Trachymyrmex septentrionalis using a combination of maternally  and biparentally inherited (microsatellites) markers. We found three distinct, spatially isolated mitochondrial DNA haplotypes; two were found in the Florida panhandle and the other in the Florida peninsula. In contrast, biparental markers illustrated significant gene flow across this region and minimal spatial structure. The differential patterns uncovered from mitochondrial DNA and microsatellite markers suggest that most long‐distance ant dispersal is male‐biased and that females (and concomitantly the fungus) have more limited dispersal capabilities. Consequently, the limited female dispersal is likely an important bottleneck for the fungal symbiont. This bottleneck could slow fungal genetic diversification, which has significant implications for both ant hosts and fungal symbionts regarding population genetics, species distributions, adaptive responses to environmental change, and coevolutionary patterns.For nearly all organisms, dispersal is a fundamental life‐history trait that can shape their ecology and evolution. Variation in dispersal capabilities within a species exists and can influence population genetic structure and ecological interactions. In fungus‐gardening (attine) ants, co‐dispersal of ants and mutualistic fungi is crucial to the success of this obligate symbiosis. Female‐biased dispersal (and gene flow) may be favored in attines because virgin queens carry the responsibility of dispersing the fungi, but a paucity of research has made this conclusion difficult. Here, we investigate dispersal of the fungus‐gardening ant  Trachymyrmex septentrionalis constructed with COI DNA sequences. Populations of T. septentrionalis in Northern Florida are characterized by two haplotypes found in the panhandle and another found in the peninsula. These clusters are largely nonoverlapping since only two sequences clustering with the panhandle were found in the peninsula.A TCS haplotype network for  Dispersal can shape population genetic differentiation, overall species distributions, and how species may respond or adapt to environmental change   ants are common ants in low to mid latitudes of the western hemisphere . Trachymyrmex septentrionalis is the only fungus‐gardening ant found entirely within the United States and is distributed from Texas to Florida to Long Island, New York, with a center of genetic diversity found in northern Florida  and local conditions  and often move significant amounts of soil in the process  and population sizes likely vary temporally as annual rainfall varies from drought to very wet , xeric adapted oaks , and sandy soils. Located just south of the ANF, St. George Island is a sandy barrier island approximately 6km from the mainland. Despite its low relief and susceptibility to hurricanes, the island contains several stands of pine forest on elevated regions , owing to different soils and geological history  is divided into two ranger districts that occur on either side of the Ochlockonee River: the Apalachicola Ranger District on the west and the Wakulla Ranger District on the east. The Apalachicola Ranger District (ARD) is comprised mainly of pine flatwood forest with high herbaceous cover, little relief, and a high water table . We implemented the M13‐tail polymerase chain reaction (PCR) method , 1.5 μl of 25 mM MgCl2 , 0.5 μl of 20 μM BSA , 0.3 μl of 2 μM tag labeled primer , 0.6 μl of a 2 μM universal dye‐labeled primer , 1 μl of 2 μM unlabeled primer , 0.1 μl of Taq polymerase , and 1 μl of DNA template. Nuclease‐free water was used to make up the remaining volume. The following thermocycling profile was used on an Eppendorf Mastercycler: initial denaturation of 4 min at 95°C, followed by 25 (or 30) cycles of 30 s at 95°C, 45 s at the primer‐specific annealing temperature found by a temperature gradient program, 45 s at 72°C, then eight cycles of 30 s at 95°C, 45 s at 53°C, and 45 s at 72°C, followed by a final extension of 5 min at 72°C. Diluted PCR products were run on an Applied Biosystems 3730 Genetic Analyzer and fragments were sized with LIZ600 size standard at the University of Texas at Austin DNA Sequencing Facility in Austin, Texas, USA. We scored alleles using Geneious v10.2.3 , 1 μl BiolineK), observed and expected heterozygosity (Ho and He), and the probability of identity . We assessed deviations from Hardy–Weinberg equilibrium (HWE) expectations using GENEPOP v4.2  and sequenced an additional 26 samples directly for this study . A total of 55 samples had both microsatellite and mtDNA sequenced  . These analyses were executed with no prior population information and under the admixture model with correlated allele frequencies. In order to determine K, we assessed K = 1 through K = 10 with default parameters. To explore each K value, we performed 10 replicates with a burn‐in value of 50,000 and 500,000 MCMC iterations. We determined the optimal K value by assessing the maximum likelihood values and ΔK . We generated several subsets to test for IBD. Specifically, we considered the following: (a) all sampling sites across all regions; (b) all sampling sites excluding the island; (c) all sampling sites within the ANF; and (d) all sampling sites within the peninsula. For measures of genetic distances, we used pairwise Fst values obtained from Arlequin and linearized them as Fst/(1 − Fst) Rousset, . Negativ2.4.2n = 87; combined samples from Seal et al. . Thus, the amount of genetic variation attributable to differences between the assigned population subsets was low and insignificant; most of the genetic differentiation occurred within and among individuals  in our dataset, providing evidence for genetic differentiation across Florida with signatures of gene flow between clusters. Specifically, the samples from St. George Island were largely assigned to one cluster. Likewise, the samples from the peninsula region were largely assigned to another single cluster with minimal admixture. The samples from the ANF appear to have substantial  admixture of alleles associated with the peninsula and St. George Island clusters  appeared to be most similar to those found in the panhandle, however, even these were genetically unique Figure . Across 4T. septentrionalis queens are not relatively large nor especially endowed with fat stores, which could impact their flying ability . Possible explanations for this conclusion could be related to Pleistocene bottlenecks and then subsequent expansion, and a subsequent time lag in the expansion of COI haplotypes. Therefore, it would appear likely that males have a greater dispersal capability than females. Field studies measuring the variation in flight distance within and between sexes could further inform our results.It is not clear how much of a barrier that rivers present to females since we did find evidence of some trans‐river female dispersal; however, the distance that females seem to move across rivers is much shorter relative to the distance males appear to disperse. The Suwannee River may be an important barrier to female dispersal, though not impenetrable since two peninsular haplotypes  were found clustered with the two panhandle clades Figure . ConversMycetophylax simplex exhibited relatively minor mtDNA (COI) variation across its range in Brazilian Atlantic Forest  unlike their fungal symbionts that were more spatially structured, though the study did not also employ mtDNA markers like the present study  likely explains the patterns in central Panama. While lower attines such as Mycetophylax and Mycocepurus cultivate fungi that are likely capable of independent life, fungi grown by higher attini such as Trachymyrmex and Atta are not  in Atta texana showed evidence of spatial structure and isolation by distance across a north‐south gradient in Texas (850 km). Though fungal symbionts also illustrate significant north‐south differentiation in this species, the patterns are not concordant with their host ants . Bottlenecks are a common feature among vertically transmitted symbionts, which generally exhibit eroded genetic variation and reduced genomes compared to horizontally exchanged relatives  , while microsatellite data illustrated gene flow and minimal spatial structure across the study region . Consequently, these results have implications for expansion and diversification of the obligate fungal symbiont, which is largely dependent on the dispersal capabilities of female ants. A genetic bottleneck or constrained diversification of fungi may have significant implications for the coevolutionary patterns in this mutualistic symbiosis overall. A complementary analysis of fungal population structure, gene flow, and potential local adaptation would allow for this possibility to be explored in more detail. This study encourages further genetic, field, and experimental examinations of the dispersal biology of this species and other ecologically important fungus‐gardening ants, which will vastly improve our ability to understand and ultimately predict how host and symbiont populations expand and evolve across larger geographic and macroevolutionary scales.The differential dispersal patterns observed here between male and female The authors declare no conflicts of interest.Alix E. Matthews: Conceptualization ; data curation (lead); formal analysis (lead); investigation ; writing – original draft ; writing – review and editing . Katrin Kellner: Conceptualization ; formal analysis (supporting); funding acquisition (supporting); writing – review and editing (supporting). Jon N. Seal: Conceptualization (lead); formal analysis (supporting); investigation (lead); methodology ; project administration (lead); writing – original draft (lead); writing – review and editing (lead).Table S1Click here for additional data file.Table S2Click here for additional data file.


Bos indicus and Bos taurus finished on pasture or grain, with fatty acid profiles being better discriminating factors than physicochemical properties. These results can be adopted as tools to be used in meat certification programs.This research was carried out to investigate the usefulness and reliability of meat quality traits such as physicochemical properties and fatty acid profiles to discriminate between meat produced by taurine and zebu cattle, finished on pasture or grain. This approach is of utmost importance to assess the authenticity of meat products, particularly when beef is certified based on criteria such as breed and finishing system. Our results using discriminant analyses indicate that meats originating from pasture- or grain-finishing can be discriminated with high reliability, essentially on the basis of their fatty acid profile. The global distinction of meat from the two genetic groups is somewhat more difficult to achieve reliably. Still, prior knowledge of the finishing system used to produce meat from a given genetic group enhances the trustworthiness of the assignment procedure, allowing the reliable allocation of meat samples originating from Longissimus thoracis were collected from 160 commercial bulls of the B. taurus (n = 75) and B. indicus (n = 85) groups, finished either on pasture (n = 46) or with grain supplementation (n = 114) and analysed by standard procedures. Data were analysed by discriminant analysis using a stepwise procedure, to select the meat characteristics that better contribute to discriminate the various groups. Our results indicate that fatty acid profiles of meat had better discriminating ability than physicochemical properties, especially to identify meat from animals finished on grain or pasture. The overall discrimination of meat from different genetic groups was achieved with a slightly lower reliability. Nonetheless, our results show that reliability of allocation to genetic group can be improved if prior information on finishing system is considered. These results are of high importance because they can be incorporated as tools to assess the authenticity of beef, particularly in meat certification programs.Meat obtained under commercial conditions shows considerable variability, mostly due to genetic background and production system. In this study, meat physicochemical properties and fatty acid profiles were analysed to investigate the feasibility of using them as tools to discriminate between meats produced by different genetic groups and finishing systems. Samples of the  In addition to price, consumer decisions regarding the choice of a specific meat product are usually based on its assumed quality and healthiness , and theB. indicus. In Brazil, which is one of the leading producers and exporters of beef in the world [B. indicus influence [taurus and indicus cattle depend on the feeding system used [B. indicus cattle tends to be of lower quality than meat from taurine breeds, and this has led some labelling systems to exclude zebu meat from their certified brands, thus discouraging the sale of such meats in top-quality markets [In parts of the world where tropical climate prevails, taurine cattle are often crossed with he world , nearly nfluence . A declinfluence ,9,10, butem used ,12. The  markets .In spite of the significance of overall mean differences between quality traits of meats originating from different genetic groups or finishing systems, the variability among individual meat samples from the same group tends to be large, which may hinder the ability to reliably distinguish meat samples according to their genetic origin or production system. However, such distinction is essential if certification programs are adopted and appropriately verified , and varCanonical discriminant analysis is designed to allow the allocation of observations to their group of origin, which is achieved by the use of classification functions, derived to maximize the distance between the groups analysed . In thestaurus and indicus cattle finished on pasture or grain, with the goal of assessing the suitability of physicochemical properties and lipid profiles of meat as tools to be used to discriminate between meats of different origin. On the other hand, in large genetic groups such as B. indicus or B. taurus, it is likely that differences in meat quality between breeds of the same genetic group may be important [Several studies have attempted to use multivariate approaches to assess the various factors contributing to variability in meat quality due to genetic background ,18,19,20mportant ,26, whictaurus or indicus cattle, finished on pasture or grain. The objective of this study was to assess the usefulness and reliability of physicochemical properties and fatty acid profiles as sources of information to discriminate between meat produced by commercial B. taurus (n = 75) and B. indicus (n = 85), which had been finished on pasture , or on grain . The sampled bulls were selected to represent some of the major cattle breeds raised in Brazil, such that the Angus, Holstein and Simmental breeds were included in the B. taurus sample and Nelore, Gir and Tabapuã cattle were included to represent B. indicus.An experiment was carried out in the State of Minas Gerais, Brazil, to assess various factors related to meat quality traits in commercial beef cattle. Details on the experimental procedures followed in this study have been previously described in detail by our group ,12 and aBrachiaria brizantha cv. Marandu, Brachiaria decumbens, Brachiaria humidicula and Panicum maximum Jacq.) in the Brazilian state of Minas Gerais. Those finished with grain had a finishing period of about 90 d where supplementation with 50% roughage (bagasse sugar cane) and 50% concentrate  was available ad libitum. Animals finished on pasture were raised on grass  law number 11977/2005. Animals were slaughtered in a meat packing plant, certified for beef export, and samples of about 500 g were collected at 24 h post mortem from the M. longissimus thoracis. After blooming, colour coordinates were obtained with a Minolta Cr-400 colorimeter , and the CIE Lab colour scores indicating lightness (L*), redness (a*) and yellowness (b*) were obtained in both fresh (24 h post mortem) and aged (10 days post mortem) meat samples. Steaks were grilled until reaching an internal temperature of 65 °C, and the difference in weight before and after grilling was considered to correspond to cooking loss. Peak Warner-Bratzler shear force was measured in grilled meat, using a texturometer TA-XT2 .Steaks with a thickness of 2.5 cm were obtained from both fresh and aged samples, by perpendicular sectioning of the trans 18:1 isomers was not complete, such that the trans-6, trans-7 and trans-8 18:1 isomers coeluted in one peak , and the resolution of the trans-10, trans-11 and trans-12 was not complete in many samples . The 17:1 cis-9 also co-eluted the 18:1 dimethylacetal. The individual FA were expressed as a percentage of total identified FA and afterwards grouped as saturated FA (SFA), monounsaturated FA (MUFA) and polyunsaturated FA (PUFA).Samples of fresh meat were minced for chemical analyses. Moisture, protein, fat, ash and cholesterol were determined by standard procedures, as described by . The totFor the purposes of discriminant analyses, some of the FA were analysed as groups, as follows:n-3 group = 18:3n-3 + 20:5n-3 + 22:5n-3 + 22:6n-3n-6 group = 18:2n-6 + 20:3n-6 + 20:4n-6 + 22:2n-6trans-6,-7,-8 + 18:1 trans-10,-11,-12 + 18:1 cis-12 + 18:1 cis-13 + 18:1 cis-14 + 18:2 cis-9, trans-11 + 18:2 trans-11, cis-15Biohydrogenation group = 18:1 Microbial FA = iso14:0 + iso15:0 + anteiso15:0 + 15:0 + iso16:0 + iso17:0 + anteiso17:0p < 0.05 for a variable to enter the function and p > 0.10 to be removed. The estimated Wilk’s lambda of each model was used as an indicator of the proportion of variability not explained by the discriminant functions. The reliability of the discriminant analyses was also assessed by the percentage of observations correctly allocated to their group of origin when a discriminant function is used. This was achieved both by direct application of each function or set of functions to the full data set, and by implementing crossvalidation with a jacknife procedure, where each observation is sequentially removed from the data set and is then allocated to a group based on the discriminant function developed when this observation was excluded.The IBM SPSS Statistics for Windows, Version 26.0  package was used for statistical analyses. A series of canonical discriminant analyses were performed in order to develop functions that maximize the ability to distinguish between meat originating from the two genetic groups and two finishing systems analysed, as well as from the combination of genetic group and finishing system. These analyses were carried out considering as discriminant factors either the physicochemical properties or the FA profiles of meat, as well as their joint influence. The discriminant analyses were implemented with a stepwise procedure, using The descriptive statistics for meat physiochemical properties and fatty acid profiles in the 160 samples used in our study are in B. indicus and B. taurus samples. It is clear that discrimination of genetic groups based on physicochemical properties of meat is very inaccurate, with large overlapping of the two distributions.In our study, the stepwise discriminant analyses converged for all traits and discrimination criteria evaluated. In the analyses, to discriminate between genetic groups based on physicochemical properties, model fitness was not very good, as implied by a large Wilk’s lambda of 0.582 . The relcis-7, 17:1 cis-9, intermediaries of the biohydrogenation pathways and 14:0. Relative to physicochemical properties of meat, the ability to discriminate between genetic groups improved substantially when FA profiles were used, as indicated by the better separation of the distribution of discriminant scores for each of the genetic groups  and meat fat and moisture.Discrimination among finishing systems based on physicochemical properties was more reliable than the discrimination of genetic groups, with a smaller Wilk’s lambda 0.222, . The disf origin . Combinif origin . The varf origin  were essThe possibility of distinguishing between meats resulting from combinations of genetic group × finishing system was investigated, and since there were four combinations, three discriminant functions were estimated. Meat physicochemical properties provided a model with modest fitness, with Wilk’s lambda of 0.07 , and thecis-9, 14:0, 18:2 cis-9, t-11, intermediate FA in the biohydrogenation pathways, 12:0 and n-3 FA. In discriminant function 2 the major factors were n-3, 17:0, 17:1 cis-9 and microbial FA, while for discriminant function 3 the major FAs were n-3, 17:1 cis-9, 16:1 cis-9 and 17:0. The application of the discriminant functions based on the estimated coefficients reported in The use of fatty acid profiles provided a much better discrimination of genetic group×finishing system combinations, with a model showing good fitness, expressed in a Wilk’s lambda of 0.004 . In thiscis-9 and 14:0, while the variables with more influence in function 3 were n-3, 17:0, 17:1 cis-9 and microbial FA. The use of the estimated discriminant functions resulted in a very good separation of the four groups analysed , constructed based on physicochemical properties and fatty acid profiles, as represented in The various models differed considerably in their ability to correctly assign an individual to its group of origin . The pooThe allocation of samples to the correct genetic group×finishing system of origin was unreliable if only physicochemical properties were used, but achieved a very high accuracy when the discrimination was based on a function derived from physicochemical properties and FA profiles of meat. Based on the combination of traits, the ability to allocate samples to the correct group of origin ranged from 96 to 100% . Among tB. taurus is generally tenderer than meat produced by B. indicus [It has been well documented that physicochemical properties and fatty acid profiles of beef are influenced by both genetic group and finishing system, which could allow the discrimination of meat samples according to their origin and thus provide tools for meat certification. For example, meat from  indicus ,10 and p indicus ,29. Howe indicus , which w indicus ,20,26,30 indicus ,22,23,24cis-9, microbial FA, 17:1 cis-9, 18:0, n-3 and n-6 FA. However, discrimination among finishing systems based on physicochemical properties was not so reliable, and was prone to some misclassifications. Combining FA profiles and physicochemical properties in the discriminant function did not improve the discriminating ability between finishing systems relative to the use of FA profiles alone, as these were already very reliable. These results were anticipated, as finishing system is expected to have a much stronger influence on FA profiles of meat than on its physicochemical properties [In our analyses, the discrimination among finishing systems was achieved with very high accuracy when FA profiles were used to build the discriminant functions, with higher discriminating ability for 16:1 operties ,11,12,31taurus and indicus cattle in rumen biohydrogenation [B. indicus meat [On the other hand, the ability to discriminate meats according to genetic group was not as reliable as it was for finishing system, and it was only feasible with good accuracy when FA profiles and physicochemical properties were combined in the discriminant function, where more than 95% of the samples could be correctly allocated to genetic group. The factors with higher discriminating ability in this case were microbial FA, n-3 FA, 17:0, 18:0 and cholesterol, largely reflecting the differences among genation ,32. Thescus meat , which dindicus animals misclassified. The very high accuracy (>95% correct classifications) achieved under these circumstances indicates that meat samples can be assigned reliably to the genetic group × finishing system combinations considered here. The first discriminant function allowed a complete separation of samples originating from each of the two finishing systems, and included as main discriminating factors the cis-9 FA, as well as the FA resulting from biohydrogenation and of microbial origin, 12:0 and 14:0. The second discriminant function allowed the separation of samples from taurus or indicus bulls, and included as main factors cholesterol, 14:0 and 16:1 cis-9. This function was unambiguous in discriminating among taurus and indicus samples in grain-finishing, but some overlapping remained for the two genetic groups under pasture-finishing. However, this issue was disentangled by the third discriminant function, which specifically separated the two genetic groups under pasture-finishing, and included as main discriminating factors the n-3, 17:0, 17:1 cis-9 and microbial FA. Thus, the distinction of meat originating from the four genetic group × finishing system combinations could be achieved by discriminant analysis with high reliability.When the goal was to discriminate between combinations of genetic group × finishing system, the use of meat physicochemical properties alone was not effective to obtain an accurate distinction between groups, but an improvement in discrimination ability was achieved when FA profiles were used instead, even though some misclassifications were still observed, especially in grain-finished animals. With the combination of FA profiles and meat physicochemical properties, the discrimination among the four genetic group × finishing system combinations was very accurate, with only a few These results are useful to develop and apply discrimination tools that can be used in certification programs, to ensure meat authenticity regarding genetic background and feeding system throughout the production chain. Along with other traceability mechanisms, discriminant analyses should be a key component of a robust follow-up of the meat supply-chain, enabling the detection of fraudulent situations, thus adding value to quality labelling programs.indicus or taurus cattle may be further enhanced by combining meat properties with the information provided by genetic markers that may enable breed assignment [taurus × indicus animals represents an additional challenge, as it has been shown that heterosis plays a role in various meat characteristics, which may differ across finishing systems [taurus × indicus cattle should be investigated in future studies, possibly in combination with genetic markers, as these should allow a better quantification of the diverse contributions from taurus and indicus in crossbred individuals, thus accounting for various degrees of genetic inflow from each of the genetic groups.Further studies are needed to clarify how different finishing alternatives, in terms of diet composition and length of the finishing period ,25,33,34signment ,38,39. S systems . Thus, tB. indicus and B. Taurus finished on pasture or grain indicate that meats originating from each of the finishing systems can be reliably discriminated, essentially on the basis of their fatty acid profile. The global distinction of meat from the two genetic groups is not as reliable, but discrimination can be enhanced by prior knowledge of the finishing system used. In this case, our results show that it is feasible to distinguish with high reliability between meat samples from B. indicus and B. taurus finished on pasture or grain, with fatty acid profiles being better discriminating factors than physicochemical properties. These results are of high importance because they can be incorporated as tools to assess the authenticity of beef, especially in meat certification programs. Undoubtedly, in combination with other traceability mechanisms, discriminant analysis is a powerful tool for a robust follow-up of the meat supply-chain, enabling the detection of fraudulent situations, thus adding value to quality labelling programs.The results of discriminant analyses with meat samples from


Hyla molleri and Pelobates cultripes, based on microsatellite (18 and 14 loci) and SNP  datasets of comparable sample size and spatial extent. Model‐based clustering analyses with STRUCTURE revealed minor differences in genetic structure between marker types, but inconsistent values of the optimal number of populations (K) inferred. SNPs yielded more repeatable and less admixed ancestries with increasing K compared to microsatellites. Genetic diversity was weakly correlated between marker types, with SNPs providing a better representation of southern refugia and of gradients of genetic diversity congruent with the demographic history of both species. Our results suggest that the larger number of loci in a SNP dataset can provide more reliable inferences of patterns of genetic structure and diversity than a typical microsatellite dataset, at least at the spatial and temporal scales investigated.Reduced representation genome sequencing has popularized the application of single nucleotide polymorphisms (SNPs) to address evolutionary and conservation questions in nonmodel organisms. Patterns of genetic structure and diversity based on SNPs often diverge from those obtained with microsatellites to different degrees, but few studies have explicitly compared their performance under similar sampling regimes in a shared analytical framework. We compared range‐wide patterns of genetic structure and diversity in two amphibians endemic to the Iberian Peninsula:  Hyla molleri and Pelobates cultripes. Larger number of loci from SNP dataset can provide more reliable inferences of patterns of genetic structure and diversity than a typical microsatellite dataset .We compared patterns of genetic structure and diversity between microsatellites and SNPs in two amphibians from the Iberian Peninsula:  We chose DArTseq because it has been reported to work well with large and complex genomes, like those of amphibians , and concentrated with QIAamp DNA Micro (QIAGEN GmbtH) kits, when necessary. DNA extracts from 2.2dartR 1.1.11 package . We kept loci with balanced alleles  and removed loci whose coverage was 3.5 times higher than the median coverage across loci to remove potential paralogs  between 1 and 8 (K = 1 to K = 8), to encompass the optimal number of clusters  found in previous studies with microsatellites for the study species  were then used across all runs of the SNP data, whereas for microsatellites lambda was fixed to 1. Lower values of lambda can improve the modeling of correlated allele frequencies when using SNPs, where often the data are skewed toward rare alleles . The CLUMPP algorithm in CLUMPAK computes a pairwise distance matrix for all runs in each K based on the SSC. For H. molleri, since we sampled different individuals from the same localities for microsatellites and SNPs, we averaged individual ancestries per locality and used R package starmie 0.1.2  for 83 individuals of P. cultripes.We produced panels of 15,412 SNPs (7.6% missing data) for 90 individuals of 3.1K = 2), but some metrics identified further substructure, with up to six genetic clusters (K = 6) when using PI , but at K = 5 in microsatellites (magenta) , but at K = 5 with microsatellites  Figure . In P. cs Figure , driven s Figure . For H. Genetic structure based on STRUCTURE analyses was highly congruent with that inferred by model‐free hierarchical clustering File , which y3.2H. molleri, SSCs = 0.27–1.00; P. cultripes, SSCs = 0.77–1.00) than intermarker similarity   for H. molleri and from K = 2 to K = 4 for P. cultripes. For SNPs, STRUCTURE results were almost identical only from K = 2 to K = 4 for H. molleri, but up to K = 6 for P. cultripes. Larger K values were in all cases associated with less consistent results across STRUCTURE runs. For most K values, pairwise SSC values in microsatellite runs had a larger spread , especially at larger K values. This spread was minimum for STRUCTURE results derived from SNPs, though at larger K values  they tended to converge into 2 or even 3 regions of the parameter space  and minimum at K = 4 (0.55). From K = 5 to K = 8, SSCs had a small increase in the 0.58–0.68 range.Both species showed higher intramarker similarity . Genetic diversity (sMLH) from SNPs in H. molleri was highest in southwest Iberia and decreased toward northern  and eastern localities   or longitude (p = .10).Correlation of genetic diversity between microsatellites and SNPs‐based measures was significant but weak  Figure . We did P. cultripes, genetic diversity decreased with latitude for SNPs  and microsatellites . Longitude had a marginal effect on diversity from SNPs  but not from microsatellites (p = .93). Both markers agreed in diversity being (a) extremely low in the northeastern localities, in coastal France, both on the Atlantic and Mediterranean sides, (b) moderately low in the Northern Plateau and along the Mediterranean coast and interior, and (c) greatest in the central southwestern localities  can yield similar range‐wide patterns of genetic structure than those inferred with a few thousand SNPs . Differences across marker types involved mainly inference of the optimal number of clusters (K), and assessment of individual and population admixture levels.Our comparative assessment revealed that a typical microsatellite dataset , the SSC fell into alternative discrete solutions  and their proportions of ancestry were not fully congruent between marker types. The similarity in the Q‐matrices between markers varied for both species across s Figure . Also, gK Figure , suggests Figure . These aP. cultripes for microsatellites. Genetic diversity as estimated from SNPs was spatially more coherent with genetic structure, showing less variance between localities from the same cluster ; Data curation (lead); Formal analysis (lead); Methodology (lead); Visualization (lead); Writing‐original draft (lead). Guillermo Velo‐Antón: Conceptualization (lead); Formal analysis (supporting); Methodology (supporting); Resources (lead); Supervision (lead); Writing‐review & editing (supporting). Jeffrey O Hanson: Data curation (supporting); Formal analysis (supporting); Methodology (supporting); Writing‐review & editing (supporting). Ana Verissimo: Conceptualization ; Formal analysis (supporting); Project administration (supporting); Supervision (supporting); Writing‐review & editing (supporting). Íñigo Martínez‐Solano: Conceptualization ; Methodology (supporting); Resources (lead); Supervision (supporting); Writing‐review & editing (supporting). Adam D. Marques: Data curation (supporting); Methodology (supporting); Project administration (supporting); Resources (supporting); Writing‐review & editing (supporting). Craig Moritz: Conceptualization (supporting); Formal analysis (supporting); Project administration (supporting); Writing‐review & editing (supporting). Sílvia Carvalho: Conceptualization ; Funding acquisition (lead); Project administration (lead); Supervision ; Writing‐review & editing (supporting).https://github.com/csmiguel/usat_snp.This article has earned an Open Data Badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at: 10.5281/zenodo.3953536 and Supplementary MaterialClick here for additional data file.


Orobanche crenata is a parasitic weed that causes considerable yield losses on food legumes in Ethiopia and the Mediterranean region. Understanding the genetic diversity of Orobanche crenata using molecular techniques generate useful information in managing the weed through resistance breeding. This study aimed at assessing the genetic diversity of O. crenata populations collected from major faba bean growing areas of Ethiopia. A total of 96 samples were collected from the Orobanche-infested faba bean farmer field. The genetic diversity of the population was studied using 30 O. cumana SSR markers. The results showed that 11 SSRs were functional and transferable markers to study the diversity of O. crenata populations. The average number of alleles, gene diversity, heterozygosity, and polymorphic information content values for the SSR loci were 9.6, 0.82, 0.38, and 0.80, respectively. The pairwise genetic similarity analysis showed the lowest genetic distance between samples collected from South Gondar and South Wollo (0.12) while the highest genetic distance (0.48) was found between South Gondar and North Wollo. The analysis of molecular variance result indicated that the variation among individuals was a major source of genetic variation (55%) followed by within individuals (43%) and among populations (2%) variation. The output of population genetic structure analysis indicated the presence of two major groups irrespective of the area of collection or region of origin. Besides, the outcome of the spatial autocorrelation computation indicated a significant and positive genetic correlation between samples collected under a 28 km radius. In general, the absence of geographic region based genetic structure presumably demonstrates the expansion of the parasitic weed between farming sites upon its recent introduction to the country. Thus, the clear absence of population differentiation warrants screening faba bean population in hot spot area. Orobanche spp.) imposes considerable yield losses on faba bean (Vicia faba), lentil (Lens culinaris), carrot (Daucus carota), pea (Pisum sativum), chickpea (Cicer arietinum), and vetches (Vicia spp.) [Orobanche spp.) are native to the Mediterranean region  and western Asia [Orobanche crenata is an obligate root parasite, which is widely distributed in the Mediterranean region, the Middle East, and Eastern Europe [O. crenata has diploid chromosome numbers  [The parasitic weed (ia spp.) . Broomraern Asia . Orobancn Europe . O. cren2n = 38) , 5.Vicia faba L.) is an important cool-season food legume in the highlands of Ethiopia. The crop is used for food, animal feed, income generations, and improving soil fertility. Despite its importance, the productivity of faba bean is below 2 t ha−1, which is caused due to low yielding landraces, parasitic weeds (Orobanche crenata Forsk), and diseases [Orobanche crenata was first reported in 1993 in one village on 10 ha of faba bean crop in the north East Amhara Region of Ethiopia [Faba bean (diseases –8. OrobaEthiopia ). BesideO. crenata population affecting faba bean is not known in Ethiopia except few surveys to determine its distribution and yield loss [Not much attention have given by researchers and extension staff to manage parasitic weeds for a long period of time, and many farmers have abandoned growing cool-season food legumes, and especially faba bean. Recently, one partially resistant faba bean cultivar Ashengie (ILB-4358) was released from ICARDA germplasm sources. The genetic diversity of eld loss .O. crenata populations were studied using RAPD markers showed low genetic variation among populations in southern Spain [Genetic diversity of rn Spain , 13, whiOrobanche crenata populations from Spain and Israel have been studied using five ISSR (Inter Simple Sequence Repeat) and one RAPD (OPG-06) markers, as a result, significant divergences were found between regions with more differences among individuals within a population [The patterns of genetic variation among pulation . Moreovepulation .O. crenata within and among populations is an important source of information for the national breeding activity to develop faba bean cultivars resistant to the pest as well as design appropriate control measures. In Ethiopia, there is a knowledge gap on the status and pattern of genetic diversity of O. crenata populations in various legume growing areas of the country. To our knowledge, this study is the first to look at the genetic diversity of O. crenata using molecular markers in Ethiopia and, therefore, will be an important starting point for further studies of this parasitic weed. Hence, the present study was carried out to test the transferability of SSR markers from O. cumana and assess the genetic diversity of O. crenata population in Ethiopia.Understanding the genetic diversity and population structure O .crenata from infected faba bean, field pea, and other legumes field. A total of 96 O. crenata samples were collected from South Tigray (30), South Wollo (31), North Wollo (5), and South Gondar (30) (O. crenata (2-3 cm long shoot tips) were collected, sliced with a blade, and then dried using silica gel for DNA extraction.A multistage purposive sampling technique was followed to randomly sample shoot tip of dar (30) . IndividO. crenata was extracted from silica gel dried shoot tips using a modified CTAB method [w/v) and visualized using the Bio-Rad gel doc system, after running 45 min at 100 V and staining using RedSafe™ .Genomic DNA of B method . ApproxiB method . DNA isoμL−1 by diluting with double distilled sterilized water for SSR-PCR analysis.The concentration and purity of extracted genomic DNA were quantified using NanoDrop (NanoDrop™2000/2000c) spectrophotometer, and the absorbance ratio of OD (260/280) was within a range of 1.8 to 2.1. The DNA samples were then adjusted to a concentration of 50 ng O. cumana [Thirty SSR markers with polymorphic information content (PIC) values ranging from 0.37-0.80 were selected from published SSR makers for . cumana . Marker μL reaction volumes containing 1 μL template DNA, 1x buffer, 0.075 units Taq DNA polymerase, 0.25 mM dNTPs, and 0.5 pM each primer. Amplification was performed by using touchdown PCR program on Applied Biosystems: Veriti96 well Thermal Cycler, which consisted of an initial denaturation of 94°C for 2 min, followed by 1 cycle of 94°C for 30 s, final annealing temperature (Tm) +10°C for 30 s, and 72°C for 30 s, nine cycles in which the annealing temperature was decreased 1°C, and 32 cycles at 94°C for 30 s, Tm for 30 s, and 72°C for 30 s, with a final extension of 20 min at 72°C and then stored at 4°C.The SSR-PCR amplifications were carried out in 10 Amplified PCR products were separated on 2% agarose gels in 1x TAE buffer with RedSafe Nucleic Acid Stain incorporated in the gel, and 50 bp DNA Ladder was used as a standard molecular weight marker to compare amplicons with their expected size. Microsatellite alleles were detected for their amplification and correctness; hence, true amplicons were subjected for QIAxcel advanced capillary system electrophoresis analysis (Qiagen) by using QIAxcel DNA High-Resolution Gel Cartridge (Cat No./ID: 929002).Fragment analysis from the raw data generated on QIAxcel capillary gel electrophoresis output was analyzed by using QIAxcel Screen Gel Software to determine and score allele peaks. Allelic data were used to compute polymorphic information content, observed heterozygosity, gene diversity, number, and frequency of alleles using PowerMarker V: 3.25 software .To see variation among and within the studied populations, analysis of molecular variance (AMOVA) was computed using GenAlEx V6 . PopulatPrincipal component analysis was carried out based on principal component values generated from 106 alleles of 11 SSR markers. The values were calculated using SAS ver. 9.3, using Princomp procedure. The first two principal components were used for the visualization of the samples on 2D scatter plot.K = 1 to K = 10. The Evanno et al. [K. For this function, a web-based program, STRUCTURE HARVESTER ver. 0.9.93 [Q). The threshold for the membership coefficient was 90%, in which samples sharing more than that were assigned to their respective subgroups, whereas those that were smaller than the threshold were considered admixed. Hence, the assignment of each sample to one group based on the membership coefficient used as criteria to group individuals on a scatter plot using the first two principal component values.To understand the genetic structure and infer the possible number of subgroups, STRUCTURE software was used . The anao et al.  method w. 0.9.93  was empl. 0.9.93  was used. 0.9.93 . To idenr = 0. The analysis was performed with an option of an even distance class of 10 km, and permutations of 9999 and a bootstrap of 1000 were used to compute the confidence interval around the null hypothesis.The spatial autocorrelation analysis was computed based on the similarity matrix calculated from 106 alleles of 11 SSR markers and geographic distance matrix generated from the coordinates of the samples. The analysis was conducted using the “Spatial” option implemented in GenAlEx ver. 6.41 . The sigFrom the total of 30 SSR, markers evaluated and screened initially 11 SSR markers with fragment size ranged from 90-274 bp and PIC value ranged from 0.59 to 0.92 were selected . These SThe highest polymorphism percentage was observed for samples collected from South Wollo (72.73%) whereas samples from South Tigray scored the lowest percentage (45.45%) value. Accordingly, the highest numbers of alleles were counted for samples collected from South Wollo (8.82) and the least for samples from South Tigray (3.45). For all four regions, the mean allele frequency was scored as 7.25. The average genetic diversity for all sites was high (0.77), which ranged from 0.82 to 0.74 for South Wollo and North Wollo, respectively. The average observed heterozygosity (Ho) in the total sample was 0.37, which is significantly deviated from the expected heterozygosity (He) 0.78 .F-statistics indicated that low among population differentiation (0.026), differing from relatively high values for among individual (0.562), and within individual (0.573) differentiation  showed that 2% of the variation resulted from the difference among populations, 55% of variation from among individuals, and 43% of the variation within individuals . F-statintiation .FST among regions showed little (0.0-0.05) to moderate (0.05-0.15) genetic differentiation indicating high gene flow among population resulting in the absence of region-based population structuring. Among the collection areas, South Wollo showed little differentiation when paired with all collections sites except North Wollo (0.058). Another two pairs of regions: South Gondar and North Wollo (0.096); and South and North Wollo (0.092) showed moderate genetic differentiation  based on 999 permutations is shown above diagonal. This result indicates the presence of significant genetic differentiation between regions, despite little FST values.In the table, Q) from the population structure was used to assign the individuals to their respective groups indicated in different shapes. The threshold for the membership coefficient was 90%, in which genotypes sharing more than that were assigned to their respective sub-groups. However, those individuals who failed to have this membership coefficient were considered admixtures and did not belong to any subgroups. The first two principal components explained 12.91% of the total variation  . The blaO. crenata in previous studies [One of the advantages of SSR markers is their higher level of polymorphism and reproducibility than RAPD and ISSR markers used to study the diversity of  studies , 23–25.  studies . Thus, t studies .O. cumana to O. cernua and reported high marker transferability with 92.4% (145) of the 157 SSRs tested as compared to the present study. The mean number of alleles per SSR locus (9.6) detected among the 96 O. crenata in the current study was higher than the mean number of alleles per locus (2.2) reported on O. cumana by Pineda-Martos et al. [O. cumana with O. cernua than with O. crenata and by the better resolution of capillary electrophoresis used in the present study than agarose electrophoresis used in Pineda-Martos et al. [ on Coffea canephora test 71 microsatellite markers originally developed for C. arabica, and 38 (53.52%) markers were successfully transferred for C. canephora and 20 primers were polymorphic.Pineda et al.  conducte et al. [ on CoffeO. crenata genotypes that represented different geographic origins and linages.In this study, the average of gene diversity was 0.82 with the maximum (0.93) at marker Ocum-059, and the minimum (0.64) was recorded at marker Ocum-063. The high level of gene diversity in this study was probably due to the presence of an extensive genetic diversity in the studied O. cumana by Pineda-Martos et al. [The PIC value of SSR markers could vary between different species. The average PIC value of the SSR markers developed on s et al.  was 0.52FST values between geographic origins of Ethiopian O. crenata populations also showed that low genetic differentiation among the population, which could be explained by the effect of low sample size on genetic diversity and exchange of contaminated seeds with neighboring regions, eventually leads gene flow among populations.This study revealed high within population genetic diversity; among the four geographic populations, South Wollo accumulated more genetic diversity as compared to others. On the contrary, populations from North Wollo showed the least genetic diversity. Pairwise The principal component analysis reduced the variables into two important components. In the two-dimensional plot, subgroups contain different proportions of samples from different geographic sources and the presence of a random mixture of samples. Overall, principal component and STRUCTURE analysis result also confirmed that the members of each subgroup were collected from different areas of origin.Orobanche has a complex genetic structure because of the high level of outcrossing [K = 2, the model-based clustering showed both subgroups consisted of samples from all regions without showing distinct correlation with the geographic population; on the contrary, a study conducted by Ennami et al. [O. crenata in Ethiopia among populations. AMOVA also revealed high genetic diversity within populations than diversity among populations.It is expected that crossing . The stri et al.  showed aO. crenata, gene flow and the recent introduction of the parasitic weed reduce among population variations. Survey made by Besufekad et al. [O. crenata appeared for the first time in 1983. Teklay et al. [O. crenata in Ethiopia were through various ways like via contaminated seed exchange, free grazing, farm equipment, and wind. These could be cited as the major dispatch mechanisms that presumably resulted in gene flow among regions leading to less diversity among populations compared to the high within population variation. Besides, the absence of geographic-based genetic grouping could be explained due to an outcrossing nature of O. crenata species that leads to gene flow among the population that resulted in within postulation genetic diversity and lack of correlation between genetic and geographic distances for all the collected samples [F-statistics result, which revealed a high percent value for within population diversity.This higher variation within the population could be associated with gene flow, seed spread, and floral biology of the parasitic weed , 31. In d et al.  indicatey et al.  explaine samples . This isO. crenata populations from Israel, using RAPD marker [O. crenata in their respective countries.Other genetic diversity study on D marker ; from EgD marker  and RAPDD marker ; from SpD marker ; from MoD marker , were alThe statistical analysis computed to know how far the samples are isolated based on the geographic distance resulted in a significant correlation for samples collected in a range of 28 km. This result indicated that as the area of collection between two samples become wide apart, the genetic similarity between the samples started to drop in response to the geographic distance.O. crenata populations. The markers used in this experiment were revealed significant genetic variation within O. crenata populations and able to structure the Ethiopian O. crenata genotypes into two genetic groups without following geographic origins. The low levels among population genetic diversity, indicating that resistance breeding for faba bean, can be done in one location. So far, in Ethiopia, the present study is the pioneer for O. crenata diversity analysis. To give a clear overview of population structure as well as the relationship among Ethiopian O. crenata populations, additional SSR markers should be either screened and/or characterized for further in-depth study of O. crenata to determine the effective population size and gene flow as an input to legume breeding activities, designing control, and management options.This study was able to identify 11 SSR markers that can be used for the future genetic diversity study of


Nomascus hainanus), once widespread across Hainan, China, is now found only in the Bawangling National Nature Reserve. With a remaining population size of 33 individuals, it is the world’s rarest primate. Habitat loss and fragmentation are the primary drivers of Hainan gibbon population decline. In this study, we integrated data based on field investigations and genotype analyses of 10 microsatellite loci  to assess genetic diversity in this Critically Endangered primate species. We found that the genetic diversity of the Hainan gibbon is extremely low, with 7 of 8 microsatellite loci exhibiting decreased diversity. Additional molecular analyses are consistent with field observations indicating that individuals in groups A, B, and C are closely related, the female–male sex ratios of the offspring deviates significantly from 1:1, and the world’s remaining Hainan gibbon population is expected to experience continued high levels of inbreeding in the future. Given extensive habitat loss  and fragmentation, this rarest ape species faces impending extinction unless corrective measures are implemented immediately.The Hainan gibbon ( Hylobates, Hoolock, Nomascus, and Sympalangus), the threat of extinction is extremely severe. Ninety-five percent (18 of 19 species) of gibbon and siamang species are EN or CR. This includes the world’s most threatened primate species, the Hainan gibbon (Nomascus hainanus). Only 33 Hainan gibbons remain in the wild. In the current study, we examine the genetic status of the critically endangered primate species.Species classified by the IUCN as Endangered (EN) or Critically Endangered (CR) face an impending extinction crisis and require immediate protection. In the case of nonhuman primates, which represent the 3rd most speciose mammalian order . In 1980, China established the Nangunhe National Nature Reserve, also in Yunnan Province, to protect the Endangered lar gibbon (Hylobates lar). Although both gibbon species were censused and demographic information collected, studies by There are several evaluation criteria used to assess a species viability and conservation status for it to be assessed as CR. These include the remaining population is small, declining, and geographically restricted; the species geographic range is highly fragmentated and decreasing; and quantitative assessments indicate that the extinction risk is high . Given tMany species are facing a significant threat due to anthropogenically induced habitat fragmentation and habitat loss that has resulted in previously continuous populations becoming isolated . As subpMirounga angustirostris) inhabiting Guadalupe Island was reduced to a relic population of only 10–30 individuals in the 19th century. By 1991, the population had increased to 127,000. Despite this rapid population increase, genetic research indicates that the genetic variation of northern elephant seals remains extremely low and has been severely affected by inbreeding and genetic drift. The genetic diversity of the population is only 45% of the original population  distributed into small isolated subpopulations. Genetic differentiation across subpopulations is high (0.109–0.177), and in at least three of these five species, genetic drift has occurred (Rhinopithecus strykeri), which has a remaining population of approximately 400 individuals  (2 (The Hainan gibbon (ainanus)  is endemanus) (2 . In the anus)  housed at the Nanning Zoo, Guangxi, China, and used these for comparative analyses.We studied Hainan gibbons inhabiting the Bawangling National Nature Reserve , Hainan, China . Male anWe extracted DNA from 100 to 150 mg of feces using a QIAamp Fast DNA Stool Mini Kit and from 1 ml of blood using a QIAamp Blood & Cell Culture DNA Kit, following the manufacturer’s instructions. The extracted DNA was subjected to 0.8% agarose gel electrophoresis, GreenView nucleic acid dye staining, and the estimated concentration and purity  were recorded using a UV transilluminator. At the same time, we employed a Qubit 3.0 fluorescence quantifier to accurately quantify the concentration of DNA.Hylobates leucogenys), 20 microsatellite loci were screened. To guarantee high-amplification success, particularly for DNA sourced from noninvasive samples, we selected microsatellites with >20 repeats and a product length of 100–300 bp. From the library of microsatellites that met our requirements, we randomly selected loci comprising different motifs for further optimization.We tested 10 microsatellite loci previously described to be polymorphic in Hainan gibbons . Using tDNA extracts from two blood samples obtained from captive yellow-cheeked gibbons were used to amplify the 30 loci . PolymerHylobates gabriellae blood sample amplifications and used the fecal samples of the Hainan gibbons to select appropriate microsatellite loci. Human blood was used for comparison to ensure that there was no contamination during the DNA extraction process.Next, we filtered the reliably sites from the PCR products were visualized on an ABI3730 XL Genetic Analyzer. Alleles were scored using GENEMARKER version 2.2.0. Readable peak: peak reading at ≤100 and lower intensity peak ≤50% of the higher intensity peak (the peak reads 50), otherwise the reading was abandoned and set to 0. According to genotyping criteria for the number of repeated experiments outlined by Three primers from We used the MICROSATELLITE TOOLKIT to obtain individual genotype data from each fecal sample , and comThe presence of null alleles and scoring errors for each locus was estimated using MICRO-CHECKER v 2.2.3. Next, we used three indices to assess the reliability of genotyping. (1) Genotyping errors that resulted in allelic dropout (ADO), false alleles (FA), ADO, and FA were calculated using GIMLET v 1.1.3. (2). PCR success rates were estimated by calculating the percentage of successful PCRs that matched the consensus genotype . (3) For a specific locus i, we calculated the mean quality index (QI) of n samples for that locus using the following equation .n is the number of samples and QIi, j the quality index of the ith locus for the jth sample. QIi,j is estimated by the proportion of correct genotypes in three PCR replicates.Where jth sample) and we calculated the global quality index using Eq. 3: In Eq. 3, n and m represent the numbers of loci and samples, respectively.We further calculated the quality index of each sample using Eq. 2 , which is an estimate of the discriminating power of markers  . We alsoX axis, the stronger the individual recognition ability.The individual identification ability of each loci can be determined by calculating the PID (probability of identity) value . We usedFor each of the selected markers, we computed standard population genetic parameters of genetic variation. First, we calculated the expected heterozygosity (He), the observed heterozygosity (Ho), allelic frequencies, and the effective number of alleles. If the observed heterozygosity is lower than expected, this indicates inbreeding, while a higher than expected heterozygosity suggests the admixture of two previously isolated populations . FurtherWe used COLONY V.2.0.6.4 to conduct kinship analyses in order to infer the theoretical parental pair . We usedBased on linkage disequilibrium, we used NeEstimator V2.1 to calculate the effective population size.To detect allelic loss in our study population, we used genotype data from the microsatellite loci and compared those results with the historical population of Hainan gibbons presented in We investigated the size and composition of four of the five remaining family groups of Hainan gibbons. The total population size of these four groups is 25 individuals . A totalOverall, 33% (10/30) of the microsatellite markers tested suitable for investigating genetic diversity in the Hainan gibbon population. These included 6 tetranucleotide and 4 dinucleotide loci with 4–9 alleles per locus .Comparing the electropherograms of the sex-marked PCR products, we found that PCR products numbered 1 to 8 had no bands in the blank control group, and the target bands were bright and the background was clean. Select A-UTXTUY_F1, A-UTXR1, A-UTYR1, A-SRY_F1, and A-SRY_R1  were fouCombined with the results of sex identification, a total of 12 different individuals  were identified. These 12 individuals included three residents of Group A , four residents of Group B , and five residents of Group C . Fecal samples of infants (wet and scattered after voided) could not be collected. Overall, the 12 genetically identified Hainan gibbons accounted for approximately 67% of the total number of individuals present in the A, B, and C Groups .None of 10 loci showed allelic loss, null alleles, or reading errors caused by stuttering (shadow peak). The amplification success rate was 74.09–100%, and the average amplification success rate was 93.40%. The quality index was 0.766–1, and the average quality index was 0.891.The PIC results ranged from 0.1948 to 0.6682, suggesting that our markers had high discriminating power. The 10 loci all conformed to a Harvin equilibrium, indicating that the selected 10 microsatellite loci were all neutrally inherited .Individual Recognition Ability P(ID)DQcar was <0.001, indicating that only five sites were useful in recognizing two unrelated individuals. Similarly, P(ID)sib D5S1457 was <0.01, and thus using data from 9 sites allowed us to recognize two related individuals . TherefoWe found that across all three of our main study groups, there was a greater number of male Hainan gibbons than female Hainan gibbons. Of the 12 genetically identified individuals, 8 were males and four were females. In addition, of the 7 individuals for which parentage was determined, 6 were males and one was female. Based on the results of individual DNA identification, although this population contains many more males than females, the observed sex ratios of the offspring in Groups A, B, and C deviate from an expected 1:1 .The observed heterozygosity (Ho) ranged from 0.250 to 0.917 and expected heterozygosity (He) from 0.219 to 0.719 . The meaWe constructed a genetic pedigree  based onThe effective population size of the Hainan Gibbon is 5 . The actWe compared the published microsatellite genotyping data of the historical population of Hainan gibbons with our results . Among tThis study represents the first integrated investigation of the population demography and genetic diversity of the critically endangered Hainan gibbon. We have conducted long-term field observations of this species, and in the present study we also collected and analyzed DNA (from feces) from 50 to 60% of all residents in three of the five remaining wild groups. Our DNA sampling coverage was greater than in any previous study of this species . In thisPrior to 2007, field surveys reported the existence of only two wild groups of Hainan gibbons, Group A and Group B . SubsequHylobates leucogenys, a close relative of the Hainan gibbon. The availability of several reference genomes provides valuable resources for genetic marker identification, and this resulted in simpler procedures for sample preparation and provided a larger amount of genetic information than other types of sequencing data . Compared with other types of genetic markers (SNPs), microsatellites have relatively high amplification success rates, especially for noninvasive samples, and have been used widely for individual identification in avian populations  is 7 and the expected heterozygosity (He) is 0.725 (Hylobates muelleri) is 14.8 (Elephas maximus), which today is only distributed in the northeastern part of Sabah, Malaysia, and has a remaining population of only 2,000 individuals, also is characterized by low genetic diversity (Ho = 0.14–0.41) and significant inbreeding (Fis = 0.14–0.38) , a Critically Endangered subspecies endemic to Mexico, extensive habitat loss and fragmentation over the past 30 years have resulted in a major population decline. Presently, this primate taxon is distributed in four forest fragments in the state of Veracruz, Mexico. Genetic testing revealed that haplotype diversity and nucleotide diversity  are extremely low compared with other Neotropical primates  of the lar gibbon  . In the primates .2 (2 (The low genetic diversity of the remaining Hainan gibbon population is consistent with their severe population decline (99.4%), which has occurred over the past 70 years . Their c2  to appro2  can be found in the article/Ethical review and approval was not required for the animal study because Noninvasive sampling method.JZ, JC, and NX designed the study. YG wrote the manuscript and analyzed the data. LH completed the experiments and analyzed the data. PG wrote the manuscript. TL and GL conducted the field investigations. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Warburgia salutaris) is one of the most highly valued medicinal plant species worldwide. Native to southern Africa, this species has been extensively harvested for the bark, which is widely used in traditional health practices. Illegal harvesting coupled with habitat degradation has contributed to fragmentation of populations and a severe decline in its distribution. Even though the species is included in the IUCN Red List as Endangered, genetic data that would help conservation efforts and future re-introductions are absent. We therefore developed new molecular markers to understand patterns of genetic diversity, structure, and gene flow of W. salutaris in one of its most important areas of occurrence (Mozambique). In this study, we have shown that, despite fragmentation and overexploitation, this species maintains a relatively high level of genetic diversity supporting the existence of random mating. Two genetic groups were found corresponding to the northern and southern locations. Our study suggests that, if local extinctions occurred in Mozambique, the pepper-bark tree persisted in sufficient numbers to retain a large proportion of genetic diversity. Management plans should concentrate on maintaining this high level of genetic variability through both in and ex-situ conservation actions.The pepper-bark tree ( Additionally, at the global level the importance of bio-based compounds continues to grow and phytochemical research towards the identification of new active compounds of medical and nutritional importance is among top research priorities (e.g.14).Medicinal plants have been used worldwide since ancient times, being particularly relevant in the developing world where 15, many of which are used in traditional medicine20. However, efforts to safeguard this biodiversity are often compromised by anthropogenic pressures, with proximal drivers being land transformation, synergistic impacts of fires, grazing, climate change and harvesting (c.f.27), and growing commercialisation of medicinal plant in high demand (c.f.29). The last is motivated by preferences for certain species due to cultural identity, traditions, and lower costs in comparison with modern pharmaceuticals, even under circumstances of access to modern medical facilities30. On the other hand, the conservation status of many endemic and native species is poorly understood32 and many natural populations may be at risk. Current exploitation rates, often in tandem with other pressures like fire, invasive species, browsing and land transformation, threaten wild populations unless management methods are established, including community-based approaches30.Sub-Saharan Africa harbours a vast repository of plant biodiversity, with 45,000 known vascular plant species34. The importance of phylogenetic data, genetic diversity, and population structure analyses to characterize the biodiversity of wild species has been well-established in numerous studies (e.g.39). Microsatellites  are amongst the most efficient and widely used markers for these studies as they are codominant and highly polymorphic loci40. Although these markers are species specific, the increasing accessibility to next-generation sequencing41 has enabled the development of SSRs for the so-called orphan, neglected or wild crop relative species (e.g.45), although sequencing large plant genomes still remains a challenge46.Under the current scenario of climate change and human population growth, the use of genomic tools is valuable to understand species evolution and adaptation in natural ecosystemsWarburgia salutaris (Bertol.) Chiov. (Family Canellaceae) is one of the most widely used and traded medicinal plants in southern Africa47. This slow growing species is part of an early diverging group of basal angiosperms, thought to be native to eastern and southern Africa48. However, subsequent studies confined the distribution of W. salutaris to only a sub-region of southern Africa, i.e. South Africa49, Eswatini (previously known as Swaziland)50, Zimbabwe53, Malawi54 and Mozambique55. This species is commonly used to treat several ailments such as common colds, throat and mouth sores, or coughs48.The pepper-bark tree, 30. However, with commercial demand increasing, W. salutaris groves were repeatedly raided by harvesters that often debarked the whole tree, especially mature plants56. Severe harvesting resulted in high tree mortality in many areas and in the extinction of many local populations57 and consequently, W. salutaris is considered threatened throughout its range59, and listed as an Endangered Species in the IUCN Red List57. The most extreme case is that of Zimbabwe, where the species is listed as extinct in the wild60. That resulted in the import of bark supplies in the late 1990s from Mozambique and South Africa53 being later trafficked from the same countries29. For instance, in South Africa, 43% of W. salutaris bark in the Johannesburg main market originated from Mozambique, with annual traded amounts estimated at 500–1000 kg28. As a result, populations of W. salutaris in Mozambique are currently restricted to fragmented patches in the Lebombo Mountains, Tembe River and Futi Corridor  have been used to solve genetic relationships between W. ugandensis, W. salutaris and W. stuhlmanni showing a high degree of genetic variation among individuals within populations as well as between populations62.In the past, sustainable harvesting of medicinal plants was regulated through traditional practises such as taboos, restrictions and harvesting toolsW. salutaris to investigate the genetic legacy of exploitation in this slow growing species and to contribute to future re-introduction actions. For that, we have used its best known area of occurrence, Mozambique  to nine (31-N2284857 and 43-N1009973 locus) with an average of 5.8 ± 2.3 alleles per locus and a total of 58 alleles considering all loci  was also higher in LM than in TR and FC. Observed and expected heterozygosis had similar average values in LM and TR being slightly lower in FC. The polymorphic information content (PIC) had high average values while inbreeding coefficients (FIS) were low and showing negative values in the three sampling areas.From the three sampling areas of as Table . The aveK = 2  and ΔK values for The first two coordinates of the principal coordinate analysis (PCoA) explained 22.9% of the total variation, and populations were spatially separated into the two main groups found by STRUCTURE Fig. . The neiFST values varied from 0.049 (TR vs. LM) to 0.114 (FC vs. TR) revealing moderate levels of genetic differentiation between FC and TR and between FC and LM and lower levels between TR and LM  markers in W. salutaris by employing next generation sequencing (Illumina platform). The 10 SSRs markers were validated and found to be highly polymorphic, with values similar to the ones found in other threatened species such as Acer miaotaiense (PIC = 0.604)69 or Corylus avellana (PIC = 0.778)70. These markers are now available to extend W. salutaris population studies to a worldwide level. Additionally, the SSRs developed during this work might potentially be suitable to study genetic diversity in other species within the genus Warburgia, since only a limited number of studies is available and based on Amplified Fragment Length Polymorphism (AFLP)71, a time-consuming and costly technique. To the best of our knowledge, the present study represents the first genome size estimation of W. salutaris and only the second within the Canellaceae family having a genome size 4 × smaller than Canella winterana (2C = 11.7 pg73). The relatively small genome size of W. salutaris (see methods) is within the range of the non-expanded genomes of currently known magnoliids  and may facilitate future genomic initiatives although further analyses are needed to determine its ploidy level.Assessment of genetic diversity is critical to understand the ability of a species to cope with changing conditions and environments, especially for threatened speciesW. salutaris is subjected in Mozambique48, genetic diversity levels were expected to be low. However, we found high levels of genetic diversity in the three surveyed areas in comparison to other narrowly distributed species, as for instance, the tropical tree Paypayrola blanchetiana 39. However, genetic diversity indices of W. salutaris were similar to other species where bark has been heavily-exploited, such as Cinchona officinalis 74 or even lower than Himatanthus drasticus 34.Due to the heavy harvesting pressure to which 75 or high gene flow76. Results from this work revealed a range of the inbreeding coefficient of -0.492 (TR) to -0.363 (LM), which is much lower than those found in e.g. H. drasticus (0.248–0.303)34, Calotropis gigantea (0.167), C. procera (0.177)77, or Phoenix theophrasti (0.9)78. The negative inbreeding values found here suggest the existence of random mating79 among individuals of W. salutaris and might also explain the levels of heterozygosis found here. Indeed, the related species Warburgia ugandensis has a mixed mating system being predominantly outcrossing62. Additionally, insect pollinators of W. salutaris such as bees are probably able to travel over the large agricultural blocks separating the three geographical areas studied here, promoting gene flow. Genetic admixture between sites might also be facilitated by frugivorous birds that often eat the berries thereby facilitating the dispersion of seeds. In accordance, we found high levels of genetic admixture between populations with only two genetic clusters being found, one grouping the northern populations and the other one, the southern populations.High levels of heterozygosis may be due to factors including the reproductive system such as self-incompatibilityW. salutaris trees.Our study suggests that, although some local populations might have been severely affected by harvesting, the pepper-bark tree might have persisted in sufficient numbers in Mozambique to allow outcrossing between sites, retaining a large proportion of genetic diversity. Although there are no records of the historical distribution of this species, the studied populations could be relicts of once much larger populations that persisted in specific locations. In addition, recent conservation efforts might have diminished trade in Mozambique, avoiding severe barking in these populations. Further research should focus on understanding the factors limiting the regeneration of Platanthera leucophaea (FST < 0.02 over distances < 2 km80) while in H. drasticus the differentiation levels were high (FST from 0.036 to 0.077 over short distances)34. In contrast, the endangered Paeoma rockii revealed a high differentiation between populations (FST varied from 0.780 to 0.982)81. Despite the narrow distributional area of W. salutaris in Mozambique, this study revealed a high genetic differentiation between the northern populations located in LM and TR and the southern populations located in FC , which are separated by only 28 km, than either between LM and FC areas  or between TR and FC . STRUCTURE analyses also found a distinct genetic cluster in the FC area, which was also supported by PCoA analyses and the NJ tree. Contrary to LM and TR areas, where W. salutaris occurs in slopes and forest patches, in the FC area this species occurs near seasonal pans in thicket vegetation associated with termitaria on clay soils83. This might imply differences in reproductive ecology, particularly regarding flowering phenology and the activity of pollinators, which would affect gene flow with the other sites, explaining the genetic structure and population differentiation found between the studied sites. Thus, the differentiated FC genetic clusters could be harbouring novel and important alleles and should be given priority in in situ and ex situ conservation strategies in Mozambique85.Population differentiation of endangered species is variable. For example, low differentiation was found between populations of W. salutaris are threatened by fire from slash and burn agriculture, as they occur in adjacent patches or in agricultural lands48. Equally, burning of natural vegetation to improve livestock fodder, poaching, and opening of new areas for settlements are also potential threats to the species (e.g.88). Vegetative propagation of W. salutaris is possible through tissue culture63 although expensive. This species is being largely cultivated ex situ in South Africa89 and in small scale in Zimbabwe53 and Mozambique (unpublished data), to encourage the sustainable use of the species. Home gardening would also be important for this species although that requires the involvement of local communities and understanding their perceptions towards the conservation of this species.Several populations of W. salutaris should be secured by conserving the maximum genetic diversity of the species. As it is impossible to designate every natural wild plant habitat as a protected area, nurseries could be implemented to ensure production stability. The disclosure of genetic variation and understanding of genetic relatedness within populations is useful for their sustainable uses90. Knowledge of genetic diversity from other countries as the one reported here would also help to implement conservation strategies including re-introduction programs, selecting the most suitable material to be used. Understanding the degree of genetic variation between Mozambique and the neighbouring countries would facilitate transborder conservation actions. Further studies must also be conducted to detect and understand how reductions of natural regeneration or fitness are affected by harvesting. Finally, efforts to educate the local population and landowners on the importance of conserving the natural populations of W. salutaris should continue.Considering the confined distribution and threatened status, the long-term persistence of Warburgia salutaris is an evergreen tree, generally 5–10 m tall, but occasionally up to 20 m57. The flowers are small (< 7 mm in diameter), white to greenish in colour, generally solitary or in tight, few-flowered heads, borne on short, robust stalks in the axils of the leaves from autumn to winter (April–June). Flowers are bisexual, actinomorphic . Flowers are visited by many insect species, most especially bees. The flowers develop rounded, oval berries (30 mm in diameter), usually dark-green and turning purple during ripening that occurs throughout winter an into early summer (July to December). Dispersion occurs by frugivorous birds that disperse the seeds, although fruits can also drop near the maternal tree. Leaves are glossy and dark green, with a bitter, peppery taste. The stem is covered by a brown bark marked with corky lenticels and is bitter and peppery and is widely used medicinally. The active compounds (drimanes and sesquiterpenoides) are mostly found in the inner part of the stem and root bark.W. salutaris48: (1) Lebombo Mountains (LM) also named the western area, (2) Tembe River (TR) or centre, and (3) Futi Corridor (FC) or eastern area  Engl. & Diels, Cleistanthus schlechteri Pax (Hutch.), Hymenocardia ulmoides Oliv. and Monodora junodii Engl. & Diels94. The open savanna woodland links the patches of W. salutaris, being composed mainly by Strychnos spp., Terminalia sericea Burch. ex DC., Acacia burkei Benth., Combretum molle R. Br. ex G.Don and Albizia versicolor Oliv.95. In FC, W. salutaris occurs near seasonal pans96 in thicket vegetation associated to termitaria in clay soils82. Common tree species found in this community include Berchemia zeyheri (Sond.) Grubov, Pappea capensis Eckl. & Zeyh. and Olea europaea subsp. africana (Miller) P.S. Green97. The primary economic activities of local residents are subsistence agriculture, livestock rearing, trade of non-timber forest products and migrant labour to South Africa99.The present study was carried out in the districts of Matutuine and Namaacha (Mozambique), in the three areas of known occurrence of taris48:  Lebombo Based on the areas of occurrence , 48 individuals were sampled: 19 individuals from LM, 15 from TR and 14 from LM 102 was used as internal standard. The nuclear suspension was then filtered through a 30 μm nylon filter, and 50 μg/mL of propidium iodide  and 50 μg/mL of RNase (Sigma-Aldrich) were added to stain the DNA only. The fluorescence intensity of nuclei was analysed using a CyFlow Space flow cytometer . Four independent replicates collected from Kazimat (TR) were measured. Conversion of mass values into numbers of base pairs was done according to the factor 1 pg = 978 Mbp103. The mean 2C-value of W. salutaris was found to be 2.91 pg (± 0.068), corresponding to an average genome size of 2845 Mbp . Samples had an average coefficient of variation of 4.18%.For the development of the markers, we first estimated the nuclear DNA content of W. salutaris  for 3–5 bp units. Based on the obtained sequences, primers were designed with Primer Premier 5.0 software (Table Na), observed heterozygosis (Ho), expected heterozygosis (He), Shannon’s diversity index (I), and inbreeding coefficient (FIS) using GenALEX software version 6.5104. The polymorphic information content (PIC) was calculated as PIC = 1 − ΣPi2, where Pi is the allele frequency for each SSR marker locus106. Values of PIC above 0.5 were considered highly informative, between 0.5 and 0.25 moderately informative, and below 0.25 less informative107.For each microsatellite locus, genetic polymorphism was assessed in 48 individuals by calculating the number of alleles  from 1–5, imposing ancestral admixture and correlated allele frequencies priors, were considered. Ten independent runs with 50 000 burn-in steps, followed by run lengths of 1 000 000 interactions for each K, were computed. The number of clusters in the data was estimated using STRUCTURE HARVESTER109, which identifies the optimal K based both on the posterior probability of the data for a given K and the ΔK110. To correctly assess the membership proportions  for clusters identified in STRUCTURE, the results of the replicates at the best fit K were post-processed using CLUMPP 1.1.2111. GenALEX software version 6.5104 was used to calculate the Nei’s genetic distance112 among individuals. A Principle Coordinate Analysis (PCoA)113 was performed to detect genetic variations between W. salutaris individuals. POPULATION 1.2114 was used to construct an unrooted neighbour-joining tree with 1000 bootstrap replicates. The Wright’s FST value was computed to estimate population differentiation104. Lower genetic differentiation was considered for FST below 0.05, moderate from 0.05 to 0.15 and high genetic differentiation above 0.25115.The Bayesian program STRUCTURE v.2.3.4Supplementary infomation.Supplementary infomationSupplementary infomation


Understanding the geographic extent and connectivity of wildlife populations can provide important insights into the management of disease outbreaks but defining patterns of population structure is difficult for widely distributed species. Landscape genetic analyses are powerful methods for identifying cryptic structure and movement patterns that may be associated with spatial epizootic patterns in such cases.Odocoileus virginianus) in the Mid‐Atlantic region of the United States, a region where chronic wasting disease was first detected in 2009. The goal of this study was to evaluate the juxtaposition between population structure, landscape features that influence gene flow, and current disease management units.We characterized patterns of population substructure and connectivity using microsatellite genotypes from 2,222 white‐tailed deer (FST ≤ 0.041), but significant genetic differentiation. Genetic differentiation was lower and migration rates were higher among neighboring genetic clusters, indicating an underlying genetic cline. Genetic discontinuities were associated with topographic barriers, however.Clustering analyses identified four to five subpopulations in this region, the edges of which corresponded to ecophysiographic provinces. Subpopulations were further partitioned into 11 clusters with subtle (Resistance surface modeling indicated that gene flow was diffuse in homogenous landscapes, but the direction and extent of gene flow were influenced by forest cover, traffic volume, and elevational relief in subregions heterogeneous for these landscape features. Chronic wasting disease primarily occurred among genetic clusters within a single subpopulation and along corridors of high landscape connectivity.These results may suggest a possible correlation between population substructure, landscape connectivity, and the occurrence of diseases for widespread species. Considering these factors may be useful in delineating effective management units, although only the largest features produced appreciable differences in subpopulation structure. Disease mitigation strategies implemented at the scale of ecophysiographic provinces are likely to be more effective than those implemented at finer scales. We characterized the spatial population structure of white‐tailed deer in the Mid‐Atlantic region of the United States in order to evaluate the juxtaposition population structure, gene flow patterns, and chronic wasting disease cases in the region. We found evidence of four to five subpopulation units, the extents of which generally corresponded with ecophysiographic provinces, with 11 subtle genetic clusters nested hierarchically within subpopulation units. Landscape genetic analyses revealed corridors of high connectivity adjacent to ridges, roads, and open areas, which may indicate directed disease transmission in regions heterogeneous for these features. Since then, additional cases have been detected in free‐ranging herds in western Maryland and central Pennsylvania, but region‐wide prevalence rates in free‐ranging populations are still estimated to be low  was included on each plate in order to ensure amplicons were not contaminated by external sources of DNA and at least one previously genotyped sample was included as well to confirm reproducibility. We used GeneMarker (Softgenetics) to determine allele identity. Alleles were binned using the MsatAllele R package . Tissue digestions were incubated for a minimum of 4 hr to ensure samples were completely lysed, and DNA elutions were carried out with a single 150 µl volume of elution buffer to maximize DNA concentration. We quantified the concentration of extracted DNA (ng/µl) using a NanoDrop spectrophotometer (Thermo Fisher Scientific) and diluted samples to approximately 20 ng/µl. All samples were genotyped using 11 microsatellite loci previously shown to be effective for genotyping in this region  and delineate population structure. Geneland was chosen as the basis for analysis because it is suggested to be better able to identify cryptic genetic discontinuities than alternative clustering algorithms  and edge detection methods  in scenarios where gene flow is widespread and dispersal barriers are permeable to movement  iterations thinning after every 100th iteration, a maximum number of nuclei set to 6,666 (three times the number of samples), and a maximum rate of the Poisson process equal to 2,222 (the number of samples). All postprocess analyses were conducted with a burn‐in period of 1,000 iterations. Cluster assignment was determined using the single run with the highest average log posterior density , observed heterozygosity (HO), unbiased expected heterozygosity (HE), and the number of private alleles (PA) for each genetic cluster. Genetic connectivity among inferred genetic clusters was described using migration estimates from BayesAss  among individuals within genetic clusters, (b) among genetic clusters within larger subpopulation units determined from the hierarchical clustering analysis, and (c) among all subpopulation units. Hierarchical F‐statistics and covariance components were calculated using the poppr R package ; however, the MCMC output indicated poor convergence relative to the chain with the second‐best run  and heterozygosity  but a low number of private alleles . Average immigration rates among genetic clusters were high  and among all subpopulations within the region , the greatest amount of genetic variation was explained by comparisons made among individuals within genetic clusters . Visual inspection of the principal components plot and K‐means clustering of lag scores identified five genetic clusters that generally corresponded to subpopulation groupings identified in the hierarchical clustering analysis, although the central Ridge‐and‐Valley population was split into two clusters  relative to both the isolation‐by‐distance‐only model  and intercept‐only model . Landscape resistance was not spatially uniform and was focused in the southeastern portion of the study domain  occurred within the topographically heterogeneous Ridge‐and‐Valley province. Ridges can affect the extent and direction of deer movement in this region , or no known occurrence in free‐ranging populations (east). Because of the juxtaposition between hierarchical population structure and ecophysiographic provinces, surveillance and management interventions may be most effective if focused within ecophysiographic provinces with known disease occurrence. This may lead to a greater probability of detecting novel disease occurrences relative to random or spatially uniform sampling strategies implemented at broader or localized scales. Outbreaks in distinct genetic clusters may also have different origins and epizootiological patterns. For example, novel cases of chronic wasting disease in the Allegheny Plateau region had a higher probability of assignment and ancestry to captive deer populations than deer from other ecophysiographic provinces (Miller & Walter, While defining population substructure can aid in defining the extent of disease management efforts, landscape connectivity models may help to identify potential transmission corridors between infected and naïve groups (Paquette et al., 4.3Our results help to elucidate patterns of spatial substructure and genetic connectivity in a continuously distributed population of white‐tailed deer where chronic wasting disease is emerging. Population‐level trends may help to describe the relative risk of transmission and provide important insights into future epizootic patterns. Genetic samples from deer with chronic wasting disease were limited in this current study, however, and we did not have access to spatial records of chronic wasting disease from neighboring states with active infection, such as West Virginia. Continued genetic sampling and disease surveillance will clarify genetic cluster membership in areas where samples were currently unavailable and improve efforts to assess the association between subpopulation structure and chronic wasting disease occurrence. Integrating measures of population substructure and connectivity into diffusion models, such as those used in Hefley et al.  to prediIndividual‐based genetic analyses, such as ancestry and assignment analyses, will also allow for testing specific hypotheses regarding the origin of chronic wasting disease cases. For example, Miller and Walter  used simNone declared.WLM, DRD, and WDW collected genetic samples. WLM, CMM‐B, and WDW performed microsatellite genotyping. WLW and WDW analyzed the genetic and spatial data. All authors contributed to the preparation of this manuscript.Figure S1Click here for additional data file.Table S1Click here for additional data file.Table S2Click here for additional data file.Appendix S1Click here for additional data file.Appendix S2Click here for additional data file.