4.2.0 environment68. Twenty independent Markov chain Monte Carlo (MCMC) runs were performed with 500,000 iterations and 500 thinning intervals. Spatial model and null allele model were assumed under the possibility of having 1–10 populations (K). Correlated frequency model was selected, as it is more appropriate to detect subtle structures with a low differentiation35. There was a burn-in of 200 saved iterations. Among the 20 independent runs, a run with the highest log posterior probability was selected for further analysis. STRUCTURE 2.3.4. was run with 20 independent simulations for each value of K (1–10). The length of the burn-in was set to 100,000, and 100,000 MCMC iterations were run after the burn-in period. Admixture model and correlated frequency model were assumed. With the results, major modes on each K were obtained using CLUMPAK69. To determine the optimal number of K, Pritchard’s method using LnP(K)67 and Evanno’s ΔK method70 were both considered. STRUCTURE HARVESTER71 was used to obtain the results of the two methods. If clusters were detected, FST between the clusters was calculated using the analysis of molecular variance (AMOVA) in GenAlEx 6.50361, and statistical significance was determined using 999 permutations. Principal coordinate analysis (PCoA) was performed as an additional tool to validate the K value. PCoA was also conducted in GenAlEx 6.50361.To identify the genetic clusters within the study population, two different Bayesian clustering methods were used: GENELAND74 , then seeds were extracted and cleaned from the dried cones. After the cleaning, seed potential, percent developed seeds, percent damaged seeds, purity, and 100-seed weight were investigated76. Sixteen seedlings of each mother tree were transplanted to the soil and tested for survivorship in April. Thirty mother trees were used except mother tree M12 . The seeds were placed on 90 mm Petri dishes with two layers of No.2 filter paper . After the pre-chilling, a germination test was conducted in March. Seeds were placed on two layers of No.2 filter paper in a Petri dish . The germination test was carried out for 28 days in a growth chamber  in March 2022. The growth chamber was maintained at 20 °C temperature and 50% of humidity. Eleven hours of dark and 13 h of light were provided every day. Seeds were counted as germinated when a radicle or cotyledon was developed over 1 mm. After the test, germination percentage, mean germination time, and germination energy was calculated  on cone characteristics and (2) on mother tree characteristics. On both levels, we aimed to find which observable characteristics are related to the seed quality and quantity. We used purity and viability to quantify seed quality: Supplementary Information.


Pediculus humanus, is an obligate blood-sucking ectoparasite that has coevolved with humans for millennia. Given the intimate relationship between this parasite and the human host, the study of human lice has the potential to shed light on aspects of human evolution that are difficult to interpret using other biological evidence. In this study, we analyzed the genetic variation in 274 human lice from 25 geographic sites around the world by using nuclear microsatellite loci and female-inherited mitochondrial DNA sequences. Nuclear genetic diversity analysis revealed the presence of two distinct genetic clusters I and II, which are subdivided into subclusters: Ia-Ib and IIa-IIb, respectively. Among these samples, we observed the presence of the two most common louse mitochondrial haplogroups: A and B that were found in both nuclear Clusters I and II. Evidence of nuclear admixture was uncommon (12%) and was predominate in the New World potentially mirroring the history of colonization in the Americas. These findings were supported by novel DIYABC simulations that were built using both host and parasite data to define parameters and models suggesting that admixture between cI and cII was very recent. This pattern could also be the result of a reproductive barrier between these two nuclear genetic clusters. In addition to providing new evolutionary knowledge about this human parasite, our study could guide the development of new analyses in other host-parasite systems.The human louse,  Pediculus humanus, Phthiraptera: Anoplura) is a blood-sucking, wingless, human-specific ectoparasite that is obligate (cannot live without the host) and permanent (complete their life cycle on a host) [Pediculus diverged ca. 5.6 MY ago (MYA), which is contemporaneous with the known divergence of chimps and humans [The human louse ( a host) . This re a host) , 3. In t a host) , 3. Furtd humans . Human hd humans . In cased humans –10. In sd humans . Evolutid humans , 15 and d humans –18. Reced humans . Moreoved humans  described humans . The hypd humans .b (cytb) gene human louse sequences corroborated the presence of these six clades: A, B, C, D, E, and F [The genetic diversity of human lice has been widely studied based on mitochondrial DNA. However, little is known about the nuclear genetic diversity of this human parasite, particularly on a global scale. Early human louse mitochondrial studies revealed the presence of three deeply divergent mtDNA clades or haplogroups named A, B and C , 17, 39.E, and F . Their pE, and F . DespiteE, and F . In thisIn our previous study of louse microsatellite diversity, we only included 75 head lice from 11 geographic sites from four geographic regions . We founThe Institutional Review Board of the University of Florida exempted the study from review (Exemption of Protocol #2009-U-0422) and waived the need for written informed consent of the participants. This exemption is issued based on the United States Department of Health and Human Services (HHS) regulations. Specifically, HHS regulation 45 CFR part 46 applies to research activities involving human subjects. Because louse removal was voluntary and no information was recorded that would allow patients to be identified directly or through identifiers linked to them, the University of Florida waived the need for written informed consent from the participants. Additional information about collection procedures has been included in the Supporting Information section.Sampling details are provided in We followed our DNA extraction protocol as detailed in , 17 in w5’-CACGACGTTGTAAAACGAC-3’) and CAG (5’-CAGTCGGGCGTCATCA-3’), each labeled with a unique fluorescent tag  to co-amplify multiple loci. Locus-specific primers were modified by adding the matching 5′ universal primer sequence tails. The complete set of 15 loci were amplified in four separate 15 μL multiplex-PCR reactions containing 7.5 μL of 2X Master Mix , 0.015–0.15 μL of unlabeled forward primer with tail (10 μM), 0.15–0.8 of unlabeled reverse primer (10 μM), 0.5 μL labelled universal tail primer (10 μM), 1–2 μL of total genomic DNA (10–20 ng) and dH2O added up to the final volume of 15 μL. Two thermal cycling profiles were used, both beginning with initial denaturation at 95°C (5 min) and ending with a final extension of 72°C (40 min). The v1 (touch-down PCR) protocol consisted of 10 cycles of 94°C (30 sec), 60°C/55°C (-0.5°C/cycle) for 45 sec, and 72°C (45 sec) followed by 25 cycles of 94°C (30 sec), 55°C (45 sec), and 72°C (1 min). The v2 protocol consisted of 35 cycles of 94°C (30 sec), 52°C (45 sec), and 72°C (45 sec). PCR products were electrophoresed on 1.5% and 4% agarose gels stained with ethidium bromide and visualized under ultraviolet light. Dilutions in dH2O from amplicons (1:100) were run on an ABI 3730xl 96-capillary sequencer using GeneScan 600 LIZ as an internal size standard (Applied Biosystems) at the University of Florida biotechnology facility (ICBR). Microsatellite genotypes were scored using the GeneMarker version 1.60 software .A total of 15 microsatellite loci were amplified using four multiplexes as described in . We usedc oxidase 1 (COX1) was amplified through polymerase chain reaction (PCR) using the primers H7005 and L6625 [The mitochondrial gene cytochrome nd L6625  as descrp-distances (proportion of nucleotide sites at which two sequences being compared are different) with MEGA 4 [For each louse sample, the forward and reverse sequences were edited manually and aligned using Sequencher 4.5 . Consensus sequences were generated for each sample using both forward and reverse sequences. These new louse COX1 sequences were aligned along with previous sequences of lice used in our previous work . A finalh MEGA 4 . The genh MEGA 4  using PAh MEGA 4  followinO and HE), and the mean FIS over loci per population with significance tested using 1,023 random permutations. For those 11 sites with sample sizes exceeding 8 lice per site, population pairwise FST values were estimated using Arlequin 3.5.22 [FST values were estimated using the permutation procedure with 1,000 permutations.We used the software Arlequin 3.5.1.2  to estimn 3.5.22 . SignifiTo understand how the human louse genetic diversity is distributed around the globe, we used three different methods that are based on the clustering of similar genotypes. First, we used STRUCTURE , a modelK) based on the posterior probabilities given the data and model. Based on the individual multilocus genotypes and the allele frequencies estimated for the reconstructed clusters, each individual’s genome was probabilistically partitioned into membership fractions (q) (ancestry) in each cluster. Admixed ancestry is modeled by assuming that an individual i has inherited some fraction (q) of its genome from ancestors in population k [q-value. For example, individuals with q = 0.5 would likely be first-generation hybrids. We identify possible hybrids based on a q-value threshold of 0.2 as suggested in VäHä and Primmer (2005) [q-value of 0.2 means that individuals with q-value between 0 and < 0.20 or > 0.8 and 1 are classified as non-admixed and any individual with q-value between 0.2 and 0.8 are classified as hybrids. All simulations used 50,000 Markov chain Monte Carlo (MCMC) generations in the burn-in phase and 100,000 generations in the data collection phase. Ten independent runs were performed using default parameters for each K, to ensure equilibrium during burn-in and consistency in estimation of the posterior probabilities. Selection of the number of distinct clusters was based on the evaluation of the ΔK statistic [K produced nearly identical individual membership coefficients. The run with the highest likelihood of the data given the parameter values for the predominant clustering pattern (i.e. the mode) at each K was used for plotting with DISTRUCT [The Bayesian clustering approach implemented in STRUCTURE 2.3.4  uses thelation k . Hybridsr (2005) , where atatistic  using thtatistic . The tenDISTRUCT .This multivariate analysis was conducted using pairwise genetic differences between individuals calculated in GenAlEx 6.5 , 54 to vadegenet’ package 2.1.3 [This analysis was conducted using the ‘ge 2.1.3 , in the ge 2.1.3 . For theWe estimated the allelic richness within each main nuclear STRUCTURE genetic cluster using the rarefaction method implemented in the computer program ADZE  version 1.0 . BecauseP < 0.05 [X2 test to evaluate the fit of the data (frequencies) to any arbitrary set of expected frequencies among the eight geographic regions. All statistical tests were performed with a significance level of α = 0.05.To gain a better understanding of the geographic distribution of the nuclear and mitochondrial diversity, we conducted a set of Kruskal–Wallis nonparametric analyses of variance tests . We inclP < 0.05 . We compFST based) was used to investigate the partitioning of genetic variation between the two nuclear clusters: cI and cII using Arlequin 3.5 [Analysis of molecular variance (AMOVA) considering the number of different microsatellite alleles (quin 3.5 . The staem (where Nem is the indirect measure of gene flow) were based on FST as starting parameters and we used a Brownian mutation model. The data was analyzed using 10 short (104 MCMC steps) and 3 long chains (105 MCMC steps), together with adaptive heating to assure convergence.The historical migration patterns among the genetic clusters identified using the methods describe above were estimated in Migrate-n 3.3.0 using the maximum likelihood approach , 68. MigWe further inferred the demographic history of human lice, based on microsatellite data, using the approximate Bayesian computation (ABC) approach , implemeFor each model, we considered three levels of parasitism: a low level of parasitism with 10 lice per head and only 10% infested  using data sets simulated with the prior distributions of parameters and the observed data as well as data sets from the posterior predictive distribution to check the suitability of the model (scenarios and prior parameters). The posterior probability of each scenario was assessed by performing direct approach and a polychotomous weighted logistic regression that estimates the difference between simulated (from the reference table) and observed data sets , 80 afteO values ranged from 0.032 to 0.524 (average of 0.257) and HE values ranged from 0.248 to 0.706 (average of 0.402), reflecting a general pattern of deficit of heterozygotes   and Netherlands (Neth) (S4 Table in FST of 0.053 was found between sites in New York (Oce) and Tennessee (Nash).The 274 human louse specimens comprising 25 geographic sites through 10 worldwide geographic regions revealed high microsatellite diversity with overall five to 20 alleles per locus and an average of 12 alleles per locus . In the ozygotes . Further0.00001) . OverallWe also obtained the COX1 sequence data from 175 head lice spanning 18 sampling locations throughout nine geographic regions . One hunq-values less than 0.8), with 75% (25 lice) of the hybrids found in the New World.All clustering methods: STRUCTURE, PCoA and DAPC were concordant in identifying the distinct nuclear genetic clusters: Cluster I (cI) with subclusters Ia and Ib and Cluster II (cII) with subclusters IIa and IIb Figs  and S1. K = 2 . When K was increased to 4 a population from Honduras and other parts of the Americas emerged from cluster I as the Ib subcluster, with the other samples remaining in subcluster Ia. This Honduras subcluster (Ib) may be indicative of Native American louse lineage.In the STRUCTURE analysis, after a signal for The Principal Coordinate Analysis (PCoA) supported the two main nuclear genetic clusters and subclusters identified by STRUCTURE, with putative hybrid lice not assigned to either cluster, rather placing hybrids between them . Finallyq-values. Thus, when using the reduced dataset only non-admixed individuals with shared ancestry q-values larger than 0.8 as suggested by [K = 4  were included in a second STRUCTURE simulation to assess the substructure within this cluster. At K = 2, this figure showed the presence of two clusters: one composed of lice from the Old World , and the other of lice from the New World (Americas)  . The fur cluster . At K =  cluster .K = 2 where most of the lice from the Netherlands plus a few others form a distinct cluster (light blue in plot)  . Both thWe estimated the allelic richness per main non-admixed clusters I and II (without hybrids) using the rarefaction method implemented in the computer program ADZE  Version 1.0 . AllelicP < 0.0001). The cluster membership median values were significantly different among: South Asia (SAs), East Asia (EA), Africa-Israel-Spain (AIS), Central America (CA), and Europe (E) (P < 0.05). On the other hand, cluster membership medians values for North America (NA), South America (Sam), and Mesoamerica (MA) were not significantly different. Both nuclear genetic assignment and haplogroup frequencies differed significantly among the eight geographic regions .The combined analysis of the nuclear cluster membership frequency and the mitochondrial haplogroup were plotted using a Correspondence Analysis (CA) and showed the presence of four well defined groups . DimensiΦST = 0.33; P < 0.00). When examining only the non-admixed individuals  the differentiation between cI and cII increased .Hierarchical analyses of molecular variance (AMOVA) employed to explore the distribution of nuclear genetic variation considering the two nuclear genetic clusters: cI and cII revealed significant genetic differentiation between them  could be the result of the retention of ancient polymorphisms due to incomplete lineage sorting (ILS) or admixture from previous isolated lineages. We tested seven different demographic models in which each louse genetic cluster and its hybrids evolve on different human host populations and diverge in tandem with them using the Bayesian computation (ABC) method as implemented in the DIY-ABC package . The modΦST = 0.33; P < 0.00) despite having geographic overlap in either Europe or the Americas. In the Structure analysis at K = 4 each of the two Clusters further split into subclusters: Ia-Ib and IIa-IIb, which were sorted based on their geographical origin . These results are consistent with our previous work where we assessed louse microsatellite genetic diversity in fewer samples from only four geographic regions  [In this study, we found that the nuclear microsatellite data from lice were grouped in two distinct genetic clusters: cI and cII. Cluster I had a worldwide distribution whereas cII was restricted to Europe and the Americas . Remarka Europe) . Both th Europe) –83  . This woHelicobacter pylori, which infects the stomach of humans, has been studied to provide insights into human migrations and strong correlations between the parasite and human host have been found reflecting the out of Africa expansion [Pediculus humanus, is one of the most well studied human parasites [Other human parasites have also shed light into different aspects of human evolution –13. For xpansion , 85, thexpansion , and thexpansion . Howeverxpansion . Thus, sxpansion  and licexpansion , 3, thatarasites , 21–28.Human lice can disperse from a host to another at any motile stage (nymphs and adults), however adults are more likely to transfer from one head to another . Lice caP. h. humanus ceased to lay eggs at temperatures beneath 20ºC and lay rapidly at 37ºC. These conditions lead to a mean life span of 16 days and 27 days, respectively [We performed ABC analyses for seven demographic models, three different levels of parasitism and three different generational times Tables  and S9. ectively . Despiteectively . This coectively . For theectively –108.While most of the genetic diversity in human louse populations around the world seem to be highly geographically structured, there are a total of 33 hybrids out of 274 lice analyzed, reaching 12% of our current sampling. However, 25 of those hybrids (75%) are found in the New World, which could represent a zone of secondary contact as a consequence of human colonization. The three models that consider recent admixture events from European migration after both World Wars (Model 5), initial globalization (Model 6) and current times at sampling (Model 7) were the most supported Tables . Thus, aWolbachia is a common intracellular bacterial symbiont of arthropods and filarial nematodes that has been shown to infect human lice [Wolbachia interbreed, or when one population has Wolbachia and the other population does not, the matings (“hybrids”) resulted in reduced fitness or the complete absence of progeny. If this process were to occur in human lice, it could explain the low number of hybrids; however, because Wolbachia endosymbiont is transmitted with the mitochondrial genome through the egg cytoplasm, endosymbionts and mtDNA should reflect a similar history. In our study, mitochondrial lineages were grouped in two mitochondrial haplogroups. We found individuals of both the A and B haplogroups in both nuclear clusters (cI and cII). This is consistent with our initial findings [One potential mechanism of reproductive isolation may involve the effect of endosymbiont on host biology. Endosymbionts could also alter host biology in diverse ways, including the induction of reproductive manipulations, such as feminization, parthenogenesis, male killing and sperm–egg incompatibility, which could lead to reproductive incompatibility . Wolbachman lice –112. Whefindings  in that Pediculus humanus capitis, family Pediculidae) and human body louse (Pediculus humanus corporis) have the most fragmented mt genomes with 20 minichromosomes with a conserved common pattern whereas each of the other protein-coding and rRNA genes has its own minichromosome [The human louse, unlike most animals, which have single-chromosome mitochondrial (mt) genomes , has fraromosome . Furtherromosome . Becauseromosome  however Wolbachia, these endosymbionts are intracellular, and are transmitted vertically from mother to offspring. The human lice endosymbiont is Candidatus Riesia pediculicola [Candidatus Riesia pediculicola found in lice from Cambodia (cI-mtDNA A) and the Netherlands (cII-mtDNA A) with the lab strain, and they found no indels between these two genomes. However, when they included the genome obtained from louse from Honduras (cI-mtDNA B), the authors found indels [Candidatus Riesia pediculicola and the mt clades of their P. humanus host [Candidatus Riesia pediculicola co-diverge with the mtDNA lineages, this endosymbiont does not explain the low prevalence of louse hybrids.Insect species with nutritionally incomplete diets , such as human lice often harbor mutualistic bacteria that synthesize missing nutrients –119. As culicola , and basculicola  suggesticulicola , 123. Stculicola , 125. Inculicola  they comd indels , reflectnus host , 125. InP. h. humanus, only transmitted their maternal copy of microsatellite markers while females showed a Mendelian gene transmission [P. humanus louse males exclusively  transmit only the maternally inherited alleles to their offspring revealing a genome-wide male transmission ratio distortion for both ecotypes in agreement with early findings from McMeniman and Barker (2006) [An alternative explanation could be related to an unusual paternal genome elimination (PGE) that has been reported in other members of Psocodea particularly Liposcelididae and Phthiraptera where for these two lineages PGE has been suggested as the mode of sex determination . Earliersmission . This mosmission . A more smission  assessedr (2006) . In our If hybrids present some type of phenotypes that are not well adapted compared to the non-admixed parental lice, this could lead to an alternative hypothesis. For example, epigenetic mechanisms like DNA methylation and histone modification are well known to influence gene regulation, phenotypic plasticity, development, and the preservation of genome integrity. When most of the studies of epigenetics are related to intra-generational times, there is a growing number of studies focusing on transgenerational epigenetics: the inheritance of a modified phenotype from the parental generation without changes in genes or gene sequence. This transgenerational epigenetics suggest that there are direct and indirect contributions of epigenetics to evolutionary processes . One of In this work, we assessed the use of human louse nuclear genetic diversity as a tool to reconstruct human migration around the world, by analyzing microsatellite data from 274 lice. In addition to well-known genetic analysis methods, we developed a new approach to evaluate demographic scenarios through DIY-ABC models by using data from the human host. This novel approach could also guide the development of new analyses in other host-parasite systems. Our results showed the presence of two divergent nuclear louse genetic clusters, with very limited and recent admixture, mostly in the New World. We suggested that this pattern is reflective of human migration to the Americas, with an early wave of louse-human co-migration during the population of the New World followed by the most recent European migration. We also hypothesized that there is a potential mechanism that is preventing admixture between these two divergent nuclear clusters, most likely epigenetic in origin. Due to the use of microsatellites that are known to be fast-evolving markers, our analyses are more suited to recent events, and slower evolving markers could provide insights into more ancient events. Further studies in human lice including more samples, and both whole genomic, and epigenomic approaches could provide new knowledge about louse evolution as well as their human host.S1 FileIncluding a) Protocol for collecting human lice developed by the Reed lab; b) Questionnaire on inclusivity in global research; and c) Microsatellite data.(PDF)Click here for additional data file.S2 FileS2_S3 Tables. Prior distributions of population sizes parameters and times of events for testing for the demographic scenarios described in  Between the brackets  are the host values obtained from anthropological references as shown in S2 Table. Population size priors considering 10% and 50% louse infestation level. S3 Table. Louse time priors are expressed considering number of generations of lice back in time assuming a generation time of 27 and 36 days, respectively. The values for hominins refer to years. S4 Table. Genetic differentiation. Louse pairwise genetic differentiation based on FST values from 15 microsatellite loci among sites where 8 or more lice were collected. Sample sizes are in parentheses following population name. Values below the diagonal indicate FST values, p-values are shown above the diagonal; * indicates significant at nominal alpha level of 0.05.Groups reflect their geographic distribution and STRUCTURE clustering: Africa-Israel-Spain (AIS), South and Southeast Asia (SAs), East Asia (EAs), Europe (E), North America (NA), Mesoamerica (MA), Central America (CA), and South America (SAm). (ZIP)Click here for additional data file.S1 FigCluster membership of each louse is depicted by a different colour inside their 95% inertia ellipses. DA eigenvalues are shown in the inserted graphs at the bottom right, whereby the numbers of the discriminants plotted against each other are indicated by dark grey and the remaining discriminants retained for the analysis in light grey. A total of 10 axes were retained in this DAPC, this is referred to the n-dim function in the adegenet package, and indicates the number of retained DAPC axes, which is affected by both the number of PCA axes and DA axes retained.(TIF)Click here for additional data file.S2 FigΔK statistic of Evanno et al.  from STR(TIF)Click here for additional data file.S3 Figq-values as suggested in [q-value between 0 and < 0.20 or > 0.8 and 1 are classified as non-admixed and were included in this analysis.An ancestry threshold value of ested in  was used(TIF)Click here for additional data file.S4 FigSTRUCTURE plot including only non-admixed lice (no hybrids).(TIF)Click here for additional data file.S5 FigSTRUCTURE plot including only non-admixed lice (no hybrids).(TIF)Click here for additional data file.S6 FigAllelic richness per nuclear genetic cluster  using the rarefaction method implemented in the computer program ADZE  Version 1.0 . Because(TIF)Click here for additional data file.S7 FigCA of the nuclear cluster membership frequency and the mitochondrial haplogroup of head lice.(TIF)Click here for additional data file.S8 FigFull migration model with four units defined by both the nuclear clusters inferred from STRUCTURE and the mitochondrial haplogroups: unit 1) cI–mtDNA A; unit 2) cII–mtDNA A, unit 3) cI–mtDNA B; and unit 4) and cII–mtDNA B. Values above and below the arrows indicate migration rates, arrows indicated directionality.(TIF)Click here for additional data file.S9 FigLouse infestation included three levels: 10% , 30%  and 50% , where 10% indicates that 10% of the hominin population have 10 lice per head, the 30% level considers that each head would have 20 lice and only 30% of the population is infested, while the 50% reflects high level of parasitism with 50 lice per head in 50% of the population. For this study we considered the time of head lice maturation from egg to reproductive male adult and egg-laying-adult female of 18 days, 27 days and 36 days. Each demographic model was color-coded as follow Scenario 1 –green, Scenario 2 –red, Scenario 3 –light blue, Scenario 4 –pink, Scenario 5 –yellow, Scenario 6 –black, Scenario 7 –grey.(ZIP)Click here for additional data file.


Schemes that use genomic prediction outperform others, updating testers increases hybrid genetic gain, and larger population sizes tend to have higher genetic gain and less depletion of genetic varianceOne of the most common methods to improve hybrid performance is reciprocal recurrent selection (RRS). Genomic prediction (GP) can be used to increase genetic gain in RRS by reducing cycle length, but it is also possible to use GP to predict single-cross hybrid performance. The impact of the latter method on genetic gain has yet to be previously reported. Therefore, we compared via stochastic simulations various phenotypic and genomics-assisted RRS breeding schemes which used GP to predict hybrid performance rather than reducing cycle length, which allows minimal changes to traditional breeding schemes. We also compared three breeding sizes scenarios that varied the number of genotypes crossed within heterotic pools, the number of genotypes crossed between heterotic pools, the number of hybrids evaluated, and the number of genomic predicted hybrids. Our results demonstrated that schemes that used genomic prediction of hybrid performance outperformed the others for the average interpopulation hybrid population and the best hybrid performance. Furthermore, updating the testers increased hybrid genetic gain with phenotypic RRS. As expected, the largest breeding size tested had the highest rates of genetic improvement and the lowest decrease in additive genetic variance due to the drift. Therefore, this study demonstrates the usefulness of single-cross prediction, which may be easier to implement than rapid-cycling RRS and cyclical updating of testers. We also reiterate that larger population sizes tend to have higher genetic gain and less depletion of genetic variance. Oryza sativa L.); rice hybrids, which RRS does not always produce, currently outperform the best inbreds by around 30% with appropriate management  is thought to be one of the most effective strategies for improving the genetic value of crops with heterosis due to dominance  can increase the rate of genetic gain in RRS programs by reducing the cycle length . Genomic information also has a further application in increasing the genetic value of hybrid value if used for genomic prediction of hybrid performance . The trait was comprised of 30 QTN per chromosome, totaling 360 QTN. A simulated SNP chip with 83 SNPs per chromosome was used for genotyping, totaling 996 SNPs; SNP and QTN sites were not allowed to overlap. The additive, dominance, and average degree of dominance parameters were defined based on  single-seed descent (SSD) method, which accelerates the growth cycle to 90—100 days  were obtained and evaluated. After that, we selected the P best hybrids based on their phenotypic performance, then identified their parents, which the females will belong to HP A and the males to HP B. The best phenotypically performed hybrid was also “released” as a variety , and consequently, the parents were chosen by chance. The DRIFT_RRS is important to detangle/separate the changes in genetic variability due to selection or by genetic drift . The latter happens when a small number of parents are used for recombination. It is a well-known phenomenon in the literature . The HO hybrids with the highest total genetic values were advanced to the inter-pool crossing block and phenotypically evaluated  for GS, we used the phenotypes and marker genotypes of 384 hybrids resulting from the base population after the burn-in stage. Markers’ effects were estimated using the ridge-regression best linear unbiased prediction (RR-BLUP), considering the respective functions in the G is the genotype matrix  under an additive model), and W is the design matrix relating lines to observations (y). The BLUP solution for the marker effects can be written as Z = WG and the ridge parameter To perform the genomic predictions, the AlphasimR package  for an additive effects), T is the genotype matrix  for dominance effects), and W is the design matrix relating lines to observations (y). The BLUP solutions for the marker effects can be written as Z = WG, and the ridge parameter Zd = WT, and the ridge parameter Additionally, for the additive-dominance scenario, we used the following model:L) sample from each heterotic pool, hybrids obtained in silico (HI), and field evaluated/obtained (HO), and finally, the number of parents used for recombination within each heterotic pool   methods outperformed the traditional  and drift (DRIFT_RRS) for both the average interpopulation hybrid population performance and the best hybrid performance Fig. a, b. FurVa) by drift  increased over the cycles, even in the drift scenario, being more substantial in breeding size I and less accentuated considering breeding size III. In the latter, there was a better separation between the FST produced by selection or drift  or additive + dominance (GS_AD_RRS) to predict hybrid performances, there were no significant differences between them for any parameters studied over the reciprocal recurrent breeding cycles.Finally, after 20 breeding cycles, using GS and breeding size III rather than TRAD_RRS and size I, it was possible to increase by more than 56% the average interpopulation hybrid population performance and the best hybrid performance. Please note that genomic selection by the A and A + D models has almost overlapped (since the light blue broken line is not visible in many figures).Simulations have proven to be a powerful tool to assess the main factors in long-term breeding programs because several features can be controlled to make inferences on given genetic parameters over cycles in a fast, inexpensive, and consistent way  As the selection will be very intense, drift must be minimized to guarantee that the losses in genetic variability will be driven by selection.As expected and well described in the literature, the bigger the population, the bigger the genetic gains. Hence, breeding size III provides higher responses to selection Fig. a. Also, zes Fig. a, b. AnyNe) increase the effect caused by the drift (Hartl and Clark In this context, it is well known that smaller effective population sizes (Finally, after the horizon of 20 breeding cycles, using GS and breeding size III rather than the phenotypic selection and size I, it is possible to increase by more than 56% the average interpopulation hybrid population performance and the best hybrid performance. Thereby showing the importance of combining the appropriate method of selection, having a dynamic pairwise and updating system of testing using the possibility of creating all possible testcrosses in silico, and the effective population sizes to evaluate and recombine parents to avoid genetic drift and better conserve the genetic variation.


Ceratina calcarata). Using genome‐wide SNP data (n = 8302), collected from specimens across the species' entire distribution, we evaluated population differentiation and genetic diversity and identified putative signatures of selection in the context of geographic and environmental variation. Results of the analyses of principal component and Bayesian clustering were concordant with the presence of two to three genetic clusters, associated with landscape features and inferred phylogeography of the species. All populations examined in our study demonstrated a heterozygote deficit, along with significant levels of inbreeding. We identified 250 robust outlier SNPs, corresponding to 85 annotated genes with known functional relevance to thermoregulation, photoperiod, and responses to various abiotic and biotic stressors. Taken together, these data provide evidence for local adaptation in a wild bee and highlight genetic responses of native pollinators to landscape and climate features.Deciphering processes that contribute to genetic differentiation and divergent selection of natural populations is useful for evaluating the adaptive potential and resilience of organisms faced with various anthropogenic stressors. Insect pollinator species, including wild bees, provide critical ecosystem services but are highly susceptible to biodiversity declines. Here, we use population genomics to infer the genetic structure and test for evidence of local adaptation in an economically important native pollinator, the small carpenter bee ( First, we inferred the population structure of C. calcarata and compared genetic diversity estimates across different sampling locations to help characterize the ecological biogeography of the species. Additionally, we tested for evidence of adaptive divergence by identifying putative signatures of selection associated with genetic structure and environmental variation. Combined, these objectives provide insights into the population genomics of an ecologically important pollinator species, and, more broadly, demonstrate how geography and climate shape patterns of local adaptation in wild bees.Here, we employed genotyping by sequencing to collect genome‐wide data for 22.1C. calcarata (n = 129) were collected from 33 sites from 14 regions spanning the range of the species , with 468.5 million reads (89.86%) retained following demultiplexing. Reads were filtered out because of ambiguous barcodes (9.41%), low quality scores (0.09%), or ambiguous RAD tags (0.63%). Due to a low number of reads (<7000), two individuals were removed from further analysis. Generated FASTQ files were aligned to the Ceratina calcarata genome , minimum minor allele frequency of 0.05 (‐‐min‐maf 0.05), maximum observed heterozygosity of 0.5 (‐‐max‐obs‐het 0.5), and retaining one SNP per locus (‐‐write‐single‐snp) to decrease the effects of linkage disequilibrium. Following the initial populations run, we identified and removed low coverage individuals (depth < 6×) and/or individuals with high missing data percentage (>50%), calculating both statistics using vcftools v0.1.16  and missing data below 10% (‐‐max‐missing 0.9). To ensure that no potential sibling pairs were present in the dataset, we calculated relatedness using the kinship coefficient method . The resulting dataset was used to identify outlier SNPs.We demultiplexed FASTQ files and removed multiplex identifying barcode sequences using 2.3FST‐based method implemented in Bayescan v2.0  method, as implemented in ekutieli , using thttps://www.worldclim.org/data/worldclim21.html). For each sample in the dataset, we extracted environmental variables based on sample coordinates, using the R package raster v3.4–5. To control for multicollinearity, we conducted a collinearity test between potential environmental predictors using the cor command within R package stats v4.04 and removed one variable from each pair, where collinearity estimate (r) was higher than 0.8. Based on this test, temperature was highly correlated with latitude, and hence, only one of these variables (temperature) was kept as a predictor for GEA tests. First, we used latent factor mixed modelling (LFMM), as implemented in the R package LEA . Following λ recalibration and a subsequent correction for multiple comparisons, SNPs with a q‐value below 0.05 were considered outliers.Third, to identify signatures of local adaptation potentially associated with environmental variables, we used the gene–environment association (GEA) approach for outlier loci detection. We selected the following geographical/environmental variables for this analysis: latitude, longitude, elevation, mean annual temperature, and mean annual precipitation between the years 1970–2000 . We investigated the putative role of these genes, using the R package TopGO  terms were used in this analysis and associations with a p‐value below 0.05 were considered significant.We extracted shared SNPs among the above four methods, using the R packages 2.5p < 0.01) deviated from Hardy–Weinberg equilibrium (HWE) in at least 50% of the populations. The resulting SNP dataset was used for all population genetics analyses below, unless otherwise specified.To create a putatively neutral SNP dataset for downstream population genetics analyses, we removed all SNPs that were identified as outliers by at least one of the above methods. Furthermore, we removed SNPs that significantly (HO) and expected (HS) heterozygosities, observed and effective numbers of alleles, and inbreeding coefficients (GIS) for each sampling location in the dataset using GenoDive v3.04  was varied from 1 to 14, with 10 iterations of each. To infer the optimal K value, we used the ΔK method  and robust outlier (n = 250) SNPs and visualized the results using R packages plotly v4.9.0  gene identifiers, of which 97 (Table rdgA), a gene crucial for photoreceptor maintenance , which contributes to insecticide resistance; synaptic vesicle membrane protein VAT‐1 homolog‐like (Vat1l)—a gene expressed in brains of a variety of taxa from zebrafish to humans , which is involved in glycometabolism  that has a role in eye development  belonged to the Northeastern genetic cluster; the Wisconsin samples formed a Western cluster, while Georgia and North Carolina‐Southern Virginia samples comprised the Southern cluster  than the average level of inbreeding in the Northeastern (mean GIS = 0.30 ± 0.18) or the Southern genetic cluster (mean GIS = 0.14 ± 0.09). However, given the variation in sample size between different locations in this study, this comparison should be interpreted with caution. Additionally, we did not find any evidence for substructure within the Northeastern cluster; despite this region spanning a large geographic distance, there was little genetic differentiation between sampling locations. This pattern could be attributed either to high gene flow between these locations or indicate that the founding population was characterized by low levels of genetic diversity. Bee foraging distance is correlated with body size  capture only a fraction of the genome and likely underestimate the true number of divergent loci  was related to glycolysis regulation, and more specifically to the phosphofructokinase/fructose‐l,6‐bisphosphatase‐mediated substrate cycle , which is involved in the uptake of trehalose—sugar circulating in insect hemolymph—which plays a role in energy metabolism and stress recovery : in eukaryotic cells, inositol monophosphatase is an enzyme involved in myo‐inositol synthesis  and calcium‐transporting ATPase type 2C member 1 (Atp2c1), which have been associated with climate adaptations ; furthermore, one of the significantly enriched GO terms (GO:0007616) was associated with long‐term memory. These findings are consistent with previous research that revealed genes involved in neural and neuromuscular processes to be under selection in other bee species, across temperature , which play a role in the development of photoreceptor cells , which could be a signature of selection related to increased pesticide usage. Research has shown that interaction with certain compounds commonly found in bee habitats , can inhibit multidrug resistance transporters, increasing honeybee sensitivity to ivermectin and acetamiprid  were linked to biological processes associated with light responses. Exposure to ultraviolet (UV) light constitutes a type of oxidative stress; in honeybees, nurse bees subject to UV radiation show an elevated expression of heat shock proteins in abdomens and heads, which is a marker typically indicative of thermal stress (Kim et al., 5C. calcarata as an example. We demonstrate that despite its widespread occurrence, this wild pollinator exhibits decreased heterozygosity and elevated levels of inbreeding. Furthermore, our results provide evidence that patterns of neutral divergence in C. calcarata are associated with longitude, forming two main genetic clusters; at the same time, evaluation of adaptive divergence reveals a third genetic cluster in the Southern part of the continent. Analysis of signatures of selection shows that C. calcarata is undergoing geography‐ and climate‐associated adaptation, with molecular processes linked to thermoregulation, abiotic and biotic stress, and light sensitivity being under putatively divergent selection. Finally, our work highlights the utility of a small carpenter bee as a potential model species for evaluating the interactions between genetics and environment. As anthropogenic disturbances and global warming continue to modify critical pollinator habitats, wild bees are going to be disproportionally affected. Continuous monitoring of the genetic diversity, structure and adaptive processes of vulnerable populations is going to be vital in determining the resilience potential of bee communities as a whole.Combined, our data show how geographic and climatic features shape genetic structure and diversity of natural populations and provide important insights into mechanisms by which native pollinator insects adapt to environmental conditions, using Figure S1.Click here for additional data file.Table S1.Click here for additional data file.


Mating control is crucial in honeybee breeding and commonly guaranteed by bringing virgin queens to isolated mating stations (IMS) for their nuptial flights. However, most breeding programs struggle to provide sufficiently many IMS. Research institutions routinely perform instrumental insemination of honeybees, but its potential to substitute IMS in breeding programs has not been sufficiently studied. We performed stochastic simulations to compare instrumental insemination strategies and mating on IMS in terms of genetic progress and inbreeding development. We focused on the role of paternal generation intervals, which can be shortened to two years with instrumental insemination in comparison to three years when using IMS. After 70 years, instrumental insemination yielded up to 42% higher genetic gain than IMS strategies—particularly with few available mating sites. Inbreeding rates with instrumental insemination and IMS were comparable. When the paternal generation interval in instrumental insemination was stretched to three years, the number of drone producers required for sustainable breeding was reduced substantially. In contrast, when shortening the interval to two years, it yielded the highest generational inbreeding rates (up to 2.28%). Overall, instrumental insemination with drones from a single colony appears as a viable strategy for honeybee breeding and a promising alternative to IMS. Apis mellifera) has gained significant popularity in many parts of the world. Typically, honeybees are bred for production traits, such as honey yield; manageability traits, such as gentleness; and health traits, such as resistance against the parasite Varroa destructor [conservation by utilization’ [4a-queen [In recent years, breeding of honeybees  i4a-queen ,21. Howe4a-queen ,23. This4a-queen , a breedwww.beebreed.eu, accessed on 8 September 2023, approximately 17% of queens are instrumentally inseminated, while the use of IMS remains the predominant mating strategy [In many agricultural species, instrumental insemination has become the default reproduction technique as it provides maximum control over the mating process. The first believable reports of successful instrumental inseminations of honeybee queens date back to the early 20th century . In the strategy . Howeverstrategy , shows tFrom a theoretical point of view, instrumental insemination of honeybees is expected to have several potential advantages in comparison to mating on IMS. Even by carefully selecting suitable areas for IMS, the possibility of foreign drones participating in a mating can never be ruled out completely ,22. Thuswww.beebreed.eu, approximately a fourth of all instrumentally inseminated queens are fertilized with drones from a single colony.It should be mentioned, however, that only a fraction of breeders who practice instrumental insemination actually exhaust these potential advantages. Following the observation that colonies with more diverse paternal ancestry often display greater vitality and health ,39,40, mComputer simulation studies have been used to search for optimized breeding schemes in honeybees since the 1980s ,42. In rwww.beebreed.eu, which span from 120  to over 8000 queens per year . Queens were selected for a purely additive trait. Since honeybee traits are typically influenced by both queen and workers [Breeding populations of honeybees were simulated with the program BeeSim . Honeybe workers ,4, the tAccording to , long-tey-tailed ,53. Folly-tailed ,47,54, wEvery simulated year, we updated two separate relationship matrices. True relationships between queens were calculated following the algorithm of Fernando and Grossman  for X-chAt the age of one year, a performance test was simulated for queens and their colonies and, subsequently, a best linear unbiased prediction (BLUP) breeding value estimation was performed with the BLUPF90 program (version 1.63) . For breve years . Based ove years ,58,59.vice versa, insemination events may be held, or experienced breeders can inseminate their queens by themselves. However, for better comparison of the fertilization strategies, we modeled all instrumental inseminations to take place at fixed instrumental insemination stations (IIS). While an IIS comprised multiple drone producing colonies, the drones for an individual insemination were always taken from only one colony (single colony inseminations). We use the term fertilization station to mean either an IMS or an IIS. Four types of fertilization stations were implemented in the simulations. These were:IMS,2),IIS with a two-year paternal generation interval ,IIS with a three-year paternal generation interval .IIS with a mixed paternal generation interval . Three different numbers A. m. mellifera in Switzerland [tzerland ),with IMS ,All queens of a population were mated at fertilization stations of the same type; no mixed strategies were implemented. For brevity, we may thus use the names of the different fertilization stations synonymous with the associated breeding strategies  only differed in the group of queens from which the drone producers were selected. These were all two-year-old queens, all three-year-old queens, and all two-or-three-year-old-queens, respectively , simulating the different types of IIS in this way allowed us to effectively separate the effects of shortened generation interval and higher precision in the breeding value estimation when comparing different mating strategies. The combinations of 2 population sizes, 2 sets of trait parameters, 4 types of fertilization stations, and 3 different numbers of fertilization stations constituted a total of 48 simulation setups. Simulations for each of these setups were repeated 200 times to achieve stable results.No queen losses were simulated, so all queens from the relevant age cohorts were actually available for selection. While this may not be a realistic setup . Subsequently, we calculated means and standard deviations of these averaged values over the 200 repetitions for each setting. While the mean values report the expected behavior of breeding strategies and thus constituted the center of our interest, the standard deviations allowed us to perform statistical tests to underline the significance of observed differences between strategies. Statistical tests were carried out in the form of Welch’s t-test [The statistic analysis of the simulation output was performed with the software R (version 4.2.2)  using thpackages . For eacriterion ), and ths t-test .sire? To answer this question, we derive the concept of an effective number of sires for honeybees.In animal breeding, important statistics of a selection program, such as the effective population size or the selection intensity, can be estimated by the numbers of selected dams and sires per generation. For example, Wright’s  classic pseudo-sire [Traditionally, the group of DPQ on an IMS is seen collectively as a udo-sire ,47,65. Hudo-sire .To arrive at a meaningful notion of effective numbers of sires, we assume a group of The reason is the following: Since the For a general group of sires, we can determine the probability For We turn to the case of DPQ on IMS. Again, assume that there are y of 0.4 ,65,66. Iient ass  (p. 178)In our simulations with 3) to 22.85 units (mix). Ceteris paribus, the genetic gain in the larger population  but slowed down considerably over time so that after 70 years both strategies differed by less than 0.35 units. Throughout, genetic response with strategy IIS2 showed the behavior of a step function with genetic progress being achieved only in every second year. All of the above observations showed consistently in both traits and for both population sizes For all traits, population sizes, and selection intensities, strategy IIS3 (Increasing the number of fertilization stations to 3) to 0.549 (2). With all other parameters equal, inbreeding in the smaller population ; this gap narrowed for mix was 14.6% to 15.1% lower than with strategy IMS. In all settings, the gap between IIS3 and the two other IIS-based strategies in terms of inbreeding was substantial.Comparing the different types of fertilization stations revealed that with fixed 2, and IIS3 had clearly defined paternal generation intervals of three, two, and three years, respectively. The averaged generation intervals were thus 2.5 years for strategies IMS and IIS3, and 2 years for strategy IIS2. In strategy IISmix, paternal generation intervals were shaped by the respective selection frequencies of two- and three-year-old queens as drone producers.An important parameter of a breeding program is the increase of inbreeding per generation ,68. To amix oscillated strongly from year to year, taking on values between 2.00 and 2.55  are selected for drone production.2, both maternal and paternal generation intervals were two years. Consequently, there was no genetic exchange between queens of even and odd years. In effect, two entirely separate populations were maintained in parallel, which explains that genetic progress was only made every other year.In strategy IISAs in the case of genetic gain, the general influences of population size and the correlation  studies ,43,47.2 were partly caused by the fact that queens of even and odd birth years were genetically strictly separated, which halved the effective population size. However, also strategy IISmix led to high inbreeding rates, even though this strategy allowed for genetic admixture between even and odd years. As we had anticipated the risk of high inbreeding rates, we had avoided to inseminate queens with drones from their own dam or an aunt. However, this simple ad hoc strategy to avert high inbreeding coefficients could not prevent overall inbreeding rates being high. The higher inbreeding rates of strategies IIS2 and IISmix in comparison to strategy IMS, despite a higher effective number of sires, indicate that not only the number of selected animals but also the choice of the concrete individuals had a major influence on inbreeding rates. This is in contrast to what has previously been claimed by Uzunov et al. [The high inbreeding rates in strategy IISv et al. .mix, the average paternal generation interval indicated that between a fourth and a third of the selected sire queens were three years old. This shows that exceptionally good queens may be used for reproduction over an extended period of time, as they remain competitive. The oscillations in the initial years can be explained by the design of the simulations. The queens of the first two years formed a base population and were randomly mated because no drone producers were available yet. Queens of year three were the first who could be inseminated, but only with drones from queens of the first year, so the generation interval necessarily was two years. Queens of year four were inseminated with drones from queens of the two base years. As there are no structural genetic differences between the first 2 years, the expected average paternal generation interval is 2.5 years. Queens of year five were inseminated with drones of queens from years two (base population) or three (first generation that benefited from selection). Evidently, there was a strong favor for the latter. These considerations may be continued, but the differences in selected generations between years will become less and less pronounced, thus evening out the oscillations.In strategy IISAs for all agricultural species, selective breeding in honeybees leads to accumulation of inbreeding and reduction of genetic diversity. A lower genetic variance means less potential for natural selection and adaptation to changing environments and other stresses . For thi3 showed that in theory it is possible to build sustainable breeding programs with instrumental insemination and only few IIS. But in practice, it is questionable if enough three-year-old queens will still be alive and thus available for drone production. Only in 22% of single colony inseminations currently registered in www.beebreed.eu, the drone producing queen was aged three years or older. However, we expect that by use of within-family selection [Following this definition, breeding with IMS was sustainable when there were at least 20 mating stations. This is in line with earlier findings of Plate et al. . With 20election ,42 or Opelection , sustainwww.beebreed.eu, IMS and IIS are used in parallel and the selection intensities differ widely. Breeders tend to place their focus on different selection traits and from time to time introduce new stock into the population [By its nature, a simulation study will always be a simplification of reality. We therefore could not factor in all influential aspects of real-life honeybee breeding. In existing breeding programs such as those managed under pulation ,4. TheseNevertheless, it is possible to draw real-life conclusions from our findings because they show the extreme ends of possible scenarios. Unlike IMS, instrumental insemination does not rely on geographic features, and IIS can harbor almost arbitrary numbers of sires. Using instrumental insemination, it is thus possible to actually implement breeding schemes that are theoretically found to be optimal. In this regard, our simulations clearly indicate that instrumental insemination can serve as a substitute for IMS and that it is not necessary to emulate the situation on an IMS; instead, drones may be taken from a single colony. This practice will lead to higher genetic progress at comparable inbreeding rates.www.beebreed.eu, accessed on 8 September 2023, allows to check in advance if a certain mating will lead to high inbreeding coefficients, a tool that is regularly used by breeders [3 further hints at the possibility to drastically decrease inbreeding rates if many three-year-old queens are available for selection as drone producers. However, in most real-world breeding systems, this is currently not the case.It should further be noted that strict truncation selection for estimated breeding values, as we simulated it, is rarely practiced. Particularly for small and endangered honeybee populations, breeders will have a strong focus on subspecies preservation and thus incorporate strategies of inbreeding avoidance in their decisions. For example, breeders . By use honey yield, Neumann and Moritz [Several studies have shown that colonies with genetically diverse worker bees have fitness advantages in terms of colony strength , diseased Moritz  found a However, the ultimate goal of breeding is not that the current generation of queens has strong colonies, but rather that the next generation of queens has good genetic properties. This can be seen by the fact that the selection criterion for a queen is the predicted genetic quality of her daughters ,58,59. HThe genetic model for a queen in our simulations consisted of 400 unlinked loci with purely additive allele effects. This is a vast simplification of reality. In general, it is computationally possible to perform stochastic simulation studies with realistic genomes , includiHowever, the current knowledge on how relevant honeybee traits are influenced by genomics or colony interaction is scarce. Few causative genes have been detected by genome-wide association studies ,91,92, bDespite our findings, it may be ill-advised to hastily dismiss IMS altogether and solely rely on instrumental insemination. In this study, we only investigated the theoretical quantitative genetic aspects of the mating strategies. For a holistic judgment, many more factors would have to be considered. These include, but are not restricted to:When queens mate freely in drone congregation areas, thousands of drones compete for mating success, which imposes strong natural selection on reproductional fitness of drones . While tIn addition to genetic factors, other biological factors may influence the attractiveness of mating strategies IMS and IIS. For example, success rates of the mating procedure may differ, and the queen’s productivity and longevity may be affected. In the past, different studies yielded inconclusive results in these respects (see  for a suOperating costs for IMS and IIS are likely to differ in a site-specific way. In a large economic assessment of honeybee breeding in Europe, Buechler et al.  found laAnother economic factor is the question of whether sufficiently trained personnel is available. Both IMS and IIS need well-trained staff in order to work properly. On IMS, it requires experience to constantly ensure the necessary density of drones , while iAn important aspect that is difficult to monetize is social acceptance. In comparison with other forms of animal husbandry, the public eye generally holds beekeeping and honeybee breeding in high esteem. One reason is that beekeeping is widely seen as a relatively unspoiled and close-to-nature form of agriculture , a perceInstrumental insemination with drones from a single colony appeared as a viable alternative to mating on IMS. At comparable generational inbreeding rates, IIS yielded greater genetic progress. With a prolonged paternal generation interval of three years, much fewer IIS were needed for sustainable breeding than when two-year-old queens were selected as drone producers. From a quantitative genetic point of view, nothing speaks against incorporating IIS into breeding schemes. However, when deciding between IMS and IIS as means of controlled mating, other aspects have to be considered that were not covered by our study. These include biological, economic, and sociological factors.