Temnothorax nigriceps in a highly anthropized environment.Human activities, including changes in agricultural landscapes, often impact biodiversity through habitat fragmentation. This potentially reduces genetic exchange between previously connected populations. Using a combination of nuclear and mitochondrial markers, we investigated (i) genetic diversity and population structure at multiple spatial scales and (ii) colony genetic structure and queen mating frequency in the ant species Although the results highlighted genetic structure on a European spatial scale, they did not reveal an impact of fragmentation on a regional scale, and we did not observe any genetic population structure on a regional scale. Across all populations, regardless of their geographical location, colony structure suggested monogyny (a single queen per colony) and monandry (single mating). However, nestmates were more related than expected, indicating that large-scale dispersal does not fully prevent genetic isolation.Temnothorax nigriceps are apparently genetically not isolated at a regional scale. However, large-scale dispersal alone does not prevent genetic isolation. The ecological requirements of T. nigriceps may explain their resilience to habitat fragmentation by allowing them to survive in very small patches of suitable habitat. The deeper investigation of the diversity of functional habitats for this species should allow to appreciate better the mechanisms permitting this species to overcome the negative impacts of fragmentation.Despite living in fragmented patches of habitat, populations of The online version contains supplementary material available at 10.1186/s12862-022-02044-3. Human activities convert natural habitats into a highly modified landscape, which is characterized by a high density of built-up areas and impervious surfaces and an intensification of agricultural activities in urban peripheries –3. In EuLeptothorax sp. A, patchy habitats are associated with a higher proportion of multi-queen colonies and the predominance of non-dispersing, wingless queens [Temnothorax longispinosus, the availability of empty nest sites influences the number of queens per nest and the number of nests inhabited by individual colonies [The fragmentation and loss of habitat not only affect rare species but also species that are widely distributed in fragmented landscapes and whose populations can have very small effective sizes . Social s queens . In Temncolonies . Hence, Temnothorax nigriceps (Mayr 1855) nests predominantly in cracks and crevices in limestone rocks [th due to the cessation of grazing or afforestation, and large areas were replaced by new grasslands, exempt of the rocky outcrops favorable for the studied species [T. nigriceps, represent now a highly fragmented landscape for this species.ne rocks . It is t species , 17. As T. nigriceps and its response to fragmentation, neither on the scale of populations nor that of colonies. The objective of this study is therefore to investigate the genetic exchange dynamics in T. nigriceps in the Franconian Jura, in a landscape experiencing a strong decrease in the favorable habitats for this species. Because of the scale dependence of the ecological patterns related to fragmentation, changing the observation scale across a landscape may reveal different patterns, and the same phenomenon may occur differently at different scales [T. nigriceps at different spatial scales, from a local to a biogeographic level, to understand if the scarcity of favorable habitats influences the genetic structure of this species and how habitat isolation affects colony composition and genetic colony structure. We hypothesize that because of the scarcity of suitable nest sites for this species, it should exhibit a strong genetic structure, both at a large European scale but also at a regional scale . At a local (habitat) scale, we predict that the flight ability of sexuals of this species should preserve the genetic exchange among populations.At present, nothing is known about the dispersal capacity of t scales , 19. Suct scales . We therT. nigriceps exhibits population structure at the European scale, we collected 70 colonies from 5 European countries , separated by 60 to 2480 km from each other. Bayesian clustering analysis based on microsatellite genetic data at 12 loci without location prior did not reveal a significant genetic structure  > 0.99). Investigation of structuring with location prior suggested three distinct genetic populations (Delta(K = 3) = 46.05; Prob(K = 3) > 0.99). All German samples were grouped in the same genetic cluster with the sample from Austria, whereas the other samples were divided into two clusters: the Romanian samples (N = 3) and the remaining 4 samples from France (N = 1) and Spain , suggesting that the populations are at Hardy–Weinberg equilibrium.Colony sizes varied from 1 to 209 workers, with an average 104.3 ± 55.6 workers in Kallmünz and 112.3 ± 32 in Schönhofen, n = 63 colonies; however, the average increased to 118.9 ± 56.2 workers in Kallmünz and 130.2 ± 24.4 in Schönhofen based on n = 48 colonies, excluding those with fewer than 10 workers, which might have been incompletely collected  estimator.In this study, we investigated the impact of habitat scarcity on gene flow and genetic structure of colonies of the ant T. nigriceps both based on mitochondrial and nuclear DNA could be explained by a combination of isolation by distance and/or historical processes . However, at smaller spatial scales, such as the regional scale investigated in the present study, these historical processes can be confounded with more recent disturbance on contemporary genetic admixture [T. nigriceps populations, the restricted habitats of this species combined with the presence of various potential physical barriers to dispersion  were therefore assumed to induce a strong genetic structure of the species at the regional scale around Regensburg. The results of the present study indicated a lack of genetic differentiation between German populations of T. nigriceps separated by more than 15 km. This could suggest that the small queens of this ant have surprisingly large dispersal abilities. In ant species with long-range dispersal strategies, gynes typically mate during large flights away from the nests and often found monogynous colonies [T. nigriceps disperse by flight [T. nigriceps might be able to use man-made local microhabitats, such as stone walls [Various processes acting both at large and fine spatial scales can drive the genetic structure observed. Although gene flow within ant species is not always constrained by large geographical barriers , the gedmixture , such asdmixture ) or by mdmixture ). By indcolonies –27. Simine walls  with altne walls .Temnothorax nylanderi displays only weak population genetic structure in urban habitats, probably due to the micro-geographical home ranges of this forest species [Temnothorax crassispinus .Similarly, the related species  species . Neverth species , 31), inT. nigriceps exhibited non-random mating as mating pairs were more related than pairs of sexuals randomly drawn from the population. As a locally limited dispersal is unlikely in species with nuptial flights (see above), this pattern was unexpected and is difficult to explain. A synchronic initiation of nuptial flights in nests sharing micro-environmental conditions could explicate this pattern: more distant nests, experiencing different climatic conditions, might produce sexuals in different short periods of summer, leading to local nuptial flights. Such local, asynchronous mating has been observed in several ant species , culatus, ) includicolonies . This mi species . NuptialT. nigriceps and did not give evidence of the fusion of colonies or the adoption of alien queens or workers as observed in T. nylanderi and T. crassispinus. This reflects the different nest sites inhabited by the species. Nest sites of T. nigriceps, e.g., rock crevices, are comparatively stable compared to those of Temnothorax species nesting in decaying branches and hollow acorns , wh, whT. niolyandry , inducinT. nigriceps a highly fragmented landscape, populations of this species are apparently genetically not isolated at a regional scale. The results observed at the European scale suggest that the current genetic structure of the species results from past historical events rather than recent fragmentation. The investigation of genetic structuring at intermediate spatial scales would allow to untangle the drivers of gene flow within this species and to investigate demographical events implied. Models studying genetic structure at a landscape scale could be less appropriate for small species exploiting micro-habitats such as ant species, as their local ecological and/or life-history requirements drive species-specific patterns of landscape functional connectivity [T. nigriceps population structure within landscapes and genetic exchanges between colonies at a local scale. The deeper investigation of ecological requirements as well as the diversity of functional habitats for this species should allow to appreciate better the mechanisms permitting this species to overcome the negative impacts of habitat fragmentation.Despite living in very specific remnants of habitat that have been largely replaced by less favorable grasslands in the last century, constituting for the ant ectivity , 29. TheTemnothorax is a diverse genus occurring in most parts of the world, with more than 150 species in Europe, Caucasia, and Anatolia alone [riceps (Mayr 1855) is a European ant species living in sunny xerothermous habitats with sparse vegetation and bare rock  disperse by flight for mating and claustral colony founding [T. nigriceps inhabits rare, fragmented habitats and might therefore be of interest for research on gene flow in anthropized landscapes, dispersal and mating tactics have not yet been investigated in more detail and most previous studies only mention its occurrence in different European locations [ia alone ) and occia alone , 37–40).ocations –45.Fig. . nigriceps colonies separated by at least 5 m from each other were collected between June and September in 2011, 2012, and 2021 and stored in 90% ethanol. Among them, 62 colonies were collected in three distinct sites near Regensburg, Germany: Kallmünz , Schönhofen  and Riedenburg  , and for 10 of these colonies we also extracted the queen  using tmultcomp  in R v. multcomp   the five European locations and (ii) the three German geographic sites using Genepop. The degree of genetic differentiation was defined as low (0 ≤ FST < 0.05), medium (0.05 ≤ FST < 0.15), high (0.15 ≤ FST ≤ 0.25) or very high .Based on the eight worker genotypes of the 32 colonies studied , pairwise relatedness between the inferred genotypes of queens and males was calculated using two different estimators. The estimator of Queller and Goodnight  allowed Temnothorax species . All sequences were aligned using the default options in MUSCLE v3.8.31 [Global relationships among the 47 mitochondrial haplotypes were based on consensus sequences of the COI and COII sequences, corresponding to fragments ranging from 1156 to 1400 bp lengths. The sequences generated in this study were compared with two sequences obtained from GenBank for two  v3.8.31  as imple v3.8.31 . The rel v3.8.31  was usedAdditional file 1. Additional tables and figures.


Look-ahead selection is a sophisticated yet effective algorithm for genomic selection, which optimizes not only the selection of breeding parents but also mating strategy and resource allocation by anticipating the implications of crosses in a prespecified future target generation. Simulation results using maize datasets have suggested that look-ahead selection is able to significantly accelerate genetic gain in the target generation while maintaining genetic diversity. In this paper, we propose a new algorithm to address the limitations of look-ahead selection, including the difficulty in specifying a meaningful deadline in a continuous breeding process and slow growth of genetic gain in early generations. This new algorithm uses the present value of genetic gains as the breeding objective, converting genetic gains realized in different generations to the current generation using a discount rate, similar to using the interest rate to measure the time value of cash flows incurred at different time points. By using the look-ahead techniques to anticipate the future gametes and thus present value of future genetic gains, this algorithm yields a better trade-off between short-term and long-term benefits. Results from simulation experiments showed that the new algorithm can achieve higher genetic gains in early generations and a continuously growing trajectory as opposed to the look-ahead selection algorithm, which features a slow progress in early generations and a growth spike right before the deadline. The core of plant breeding is in the selection of breeding parents to improve traits of interest, such as yield, tolerance to environmental stress, resistance to pests, most of which are quantitatively inherited . TraditiImprovements in genomic prediction models for complex patterns, such as genotype by environment interactions (G × E), have received great attention. Much of the work on GS has been on the design and execution of field trials  selects the individuals with the highest GEBVs as breeding parents  from the field of finance and uses it to define a new breeding objective, which converts genetic gains in different future generations over a planning window back to the current time using a discount rate, and the trade-off between short-term and long-term performances can be adjusted using the parameters of window length and discount rate. Details of this method are developed in the next section.Here, we define some of the parameters and variables used for modeling GS.i as μ is overall mean  or not (ix = 0);decision variable i is mated with j  value of which will incentivize the model to maximize the performance in more (less) optimistic scenarios; andparameter T, created using the breeding decisions x and Y through a look-ahead simulation proposed in Y allows the model to further accelerate genetic responses by optimizing mating strategies of the selected individuals , which is to maximize the genetic gain in the best possible scenario with a probability of at least S crosses are made and that the mating is symmetric. Constraint (9) requires all decision variables to be binary.The introduction of the additional decision variable Despite the effectiveness of the LAS algorithm in accelerating genetic gain while preserving genetic diversity, it has 2 major limitations that motivated the design of the proposed algorithm.First, it is challenging to determine an appropriate value for the breeding deadline, since the goal of breeding projects is usually to achieve continuous genetic improvements. To address this limitation, we replace the fixed deadline with a rolling horizon, which restarts its planning timeline over an adjustable time interval. The interval acts as a sliding window to smooth the variability in future offspring and consider the dependence along the breeding process.λ, accounting for the time value of genetic gains and the market value of successful release of new commercial lines from the breeding program. A genetic gain achieved in generation τ would be only λ assigns a higher time value of genetic gain, putting higher weights on shorter-term performances.Second, the LAS algorithm focuses exclusively on maximizing genetic gain in the terminal generation without considering earlier performance, potentially resulting in unacceptably low short-term genetic gains. In the proposed model, we redefine the breeding objective as the PV of genetic gains over the rolling horizon, which takes a user-defined discount rate, As a result, the new method is expected to achieve higher genetic gains in earlier generations albeit at the cost of a weaker performance in the final generation, as illustrated in λ is the compound interest rate, indicating the time value of money. In the context of GS, if we use τth future generation, W the number of generations that we look ahead to, and λ the discount rate that indicates the “time value of genetic gains,” then the new objective becomes We propose to use the PV of GEBVs as the new objective for maximization. In finance , for a sHere,W is the length of the sliding window, indicating the number of generations to look ahead;parameter λ is the discount rate, indicating the time value of genetic gains. Specifically, the genetic gain τ generations is as valuable as parameter γ quantile of a random progeny’ GEBV in the τth future generation given the current decision variables x and Y.W and the discount rate λ. The window length defines the longest term that the breeders look ahead in the planning horizon, whereas the discount rate determines the trade-off between short-term and long-term genetic gains. A larger  λ places a higher emphasis on shorter-term (longer-term) performances.The model introduces 2 additional parameters: the length of the sliding window W. As such, PV-LAS is more applicable to breeding programs with goals for continuous genetic improvement. The change in planning horizon requires a different formula to calculate the recombination frequency in a future generation. In particular, PV-LAS can be seen as an extension of LAS with a modified approach to looking ahead. LAS maximizes the performance at a predefined target deadline, which gradually reduces the planning horizon as the breeding process progresses toward the deadline. In contrast, a moving horizon is used in PV-LAS, where the planning horizon is always the length of the sliding window, For all We propose a heuristic search approach to find optimal selection and mating decisions for PV-LAS by iteratively searching the solution space. The workflow of this heuristic algorithm is described as follows:Input: G, r, W, λ, S, K, and γ.Step 1: Identify a feasible solution Step 2: Randomly choose Output: the locally optimal x and Y.From our computational experiences, the LAS algorithm almost always found selfing as the optimal breeding strategy for the last generation. Our explanation for this observation is that when the breeding goal is to maximize the genetic gain in the immediate next generation, the value of a breeding parent can be largely determined by its best gamete that can be produced (within certain risk tolerance). As such, selfing the top #1 breeding parent would be more likely to produce a better progeny than crossing the top #1 with top #2. While this strategy has produced satisfactory results for the case study, it is unnecessarily the optimal strategy for all breeding programs.S = 3 crosses from a group of N = 8 diploid individuals, each genotyped with L = 10 SNPs. The breeding deadline in LAS and the length of sliding window in PV-LAS were both set as K = 500 future gametes have been simulated. We used We use a toy example to illustrate the difference between LAS and PV-LAS. Suppose we aim to make G contains genotypes of 369 maize inbred lines consisting of L = 1,406,757 SNPs distributed across 10 maize chromosomes  λ values put higher (lower) emphasis on the time value of genetic gain and led to higher (lower) growth in the short-term and weaker (stronger) performance in later generations.The introduction of the PV concept to GS is central to this work. PV-LAS uses the PV of GEBVs over a certain window period as the breeding objective by discounting genetic gain in future generations back to the current time. As such it balances the short-term and long-term benefits of genetic growth and provides a continuous growth trajectory. At the same time, PV-LAS makes a moderate compromise on genetic diversity in order to achieve a higher growth in early generations.W and discount rate λ for specific data sets can be determined using sensitive analyses.Computational results demonstrated the effectiveness of the new algorithm. Optimal window length Several research directions are worthy of future investigation. First, the simulations in this paper were based on the assumption that the estimates of additive effects of SNPs and recombination frequencies are reasonably accurate. Analysis should be conducted to assess the effects of inaccurate estimations and how to mitigate such effects. Second, we can extend PV-LAS to accommodate both additive and nonadditive effects, such as dominance and epistasis effects. Third, PV-LAS does not explicitly address G × E, which can often be substantial and create problems in finding consistently superior genotypes, leading to reduced heritability and overall genetic gain. Future research should focus on the convergence of crop modeling and machine learning approaches to explore more advanced strategies to address G × E in the breeding process.Data Sources.The datasets used the computational experiments were derived from sources in the public domain as described in


Andrographis paniculata, commonly known as kalmegh is among the most popular medicinal herbs in Southeast Asia. It is widely cultivated for medicinal purposes. The bioactive molecule, Andrographolide accumulated in herb leaves has immense therapeutic and economic potential. However, comprehensive information regarding genetic diversity is very limited in this species. The present study assessed genetic diversity between and within the six populations (ecotypes) of twenty-four kalmegh accessions using multiple datasets . This is the established report where EST-SSR (Expressed sequence tags-Simple Sequence Repeat) markers have been used to unlock genetic variation in kalmegh. Here, we identified and developed ninety-one metabolic pathway-specific EST-SSR markers. Finally, 32 random EST-SSR primer pairs were selected for genetic diversity assessment. Multivariate analysis to unveil the agro-morphological, phytochemical and genotypic variability was helpful in discriminating various germplasms studied in the present study. Among all the morphological discriptors used in present study, days to fifty percent flowering and dry herb yield were found as potential selection index for AP genetic improvement. Hierarchical cluster analysis built with agro-morphological data identified three major groups. However, corresponding analysis with phytochemical and molecular data generated two clear-cut groups among the studied individuals. Moreover, the grouping of individuals into different clusters using multiple datasets was geographically independent, and also showed inconsistency in grouping among agromorphological, phytochemical and molecular dataset based clusters. However, joint analysis using agro-morphological, phytochemical and genotypic information generated two genetic groups, which could be a valuable resource for identifying complementary crossing panels in the kalmegh breeding program. The accessions AP7, AP13, AP5, AP3 belong to cluster I and accessions AP17, AP18 belong to cluster II could be utilized as potential donors for high dry herb yield and andrographolide content, respectively in different selective breeding programs of AP. Thus, our results provided useful information about the overall genetic diversity and variation in economic traits useful for initiating selective breeding programs for contrasting traits of interest and maximizing genetic gain in kalmegh. It is desirable to assess new alleles for target traits and introgress them in breeding populations while maintaining genetic diversity. Comprehensive approaches involving phenotyping, chemotyping, genotyping, and bioinformatics tools present an enormous opportunity to measure novel alleles precisely and review the breeder’s equations for genetic improvement over time.Integrated approaches are required to accelerate the genetic gain over time in crop improvement programs concerning various economic traits and to realize the improved gain in farmers’ fields. One of the critical components required to maximize genetic gain is the enhanced genetic variance (σAndrographis paniculata (Burm. f.) Wall. ex Nees.) is a self-pollinated, annual, diploid (2n=50), and highly traded medicinal herb of the family Acanthaceae. It is well known with other vernacular names like Green Chirata, bhui-neem, king of bitter, etc. There are roughly 40 species in the genus Andrographis, with kalmegh (Andrographis paniculata) being the most popular medicinal plant species (Andrographis paniculata (AP), including ent-labdane-related diterpenes (ent-LRDs), phenylpropanoids, xanthones, and flavonoids  (Andrograhis paniculata (AP) has immense therapeutic and economic potential. Quality dry herbs of the plant are sold for as much as Rs. 17-30/kg  . Thus, A source: . The cos source: . HoweverSystematic evaluation and cataloging of genetic diversity at morphological and phytochemical levels are extremely useful for effective conservation and optimum genetic amelioration of allelic and genotypic variability. In the recent past, the introgression of molecular markers has augmented the accumulation of genetic gains achieved by morpho-chemical descriptors based characterization. In kalmegh, an array of genetic diversity studies has been done using agro-morphological traits , phytochdenovo transcriptome assembly in kalmegh has rapidly paved the way to mine and develop a large number of high throughput unigene-based SSRs (EST-SSRs) at low cost. These SSRs are possibly linked with particular transcriptional regions that contribute to agronomic traits and are well suited for marker-assisted breeding in Andrographis paniculata. To date, EST-SSR based genetic characterization has not been done in AP. Moreover, comprehensive data regarding genetic diversity studies are scanty and provide the rationale for this study , including one released and cultivated variety as a local check , where the annual temperature varies between 5°C to 45 °C. For the genetic diversity study, nursery planting was done under outdoor conditions using individual open-pollinated seed lots of twenty-four accessions in earthen pots having a combination of sandy loam soil and vermicompost in the ratio of 4:1 in the month of June 15Nine agro-morphological descriptors were measured at the reproductive stage [120-130 days after transplanting (DAT)]. Data on days to 50% flowering (DFF) and days to maturity (DM) was scored on a plot basis. However, in each replication, ten competitive plants of each accession were selected to measure other traits, i.e., plant height (PH) (cm), Number of nodes per plant (NNP), Number of secondary branches per plant (NSBP), leaf length (LL) (cm), leaf width (LW) (cm), Inflorescence length (IL) (cm), and dry herbage yield per plant (DHY) (g)Aerial parts of the plant of each accession were picked at the maturity stage and were shade dried at room temperature for seven days. Dried samples were ground into a fine powder and stored under -20°C for a short period. About 100mg of powdered samples were extracted three times in 10ml of analytical grade methanol on a sonicator at 30mins intervals. All the filtrates were combined to obtain a total volume of 30ml and evaporated to dryness under a water bath. For HPLC analysis, the dried filtrate of each sample was dissolved in 1ml HPLC grade methanol . The extraction process for each accession was done using five biological replicates.A 20ml solvent extract of individual accession was filtered into HPLC vials using disposable polypropylene syringe filters and injected into the HPLC-UV  system. The analysis was carried out as defined earlier by The genomic DNA of each accession was isolated from 0.2g frozen leaves with a modified CTAB (Cetyl triethyl ammonium bromide) extraction method  (Supplehttp://probes.pw.usda.gov/cgibin/batchprimer3/batchprimer3.cgi) developed by M) as 50-60°C, GC percentage as 40-60%, and optimal primer length between 18-25bp.The 53 non-redundant combined master control transcripts annotated and reported to be involved in specialized metabolic pathways in kalmegh variety “CIM-Megha” by M and extension for 2mins at 72 °C followed by final extension for 7mins at 72 °C. PCR products were stored at 4 °C for gel electrophoresis. Metaphor agarose gel (2%) was used to separate amplified products using a power supply of 80V for 2.5-3h and visualized under Gel documentation System . DNA ladder of 100bp  was used as standard.PCR reactions were carried out in a10µL volumes containing 5µL of dye mixed with One PCR™ supermix , 0.5µL of forward primer (5pmol), 0.5µL of reverse primer (5pmol), and 40ng of template DNA. PCR reactions were performed in a Thermal Cycler  using the following cycling conditions: initial denaturation for 5 min at 94°C followed by 35cycles of denaturation for 1min at 94 °C, annealing for 1min at temperatures ranging between 50.5 °C to 57.8 °C depending upon the primer TAll the quantitative data were statistically analyzed in software R-studio v4.0.3. The ‘variability’ package was used to perform an analysis of variance (ANOVA) on mean values of agro-morphological traits across replications . Pooled 2, where, ‘fi’ = frequency of the ‘ith’ allele (band present). Similarly, the resolving power of each primer was measured following A binary data matrix was prepared to perform molecular data analysis by scoring the presence (1) or absence (0) of amplified bands produced after gel electrophoresis. The discriminating power of primers was assessed by measuring four parameters; PIC (Polymorphic Information Content), Rp (Resolving Power), MI (Marker Index), and EMI (Effective Marker Index). The PIC was calculated following http://taylor0.biology.ucla.edu) to compute the final number of K in population structure. The analysis of molecular variance (AMOVA) and Principal Coordinate Analysis (PCoA) was performed using GenAlEx6.501 software   were used.The present study conducted with twenty-four accessions of regions) Figure 1The phenotypic diversity was assessed among experimental sets using nine agro-morphological (quantitative) traits. The analysis of variance (ANOVA) results are mentioned in Different clustering methods were used to execute phenetic analysis considering agro-morphological traits to gain reliable and precise estimates of genetic diversity present in the experimental sets. K-mean clustering, Euclidean distance-based agglomerative hierarchically clustered heatmap, and Eigen value-based Principal Component Analysis (PCA) divided all the studied germplasm into three clusters  collectively elucidated 48.40% of the total variation, as mentioned in A phytochemical dataset of twenty-four accessions was also used to estimate the level of variability present among them  collectively described 73.28% of the total variability, as shown in A. paniculata. Of these 32 primer pairs, 23 could amplify unambiguous bands, and thirteen showed polymorphic and reproducible bands. In total, 91 primer pairs were designed from 50 unique transcripts (ESTs), 23 (46%) of which comprised more than one SSR loci, as shown in A.paniculata. An average of two alleles/primer pairs were spotted, with a total of 26 alleles at 13 marker loci. The percentage polymorphism across all the primer pairs was 100%. Three representing profiles  are displayed in Finally, 13 polymorphic EST-SSR primer pairs were utilized to fingerprint twenty-four accessions of Genetic diversity was studied using binary data matrices produced by thirteen polymorphic marker loci. The pair-wise genetic similarity coefficient showed 100% genetic similarity among accessions AP4, AP17, and AP18; between AP5 & AP7; among accessions AP8, AP9, AP10 & AP12; between AP6 & AP11, and between AP13 & AP14. However, the minimum genetic similarity (40%) was observed between accession AP1 & AP10  indicated a clear peak at two with an optimum delta k value, indicating the distribution of two populations across all the studied accessions  besides forming two clear-cut clusters with each dataset  were introduced for the first time to determine the genetic variability among kalmegh accessions and to analyze the inter-relationship between agro-phytochemical traits and EST-SSR markers to speed-up trait-specific breeding in kalmegh.A. paniculata for morphometric traits.By analyzing ANOVA for nine agro-morphological traits of studied accessions, we demonstrated that all the accessions have sufficient phenotypic diversity for all traits except leaf length (LL), which could provide the basis of selection in the kalmegh breeding program. A broad range of variation was seen in kalmegh accessions against dry herb yield, plant height, number of secondary branches per plant, days to fifty percent flowering, and andrographolide content, suggesting the diverse genetic makeup of these accessions. These promising accessions from different ecological regions may be valuable resources for augmenting the genetic gains of cultivated varieties  for all traits studied except leaf length (LL), showing significant genetic control and little environmental influence on trait expression Figure 2A.paniculata accessions into different groups and revealed significant variability in chemical concentrations among experimental sets, which appears to be associated with genetic factors accumulated during selection.Different multivariate clustering methods were used to classify twenty-four kalmegh accessions based on agro-morphological and phytochemical traits. The silhouette algorithm-based k-mean clustering, Euclidean distance-based clustering, and PCA divided the experimental set into three groups based on agro-morphological attributes  successfully amplified genomic DNA and over 40% (13primer pairs) produced polymorphic and reproducible bands across twenty-four accessions (Coriandrum sativum (0.38) (Docynia delavayi (0.587) (Ginkgo biloba (0.781) (Quercus petraea (0.787) (Rhododendron arboretum where PIC was reported to be low (0.195) . In the present study, thirty-two SSRs primer pairs discovered cessions . Primer cessions Table 1.cessions . All thecessions . Our resm (0.38)  Docynia  (0.587) , Ginkgo  (0.781) , and Que (0.787)  identifi (0.195) . This intructure . The Rp,A.paniculata into two groups showing the presence of reasonable variability among them that could be potential sources for selecting parents for breeding purposes. In UPGMA-based clustering  through insect-pollination.  interaction effects observed for quantitatively inherited agro-phytochemical traits . SimilarAdequate genetic diversity is crucial to project appropriate breeding programs and develop improved varieties in kalmegh genetic improvement. In the present study, genic EST-SSR markers along with agronomic and phytochemical traits, were used to assess genetic diversity among twenty-four kalmegh accessions collected from diverse agroecological zones of India. Our results on genetic diversity revealed sufficient genetic variation in the studied population, which can be exploited for kalmegh genetic improvement and germplasm conservation. The agro-morphological descriptors, days to fifty percent flowering and dry herb yield identified as potential selection index in the present study could be utilized further in kalmegh genetic improvement program. The low genetic differentiation observed among the different agroecological populations could be improved by increasing the sample size from extended geographical regions. In our study, the inconsistency observed between genotypic and phenotypic information could be resolved by enhancing genome-wide information with more number of functional EST-SSR markers to obtain concrete outcomes from them. Our results on combined datasets expanded the scope of selective breeding in kalmegh by utilizing different trait-specific parental lines grouped in different genetic clusters generated by phenotypic and genotypic information. However, further research on economic traits using more genetic and genomic resources can complement the current study and generate more reliable information on Indian kalmegh ecotypes.The original contributions presented in the study are included in the article/GT: Conceived and designed the whole research. Designed EST-SSR markers and performed all statistical analyses. Wrote the manuscript; TC: Collected the phenotype data and performed molecular genotyping; AG: Provided experimental materials from the gene bank; KS: Performed chemical analysis; BK: Supported in lab activity required to perform whole research. All authors contributed to the article and approved the submitted version.We are grateful to the Late Dr. Hari Om Misra, Ex-Senior Principal Scientist, Division of Plant Breeding and Genetic Resource Conservation, Council of Scientific and Industrial Research-Central Institute of Medicinal and Aromatic Plants (CIMAP), Lucknow who collected the kalmegh germplasm from different parts of India. The authors are also thankful to Dr. Sumit Ghosh, Senior Principal Scientist, Division of Plant Biotechnology, CSIR-CIMAP for providing combined transcript sequences of AP variety ‘CIM-Megha’ and giving guidance for SSR marker development. The institutional communication number of the publication is CIMAP/PUB/2022/99.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Spirometra mansoni is the main causative agent of human and animal sparganosis. However, the population genetic structure of this parasite remains unclear. In this study, we genotyped S. mansoni isolates with the aim to improve current knowledge on the evolution and population diversity of this cestode.In China, the plerocercoid of the cestode We first screened 34 perfect simple sequence repeats (SSRs) using all available omic data and then constructed target sequencing technology (Target SSR-seq) based on the Illumina NovaSeq platform. Next, a series of STRUCTURE. clustering, principal component, analysis of molecular variance and TreeMix analyses were performed on 362 worm samples isolated from 12 different hosts in 16 geographical populations of China to identify the genetic structure.S. mansoni population was observed to harbor high genetic diversity, moderate genetic differentiation and a little genetic exchange among geographical populations.A total of 170 alleles were detected. The whole population could be organized and was found to be derived from the admixture of two ancestral clusters. TreeMix analysis hinted that possible gene flow occurred from Guizhou (GZ) to Sichuan (SC), SC to Jaingxi (JX), SC to Hubei (HB), GZ to Yunnan (YN) and GZ to Jiangsu (JS). Both neighbor-joining clustering and principal coordinate analysis showed that isolates from intermediate hosts tend to cluster together, while parasites from definitive hosts revealed greater genetic differences. Generally, a A Target SSR-seq genotyping method was successfully developed, and an in-depth view of genetic diversity and genetic relationship will have important implications for the prevention and control of sparganosis.The online version contains supplementary material available at 10.1186/s13071-022-05568-1. Spirometra mansoni (Cestoda: Diphyllobothriidae)  and cytochrome b [cytb]). The study identified 148 (cox1) and 83 (cytb) haplotypes within 239 and 213 isolates, indicating that mitochondrial haplotypes of Spirometra erinaceieuropaei and Spirometra decipiens were found in the three Asian countries [cox1 sequences, Yamasaki et al. [Spirometra species, Type I and Type II, are present in Asia, neither of which is close to the likely European “S. erinaceieuropaei.” Kołodziej-Sobocińska et al. [Spirometra isolates based on cox1 and cytb, and suggested that isolates from Polish and Chinese populations should be two species. Using a global full-length DNA sequence dataset of cox1, Kuchta et al. [Spirometra tapeworms and suggested that there are at least six distinct lineages of the genus. In China, the genetic diversity of isolates of Spirometra tapeworms from different geographical locations and different hosts (frogs and snakes) have been investigated in recent years [Spirometra tapeworms, there is room for improvement: (i) previous studies have relied on relatively small sample sizes with few representative isolates; (ii) the isolates used were collected mainly from intermediate hosts (frogs or snakes), with few samples from final hosts included; (iii) previous estimates of genetic diversity were based on one or only a few traditional mitochondrial markers (mostly cox1 and cytb); and (iv) no high-throughput sequencing method was applied. Therefore, our knowledge of the population diversity of S. mansoni obtained from different geographical areas of China is still fragmented.Knowledge of the extent of intraspecific genetic diversity of  and Eom  performei et al.  suggestea et al.  found dint years –16. AlthS. mansoni using a high-throughput simple sequence repeats (SSRs) genotyping method. SSRs, also known as microsatellites, are highly variable repetitive elements with nucleotide motifs of 1–6 bp and are ubiquitous in most eukaryotic organisms [In the study reported here, we explored the genetic diversity of rganisms . SSRs harganisms , 18–22. rganisms . Recentlrganisms , 24–26. rganisms . Moreoverganisms .S. mansoni isolates, we collected a total of 368 isolates from 76 different geographical locations in China, which encompassed 16 out of 26 endemic regions of human sparganosis in the country. Specifically, the following objectives were addressed: (i) development of a high-throughput SSR genotyping (Target SSR-seq) method sensitive enough to genotype S. mansoni; and (ii) exploration of the genetic structure of S. mansoni populations with broad representative samples.In order to conduct a comprehensive genetic diversity analysis of This study was performed strictly based on the recommendations of the Guide for the Care and Use of Laboratory Animals of the National Health Commission of China. The protocol was approved by the Life Science Ethics Committee of Zhengzhou University (Permission No. 2020-0704).S. mansoni isolates in 16 of these regions. For the 10 endemic regions where no samples were collected, we surveyed wild frogs for S. mansoni infections in Heilongjiang, Jilin, Liaoning, Beijing, Hebei, Shandong and Qinghai , but found no parasite-positive frog. In total, 368 samples isolated from 12 different hosts in 76 geographical locations were included in this study , 42 were plerocercoids collected from snakes  and eight were adults collected from felids . The precise locality, origin and date of collection of each sample are presented in Additional file S. mansoni by molecular genotyping with bidirectional sequencing of the mitochondrial cox1 gene  [A method for SSR genotyping using a target sequencing technology called Target SSR-seq was used to explore the genetic structure of ina Fig. . The firA761840)  to uncovA761840) . The seaA761840) . Primershttps://www.bioinformatics.babraham.ac.uk/projects/fastqc/), and subsequent analyses were based on clean reads. The total number of reads was calculated, and the samples were classified. A Perl script “SSRSeq count” str_count.pl (https://github.com/ccoo22/SSRseq_count) was used to process the clean reads to generate an SSR read count table. A Perl script str_type.pl (https://github.com/ccoo22/SSRseq_count) and the SSRSeq V1.1 online SSR genotyping tool (http://bioinfo.geneskybiotech.com/software/ssrseq_type/v1.1/en/) were used to output SSR genotypes.Two rounds of PCR were performed to construct the library. In the first round, the optimized panels were used for multiple PCR amplification using the genomic DNA of each sample as a template. After quality control, the amplified products were mixed, and the quantity of amplified products of each SSR marker was ensured to be equal. In the second round, primers with index sequence were used to add 8 bp of specific label sequences compatible with the Illumina NovaSeq 6000 platform  to the end of the library. After that, the amplified products of all samples were mixed in equal quantities, and the final FastTarget™  sequencing library was recovered by gumming. The length distribution of fragments in the library was verified using an Agilent 2100 BioAnalyzer . After the molar concentration of the library was accurately quantified, the Illumina NovaSeq 6000 platform was finally used for high-throughput sequencing in a 2 × 150-bp double-ended sequencing mode, and each SSR region was sequenced for at least 1000× coverage. In addition, positive and negative controls of PCR amplification were set to assay the repeatability of the Target SSR-seq method. Specifically, in the Target SSR-seq experiment, 3% of the total samples were selected using a double-blind method to set up as positive control, and pure water was used as a negative control. To ensure quality, raw reads must be filtered to get clean reads with FastQC , the effective number of alleles (Ne), Shannon’s information index (I), observed heterozygosity (Ho), and expected heterozygosity (He), were calculated by using the software POPGENE32 . PolymorK) was evaluated from 1 to 10. The optimal K value was determined by comparing the LnP (D) and ΔK based on the rate of change in LnP (D) [The STRUCTURE v2.3 software program was used to infer the population structure . The pop LnP (D) . Polysat LnP (D) . Nei’s g LnP (D) . The gen LnP (D) , and pop LnP (D) . The resS. mansoni isolates, we used a script in Perl to calculate the discrimination power for SSRs with the following formula: discrimination power = the number of isolates showing unique genotypes/total isolates. High discrimination power refers to high saturation value and high SSR discernibility. A core set of SSRs with the best discernibility ability was obtained, and the saturation curve was plotted by discrimination power for SSRs. Core Hunter software was used to construct a core collection based on MR (modified Rogers Distance) [To screen a minimal number of SSRs for distinguishing the maximal number of istance) . MR treaS. mansoni were obtained based on the public EST database, of which 2326 ESTs remained after a redundancy analysis to reduce overestimation. Of these 2326 ESTs, 2059 overlapped and 267 were singletons. Further analysis revealed that the 2059 overlapped ESTs could be clustered into 255 clusters; thus, a total of 522 non-redundant ESTs that contained 915 SSRs were identified after screening the EST database. In addition, combined with 3365 SSRs generated from the transcriptome data, a total of 4280 SSRs were identified by MISA analysis. Of these 4280 SSRs, 1024 (23.93%) were di-nucleotide repeats, 2720 (63.55%) were tri-nucleotide repeats and 101 (2.36%) were tetra-nucleotide repeats  was > 1000×  varied from 0.0409 to 0.9064 (mean = 0.5004), while the PIC value ranged from 0.0401 to 0.8971 (mean = 0.4508). Overall, the 34 target SSR loci showed various alleles and high polymorphism rates, which were proven to be suitable for the identification of the varieties of S. mansoni isolates.Target SSR-seq captured 170 alleles of 34 target SSR loci in 362 samples. Two motif types, trinucleotide and tetranucleotide, accounted for 88.2% and 11.8% of the 170 alleles, respectively. The number of SSR motif repeats ranged from three to seven, and 55 alleles (32.4%) contained four repeat units. The number of alleles per SSR locus varied from two to 18, with an average of five; however, the average effective number of alleles (Ne) was 2.4763, indicating a non-uniform distribution of alleles in the population  and two cats . The second group contained isolates from one frog (S. latouchii), two snakes (Z. dhumnades and E. carinata) and one tiger (P.t. tigris). The third group included isolates from one snake (E. taeniura) and one tiger . The PCoA analysis showed 54.21% and 30.5% explained variance of PCoA1 and PCoA2, respectively , CQ (17), FJ (5), GD (5), GX (3), GZ (17), HB (17), HeN (20), HN (4), HuN (37), JS (17), JX (19), SC (36), SH (3), YN (6) and ZJ (22), and samples in Pop2 were collected from FJ (n = 4), GD (12), GX (21), GZ (4), HeN (1), HN (5), HuN (39), JX (4), SC (11), YN (8) and and ZJ (8) , CQ (17), HB (17), JS (17) and SH (3) revealed one prominent genotype, whereas the remaining isolates indicated the admixture of two genotypes  based on the optimal number of  and Pop2Fst) values between specified regions were estimated to measure the population differentiation. Except for Fst values between several geographical populations , most were within the range of 0.05–0.15, indicating moderate genetic differentiation . In addition, four migrations with weak signals were detected, including one event that began from SC to JX (migration weight: 0.25), one that began from SC to HB (migration weight: 0.3), one that began from GZ to YN (migration weight: 0.5) and one that began from GZ to JS (migration weight: 0.45).The AMOVA analysis of 34 SSR genotypes in 362 samples indicated that the maximum variation of 94.40621% resulted from differences within populations, while the remaining variation came from “among groups” and “among populations within groups,” accounting for 2.13143% and 3.46236% of the total variance, respectively  had a > 1000× average sequencing depth, indicating high sequencing depth in this population genetics study. Only six of the 368 samples failed to be genotyped due to the quality of the samples, suggesting high genotyping efficiency. Additionally, the number of PCR cycles in this study was 11, while traditional genotyping methods usually reach up as high as 40 cycles; taking into account that the higher the number of PCR cycles, the higher the possibility of incurring DNA polymerase slippage, the low number of PCR cycles in our study indicate that the PCR quality was highly reliable. Moreover, the Target SSR-seq method processed our multi-target SSR loci (34 SSRs) in a large number of samples (368 samples) in a short time, confirming that this method has the advantages of higher accuracy regarding genotyping results and shorter time consumption , which is consistent with previous studies using multi-gene markers  and traditional SSRs [S. mansoni population, and both genotypes have sympatric distribution in most of geographical populations, with genotype 1 being a prevalent genotype; and (ii) there are two sub-populations: Group 1 and Group 2 are verified, with Group 1 mainly containing isolates from east and central China, and Group 2 containing isolates from south and southwest China.STRUCTURE analysis divided all nal SSRs , 14. HowFst value was used to measure genetic differentiation among geographical populations [Fst value within the range of 0–0.05 indicates little genetic differentiation; 0.05–0.15, moderate differentiation; 0.15–0.25, large differentiation; and > 0.25, very large genetic differentiation [Fst between Pop1 and Pop2 was estimated at 0.066, indicating moderate genetic differentiation between the two sub-populations. When considering the 16 geographical populations, except for Fst values between ZJ and AH, ZJ and CQ, ZJ and GZ, SC and GZ, ZJ and HuN, and SC and HuN, respectively, most of the Fst values were fell within the range of 0.05–0.15, also indicating moderate genetic differentiation. In addition, we observed higher pairwise Fst values between HN and the other 15 geographical populations, possibly due to the isolation of HN island from the mainland, leading to difficulties in gene exchange. Consistent with the results of estimated Fst, the AMOVA analysis estimated moderate genetic variation of S. mansoni in China. Generally, genetic variation among populations is highly affected by genetic drift, gene flow, mutations, selection and long-term evolution [S. mansoni is not very frequent, which may also account for the moderate genetic differentiation between populations. The ulations . Generalntiation . The paivolution . Of the volution . Gene exS. mansoni samples in each geographical population was successfully generated using the core set of 23 SSRs. Finally, a total of 76 isolates were collected thatcan represent 91.1% genetic diversity of all 362 samples. The establishment of core SSRs and core samples is essential for the optimal management and use of genetic resources of S. mansoni, and they provide a strong foundation for establishing core SSRs and core samples for the Spirometra species.Last but not least, a core set of 23 SSRs were screened further, and a core set of S. mansoni isolates. The Target SSR-seq method provides high-throughput SSR genotyping with high accuracy and efficiency. It enables accurate genotyping of S. mansoni populations and can be widely extended to genetic diversity analyses of other parasites. The results of our comprehensive genetic diversity study based on this newly established method suggest that S. mansoni samples in China have high genetic diversity and moderate genetic differentiation, and that little genetic exchange exists among geographical populations. In future studies, more populations of Spirometra isolates across worldwide geographical ranges are needed to reveal the exact genetic patterns of this medical tapeworm and discover the underlying mechanisms generating such genetic variation patterns.In this study, we successfully established a Target SSR-seq method containing 34 perfect SSR loci for genotyping Additional file 1: Figure S1. Estimates of pairwise Fst between S. mansoni populations. Figure S2. Estimated genetic structure of S. mansoni in China as inferred by the STRUCTURE software on the basis of the data on a core set of 23 SSRs. Figure S3. Principal coordinate analysis (PCoA) describing the relationships of 362 S. mansoni isolates on the basis of the data on a core set of 23 SSRs. Table S1. Information of origin, locality and date of collection for 368 S. mansoni isolates. Table S2. Primers of cytochrome c oxidase subunit 1 (cox1) gene. Table S3. SSR mining in S. mansoni. Table S4. Characteristics of a core set of 23 SSR markers. Table S5. Analysis of molecular variance (AMOVA) of the populations of S. mansoni based on a core set of 23 SSRs. Table S6. Core samples of S. mansoni identified in each geographical population of China.


Tinca tinca), a Eurasian freshwater fish that has been expanding geographically in eastern North America for three decades. Consistent with the reported history of a single introduction event, our findings suggest that multiple introductions from distinct genetic sources are unlikely as Tench had a small effective population size , no strong population subdivision across time and space, and evidence of a recent genetic bottleneck. The large genetic neighbourhood size (220 km) and weak within‐population genetic substructure suggested high connectivity across the invaded range, despite the relatively large area occupied. There was some evidence for a small decay in genetic diversity as the species expanded northward, but not southward, into new habitats. As eradicating the species within a ~112 km radius would be necessary to prevent recolonization, eradicating Tench is likely not feasible at watershed—and possibly local—scales. Management should instead focus on reducing abundance in priority conservation areas to mitigate adverse impacts. Our study indicates that introduced populations can thrive and exhibit relatively high levels of genetic diversity despite severe bottlenecks  and suggests that landscape heterogeneity and population demographics can generate variability in spatial patterns of genetic diversity within a single range expansion.Introduced and geographically expanding populations experience similar eco‐evolutionary challenges, including founder events, genetic bottlenecks, and novel environments. Theory predicts that reduced genetic diversity resulting from such phenomena limits the success of introduced populations. Using 1900 SNPs obtained from restriction‐site‐associated DNA sequencing, we evaluated hypotheses related to the invasion history and connectivity of an invasive population of Tench ( Following introduction to a new area, founding individuals typically carry only a fraction of the alleles present in their source population. This loss of genetic diversity, known as a genetic bottleneck, can increase inbreeding, reduce heterozygosity, and lessen the ability of introduced populations to adapt to novel environments  is a fish of conservation concern; on other continents, it is an invasive species  Wright, . Alterna22.12.1.1n = 238). To further understand the demographic history of the population, we also extracted DNA from 40 archived fin clips collected from individuals sampled in 2002, when the species was still geographically restricted to the Richelieu River. While the DNA was degraded for most of those fin clips, we were able to include 10 samples  in the sequencing effort.Tench were sampled across their eastern North American range Figure , spannin2.1.2Restriction‐site‐associated DNA (RAD) libraries were prepared following a three‐enzyme protocol  from M − 1 to M + 1. The other parameters were kept constant as they were shown to work well in previous reviews of stacks' parameter space .To test whether the Tench population experienced a genetic bottleneck, we used the approximate Bayesian Computation random‐forest method in DIYABC Random Forest v1.0 , we estimated the parameters involved in the invasion history: ancestral  and bottleneck population size (Nbottleneck) and the bottleneck time (td). For this analysis, the training set included 10,000 simulated datasets and 1000 trees in the random forests. We ensured that the number of simulated datasets was sufficient for scenario selection and parameter estimation by evaluating the stability of both results and accuracy metrics (results not shown).To identify the most likely demographic trajectory, we conducted the scenario‐choice analysis twice. First, we tested whether the occurrence of a genetic bottleneck was important by conducting an analysis at the group level (with vs. without bottleneck). Second, we considered the eight scenarios separately. The training set included a total of 40,000 simulated datasets (i.e. 5000 per scenario), and we fixed the number of trees in the constructed random forest to 1000. Next, for scenario 5 , within‐population gene diversity (Hs), and within‐population inbreeding coefficient (Fis) using HierFstat  method implemented in NeEstimator V2.1  to explore patterns in the genetic data and a discriminant analysis of principal component (DAPC) using the R package Adegenet , MEMgene). For these analyses, the historical samples were excluded. sPCA aims to identify spatial genetic patterns by analysing spatial autocorrelation. To do so, it computes a matrix of Moran's index inferred from the comparison between individual allelic frequencies to that of a user‐defined connection network , we computed observed heterozygosity (Ho), expected heterozygosity (He), and allelic richness (Ar) for each genetic neighbourhood with a minimum sample size of 20 individuals. We did not compute these metrics for the Lake Ontario sample because no other samples were within its genetic neighbourhood distance. Finally, as a comparison to the neighbourhood grouped metrics of genetic diversity, we also examined spatial variation in the individual‐level metrics of genetic diversity .To understand how genetic diversity is spatially distributed across the invaded range, we used sGD  from the putative origin, individual location relative to the putative origin (north or south), and their interaction, as explanatory variables in the models. To select the best models, we conducted backwards model selection by testing the significance of the fixed effects with likelihood‐ratio tests. We started with the interaction term and removed nonsignificant fixed effects from the models. We removed the Lake Ontario individual whose distance from the putative origin of the invasion was 4.5‐fold greater than the mean distance and, consequently, had a disproportionate influence on the linear regressions; however, interpretation of the results was consistent across analyses including or excluding this individual. We used gdistance . Many of the individuals discarded from the analysis were from dried fin clips, and the loss of those individuals is likely due to degraded DNA. The average read number per individual was 2,401,426 . Overall, missing data averaged 11.9% (SD = 7.8%) per individual and 11.9% (SD = 5.9%) per loci across the entire dataset. Average individual missingness was 20.1% (SD = 5.7%) and individual depth 100 (SD = 9.6) for the historical samples; average individual missingness was 11.6% (SD = 7.7%) and depth 167 (SD = 58) for the contemporary samples.3.2The DIYABC Random Forest analysis showed clear evidence of a recent bottleneck in the SLR‐Richelieu‐Champlain Tench population. Classification votes and estimated posterior probabilities were supportive of scenario group 2 , which included the contemporary bottleneck. When considering the eight scenarios independently, the highest classification votes and estimated posterior probabilities were for scenario 5 , which assumed a contemporary population bottleneck and no subsequent recovery. We observed that our capacity to discriminate between scenarios was better at the group than the scenario level, as shown by the lower overlap between the simulated datasets on the LD axes Figure  and the Focusing on scenario 5, parameter values had broad confidence intervals spanning most of the prior range. Estimated parameters (median [95% CI]) were as follows: 5244 [2138–9375] for the ancestral population size, 75 [37–99] for the bottleneck population size, and 52 generations [25–93] for the timing of the bottleneck event. Estimations were substantially more accurate for the bottlenecked population size and its timing than the ancestral population size, as determined by lower normalized mean absolute error (NMAE) values (results not shown).3.3p = 0.461) in observed heterozygosity between the historical (Ho mean [SD] = 0.308 [±0.276]) and the contemporary samples (Ho = 0.298 [±0.196])  in the contemporary (Hs = 0.295 [±0.159]) relative to the historical sample (Hs = 0.272 [±0.200]); the change represents an average gain of 2.3% of polymorphism between samples. Observed heterozygosity was higher than Hs by 3.6 and 0.3% in the historical and the contemporary samples. Accordingly, Fis was negative and significantly different from zero in the historical (95% CI = [−0.172 to 0.119]) but not in the contemporary sample ([−0.020 to 0.006]). Finally, in the contemporary sample, we obtained a point estimate for NeLD of 113.8 (95% CI = [106–122.5]). We observed that NeLD varied by nearly 25% across Pcrit values  higher internal relatedness (mean IR [SD] = 0.468 [0.109]) than the contemporary ones (IR = 0.379 [0.116]) and significantly lower values (p = 0.015) of multilocus heterozygosity . These changes represent a loss of 8.9% of the inbreeding and a gain of 2.5% of polymorphism present at the individual level between the 2002 and the contemporary samples. The internal relatedness values were all positive, indicating that both samples showed signs of inbreeding.At the individual level, genetic diversity was lower in the historical sample Figure . Histori3.4The PCA, DAPC, and tests of genetic differentiations indicated that the Tench population of eastern Canada, including both historical and contemporary individuals, is best described as a single genetic population. In the PCA, PC1 and PC2 cumulatively accounted for less than 5% of the total variance in genetic diversity Figure . While t3.5p = 0.001). For visualization, we retained the two largest positive values. sPCA axis 1 showed a clinal pattern of genetic differentiation across the invaded range . In the MEMgene analyses, a spatial pattern of genetic structuring emerged that was not evident in the sPCA analysis .Together, the sPCA and MEMgene analysis revealed patterns of weak within‐population sub‐structuring across the contemporary range of invasive Tench. In the sPCA, the global test suggested statistically significant global structure across the invaded range (max(t) = 0.001, e Figure . Genotype Figure  captureds Figure . Specifi3.6The Mantel correlograms revealed the presence of significant positive spatial structure up to the distance class of 220 km Figure . EstimatR2(191) = 0.02, p = 0.046); specifically, as distance from the origin increased, MLH decreased (−0.007 MlH/100 km). In all other models, the interaction between least‐cost river distance and individual location relative to the introduction site was significant. These models included the IR model (adj. R2(189) = 0.095, p < 0.001) and, at the genetic neighbourhood level, the Ar (adj. R2(189) = 0.85, p < 0.001), the Ho (adj. R2(189) = 0.98, p < 0.001), and the FIS model (adj. R2(189) = 0.92, p < 0.001). Ar richness decreased by 0.003 and <0.001 with distance from the origin on the northern (towards the SLR) and southern (towards Lake Champlain) invasion axes, respectively. For the other metrics , trends were in opposite directions on the two invasion axes.Linear models highlighted contrasting trends in genetic diversity metrics as a function of invasion directionality  Figure . In the In general, changes in genetic diversity metrics were of small magnitude Figure . Specifi4We analysed genomic data from the invasive population of Tench in eastern North America to discriminate between hypotheses related to the species' demographic history and connectivity. Using a dataset with 1898 SNPs for 203 individuals, we found low effective population size, a lack of marked population subdivision across space, and evidence of a recent genetic bottleneck. Consistent with the presumed invasion history of the species in Quebec  is common in species with high fecundity and early life‐stage mortality , Tench retained levels of genetic variability comparable to those exhibited by the species throughout the native range , while genetic diversity was preserved or increased along the southern Lake Champlain invasion axis. This result is compatible with two nonexclusive hypotheses related to neutral evolutionary processes. First, Tench dispersal characteristics might result in stochastic changes in allelic frequencies among invasion fronts. Indeed, fish movement is best described by dispersal kernels with greater likelihood of long‐distance dispersal events      (Bryan et al., Previous evidence from the Great Lakes suggested that losses in genetic diversity during range expansions might be a general characteristic of some populations (Brown & Stepien, 4.5if multiple introductions from undifferentiated sources have occurred, the invasive population retained its original genetic signature. Third, conclusions related to differences in genetic diversity between the two time periods are hampered by the facts that the historical samples were limited in number and their DNA, despite meeting our quality threshold, more degraded than that of the contemporary samples. As a result, allelic dropout could have led to the underrepresentation of heterozygous genotypes in the historical samples, contributing to the observed differences between the two time periods Fourth, spatial patterns of genetic diversity and structure are simultaneously shaped by ongoing range expansion and gene flow, which are themselves influenced by landscape heterogeneity and dispersal. These processes operate on different spatial and temporal scales, and their respective influence on spatial patterns of genetic diversity is difficult to disentangle (Cushman, Several issues might influence the results of our study. First, the Tench population is relatively new to the studied area, and it is possible that the effects of isolation‐by‐distance and the landscape context on population substructure require time to be realized (Anderson et al., Cushman, . To confCushman, .5Understanding the consequences of founder effects and population bottlenecks for population persistence in new environments is of great practical interest, as these eco‐evolutionary challenges are commonly experienced by both invasive and endangered species (Colautti et al., The authors declare no conflicts of interest.A research collaboration was developed between all collaborators, including scientists in academic and government agencies. Results of the research were shared with the broader scientific community. The research addresses an important topic for conservation, the rapid spread of an invasive species of major concern for native species in the St Lawrence River.Figures S1–S4Click here for additional data file.


Monitoring the evolutionary responses of species to ongoing global climate change is critical for informing conservation. Population genomic studies that use samples from multiple time points  are uniquely able to make direct observations of change over time. Consequently, only temporal studies can show genetic erosion or spatiotemporal changes in population structure. Temporal genomic studies directly examining climate change effects are currently rare but will likely increase in the coming years due to their high conservation value. Here, we highlight four key genetic indicators that can be monitored using temporal genomics to understand how species are responding to climate change. All indicators crucially rely on having a suitable baseline that accurately represents the past condition of the population, and we discuss aspects of study design that must be considered to achieve this. Population genomic studies that use samples from multiple time points  are uniquely able to make direct observations of change over time, and are critical to documenting how species are responding to climate change. Here, we highlight some key genetic indicators that can be monitored using temporal genomics to understand how species are responding to climate change: genetic erosion, spatiotemporal population structure, hybridization, and adaptation. ContempDue to the valuable genetic information obtained, temporal genomics is increasing in popularity and demand  may be readily available in good numbers in research collections and likely have meta‐data. Because many of the direct impacts of climate change began in the last century  by revisiting a population that they had fortuitously sampled a few months prior to the event. Their study revealed rapid and strong selection on gene expression and cold tolerance. Similarly, in invasive species such as Burmese pythons (Python bivittatus), a rare freeze event leading to mass mortality was also used to identify directional selection on loci putatively associated with freeze tolerance  are becoming increasingly common due to global climate change and have strong biodiversity impacts  are currently rare. A now well‐known example is from populations of Tamias alpinus, an alpine specialist chipmunk, in Yosemite National Park. It has undergone upslope range retractions due to increases in minimum winter temperatures, and analysis of temporal samples from the 1910s and present found genetic erosion had occurred because of this  is thought to have masked signals of severe genetic erosion , several scenarios may have played out: (a) local extinction and recolonization by a different lineage occurred ; (b) increased gene flow with other populations caused large shifts in allele frequencies; or (c) the population became isolated and experienced strong genetic drift. Climate change could drive any of these three scenarios, and understanding what has occurred can provide valuable insights into how species are responding and how to manage them.Climate change is altering species ranges see Box , which iBOX 3Aedes aegypti mosquitoes . They used temporal samples from the center and margins of the native range and a broad spatial sample of the recently invaded range to investigate the range expansion process.As climate shifts, the geographic locations where species are found are changing. Some species' ranges are expanding, while others are contracting and others shifting to follow their historical climatic niche  have shown population‐specific patterns of lineage stability in the face of climatic shifts and over‐fishing. In some cases, little differentiation is observed, indicating populations have remained highly stable since the 1900s, while other populations have clearly gone extinct and been replaced by another lineage , for example, were present in North America for several decades but only recently began to expand and hybridize with native cutthroat trout. In this case, temporal samples tracking levels of admixture over a 30‐year period and modeling of climatic variables showed that decreases in spring precipitation and increases in summer stream temperature were facilitating the spatiotemporal spread of hybridization between the two trout species ; investigation ; visualization ; writing – original draft ; writing – review and editing . Deborah M. Leigh: Conceptualization ; investigation ; visualization ; writing – original draft ; writing – review and editing .Lib4RI ‐ Library for the Research Institutes within the ETH Domain: Eawag, Empa, PSI & WSL, funded the open access publication fees for this article.The authors declare that there is no conflict of interest.


Callinectes ornatus Ordway, 1863 exists as two distinct genetic clusters separated by the AOP. However, questions concerning migration, diversification time, and species delimitation are unresolved. Densely sampling markers across the genome (SNPs) could elucidate the evolutionary processes within this species. Here, we combined mtDNA data and ddRAD-seq to explore the diversification patterns and processes within the swimming crab C. ornatus. We show great genetic differentiation between groups on the north and south sides of the plume but also signs of hybridization. Demographic modeling indicates the divergence between groups starting around 8 Mya following the AOP’s formation. After a period of isolation, we detect two incidences of secondary contact with stronger migration in concordance with the North Brazil Current flow. Our results suggest speciation with gene flow explained by the interplay among the AOP, oceanographic currents, and long larval dispersal. This work represents the first investigation employing ddRAD-seq in a marine invertebrate species with distribution encompassing the north and south Atlantic and sheds light on the role of the AOP in the diversification of a marine species.The Amazon–Orinoco plume (AOP) is the world’s largest freshwater and sediment discharge into the ocean. Previous studies limited to mtDNA suggest that the swimming crab  Understanding marine species diversification remains challenging for ecologists and evolutionary biologists . The int3/year and extends 400 km off the coast and 30 m in depth  150).Double digest RADseq libraries were prepared according to the ddRADseq method . Brieflyprocess_radtags program in STACKS v.2.3d [Callinectes sapidus) reference genome  using no threshold. Then, we used the function --missing-indv on VCFtools v. 0.1.17 [Raw sequence files were demultiplexed (--inline-index), cleaned (-c), quality-filtered (q), and rescued (-r), allowing two mismatches using the S v.2.3d . Short rIMET_V1, ) using BIMET_V1, ,53,54 wiIMET_V1, . Using B. 0.1.17  to asses. 0.1.17 . We set . 0.1.17 . The pop2) between SNP pairs using the function --geno-r2 in VCFtools v. 0.1.17. Only pairwise SNP comparisons within the same chromosome and with more than half of our final sample size were considered. SNPs showing r2 > 0.8 were excluded from the final dataset. Two different approaches were implemented to identify outlier SNPs , BayeScan v.2.1 [Because most of the analyses assume that SNPs are independent, SNPs potentially under linkage disequilibrium (LD) were detected by calculating the squared correlation coefficient . Nref was determined using θ/θ0, in which θ is the population-scaled mutation rate given in the output of the GADMA run and θ0 = 4 × µ (mutation rate per base per generation) × L (length of the sequence that was used to build the data). Because there is no µ estimate for C. ornatus or swimming crabs, we used the value calculated for Drosophila melanogaster [Daphnia pulex [−9. The average sequence length of the ddRAD-loci used as L = 188.41 bp. Callinectes ornatus generation time was considered as one year [We performed demographic modeling analyses to find the best scenario explaining the two genetic groups—north and south, separated by the AOP (see results). Simulated and observed two-dimensional joint site frequency spectra 2D-JSFS) were compared using the Genetic Algorithm for Demographic Model Analysis . Loci ws engine  were uses engine ,1; finalD-JSFS wenogaster  and Daphia pulex : 4 × 10−one year .We used 66 sequences (570 bp), including 12 new sequences not included in , represeAfter process_radtags , we retained ~570 million reads across 63 individuals (69% retained reads). After the ref_map pipeline, the unfiltered set of markers consisted of 91,098 loci, composed of 15,501,392 sites, covering approximately 2% of the genome. After the filtering steps, 10 individuals were excluded  and we kept 53 individuals . The refThirteen SNPs showed signals of LD and were excluded from the dataset. Although BayeScan and PCAdapt detected potentially non-neutral SNPs, the analyses did not converge to the same SNP set. Therefore, we decided not to exclude any SNPs and assume differences in allele frequency and genetic differentiation in some loci due to neutral processes . Our final dataset for downstream analyses was composed of 899 SNPs. ST indicates high divergence between genetic groups detected by STRUCTURE (FST = 0.267). FST across the genome indicates moderate to high differentiation in all chromosomes  . The splC. ornatus on the north and south sides of the AOP. However, we also found evidence for secondary contact, the first occurring during the Miocene (~4 Mya) and characterized by migration from the south to the north, and the second occurring during the Pleistocene and characterized by asymmetrical migration, which causes admixture between both lineages. These results challenge the validity of C. ornatus as a single species and suggest a cryptic speciation scenario with gene flow. Employing mtDNA and ddRAD-seq, we provide an example of how dynamic the diversification process can be in the marine realm and stress the importance of the AOP for the diversification of marine species within this region.Our results indicate allopatric divergence following the emergence of the Amazon–Orinoco plume (AOP) between ST and STRUCTURE also find two genetic groups (north and south), showing high genetic differentiation (FST = 0.26). However, the STRUCTURE plot also shows admixture between north and south, indicating that complete differentiation has not occurred, as expected in cases of complete speciation  in both types of markers (mtDNA and SNPs). Here, we added to  COI datan e.g., ,78). We . We ST aC. ornatus’s sensitivity to salinity changes. A comparative phylogeographic study investigating C. ornatus and C. danae, two swimming crabs with the same dispersal potential but different salinity tolerance, indicates that the tolerant species (C. danae) is not affected by the plume [C. ornatus groups on the north and south sides of the plume.Considering that there are sister species separated by the AOP in a broad range of taxa , the allopatric periods between north and south might have been enough to accumulate divergence caused by genetic drift. This result is corroborated by the fact that we found regions showing high FST across the whole genome and not concentrated in specific regions, indicating that genome-wide divergence has been accumulating for a long time [GADMA detected low migration rates from south to north around 4 Mya, which can be explained by the closure of the Isthmus of Panama, leading to the formation of the North Brazil Current (NBC) . Howeverong time . At the ong time .C. ornatus.A traditional paradigm postulates marine environments as open systems because of the lack of barriers and potential broad dispersal due to an extended larval stage of several marine species . HoweverEven isolated for millions of years, lineages can interbreed after secondary contact if no reproduction isolation has evolved ,93. As wC. ornatus.Speciation is often a continuous process that eventually results in complete reproductive isolation . In mariC. ornatus has gone through a divergence period likely driven by the emergence of the AOP, but the two lineages mixed after secondary contact caused by larvae transported by marine currents. Low salinity tolerance is likely the trait responsible for differentiation, and PLD is responsible for secondary contact. A thorough morphological investigation has failed to reveal a diagnostic character that allows species-level differentiation ([Many questions remain concerning the diversification patterns and processes of marine species ,97. Our tiation (, personatiation (. Howevertiation (.