Coptotermes formosanus (Shiraki) is recognized as one of the 100 worst invasive pests in the world, with established populations in Japan, Hawaii and the southeastern United States. Despite its importance, the native source(s) of C. formosanus introductions and their invasive pathway out of Asia remain elusive. Using ~22,000 SNPs, we retraced the invasion history of this species through approximate Bayesian computation and assessed the consequences of the invasion on its genetic patterns and demography. We show a complex invasion history, where an initial introduction to Hawaii resulted from two distinct introduction events from eastern Asia and the Hong Kong region. The admixed Hawaiian population subsequently served as the source, through a bridgehead, for one introduction to the southeastern US. A separate introduction event from southcentral China subsequently occurred in Florida showing admixture with the first introduction. Overall, these findings further reinforce the pivotal role of bridgeheads in shaping species distributions in the Anthropocene and illustrate that the global distribution of C. formosanus has been shaped by multiple introductions out of China, which may have prevented and possibly reversed the loss of genetic diversity within its invasive range.Native to eastern Asia, the Formosan subterranean termite  Coptotermes formosansus from eastern Asia to the US using approximate Bayesian computation. They find a complex invasion history, with multiple introductions originating from eastern Asia, as well as a bridgehead introduction originating from Hawaii, which appears to have mitigated the loss of genetic diversity within the invasive US range.Blumenfeld and Eyer et al. retrace the invasion history of the termite  Remarkably, the accumulation of introduced species worldwide has yet to reach saturation6, and the harmful effects these invasive species have on the communities and ecosystems they invade cannot be overstated8. The success of invasive species in their new environments has often been considered paradoxical, as they are able to persist and outcompete native, locally adapted species despite experiencing bottlenecks that reduce their genetic diversity, and thereby possibly their fitness10. However, there is growing evidence that genuinely paradoxical invasions are not so common11, as the loss of genetic diversity in invasive populations is less frequent and less intense than previously expected14. In addition, low genetic diversity in introduced populations measured at neutral markers  does not necessarily correlate with low variation in ecologically relevant traits11. Indeed, quantitative variation is usually lost at a reduced rate during invasions compared to diversity at molecular markers15, and pre-adaptive traits that confer success in the invaded range may render reduced genetic diversity inconsequential17. Furthermore, the degree of genetic loss may differ under distinct invasion histories. The amount of genetic diversity brought to the introduced population increases with the size of the propagule and additional re-introductions during multiple introduction events from the same or genetically distinct source populations17. In rare cases, genetic diversity might be higher within an introduced population than its native, source populations18. Sometimes, introductions originate from an already invasive population rather than a native population—a phenomenon known as the ‘bridgehead effect’21. This may lead to an extreme loss of diversity, as subsequent introductions arise from an already depauperate introduced population22. Investigating patterns of genetic diversity within the native and introduced populations of a species may provide insights into past demographic events and allow for reconstructing its invasion history24.Biological invasions are a defining feature of the AnthropoceneCoptotermes formosanus (Shiraki) is currently recognized by the IUCN as one of the 100 worst invasive species in the world25, establishing invasive populations in Japan, Hawaii, and the southeastern United States26. Like all invasive termites, this species nests in and feeds on wood, thereby increasing its chance of being transported through merchandise trade27. Coptotermes formosanus is thought to be native to eastern Asia, though its exact origin remains unclear. It has long been suspected to originate from the vicinity of Formosa , where the type specimen was described28. A southern China origin was also suggested due to the presence of termitophilous beetles associated with C. formosanus colonies29; however, these beetles were later found to also occur within colonies in Japan31. This southern China origin was previously supported by the high diversity of Coptotermes species present (24 species32), but the recent identification of at least nine synonymized species of C. formosanus in the region undermines this hypothesis33. Recent phylogeographic studies using mitochondrial DNA (mtDNA) have also struggled to determine the origin of this species, as the variation of this marker is extremely low. These studies found either no variation between samples from Taiwan, China, and Japan35, or extremely low levels38. Even the complete mitochondrial genome reveals more than 99.9% similarity, with only a six nucleotide difference between three Japanese islands39. Overall, these studies have failed to conclusively identify the origin of the species within East Asia; however, they all suggest that the Chinese, Taiwanese, and Japanese populations are closely related, hinting at an early human-mediated movement of the termite throughout this region40.The Formosan subterranean termite C. formosanus. However, these studies have similarly suffered from the lack of genetic variation in the mtDNA present within native populations43. As a result, no mtDNA variation was found in Hawaii41, and only 0–0.3% of variation was found on three mtDNA genes despite global sampling, with clades separated by a maximum of 3 bp differences37. Although the lack of mtDNA variation hampers the reconstruction of the invasion history of this species, several studies have found that introduced populations do belong to the same clade, suggesting that US populations of C. formosanus arise from at least two introduction events out of eastern Asia45. Based on microsatellite markers, at least five different sources of introduction have been suggested46, with high similarity between the populations of Hawaii, Louisiana, and North Carolina44. This finding suggests that these introduced populations either stem from a common native source population or that the mainland US population originated from a Hawaiian bridgehead. Conversely, strong differences in cuticular hydrocarbon signatures between Hawaiian and continental US samples of C. formosanus suggest that Hawaiian populations may not be the source of the continental US populations47. Overall, despite many studies attempting to elucidate this termite’s path out of eastern Asia, its exact invasion history remains unresolved.Several studies have also attempted to reconstruct the invasion history of C. formosanus out of eastern Asia and into the US. We sampled this species in both its native and introduced ranges and used double digest restriction-site associated DNA sequencing (ddRADseq48) to obtain markers of high resolution . We first conducted population structure and phylogenetic analyses of the global C. formosanus population to assess genetic structure within its native range and determine the genetic relationship between native and introduced populations. Second, we used approximate Bayesian computation (ABC) to decipher its worldwide routes of invasion. Finally, we investigated introduction-induced effects on population demography, such as population bottlenecks, expansions, migration, and admixture, to assess the consequences of the invasion on the global genetic patterns of this species.In this study, we aimed to determine the origin(s) and the number of introduction events of FIS) as well as the observed and expected heterozygosity values for each locality are provided in Supplementary Fig. The 359 samples yielded 0.16–43.7 million paired reads per individual, with an average of 12.9 million reads. Thirty-four individuals had a high amount of missing data , and were thus removed from the dataset. The final dataset contained 22,229 polymorphic loci and 33,601 SNPs for 325 individuals from the 22 populations, with an average coverage of 44× and 6.8% of missing data. To prevent linkage from affecting the population structure and phylogenetic results, only one random SNP per locus was kept. The inbreeding coefficients , rather than from southcentral China (46 RF votes) or eastern Asia (79 RF votes) exclusively. For the second step, the Hong Kong region , was separated from eastern Asia , with the introduced US population best explained by admixture between eastern China and Hong Kong (S2c) when considering only two-population admixture. However, this scenario was outvoted (only 31 RF votes) in the third step when the possibility of admixture between all three populations was considered, regardless of the first admixture event . In addition, sub-steps 2A and 2B confirmed the inclusion of the Japanese populations into the two eastern Asian sub-regions.When the Hong Kong region was reintegrated within eastern Asia, the fourth step  was not conclusive, as two scenarios gained a similar number of RF votes. The first one suggested that Hawaii and the US mainland originated independently from eastern Asia and southcentral China, respectively , while the other proposed that Hawaii results from admixture between eastern Asia and southcentral China, with the US mainland arising from a Hawaiian bridgehead . This discrepancy seemed to be driven by a split between most Florida samples and the rest of the mainland, which is also depicted in fastSTRUCTURE. Indeed, sub-step 4 subsequently confirmed a Hawaiian bridgehead to the US mainland , when the US mainland was split between Florida and Louisiana/Texas. The fifth step confirmed that both eastern Asian regions were involved in the invasion of Hawaii and Louisiana/Texas , when the Hong Kong region was separated from eastern Asia .Finally, the sixth and final step revealed that the population in Florida most likely resulted from admixture between Louisiana/Texas (49%) and southcentral China 51%) 87 years ago, and Louisiana/Texas to originate solely from the admixed Hawaiian bridgehead population 98 years ago  that originated from at least two distinct events, and their admixture, out of sub-eastern Asia and the Hong Kong region. This introduced Hawaiian population later served as the source for the invasion of the US mainland (~1930), where an additional introduction event from southcentral China occurred in Florida (~1940). These dates match up well with the generally accepted timeline of its invasion to the US. The first recorded observation of this species in the US dates back to the early 1900s in Hawaii50, although there is evidence that it had been established as early as 186951. Within the mainland US, C. formosanus was first recorded in South Carolina (195752), Texas (196553), and Louisiana (196654). However, its strong association with military ports receiving and storing equipment and supplies from the Pacific theater after World War II54 led to the widely held theory that it was introduced to the US mainland around this time period, aligning closely with our time estimates.Our study unravels the global invasion history of 56, and has been proposed to be a relic of the Last Glacial Maximum that would have restricted available habitat for subtropical species to the extreme southern edge of China57.Much of the diversity present in the native range is highly structured among the native populations, with almost every native population representing a unique genetic cluster. The PCA and low values of K revealed two primary groups within the sampled Chinese range . Such a split is found in other eastern Chinese organismsC. formosanus between its native and introduced range using microsatellite markers, which found substantially reduced diversity in each introduced population sampled relative to the native range46. However, RADseq derived SNPs have been found to more accurately estimate genome-wide diversity than microsatellites59, which may explain the contrasting results obtained in the present study. This outcome is perhaps surprising because the founding event following an introduction usually reduces diversity within invasive populations, suggesting that multiple introduction events from distinct source populations may have prevented and even reversed the loss of diversity within the invasive range of C. formosanus.There was a slight reduction of genetic diversity within the introduced US range compared to the entire native range. Yet, the genetic diversity within each US population was equivalent to the diversity present in each of the native populations, indicating this termite’s invasion has not been accompanied by a drastic loss of diversity at the population level Fig. . This fi46. Interestingly, Husseneder et al.46 also identified two genetic clusters within the US mainland, with South Carolina being distinct from Louisiana and North Carolina. Unfortunately, samples from South Carolina were not included in our analyses, preventing the identification of a possible link between South Carolina and the second cluster we found in Florida. In addition, we are unable to rule out a Japanese influence in the C. formosanus invasion of the US, and whether the Japanese populations60 are invasive. While the demographic histories for both Okinawa and mainland Japan did display evidence of a bottleneck, genetic diversity statistics of the two populations were not drastically different from Chinese populations and clustering between the two is not present unless K is substantially reduced.Our clustering, phylogeographic and ABC results consistently show that eastern China is the prominent source of the invasive populations in Hawaii and the mainland US, congruent with the hypothesis of Husseneder et al.62, and eastern Asia includes some of the largest and busiest ports in the world, such as Hong Kong, Shanghai, and Tokyo. The long history of both trade and immigration between China and the Kingdom of Hawaii dates back to the late 1700s, and centers around the southeastern region of China  and Honolulu (main port of Hawaii)64. Notably, the population of Chinese in Hawaii drastically increased from 364 individuals in 1852 to 18,254 individuals in 188463, with most immigrants originating from this southeastern portion of China. Japan has also had a long history of immigration to Hawaii, from both the mainland65 and Okinawa66, as almost 200,000 Japanese moved to Hawaii between 1886 and 192465. These large-scale immigration events from eastern Asia coincide with the first suspected evidence of a subterranean termite in Hawaii51.Human and merchandise transportation hubs have been shown to be an important factor in the spread of invasive species throughout the worldC. formosanus likely arose from an already established invasive population in Hawaii through bridgehead rather than from an independent introduction directly from the native range. Indeed, cases of introduced populations themselves becoming the source of further introductions are being recognized more commonly71, including in other eusocial insects like invasive ants. For example, global phylogeographic analysis of the red imported fire ant Solenopsis invicta revealed that after its primary introduction event into the southeastern US from South America, this southeastern US population served as the source for its further spread to the rest of the world72. Furthermore, ants as a whole display striking secondary introduction rates, with over 75% of ants intercepted at US and New Zealand ports of entry originating from locations where they had already been introduced21. While termite interceptions at US ports of entry have hinted at their potential to spread via bridgeheads73, our study empirically elucidates a bridgehead invasion in a non-ant social organism, with C. formosanus utilizing Hawaii as a stepping-stone for its subsequent invasion of the US mainland. This suggests that bridgeheads may play a crucial role for social insects in achieving multi-continental distributions, warranting further research into the invasion histories of other globally distributed social insects. For example, the West Indian drywood termite Cryptotermes brevis  likely represents a bridgehead invader, as it is native to the coastal deserts of Peru and Chile and is now invasive on five continents27.Our ABC analysis suggests that the US mainland populations of 76. In this context, bridgehead populations may reduce inbreeding depression in subsequent invasive populations through the purge of deleterious alleles during recurrent founder effects77. On the other hand, reduced genetic diversity in bottlenecked bridgehead populations may promote the rapid evolution of invasive traits, as rates of adaptive evolution substantially increase with reductions in population size79. For this reason, bridgeheads have been hypothesized to be a stepping-stone for invasion by selecting for invasive traits81. These traits may increase the ability of an invader to be further spread to novel locations, confer greater ecological advantage that enables them to outcompete native species, and aid in circumventing the low genetic diversity in bottlenecked populations86. Despite this hypothesis of adaptive spread as a driver of the bridgehead effect, empirical evidence for this evolution of invasiveness is still lacking22, and the evolution of specific invasive traits within the Hawaiian population of C. formosanus remains undetected.Bridgehead introductions have drastic effects on genetic diversity as introduced populations often experience bottleneck events. While some invasive species merely tolerate this genetic depletion, some benefit from the periodic purge of deleterious alleles through founder effectsC. formosanus, C. gestroi (Wasmann), is also established in Florida87. These species have overlapping nuptial flights88 and form tandem pairs of reproductive individuals90; however, this hypothesis was ultimately found to be unlikely, as hybridization should be identifiable at low values of K. Furthermore, these two species are also sympatric in Hawaii and Taiwan, and none of the three regions display a highly negative FIS commonly observed due to hybridization. Instead, Florida as a separate genetic cluster appears to stem from a distinct introduction event out of southcentral China.The presence of two genetic clusters in the mainland US signaled that the invasion pattern was more complex than just a single introduction from the Hawaiian bridgehead, and subsequent analysis confirmed a separate introduction event from southcentral China had indeed occurred. It seems most likely this additional event occurred within Florida, given it clustered separately from the other US populations and that the scenario describing Florida as a result of admixture between Louisiana/Texas and southcentral China was found most probable, as well as its unique demographic history. We also considered the possibility of interspecies admixture being the cause of Florida clustering separately, as a sister species of Reticulitermes flavipes. This species is native to the eastern US and has been introduced to France, Canada, the Bahamas, Uruguay, and Chile. Interestingly, most introduced populations of this species seem to originate specifically from New Orleans, Louisiana92. While New Orleans is an important hub for global trade, this species is also present in major trading cities along the eastern seaboard that have seemingly played no role in their spread. This suggests that certain traits of R. flavipes colonies within the New Orleans region may have pre-adapted this population to invasion, such as their distinct breeding structure and reduced antagonism between non-nestmates93, which they share with introduced populations in France97 and Chile92. Therefore, this finding is similar to the hypothesis suggested for bridgehead populations, whereby the evolution of specific traits conferring higher invasiveness primes a population for further invasion. This similar scenario has been coined the ‘Anthropogenically Induced Adaptation to Invade’ and suggests the evolution of adaptations to human-modified habitats in specific native populations favor their subsequent spread16. Such local pre-adaptation to invasion has been observed in the native range of the little fire ant Wasmania auropunctata, with natural populations mostly displaying small non-dominant colonies headed by sexually produced reproductives, while anthropogenic populations shift to large and dominant supercolonies headed by clonal reproductives98. The similar life‐histories of native anthropogenic populations and invasive populations suggest that these traits, which evolved within its native range, may act as pre-adaptations to human-altered habitats and favor its worldwide invasion16. Yet, despite being one of the most widespread invasive termites worldwide, introduced colonies of C. formosanus do not appear to have experienced a major shift in their breeding system or colony structure when compared to native colonies100. Therefore, the worldwide invasion of this termite seems unrelated to these life-history traits. However, as native samples in this study were collected solely from human-disturbed habitats, we cannot be certain C. formosanus has not already undergone selection toward anthropogenic landscapes in their native range, like W. auropunctata. Whether there are other physiological factors enhancing their ability to thrive in human-modified habitats or whether no specific pre-adaptation is required, meaning each native population has the capacity to produce an invasion viable propagule, remains to be seen. Overall, these findings stress the need for comparative research between the introduced and native range, where key evolutionary processes promoting invasions may be occurring.Multiple events out of the native range from different source populations differ from the invasion pattern observed in another invasive subterranean termite, Coptotermes formosanus colonies were sampled in both their native and introduced ranges , and purified using AMPure XP beads (Beckman Coulter Inc.) to make the ddRADseq library. Each library pool was size selected to a range of 300–500 bp using the BluePippin system (Sage Science Inc.). Quantity and size distribution were assessed using the Qubit® 2.0 Fluorimeter (Life Technologies Corp.) and Bioanalyzer 2100 System (Agilent Technologies). Amplified fragment libraries were then pooled in equimolar amounts and sequenced on six lanes of an Illumina HiSeq 2500 machine to generate 150 bp pair‐end reads.101, with reads of the two lanes then concatenated after ensuring no lane discrepancies . Forward and reverse reads were assembled and SNPs were generated using the de novo pipeline of Stacks v.2.41102. The main parameters for the analysis were optimized following the r80 loci method103. Briefly, a representative subset of samples was taken from the main dataset to run through the de novo pipeline under varying values of its most influential parameter , in order to identify the value that produced the greatest number of polymorphic loci found in 80% of the population. After parameter optimization, filtered reads were run through the de novo pipeline of Stacks, which built and genotyped the paired-end data, as well as called SNPs using the population-wide data per locus. Only SNPs present in at least half of the individuals in all populations were kept for downstream analyses. In addition, alleles at low frequency (<0.05) and loci with high heterozygosity (>0.7) were filtered out as these are likely byproducts of sequencing errors and paralogs104. Furthermore, SNPs with <5× mean coverage and exceeding 200× mean coverage were filtered out using VCFtools v.0.1.15105, to buffer against unlikely SNPs and avoid highly repetitive regions of the genome. To prevent linkage disequilibrium (LD) between SNPs from affecting the population structure and phylogenetic analyses, only one random SNP per locus was kept. All subsequent file format conversions were accomplished through PGDSpider v.2.1.1.5106.Raw sequences for each lane were examined separately to check for read quality and adapter contamination using FastQC v0.11.8E), observed heterozygosity (HO), inbreeding coefficients (FIS)), and population differentiation (FST) indices for each locality were calculated in Stacks. Population structure among the 22 sampled locations was analyzed using three complementary approaches. First, population structure was assessed by estimating the most likely number of genetic clusters  in the dataset using fastSTRUCTURE v1.040107. fastSTRUCTURE runs were parallelized and automated using Structure_threader108. Different values of K ranging from 1 to 22 were analyzed, and the best value was selected using the chooseK.py function from the fastSTRUCTURE package. Plots were created by Distruct v2.3109 (available at http://distruct2.popgen.org). Second, we used both a principal component analysis (PCA) and discriminant analysis of principal components (DAPC) to estimate clustering in the data .Genetic diversity . We then conducted a rapid bootstrap analysis and search for the best-scoring maximum likelihood tree using the extended majority rule (MRE)-based bootstopping criterion117 to determine an appropriate amount of bootstrap replicates. All searches were performed using the GTR + G nucleotide substitution model.Maximum likelihood (ML) phylogeny among C. formosanus by selecting the most likely evolutionary scenario using ABC118. The number of competing scenarios exponentially increases with the number of potential source populations and demographic events compared in the analysis24, which requires considerable computational effort. Therefore, to more efficiently allocate this effort, we utilized a recently developed random forests (RF) machine learning tool to conduct model selection and parameter estimation (ABC RF119). ABC RF requires a considerably reduced number of simulated datasets compared with alternative methods, while also providing a more reliable estimate of the posterior probability for the best model. We also decreased the required computational effort by inferring the invasion history of C. formosanus through a step-by-step analysis (six different steps), which is commonly performed in ABC studies121. The mainland Japan and Okinawa populations were included in the ABC analysis as a member of the eastern Asia region given their strong clustering within the region in the population genetic and phylogenetic analyses (see “Results”). In addition, two localities (Xinyu and Mississippi) were excluded from all ABC steps as only one sample was available for each location. Briefly, the first step aimed at identifying which region(s) of the native range  have contributed to the introduction of C. formosanus, with the introduced US range pooled as a single population. The second and third steps aimed at determining which region(s) of eastern Asia  played a role. The fourth and fifth steps tested for the origin of the Hawaiian population and the possibility of a bridgehead effect in Hawaii; thus, Hawaii was analyzed separately from the mainland US. Finally, the sixth step considered the occurrence of a distinct introduction event to Florida.We inferred the invasion routes and colonization history of 122, with at least 10,000 simulations per model performed on 2000 randomly sampled SNPs for each of the steps above. Priors were set uniform for all model parameters and selected based on historical records. The timing of introduction events to the US was set to between 50 and 300 years ago, with the condition that the introduction in Hawaii (for steps 4–6) occurred prior to the introduction to the southeastern US, consistent with historical records46. In addition, for all scenarios tested, the decrease in effective size of an introduced population was allowed to vary between 1 and 100 migrants, and the duration of the bottleneck set to vary between 0 and 50 years for each introduction event. The range of all other priors was adjusted by evaluating the posterior distributions of the preliminary simulated datasets, then setting the prior distribution as wide as possible while retaining biological meaning. All summary statistics included in the DIYABC software were used for each analysis, and both model selection and parameter estimation were performed through ABC RF123, available in the abcrf R package.Model simulations were first run in DIYABC v2.0124 to investigate recent changes in population size . Unlike traditional skyline plot methods for demographic inference which compute a likelihood for a whole sequence125, Stairway Plot 2 instead calculates the composite likelihood of a given SNP frequency spectrum (SFS)127. This method uses the expected number of mutation(s) per base pair to measure time and θ per base pair to measure population size . The full catalog of SNPs was retained for this analysis; however, only SNPs with no missing data (by population) were used in the SFS calculations due to the difficulty of integrating missing data when modeling the SFS under coalescent approaches. Folded SFSs for each locality were generated by the vcf2sfs R script128. The demographic history for each population can be seen in Supplementary Fig. We inferred the demographic history of each locality by using Stairway Plot 2Sampling locations and sample sizes for each location are listed in Supplementary Table Further information on research design is available in the Supplementary InformationSupplementary DataReporting Summary


Aedes aegypti (Ae. Aegypti) is considered the primary vector of Dengue virus transmission in Yunnan Province, China. With increased urbanization, Ae. aegypti populations have significantly increased over the last 20 years. Despite all the efforts that were made for controlling the virus transmission, especially on border areas between Yunnan and Laos, Vietnam, and Myanmar (dengue-endemic areas), the epidemic has not yet been eradicated. Thus, further understanding of the genetic diversity, population structure, and invasive strategies of Ae. aegypti populations in the border areas was vital to uncover the vector invasion and distribution dynamic, and essential for controlling the infection. In this study, we analyzed genetic diversity and population structure of eight adult Ae. Aegypti populations collected along the border areas of Yunnan Province in 2017 and 2018. Nine nuclear microsatellite loci and mitochondrial DNA (mtDNA) sequences were used to achieve a better understanding of the genetic diversity and population structure. One hundred and fourteen alleles were found in total. The polymorphic information content value, together with the expected heterozygosity (He) and observed heterozygosity (Ho) values showed high genetic diversity in all mosquito populations. The clustering analysis based on Bayesian algorithm, the UPGMA and DAPC analysis revealed that all the eight Ae. aegypti populations can be divided into three genetic groups. Based on the mtDNA results, all Ae. aegypti individuals were divided into 11 haplotypes. The Ae. aegypti populations in the border areas of Yunnan Province presented with high genetic diversity, which might be ascribed to the continuous incursion of Ae. aegypti.Dengue fever is a mosquito-borne disease caused by the dengue virus.  Aedes mosquitoes and one of the major public health problems worldwide. More than 3.9 billion people across 128 countries are at risk of DF infection, while some 100–400 million infections occur each year1. Since the first outbreak of DF in China, which occurred in Guangdong province in 1978, DF has been causing epidemic cycles every 4–7 years in China2.Dengue fever (DF) is an acute infectious disease transmitted by 3, especially in the Yunnan Province. This southeast Chinese province comprises 16 prefectures and 129 counties and is characterized by a tropical and subtropical climate, which is conducive to dengue virus infection4. Besides, Yunnan Province shares a 4,060-km border with Laos, Vietnam, and Myanmar, all of which are dengue-endemic areas2. Since 2004, sporadic imported cases of DF have almost been reported annually in Yunnan Province, China, while the first cases of local infection occurred in 2008 in Dehong prefecture and Lincang City6. In 2013, a large-scale dengue outbreak occurred in Dehong and Xishuangbanna prefectures.Over recent years, an increase in human cases of DF has been observed in ChinaAedes aegypti and Ae. Albopictus mosquitos are the main vectors that transmit the virus to humans7. These mosquitoes are widely distributed in tropical regions, especially in Southeast Asia8. Ae. aegypti is mainly found in densely populated urban areas9. In Yunnan province, the first case of Ae. aegypti-borne viral infection was reported in Jiegao Port, Ruili, in 200210. At present, the distribution of Ae. aegypti is still limited to border port areas and has not spread to the inland area of Yunnan Province. However, it has been gradually adapting the climate and environment of Yunnan Province. It has been confirmed by field monitoring that a large number of breeding sites has been found in Dehong, Longchuan County and other ports in nearby areas, and it has become a new member of mosquito population in this area13.DF prevention and control depend on effective vector control measures. However, DF has four different serotypes that may affect epidemic control. 14 indicated a population invasion of Ae. aegypti in the border areas of Yunnan Province. Over the last few years, Yunnan Province has taken measures to comprehensively control Ae. aegypti populations in this area. For example, the “Patriotic Health Movement” and “Building a civilized city” campaigns were carried out in the border cities. The ports of Yunnan Province adopted integrated prevention and control methods to control the vectors, using environmental governance and vector monitoring so as to cut off the transmission channels and prevent large-scale invasion and spread of vectors in the region. However, the DF epidemic has become a serious public health threat, which kept being among the top 5 reported cases of the infectious diseases in Yunnan Province. Therefore, it is necessary to continue implementing the analysis of Ae. aegypti population and the tracking of invasive events.Shi et al.16. Microsatellites, also known as simple sequence repeats (SRSs) or short tandem repeats (STRs) are short, tandemly repeated DNA motifs of 1–6 nucleotides distributed throughout eukaryotic genomes17. The microsatellite markers show the advantages of high polymorphism, co-dominant expression, and extensive genomic distribution, and have been proven useful for detecting the subtle population structure18. Mitochondrial DNA (mtDNA) is commonly used in molecular evolution studies of insects19. The mtDNA is more sensitive to genetic drift and has greater genetic differentiation. It is particularly useful for detecting genetic differences and reconstructing the transmission history of invading mosquitoes21. Previously, nuclear microsatellite markers and mtDNA sequences were used to investigate the genetic diversity and population structure of Ae. aegypti across the Yunnan Province region22. The whole genetic information can inform us on the invasion routes, the colonizing capacity, adaptability, and behaviors of invading mosquito lineages23.Genetic techniques could be used to infer the pathways and sources of invasive species, inform the genetic composition and demographic history of founding populationsAe. Aegypti those were collected along the border area of Yunnan Province in 2017 and 2018.In this study, we analyzed genetic diversity and population structure in eight populations of adult Ae. aegypti populations24. The microsatellite locus SQM 6 had the highest PIC value (0.886), whereas the locus SQM 1 the lowest PIC value (0.392) (Table The polymorphic information content (PIC) value is one of the indicators used to measure allele richness of genes. A total of 114 alleles were found for the nine genetic markers; all alleles were sequenced. As shown in Table He and Ho value of all Ae. aegypti populations ranged from 0.385 to 0.605, which suggests that the genetic diversity of all mosquito populations is relatively high  and observed heterozygosity (Ho) value of the population. igh Fig. . Except IS values in all Ae. aegypti populations, except population YJ, were positive, ranging from 0.05882 to 0.24657 , the ratio was relatively low  after Bonferroni corrections were applied.The pairwise F20 Table , showingAe. aegypti, all Ae. aegypti individuals from nine populations were divided into 11 haplotypes, among which H1, 2, 3, 7, and 8 were the main haplotypes. The distribution of these haplotypes in a specific population is shown in Fig. Aedes aegypti showed that the distribution of nucleotide mismatches in this population had a single peak structure, indicating that the population of Ae. aegypti had experienced at least one significant population expansion  in human and is mainly distributed in southeast China. The most suitable habitats of Ae. aegypti include Hainan, Guangdong, Guangxi, the western and southern border areas of Yunnan, and parts of the southern Guizhou region27. Yet, due to climate changes and increased urbanization, a significant northward shift occurred in the northern Chinese region over recent years28.The information on invasion and spread of mosquito vectors is essential for understanding vector-borne disease outbreak, transmission dynamics among human populations and implementing effective mosquito control programsAe. aegypti is an invasive species and potential vector of disease agents in China, which has a significant impact on public health. Ae. aegypti-associated infection was first reported in Yunnan Province  in 200229. In 2009, the Ae. aegypti was detected for the first time in Guanlei Port, Mengla city, Xishuangbanna prefecture30, and later on (2014) in Lincang, Mengding county31. The distribution range and abundance of Ae. aegypti species have significantly increased, and were established in at least eight cities in Yunnan Province. Therefore, the monitoring of Ae. aegypti species is essential for preventing and controlling vector-borne infectious diseases. In our study, all the Ae. Aegypti samples were collected from eight sampling places in three prefectures of Yunnan Province . The DF cases in Yunnan Province mainly originated from these prefectures.Ae. aegypti species in the Yunnan border region had a great allelic variation. The Ae. aegypti mosquitoes may easily transmit the virus to humans and usually find shelter in indoor habitats. Their flight range is limited, which means they can only move hundreds of meters around their larval habitats32. The relatively high genetic diversity of all mosquito populations is most likely caused by invasion events and human activities33. The results of IBD analysis support this conclusion that the dispersal of Ae. aegypti species is aided by human activities and transportation in Yunnan Province.Our population genetics analyses of the populations from Yunnan border area that were based on two types of genetic markers (Microsatellites and mtDNA) revealed the genetic structure and the population distribution within this region. The PIC value, He and Ho value were important parameters for measuring the genetic diversity of a population; the higher the value, the more complex the population structure is. Our results revealed that Ae. aegypti populations could be divided into three genetic groups. The first group had four populations in the Xishuangbanna prefecture  and RL city, which might be related to the close tourism and commercial trade exchanges between these two regions. The second group represented two populations from Lincang City. The third group was composed of LC and YJ. Contrary to other six populations, YJ population is closely related with LC population, which is significantly different from the UPGMA result. The differences may come from the sample size and range.Bayesian algorithm-based population analysis showed that all IS) values of eight other Ae. aegypti populations were positive. Combined with the UPGMA and DAPC analysis, the results indicated that there may have a recent invasion and colonization of the Ae. aegypti in YJ city. Due to the limited flight range, this phenomenon is common for Ae. aegypti population on a small spatial scale33. In 2016, the Xishuangbanna Prefecture established a “Spring Patriotic Health Movement” with the scope to provide the integrated control for infectious disease vectors. This may explain the bottleneck effect observed in ML and RL.Except for Yingjiang, the inbreeding coefficient . The H1, which was the dominant haplotype, was found in five places. The analysis of all mosquito samples from two localities in Lincang City (MD and CY) showed only one haplotype (H1) for each gene. Dehong Prefecture is close to Myanmar border, and the intensive personnel activities have led to a large number of invasion events. The abundant waters and commercial activities in Xishuangbanna prefecture have also contributed to many invasion events. This idea was supported by the high levels of polymorphism detected in Xishuangbanna and Dehong prefectures , which may be the main entry points of Ae. aegypti in Yunnan Province. The H2 haplotype was only distributed at YJ independent from other regions. Combined with the negative FIS value of population YJ, the Ae. aegypti species likely invaded Yunnan Province from this region over recent years.MtDNA markers have been widely used to evaluate the genetic diversity of Ae. aegypti population invade these areas because of the continuous tourist and business activities. Inspection and quarantine need to be strengthened at the border ports and further investigation and research on mosquito vectors should be carried out. The government needs to designate effective prevention and control measures, strengthen environmental governance in the border areas and implement mosquito control measures.Our research shows that in Dehong and Xishuangbanna prefectures, Ae. aegypti in the border area of Yunnan Province. Although several attempts have been made by the government of Yunnan Province to control the mosquito vectors, the Ae. aegypti populations in this region showed high genetic diversity and genetic structure due to the continuous invasion, and increased urbanization. Our research confirms that, over recent years, a significant Ae. aegypti invasive event occurred in YJ City; and that the Xishuangbanna and Dehong prefectures were important areas for the Ae. aegypti invasion.The nuclear microsatellite markers and mtDNA sequences  were used to uncover the population genetics of the Ae. aegypti in Yunnan Province is still a demanding task that needs to be taken seriously. Thus, monitoring of suspected cases of DF and the vectors should be enhanced.In summary, our results suggest that the control of Ae. aegypti samples were collected from following eight locations along the border area of Yunnan Province between May 2017 and September 2018 ; the quality and quantity of extracted DNA were analyzed using NANOdrop1000, after which samples were stored at − 20 °C until further analysis.39. The primer sequences and information are summarized in Table 8, forward primers were labeled with a fluorescent dye . All the samples were amplified in the 25 μL reaction, which consisted of 2.5 μL 10 × PCR Buffer, 1 μL 1:10 DNA template, each primer at 0.3 μM, dNTPs at 0.25 μM, MgCl2 at 1.5 mM, TaqDNA polymerase 1.25U and ddH2O. The PCR conditions were as follows: 94 °C for 5 min; 35 cycles at 94 °C for 45 s  capillary sequencer. All microsatellite alleles were evaluated using GeneMapper software (Applied Biosystems)14. The genetic diversity of all Ae. Aegypti populations were characterized by expected heterozygosity (He) and observed heterozygosity (Ho), using POPGENE version 1.32. The FIS value of each mosquito population was also calculated. The statistical significance test was performed with the exact tests available in POPGENE40.The PIC values of all nine loci were calculated with PIC-Calc 0.641. The sign test implemented in the software was used to test for significant heterozygosis excess. The isolation by distance (IBD) was estimated with Mantel's test in R, using the correlation between genetic distance and geographic distances by the regression of pairwise FST/(1 − FST) on the natural logarithm (Ln) of straight-line geographic distance.The genetic variation was tested by the AMOVA test with Arlequin (version 3.5.2.2) for the interpretation of genetic variability and structure among different locations, mosquito populations. The AMOVA was evaluated at four different hierarchical levels: (1) all samples (non-grouped) were analyzed as a single group to test the overall genetic differences between samples; (2) the samples in one region were analyzed as a unique group; (3) the interregional populations were analyzed as an unique group; (4) the individual sample within population was analyzed as an unique group. Based on the stepwise mutation model (SMM), the recent genetic bottleneck in each mosquito populations was calculated by the software BOTTLENECK 1.2.02. The data were analyzed with the recommended settings: an index statistic closer to 1 indicates that the population is in a stable state, while a very low value indicates that the population has experienced a genetic bottleneck in the past42. The software parameters were set as follows: the assumed populations ranged from 1 to 8, and the calculation model was set as admixture ancestry and independent allele frequency models 100,000 burn-in steps followed by 1,000,000 MCMC replicates, and each population was calculated for 10 runs. The optimum K value was estimated with Evanno’s △k method based on the second-order rate of change in the log probability of the △k among 10 runs of each assumed K43, and all the results were uploaded to a web-based utility Harvest for the calculation of the optimum K value (https://taylor0.biology.ucla.edu/struct_harvest/). Furthermore, the software CLUMPP 1.1.1 and DISTRUCT 1.1 (Rosenberg 2004 and 2007) were also used to calculate the average coefficients of membership across the 10 replicates of real K value, and the final results were displayed. In order to further explore the genetic structure, UPGMA trees were computed with NTsys, based on microsatellite Nei’s genetic distance. The DAPC analyses were conducted under the R (vision 3.6.2) condition with the R package “adegenet 2.1.0”.For the determination of real genetic clusters (K) within all mosquito samples, a Bayesian clustering algorithm-based software STRUCTURE 2.2 was employed. All mosquitos were divided into different populations represented by a specific number (K = 8), under the assumption of Hardy–Weinberg equilibrium and linkage equilibriumAe. aegypti were chosen as the examination sites for exploring sequence polymorphism. At least ten mosquito individuals from each population were selected from the previous microsatellite analysis and identified by the amplification and sequencing of the COI gene. All the mosquito DNAs were amplified with the ND4 primers, which were composed of ND4 forward-(5′-TGATTGCCTAAGGCTCATGT-3′) and ND4 reverse-(5′-TTCGGCTTCCTAGTCGTTCAT-3′) primers targeting 344 bp fragment. The following PCR procedure was used: 5 min of initial denaturation (94 °C) followed by thirty cycles of 94 °C, 40 s of denaturation at 56 °C, 40 s of annealing at 72 °C, 1 min of extension and a final extension at 72 °C for 5 min. The 50 μL PCR solution was composed by 5 μL 10 × PCR buffer, 0.3 μL TaqDNA polymerase (5 U/L), 5 μL dNTP (2 mmoL/L), 2 μL of each of the forward and reverse primers (10 μM), 5 μL template DNA and ddH2O. The PCR amplification products were confirmed by agarose gel electrophoresis. All the PCR products were purified with the PCR Purification Kit (OMEGA D6492-02) and cloned to the pMD18-T vector  for the final sequencing with ABI 3730XL automatic sequencer (Applied Biosystem).The mitochondrial genes ND4 and COI of All the sequences were analyzed with the software Sequencer 5.0 and BioEdit v7.0.570, and aligned with Clustal W. For the ND4 gene, haplotype diversity (Hd), nucleotide diversity (π) and the Tajima and Fu and Li neutrality tests of all mosquito populations were computed by DNA Sequence Polymorphism v6.12.01. A haplotype network of all mosquito populations was also constructed with the software NETWORK 5.0.1.1 for inferring the relationships of all haplotypes and the distribution of all haplotypes at different locations.Pre-permission (May 2017 to September 2018) was granted for adult mosquito observation, adult mosquito collection, and studies in Yunnan province. All the studies were authorized by the Committee for Animal Welfare and Animal Ethics in the Institute of Parasitic Diseases of Yunnan province, China .


Guizotia abyssinica) is an economically important oilseed crop in Ethiopia and India. The present study sought to develop new DNA markers for this crop. Transcriptome sequencing was conducted on two genotypes and 628 transcript sequences containing 959 single nucleotide polymorphisms (SNPs) were developed. A competitive allele-specific PCR (KASP) assay was developed for the SNPs and used for genotyping of 24 accessions. A total of 554 loci were successfully genotyped across the accessions, and 202 polymorphic loci were used for population genetics analyses. Polymorphism information content (PIC) of the loci varied from 0.01 to 0.37 with a mean of 0.24, and about 49% of the loci showed significant deviation from the Hardy-Weinberg equilibrium. The mean expected heterozygosity was 0.27 suggesting moderately high genetic variation within accessions. Low but significant differentiation existed among accessions . Landrace populations from isolated areas may have useful mutations and should be conserved and used in breeding this crop. The genomic resources developed in this study were shown to be useful for population genetics research and can also be used in, e.g., association genetics.The development and use of genomic resources are essential for understanding the population genetics of crops for their efficient conservation and enhancement. Noug ( Guizotia abyssinica (L. f.) Cass.) is among the cultivated species of the family Asteraceae. Similar to other Guizotia species, noug is diploid (2n = 30) with relatively small chromosomes [G. scabra ssp. schimperi, a suggested progenitor of noug, is only 55.3% of that of noug [G. scabra ssp. schimperi when compared with that of noug [Noug .Noug is the second-largest oil crop according to both harvest area and total production in Ethiopia, only surpassed by sesame . HoweverSingle nucleotide polymorphism (SNP) markers are the most recent and popular DNA markers with a diverse use in the analyses of the genomes of crops. SNP markers are amenable to high throughput genotyping by sequencing technologies and have been extensively used for genotyping of various crops for different applications, including genetic diversity analyses, genome-wide association research, and genetic linkage mapping ,30,31,32The objectives of the present study were (1) developing new genomic resources for noug for various applications through transcriptome sequencing of noug genotypes, SNP discovery based on the transcript sequences and converting the SNPs to KASP markers, and (2) genotyping of noug accessions using the newly developed SNP/KASP markers for population genetics analyses.Two self-compatible noug breeding lines developed from landrace populations C19 and K13  were useThe two self-compatible lines were planted in a greenhouse at the Swedish University of Agricultural Sciences (SLU), Alnarp, for RNA extraction. Total RNA was separately extracted from leaf tissue of two-week-old seedlings of the two self-compatible lines using a spectrum plant total RNA kit . The extracted RNA was treated by Qiagen RNase free DNase  to get rid of any DNA. The RNA samples were then sent to the University of California (Davis) and library preparation, transcriptome sequencing, assembly, and SNP analysis were conducted at the Genome Sciences Center. A non-normalized cDNA library was prepared following the Illumina’s guidelines and sequencing was done on the Illumina GAII, as described for the dahlia in Hodgins et al. . TranscrHelianthus annuus), and only varying from the reference in one parent were further selected. SNPs that varied from the reference in only one parent were targeted in order to use them for genotyping of a mapping population developed using these genotypes as parents. These SNPs were further filtered by eliminating SNPs with varying sites within a 10-bp range on either side or SNPs with indels in either parent. All cases where more than one noug gene hits the same mapped Helianthus contig were also removed to avoid close paralogs. This filtering procedure resulted in 959 SNPs within 628 noug contigs. The accession numbers and full sequences of the 628 reference transcripts as well as the SNP sites, reference, and alternate alleles at each of 959 SNP loci are provided in After transcriptome assembly, SNP calling was made through aligning the transcript sequences to the reference sequences, and mapping the reads to the aligned sequences using BWA , SAMtoolhttps://biosearch-cdn.azureedge.net/assetsv6/Plant-leaf-kit.pdf). Each accession was represented by 12 individuals except NG099 and NG108 (https://www.biosearchtech.com/products/extraction-and-purification-reagents/dna-purification-kits/sbeadex-kits) at the LGC-Genomics facility.The 24 noug accessions were planted in a greenhouse at SLU, Alnarp, for DNA extraction. A young leaf tissue was collected from two-week-old seedlings separately from individual plants for each accession using a LGC plant sample collection kit (KBS-9370-001) provided by LGC-Genomics  and the genotype clusters were viewed using LGC’s SNP-viewer application (https://www.biosearchtech.com/support/tools/genotyping-software/snpviewer) that displays the two homozygotes and the heterozygote classes as separate clusters plate by plate.A file containing the 628 reference transcript sequences, the reference and alternate alleles of the 959 SNP loci, and their positions in the reference sequences were provided to LGC-Genomics. These data were then used for designing a competitive allele-specific PCR (KASP) assay for each SNP locus. Among the 959 SNP loci, a KASP assay was successfully designed for 931 loci, whereas 28 of them failed the KASP assay design. Hence, 931 SNP loci were used for the genotyping of the 281 samples. The genotypic data was received from LGC-genomics and analyzed using LGC’s KlusterCaller software   was usedGenotypic data across 202 SNP loci  were useIS were −0.90, 1.00, and 0.13, for FIT were −0.89, 1.00, and 0.21, and for FST were 0.01, 0.24, and 0.10, respectively  varied from 0.01 to 0.50 with a mean of 0.29 whereas polymorphism information content (PIC) varied from 0.01 to 0.38 with a mean of 0.24 . A largeectively A. The esectively .p < 0.01) and significant (0.01 < p < 0.05) deviation, respectively. On the other hand, 5.9% of the loci showed excess heterozygosity with 4.4% and 1.5% showing highly significant (p < 0.01) and significant (0.01 < p < 0.05) deviation, respectively. Examples of the SNP loci showing a highly significant deviation from HWE and the description of their corresponding sunflower homologs are provided in The Hardy-Weinberg equilibrium (HWE) test revealed that 50.7% of the loci are at HWE whereas 49.3% of loci showed significant deviation from HWE . A totalVarious genetic diversity parameters were estimated for each accession based on the 202 polymorphic loci. The percent polymorphic loci (PPL) of the accessions ranged from 72% (NG108) to 85% (NG092) with a mean of 79%. The Shannon diversity index (I) ranged from 0.38 (NG124) to 0.42 (NG092) with a mean of 0.40. The lowest and highest observed (Ho) heterozygosity values were recorded for accessions NG124 (0.22) and NG099 (0.26) with a mean of 0.25. The expected heterozygosity (He) and unbiased expected heterozygosity (uHe) of the accessions ranged from 0.26 and 0.27 (NG106) to 0.28 and 0.29 (NG092) with a mean of 0.27 and 0.28, respectively. The fixation index (F) of the accessions ranged from 0.01 (NG099) to 0.16 (NG092) . There wST = 0.045, p < 0.0001). The vast majority of the within accession variation (93.9%) was attributed to the variation within individuals (heterozygosity). Hierarchical AMOVA was conducted by grouping 21 of the 24 accessions (excluding the two cultivars and the breeding population) into (1) three altitudinal groups, (2) six geographical regions (regions-I), and (3) two geographical regions (regions-II) (CT = 0.001 and p = 0.19). Similarly, there was no significant differentiation between the six regions-I groups (FCT = −0.001 and p = 0.67). However, there was significant differentiation between the two regions-II groups (Oromia vs. Amhara-Tigray) (FCT = 0.002 and p = 0.047).The analysis of molecular variance (AMOVA) was conducted without grouping the accessions as well as by grouping them according to their geographic region of origin or altitudinal range of their collection sites . The anaions-II) . HoweverST was also computed for each pair of the 24 accessions, and 268 of the 276 pairs (97.1%) showed significant differentiation between them with FST values ranging from 0.017 to 0.124 (ST ranging from 0.006 to 0.012). The lowest and the highest FST values were recorded for NG111 vs. NG123 and NG096 vs. NG097, respectively  to 0.076 (NG097). Accessions NG096 and NG124 also showed higher differentiation from the other accessions having mean FST values of 0.074 and 0.072, respectively. On the other hand, Fogera and NG123 are among the least differentiated accessions with mean FST values of 0.031 and 0.033, respectively.AMOVA-based Fto 0.124 . Only eiectively . The meaOne hundred twenty-six individuals having genotypic data for all loci  were selected across the 24 accessions and the evolutionary distance between each pair of individuals was computed for loci with MAF below 0.3 using Tajima-Nei method . The neiPrincipal coordinate analysis (PCoA) was also conducted to determine the relationship between the accessions. In the two-dimensional plot generated, the first and the second coordinates explained 24% and 20% of the total variation among the accessions A. This aThe admixture model-based population genetic structure analysis conducted using STRUCTURE  and STRUThe present study used transcriptome sequencing for the development of novel SNP markers for noug, which were used to design KASP assays and for genotyping 24 Ethiopian noug accessions. The fact that transcript sequences of only two genotypes were used for SNP discovery and the multi-step stringent procedures followed to identify and filter the SNP markers led to a relatively small number of SNPs 959). The use of a few genotypes as an SNP discovery panel can lead to an ascertainment bias ,59. This. The useGenetic polymorphism research remains key for the understanding of variability in organisms’ genetic makeup, and it is usually a prerequisite for the analysis of genetic variation for use in conservation and practical plant breeding. The development of genomic resources and tools for a crop is a crucial step both for the determination of genetic diversity and for the development of DNA markers associated with desirable traits for use in marker-aided breeding, and such resources and tools are often lacking for underutilized and minor crops. In the present study, useful and novel genetic information was gathered for noug despite the moderate success rate of the KASP genotyping.SNP loci can be bi-, tri-, or tetra-allelic ,61 but bGuizotia scabra, a closely related wild/weedy species [In this study, 30% of the SNP loci have a minor allele frequency of less than 0.1, and as a result, the overall mean effective number of alleles was slightly below 1.5. The average observed (Ho) and expected (He) heterozygosities across the 202 loci were 0.25 and 0.29, respectively. In a study on a single noug population conducted using 43 EST-SSR markers, Dempewolf et al.  reported species . These v species ,20. This species ,68,69. O species  when comIT, FIS, and FST), also referred to as F-statistics, are measures of inbreeding in terms of total population (T), sub-populations (S), and individuals (I) for each locus [IS and FIT indicate excess heterozygosity and a value of one for these indices indicates 100% homozygosity in each sub-population. For FST, a measure of differentiation of sub-populations, the maximum value is attained when sub-populations are fixed for different alleles. In the present study, each accession is considered as a sub-population and the 24 accessions together form a total population. Noug is a strictly outcrossing species [IS values ranged from −0.90 to 1.00, indicating that some loci are in a state of heterozygote excess whereas some other loci lack heterozygotes. The mean values of FIT, FIS, and FST revealed in the present study were 0.13, 0.21, and 0.10 in that order. The values of these indices were 0.19, 0.15, and 0.04 in an EST-SSR based study [The fixation indices . The accessions with the lowest  and highest PPL  were from northeastern and eastern Ethiopia, respectively. Interestingly, both accessions are from areas less known for noug cultivation. In terms of genetic variation within accessions , NG108 and NG106 are the lowest whereas NG092 and NG095 are the highest. These landrace populations are from different regions and hence the levels of genetic variation within landrace populations cannot be attributed to regions of cultivation. Similarly, NG092, NG095, and NG106 are landrace populations collected from middle-altitudes , and theThe 24 accessions showed several folds of variation in terms of fixation index (F) ranging from 0.013 (NG099) to 0.162 (NG092). Accession NG092 differs from most of the accessions not only in its higher genetic variation but also in having a larger deviation from HWE on average. On the other hand, the accessions are quite similar in terms of showing a low level of variation in diversity parameter Theta (H) that measures nucleotide diversity based on effective population size and mutation rate . The sim2) and loci with MAF below 0.3 (EAED3), in addition to their combined analysis (EAED1). A slightly higher positive correlation (r = 0.79) for EAED1 vs. EAED2 than for EAED1 vs. EAED3 (r = 0.75) suggests that loci with MAF equal to or above 0.3 may have a higher effect on overall evolutionary divergence within populations than loci with a MAF below 0.3. The lack of correlation between EAED2 and EAED3 suggests that the selection of noug landrace populations for conservation and breeding should consider SNP loci with a MAF below 0.3 and equal to or above 0.3 separately, as different populations may be more valuable for conserving higher genetic diversity or in harboring desirable traits in the case of the two groups of loci. For example, accession NG111 is the highest in EAED2 but the second-lowest in EAED3, revealing that it has lower frequencies for MAF below 0.3 when compared to almost all other accessions. This is different from the case in accession NG103, where all three EAEDs are the lowest.Analysis of average evolutionary divergence over sequence pairs within populations using the Tajima-Nei model  produced2 (0.447) and highest EAED3 (0.205) compared to the other two altitudinal areas. The results suggest that low-frequency alleles are more common in the lowland than in the highland areas of noug cultivation. This provides a slightly higher weight for lowland areas as sources of new alleles than higher altitude areas. The comparison of the two cultivars and the breeding population on one hand and the landrace populations on the hand clearly indicate that the breeding process did not have negative effects on the overall genetic divergence between individuals with populations, including for loci with a MAF below 0.3. This is probably because the loci included in the present study do not have an effect on the traits targeted for breeding and hence the alleles were not differentially selected.Noug accessions from low altitudes areas (1400 to 1680 masl) had the lowest EAEDPartitioning the total genetic variation into the within and among populations components is an important step in understanding the genetic structure of populations and their adaptation to local environmental conditions. Outcrossing species generally tend to have higher genetic variation within populations than among populations, which is partly attributable to higher gene flow between populations than in the case of self-pollinating species ,75. BothPlectranthus edulis), an outcrossing species, and a clonally propagating crop, also revealed very low genetic differentiation (2.5%) among populations [In an EST-SSR-based study, Dempewolf et al.  reportedulations . Generalulations ,78; 70% ulations ,80), comulations ), field ulations ), and duulations ). Howeveulations  and koraulations , respectIn agreement with previous noug research ,20, therST (0.076) followed by NG096 (0.074; Arabidopsis [The cluster analysis at the individual genotype level produced three major clusters . However6 0.074; . Accessibidopsis ,87. FurtVarious approaches have been used to determine the source of individual genotypes in population genetics research ,88,89,90In the present study, transcriptome sequencing was conducted, and novel SNP markers were identified in noug. More than 50% of these SNPs were successfully converted to KASP markers and used for the genotyping of noug populations collected from wide geographic areas in Ethiopia. Polymorphic SNP/KASP markers were used for population genetics analyses. The loci with high PIC or showing highly significant deviation from HWE should be prioritized for further research in this crop. The study revealed low but significant differentiation between noug populations. Nonetheless, there was generally a lack of, or poor differentiation between noug at different altitudinal ranges or regions level. This indicates strong gene flow between populations grown at different altitudes and regions, particularly between major noug cultivation areas. However, this study also gave clear indications that landrace populations cultivated in isolated areas deviate in genetic diversity from those populations in common noug cultivation areas. Thus, such populations from isolated areas in Ethiopia may be sources of useful mutations, and hence should be considered for their conservation and use in breeding of this oil crop. Overall, the transcript sequences and the SNP and KASP markers developed in this study are highly useful resources for applications such as population genetics analyses and genome-wide association research. However, the markers are relatively small in number and were developed based on only two genotypes. Hence, methods such as RNAseq based on a larger number of diverse germplasm should be applied to develop DNA markers, in the thousands, that can have wide applications by avoiding potential drawbacks associated with ascertainment bias. This approach facilitates the identification of markers associated with traits of interest through genetic linkage and association mapping, for their use in marker-aided breeding.