Semisulcospira reiniana. This species meets the conditions that migration from source populations can prevent local adaptation in a sink population because they inhabit the broader range of environments, including middle/upper reaches of a river and estuaries within a single river and they may be more vulnerable to being swept away by water currents due to lowered spontaneous (upward) locomotion activity. We found that river steepness was related to the lower distribution limit of S. reiniana, with a narrower distribution range in the steeper river. Population transcriptomic analysis showed that gene flow was heavily asymmetric from the upstream populations to downstream ones in the steep river, suggesting a greater migration load in the steep river. The number of genes putatively involved in adaptation to the local habitat was lower in the steep river than in the gentle river. Gene expression profiles suggested that individuals achieve better local adaptation in the gentle river. Laboratory experiments suggested that evolutionary differences in salinity tolerance among local populations were only found in the gentle river. Our results consistent with the hypothesis that migration load owing to asymmetric gene flow disturbs local adaptation and restricts the distribution range of river snails.One of the most important questions in evolutionary biology is how the spatial distribution of species is limited. Asymmetric gene flow from core populations is suggested to increase the number of poorly adapted immigrants in the populations at the range edge. Genetic load due to migration, i.e., migration load, should prevent adaptation to the local habitat, leading to decreases in distribution range via local extinction or the limiting range expansion. However, few experimental studies have examined the effects of immigration on fitness and natural selection within recipient populations. To investigate the influence of migration load on the evolution of distribution range, we performed field and laboratory observations as well as population transcriptomics for the common river snail,  In practice, abundant evidence of ongoing adaptation to environmental continuums has been reported3. Thus, given evolutionary periods of time, any species can adapt to novel environments and extend its range permanently across the globe. However, the distribution of many species ends abruptly, without the presence of obvious ecological or physical barriers, suggesting that adaptation is prevented at the edge of the range4. Elucidation of the processes preventing adaptive evolution at range margins is therefore important to our understanding of the evolutionary mechanisms that determine species ranges and the pattern of species diversity on earth.Traits within a species are known to change gradually across the geographical space. The existence of spatial variation in fitness-related traits indicates that populations can adapt to environmental continuums within the species’ range or within a habitat and that they can adapt to novel environments with inhospitable conditions8. (ii) If the range edge is highly fragmented, stochastic events and the low rate of mutational input into marginal populations may limit the availability of locally beneficial alleles, preventing adaptation and therefore range expansion (diversity loss hypothesis)9. In general, failure of adaptation along an environmental gradient due to diversity loss is recognized as the predominant process at larger geographic scales because the effect of migration input and migration load is relatively small10. In practice, many empirical studies have detected indications that the loss of genetic diversity is the predominant mechanism preventing adaptation. Genetic diversity in a population gradually decreases, and genetic differentiation among the population gradually increases, along the core to edge transects at large geographical scales13. In contrast, if an environmental gradient is steep at a small spatial scale, the population often receives poorly adapted immigrants from adjacent populations14. Thus, the failure of adaptation along the environmental gradient due to migration load is suggested to be the predominant process at a small spatial scale and in species with higher dispersal ability15. Despite theoretical progress, the actual effect of migration load on the adaptation of populations at range margins remains unclear due to the lack of estimation of gene flow and the genetic and phenotypic signature of maladaptation, although some transplant studies and metanalyses have provided circumstantial evidence for migration load17.There are two theoretical explanations for the failure of adaptation at range margins. (i) If migration moves mainly from the central, well-adapted regions of the range into the margins, asymmetric dispersal increases the proportion of poorly adapted immigrants in the margins of a population. The range margins may have lower carrying capacity  and consequently, the immigrants fail to adapt to the novel environment. This hypothesis is called the migration load hypothesis20. Despite relatively high mobility, the dispersal of fishes is also influenced by stream currents23. A previous study assessed the phenotypic traits of a stickleback, Gasterosteus aculeatus, population inhabiting a pond and its inlet and outlet rivers and showed that the population in the outlet (downstream) of the pond exhibits a phenotype intermediate between that of the river- and pond-adapted fish, whereas the upstream population has a phenotype optimized for the river environment23. This inconsistency between the optimal and realized phenotype resulted from frequent immigration from the pond population, following the water flow. Organisms with a limited ability to disperse, such as freshwater snails and other invertebrates, are assumed to be more susceptible to the effects of asymmetric gene flow because passive movements will frequently occur27. The extent of asymmetric gene flow is also affected by the geographic and physical features of each river since passive movement is caused by environmental factors, such as frequency of floods, nature of the substratum, and the velocity and steepness of the river28.The lotic environment is a suitable system to examine the effects of asymmetric gene flow on local adaptation and range expansion since lotic organisms are exposed to unidirectional water flow and occasional floods. Water currents along a river encourage organisms to move downstream; hence, gene flow occurs most frequently downstreamSemisulcospira reiniana, is a common gastropod species in Japan, inhabiting mainly sandy or muddy bottoms of flowing rivers and lakes29. This species is broadly distributed within the riverine system including estuaries. Field observation indicated that individuals transplanted into faster currents are prone to migrate downstream24. Therefore, comparative research into rivers inhabited by S. reiniana, which have different geographic features, is expected to clarify the relationship between gene flow, local adaptation, and the distribution range of species.The freshwater snail, 31. Recent technological developments in next-generation sequencing allow us to analyze both genome-wide SNPs and the transcriptome of wild organisms34. The transcriptomic analysis provides evidence for adaptation and phenotypic change by identifying SNPs located within the mRNA and changes in gene expression35. By comparing rivers with steep and gentle gradients, we could infer the impact of the river gradient on local adaptation and the distribution range along the river. Recently, the genetic basis of response to salinity stress in S. reiniana was studied by transcriptomic analysis36; however, the influence of gene flow on local adaptation and range limit is not known yet in this species. Here we performed population transcriptomics for S. reiniana populations collected from rivers of different steepness in order to investigate the influence of gene flow on local adaptation and distribution range. If river steepness influences the direction of migration and local adaptation at range margins, populations in each river should show distinct properties of genetic structure and transcriptional regulation. We also conducted a field survey to examine the influence of river steepness on phenotypic traits. To provide support for the hypothesis that migration load influences the evolution of range limit, the relationship between the river steepness and the lower range limit was analyzed using 12 independent rivers. Our results consistently imply that asymmetric gene flow affects local adaptation and the evolution of range limit.Population genetics using single nucleotide polymorphisms (SNPs) is a powerful method used to survey population structures and demography in freshwater environmentsS. reiniana was investigated in 12 rivers in Japan—Ibi, Kiso, Yodo, Sendai, Gonokawa, Yahagi, Toyokawa, Miyagawa, Kako, Fuji, Inabe, and Hayakawa Rivers—between 2017 and 2020 , indicating genetic differences in salinity tolerance among populations in the gentle river.In the present study, we selected two rivers, the Kiso and Sendai Rivers, with different steepness and enough snails to generate reliable results. In the Sendai River with a relatively steeper slope, the distribution of this species is limited to freshwater habitat, while in the Kiso River with a gentle gradient, the distribution extends into the intertidal zone. The Kiso and Sendai Rivers are referred to as the gentle and steep rivers, respectively. The shell of the juvenile snails was large in the peripheric, downstream population in the gentle river, and a significant switching point for shell size was detected between the brackish water and freshwater populations Fig. A,B. JuveC. gigas protein sequences . The basic information about the reference construction is summarized in Table Total RNA was extracted from 87 individuals collected from the Kiso and Sendai Rivers. We obtained a total of around 2.5 billion pairs of high-quality reads using Illumina sequencing, and de novo assembly produced 547,731 contigs. After removal of redundancy and screening for protein-coding sequences, 75,670 contigs were retained. We also obtained 184,501 high-quality, full-length Iso-Seq sequences from five individuals, of which 46,891 sequences were retained after removing redundancy. Based on these full-length transcripts, reference-guided assembly was performed to equalize the mapping result among populations, resulting in 18,878 sequences. Reference-guided and de novo assembly were merged to generate 89,850 reftigs with a mean length of 1,425 bp. The reftigs had 96.1% comprehensiveness for the metazoan dataset in Benchmarking Universal Single-Copy Orthologs (BUSCO) v3, and 51,009 sequences had high homology with FST among populations. Unlike our expectation, we could not detect the isolation-by-distance (IBD) patterns in gentle river  while IBD was detected in steep river  since all pairwise FST values between a brackish population and freshwater populations were low in the gentle river , though such pattern tended to be ambiguous in a case where brackish water population was included (P = 0.056). Migration probability estimated using BaysAss3-SNPs indicated that moderate to high gene flow occurs between populations within a river  function implemented in Landscape and Ecological Association (LEA) package of the R statistical language. This analysis did not identify different genetic population structures within rivers, and the best number of genetic clusters, K, was one .Variant calling and filtering resulted in 7,820 SNPs from the gentle river and 10,721 SNPs from the steep river. Most SNPs were in the UTR, and there were fewer non-synonymous SNPs than synonymous SNPs Table . Using tver Fig. A. FST vaver Fig. . DownwarBayeScan, an FST-based method, which detected nine and 24 outlier SNPs in the gentle and steep river populations (Table Bis(5'-nucleosyl)-tetraphosphatase and Caskin-1 were detected by both methods; in the steep river, five out of 18 SNPs detected by both methods were non-synonymous  based on gene expression profiles identified separation between the rivers, but not among populations within a river Fig. . To clarThe number of transcripts correlated with an elevation in each river was greater in the gentle river than in the steep river Fig. . In the To detect the genetic basis of tolerance to the highly stressful estuary environment, which includes high salinity and exposure to air during low tide, we conducted an in-depth analysis of the gentle river. The salinity of river water measured by the refractometer was 5, 0, 1, 1, and 1‰ at G0.8, G3, G4.3, G11, and G20, respectively, which show the population at brackish water is exposed to extremely high salinity stress Table . We dete37. Some studies failed to detect any swamping effect on local adaptation under asymmetric gene flow38. One possibility is that the swamping effect of asymmetric gene flow is weaker than expected from theoretical studies, owing to complex environmental and ecological conditions, and is hence difficult to demonstrate except in quite simplified systems38. These results, which appear to contradict ours, might arise from the different consequences of positive and negative gene flow. While the negative effect leads to population collapse at the edge of the range15, the positive effect of gene flow leads to the formation of stable populations and subsequent range expansion39. Therefore, populations recognized by us, the abundant and fine population, have probably been subjected to the positive effects of contemporary gene flow, so it is hard to detect the negative effects of gene flow using the existing population. In the present study, we detected the negative effects of gene flow. We overcame this challenge by focusing on whether river snails expand into novel environments and by comparing rivers with different slopes. Our results supported the hypothesis that migration load owing to asymmetric gene flow, along with the flow of the stream, disturbs local adaptation and restricts the distribution range of a river snail. The lack of replication for genetic analysis (we only studied one steep and one gentle river) is a weakness of our study, but the analysis on the relationship between the steepness of river and lower range limit by using multiple rivers can strengthen our hypothesis.In the present study, we demonstrated a relationship between river steepness and the lower distribution limit of a river snail using field data and population transcriptomic data, focusing on SNPs in transcripts and gene expression levels. Although no clear separation of population structures was observed within the rivers, the estimated direction of gene flow and differentiation among the populations supported the assumption that strong downward migration homogenizes the population in the steep river. In the saline tolerance experiment, gene expression analysis and field data suggested that local evolutionary adaptation could be attributed to the expansion of the distribution range to a novel environment, in this case, the intertidal environment, in the gentle river. In contrast, a recent review suggested that most of the studies regarding the effect of gene flow on local adaptation were consistent with the diversity loss hypothesis, and few studies support the migration load hypothesis27. The results of the present study supported the presence of passive asymmetric downward migration and low genetic differentiation among populations in the steep river , which encodes an enzyme that edits adenosine to inosine in pre-mRNA. In Drosophila melanogaster, Adar is specifically expressed in neurons, and its substrate is primarily mRNAs encoding an array of voltage- and ligand-gated ion channels55. RNA editing by Adar is hypothesized to fine-tune the neurophysiological properties of animals and mutants and appears to be involved in locomotory behavior, regulation of circadian rhythm, and response to heat and oxidative stress56. Although the hypothesis that behavioral change based on the non-synonymous mutation contributes to adaptation to the severe environment is reasonable and intriguing, to further discussion, we need investigations including genetic experiments using model organisms.Although no clear separation of population genetic structure was found between freshwater and brackish water populations Fig. , 147 nonS. reiniana. For example, heat shock protein 68 (hsp68) maintains homeostasis and prevents cellular degeneration in response to various stressors, and in Pacific oyster, is associated with stress responses to changes in salinity and heat shock50. The gene expression of hsp68 increased in response to hyperosmotic, hypoosmotic and heat stress in the Pacific oyster, but our analysis showed lower expression of hsp68 in populations from brackish environments , which were differentially expressed between brackish and freshwater populations Table . These dnts Fig. . Since aIn summary, our multifaceted results are consistent with the hypothesis that migration load owing to asymmetric gene flow along the water stream restricts the range expansion of river snails. High tolerance for salinity in downstream population in the Kiso River implies that evolutionary adaptation for local environment might be more easily achieved in the gentle river than in a steep river. To confirm the generality of such a process, we need to conduct similar population transcriptome analyses in several rivers in the future. To reveal the genetic basis of the observed changes in gene expression patterns among populations, we may need to conduct further in-depth analyses of organisms from the rivers.The altitudinal distribution range was investigated in 12 rivers in Japan. Field surveys were conducted in nine rivers—the Kiso, Yodo, Sendai, Yahagi, Toyokawa, Miyagawa, Fuji, Inabe, and Hayakawa Rivers—between 2017 and 2020. Sampling sites in each river were selected every 5 km from the estuary to 50 km from the estuary, and sampling of adult snails was carried out for about 30 min at each site. Dense sampling, at sites less than 5 km apart from each other, were conducted around the lower altitudinal limit of the snails’ distributions. For the rivers in which we found at least one individual of the species, the lowest site at which the adults were captured was defined as the lower range limit of the river. For three rivers—Gonokawa River, Ibi River, and Kako River—previously reported occurrence data were used to assess the lower range limits.https://www.r-project.org/). The relationship between steepness and lower distribution limit in each river was analyzed using Spearman’s correlation calculated using cor function.Since the downstream areas of large rivers flow through plains in Japan, the difference in steepness between rivers is small at a distance of 0 ~ 20 km from the estuary. In addition, the length of a couple of rivers that we studied is less than 40 km from the estuary. Thus, in the present study, elevations at 30 km horizontally away from the estuary were taken to estimate the “steepness” of each river Table . All staS. reiniana inhabit at a wide range of elevations. Thus, these rivers are referred to as the gentle river and the steep river, respectively. Adult individuals of S. reiniana were collected at the river edges along each river between June and August 2017. For both rivers, since the steepness is similar within 20 km of the estuary, salinity intrusion is caused up to around 20 km from the estuary. The sampling sites were located at a distance of 0–50 km from the estuary, and all sites were around 5 km apart from each other. Individuals were captured by hand. Adults used to examine the tolerance to salinity were collected from 10 and eight locations in the gentle and steep rivers, respectively. Samples used for transcriptomic population genetic analysis came from nine locations, which were 0.8, 3, 4.3, 11 and 20 m above sea level (asl) for the gentle river and 2.9, 6.3, 25, and 30 m asl for the steep river. Sampling locations are named as a combination of the steepness of the rivers  and the altitude. For example, the location at 25 m asl in the gentle river and that at 30 m asl in the steep river were referred to as G25 and S30, respectively.In the present study, we selected two rivers, the Kiso and Sendai Rivers, which have different steepness and enough individuals to conduct experiments. Though Kiso and Sendai Rivers are relatively gentle in 9 rivers that we studied, Sendai River is one of the steepest rivers in which individuals of R package “segmented” (https://cran.r-project.org/web/packages/segmented/index.html).To remove environmental effects, saline tolerance was quantified by using newborn snail. Adults captured in the natural populations were maintained in a freshwater aquarium (15 × 20 × 15 cm) in the laboratory at room temperature (~ 25 °C), and juvenile snails (< 5 days old) were collected. The juvenile snails were put into 1.5-ml microtubes filled with 1 ml of 0%, 1%, 2%, or 3% saline water, and stably stored in the dark in the incubator for 5 h. After the 5 h exposure, juvenile snails were transferred to 1.5 ml microtubes filled with 1 ml freshwater to enhance recovering from salinity shock. Since in general a living individual can recover from salinity shock and come out of their shells within an hour after exposure to freshwater, we recorded the viability  and shell size (width) of each individual three hours later after exposure to freshwater. The relationship between the elevation of sampling locations and the survival rates were tested using generalized linear models (GLMs). Shell width was used as the covariate since body size are predicted to influence the survival rate. To identify non-linear changes of shell width, the relationship between the elevation and the shell size was analyzed using segmented regression using the All individuals from each river were transported to the laboratory, rinsed with freshwater, and kept at constant temperature in an incubator until their dissection around 24 h after rinsing. The columellar muscle tissue was excised and immersed in RNAlater™ Stabilization Solution (preserved at − 80 °C until RNA extraction). Total RNA was extracted using Maxwell® 16 LEV Plant RNA purification kits in accordance with the manufacturer’s instructions. The concentration of each RNA extraction was confirmed using Qubit Fluorometer with Qubit RNA BR Assay kits . In the gentle river, 10, 10, 9, 9, and 9 individuals at G0.8, G3, G4.3, G11, and G20 respectively, and in the steep river, 10 individuals at each location were subjected to RNA extraction and RNA-sequencing. Also, individuals for Iso-Seq sequencing using PacBio Sequel system were taken from 0.8 and 1.0 m asl in the gentle river and 2.9, 6.3, and 25 m asl in the steep river to take regionality of transcript repertoire into consideration.4.5. Reference dataset construction.FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/), and low-quality reads and bases (Q < 20) were trimmed and discarded using Trimmomatic57. Filtered short reads were subjected to de novo assembly using Trinity v2.6.5 with default parameter58. To remove redundancy from de novo assembly contigs, the CD-hit program (cd-hit-est) was conducted with parameter of sequence identity threshold -c 0.9959. Subsequently, TransDecoder was conducted to screen protein-coding sequencing, with default parameters58.For RNA-seq, library preparation and 100 bp paired-end sequencing using the NovaSeq 6000 System  were outsourced to Filgen . Sequence read quality was confirmed using cd-hit-est with -c 0.99 and assigned to be reference sequences for reference-guided assembly. Filtered short reads from the RNA-seq were mapped to these reference sequences using Tophat2 with default parameter60, and the reference-guided assembly was constructed from mapped reads using cuffmerge and gffread implemented in Cufflinks61. In this study, the contigs that were merged de novo and the reference-guides assembly using cd-hit-est with -c 0.99 was defined as “reftigs” for the following analyses. The reftigs were annotated by searching homology with the protein dataset of Crassostrea gigas (oyster_v9) using BLASTX program. We used only reftig sequences with homology to C. gigas proteins for the subsequent analyses . Orthology comprehensiveness was assessed using BUSCO v3 (https://busco.ezlab.org/).Iso-Seq was outsourced to the National Institute of Genetics to obtain full-length transcripts. The sequences of each individual were merged using GATK, https://software.broadinstitute.org/gatk/documentation/article.php?id=3891). For each individual, all reads after quality control were mapped to reftigs using STAR62, and duplicated reads were identified using Picard (http://broadinstitute.github.io/picard). The variant sites were detected using HaplotypeCaller with minimum confidence threshold of 20 and merged for each river using GenotypeGVCFs63. Then, variants were filtered using VariantFilteration with threshold of FisherStrand > 30 and QualByDepth < 2. Loci that had alleles observed in at least 5% of individuals existed in all individuals within each river, or were bi-allelic, were retained using VCFtools64. To estimate the impact of each SNP on phenotypes, the SNPs were classified according to their positions in the mRNA: synonymous, non-synonymous, or UTR, using snpEff65. Classification was conducted according to the GFF file output from TransDecoder.We identified SNPs in samples from each river in accordance with the best practice for calling variants in RNA-seq of Genome Analysis Tool Kit (VCFtools and were excluded from the dataset (q < 0.05). Linkage disequilibrium was calculated using Plink v1.966 and one member of each tightly linked SNP pair was excluded from subsequent analyses (r2 > 0.8). The pairwise FST between populations within each river, mean of the allele number, and the observed and expected heterozygosity were calculated using Arlequin67. The existence of isolation-by-distance (IBD) was tested using the pairwise FST by using mantel function in vegan package (https://cran.r-project.org/web/packages/vegan/index.html). The extent of IBD within a river would reflect the migration rate of S. reiniana and the connectivity between populations, and thus we were able to infer differences in gene flow between rivers. Also, the degree of IBD between rivers was compared using GLM. In this analysis, we used only freshwater populations to compare IBD between the rivers. FST values per horizontal distance along a river were compared between rivers using a Wilcoxon rank sum test in exactRankTests package (https://cran.r-project.org/web/packages/exactRankTests/index.html). Gene flow within each river was estimated using a Bayesian method implemented in BA3-SNPs69. Using this method, we were able to estimate the extent and direction of gene flow in the past few generations using a large SNP dataset. We estimated gene flow using the Bayesian estimation and sampled every 1,000th iteration from 10,000,000 iterations after a burn-in of 1,000,000 steps. Asymmetric migration was tested using one-sample t-tests for the ratio of downward to upward estimated migrations between locations within each river. For the assignment test, we used the sNMF function implemented in LEA package70 in R, which is fast and efficient compared with conventional methods71. The population structure of each river was estimated using sNMF with 50 repetitions, using neutral loci, after removing loci that deviated from HWE and linkage disequilibrium. In the gentle river, there were 4,544 SNPs, and in the steep river, there were 6,142 SNPs).To avoid the effect of artifacts or sequencing error, deviation from the Hardy–Weinberg equilibrium were calculated using the—hwe option implemented in LEA package were used to screen SNPs whose frequencies correlated with elevation. The number of latent factors was determined using the genetic structure identified by the sNMF function in LEA package. We ran LFMM for 10,000 iterations with 5,000 burn-in iterations and regarded SNPs that had a false discovery rate (FDR) of < 0.05 as calculated by the p.adjust function in R as outliers associated with elevation. Second, FST outlier tests was conducted using a Bayesian method with BayeScan 2.172. BayeScan with a prior odds value of 10 was run for 5,000 iterations with 500,000 burn-in and identified SNPs that had an FDR of < 0.05. We detected genes related to habitat expansion into brackish water in the Kiso River using LFMM and the salinity measured by refractometer at each elevation. GO terms were linked to each reftig using homology with the top-hit to a Drosophila melanogaster protein dataset , and GO enrichment analysis was performed using Panther73.Loci subjected to natural selection were detected using two different methods using loci detected in at least 90% of individuals within each river . First, LFMM function implemented in 74 with bowtie275 as the alignment program. First, PCA based on fragments per kilobase of exon per million mapped reads (FPKM) values of all reftigs that has homology with C. gigas protein dataset was conducted using the prcomp function in R, and the pattern of gene expression  within rivers was analyzed by ANOVA using car package in R. Genes responsible for the habitat expansion into brackish water were explored by comparing expression levels between brackish water and freshwater populations in the gentle river. We tested the differences of expression levels after trimmed mean M-value (TMM) normalization between brackish water and freshwater using edger and TCC package with FDR of < 0.0577. To investigate the relationships of the local environment in the population and adaptation with transcriptional regulation, we estimated Pearson’s correlation between the elevation and TMM normalized expression values of each transcript within each river.To examine the degree of local adaptation produced by transcriptional regulation, we quantified the expression levels of the transcripts in each individual and investigated the differences within and between the river under constant conditions. The transcript abundance in reftigs was quantified using RSEMSupplementary Information 1.Supplementary Information 2.


Cryobius of the genus Pterostichus are a successful group in expansion in the tundra biome. The current taxonomy of Cryobius species is unclear and could be considered an obstacle to ecological studies; knowledge of their distribution patterns in the Arctic is rather limited. In this study, the first report on the phylogeography and phylogeny of the most abundant tundra subspecies, P. (Cryobius) brevicornis brevicornis , within its continuous range throughout northern Eurasia and North America is presented. The results indicated that the male genitalia morphology of P. b. brevicornis from Eurasian populations shared a higher geographic variability compared with the pronotum shape and the mitochondrial DNA sequences.Taxonomic studies on a polymorphic species inhabiting a region with relatively uniform environmental conditions  should involve an integrative approach. Ground beetles such as the subgenus Pterostichus (Cryobius) brevicornis brevicornis , as a model. Phylogenetic structure was assessed on the basis of a Bayesian approach using two DNA markers , while phylogeographic patterns and population genetic diversity were estimated using the COI gene only. Morphological patterns were analysed using elliptical Fourier coefficients that were calculated based on the pronotum and male genitalia shape outlines. The subspecies shares 23 COI haplotypes throughout its entire circumpolar range, while eight haplotypes of 28S rRNA were detected in Northern Eurasia. Phylogenetic analysis did not reveal subdivided species lineages with strict geographical imprint. The network, FST and uncorrected pairwise divergence analyses showed that the genetic distances between populations increase by longitude from Northeastern Asia to Europe. The genetic variability among the five studied geographical population groups of P. b. brevicornis was relatively high. The MANOVA showed significant regional divergence between local populations in Northern Eurasia based on both morphological markers, but only male genitalia variability was geographically structured. Neither the pronotum shape nor the male genitalia shape aligned with the phylogeographic patterns discovered on the basis of COI sequences. The genetic (COI) marker had more variation within, rather than among, population groups in addition to morphology of pronotum but not male genitalia.The geographic patterns of genetic and morphological variability in ground beetles were examined throughout Northern Eurasia and North America using the most abundant circumpolar tundra subspecies,  Pterostichus  of which 20 species (45%) refer to the subgenus Cryobius  [Cryobius is more diverse in the Palearctic region with 154 species, and 23 species have been detected in the Nearctic region [Cryobius species were detected in the Russian territory [Cryobius species endemic to this zone or predominantly distributed in tundra landscapes [In the Arctic there are approximately 44 species of the genus Bonelli, 810 of whspecies 4% refer tc region . In the erritory , with 15Cryobius was published in 1906 by Poppius [Cryobius were determined for North America: ventricosus, pinguedineus, and brevicornis [Cryobius in Russia and adjacent countries, five species groups and 17 species were defined outside such groups [Pterostichus brevicornis , P. empetricola , P. nivalis , P. kolymensis Erjiomin, 1998, and P. mandibularoides Ball, 1966 [Pterostichus brevicornis is divided into three subspecies: Pterostichus brevicornis brevicornis , Pterostichus brevicornis delicatus , and Pterostichus brevicornis yasudai  [Cryobius is the similar physiognomy of diagnostic features for species in each group as well as in the “brevicornis” group. Thus, limitations in descriptive taxonomy have resulted in biased estimates of ground beetle species compositions in the Arctic where the subgenus Cryobius is predominantly distributed. A contemporary integrative approach is required for clarification of these problems in taxonomy. Some research has been facilitated by molecular tools such as 28S rRNA, COI, and COII sequencing for the taxonomy of the subgenus Hypherpes  of the genus Pterostichus, the widespread Pterostichini of North America [Cryobius has focused on DNA barcoding of an arthropod community for environmental monitoring in the Arctic [Pterostichus [Pterostichus for Germany and Central Europe [One of the first revisions of the subgenus vicornis . Accordih groups . The lasll, 1966 . Additioa, 2002) ,12. The  America . Researce Arctic ,16,17,18e Arctic ,19 in thl Europe .Pterostichus b. brevicornis is one of the most widespread and numerous subspecies of the subgenus Cryobius in the northern polar region, including the territory from the Arctic tundra to the northern taiga subzones [Pterostichus b. delicatus has a range restricted to the islands of the Bering Sea of North America and Northeast Russia [Pterostichus b. yasudai were detected in the Daisetsu Mountains of Hokkaido Island (Japan) [Pterostichus brevicornis is a cold-adapted species [P. b. brevicornis from different parts of the subspecies range have a high morphological diversity of diagnostic features [P. b. brevicornis are caused by diversity at the genetic level. Therefore, the main goal of this study was to assess the genetic and morphological structures of Pterostichus b. brevicornis from Northern Eurasia and North America. The objectives were: (i) to study phylogenetic and phylogeographic aspects of P. b. brevicornis; (ii) to study the genetic diversity of P. b. brevicornis populations from different parts of the subspecies’ range; and (iii) to test the morphological differentiation of P. b. brevicornis within the Eurasian range with correspondence between morphological and genetic population structures.subzones ,10,11. Tsubzones . Pterost (Japan) . Pterost species ,25 with  species . SpecimeP. b. brevicornis were collected in various locations across North Eurasia and North America using pitfall traps, leaf litter sifting, and an exhaustor (Specimens of xhaustor .c oxidase subunit I (COI) gene and large subunit ribosomal RNA 28S (28S rRNA) gene sequences were obtained. The newly obtained sequences of P. b. brevicornis (77 for COI and 33 for28S rRNA) were combined with published GenBank data (93 for COI). The resulting dataset comprised a total of 170 sequences for COI and 33 sequences for 28S rRNA , Federal Center for Integrated Arctic Research of the Russian Academy of Sciences and Northern (Arctic) Federal University named after M.V. Lomonosov, Arkhangelsk, Russian Federation. In this study, the cytochrome 28S rRNA .2), 0.8 units of Taq DNA polymerase , and H2O added for a final volume of 25 μL. Thermal cycling was as follows: 95 °C (4 min), 32–37 cycles of 95 °C (50 s) and 42 °C (50 s) for COI or 25 cycles of 95 °C (50 s), 60 °C (50 s) for 28S, 72 °C (50 s), and a final extension at 72 °C (5 min). Forward and reverse sequencing were run on an ABI PRISM® 3730 DNA  using the ABI PRISM® Big-Dye Terminator v. 3.1 reagent kit. Regarding the results, 85 new sequences (61 for COI and 24 for 28S rRNA) were deposited in GenBank (accession numbers in P. b. brevicornis were retrieved from GenBank (NCBI) and the Barcode of Life Data (BOLD) System. All sequences were checked manually using BioEdit v. 7.2.5 [DNA was extracted from legs and dissected abdominal muscle tissue using a standard phenol/chloroform procedure . A fragmv. 7.2.5 . The aliv. 7.2.5 . For thePterostichus nivalis ) using an online FASTA sequence toolbox [Both genes were analysed separately  and comb toolbox . For 28S toolbox  was appl toolbox  of MEGA  toolbox , were as toolbox  through  toolbox . The fol toolbox . The eff toolbox .P. b. brevicornis from 26 localities of Northern Europe and North America were used .The phylogeographic analysis was performed based on a median-joining network approach using Network v. 5.0.0.1 software with default settings . Additioere used . All seqvicornis  created n = 38), Alaska: Toolik, Talkeetna, Fairbanks Borough, Denali Borough (n = 55), Northeast Asia: Wrangel Island and Chukotka (n = 25), West and Central Siberia: Yamal Peninsula and Polar Ural, Tazovskiy and Taymir Peninsulas (n = 20), Northern Europe: Pinega Reserve, Kanin Peninsula, Yugorskiy Peninsula, Vaigach Island (n = 30). Pairwise FST values using analysis of molecular variance (AMOVA) for comparisons of five population groups were calculated using Arlequin v.3.5.2. The mean uncorrected p-distance between population groups (±standard error estimate) was calculated for COI using MEGA X.Population genetic diversity indices (haplotype and nucleotide diversity) were determined using Arlequin v.3.5.2 . The totP. b. brevicornis mainly follows a redescription of Ball [The morphological study for  of Ball  and Erji of Ball . The com of Ball ,47,48,49 of Ball . The EF  of Ball . The pro of Ball . The res of Ball  to produ of Ball . A princ of Ball . The shaCorrespondence between principal component scores (shape variables) as dependent variables due to species populations, sex, or population × sex interaction was investigated using multivariate analysis of variance (MANOVA). MANOVA was also used to test the mean difference in shape markers between geographical populations. Discriminant canonical analysis (DCA) was also performed with populations as the dependent variable. The purpose was to illustrate the maximum differentiation of the multivariate means (centroids) of morphological patterns for each local population sample in shape space. The matrices of principal component scores for both morphological structures were projected onto computed canonical variate axes. Data analysis was conducted using both STATISTICA v. 10  and PASTM) by DCA were calculated in STATISTICA v. 10 [ST values using the Tamura model for the barcoding segment of COI and were calculated in Arlequin v. 3.5.2 [The relationship between morphological, genetic, and geographical differentiation was assessed by testing simple and partial Mantel tests between distance matrices. Morphological distances (shape distance) corresponding to Mahalanobis distances (DCA v. 10 . Geneticv. 3.5.2 . The geoP. b. brevicornis based on 23 COI and eight 28S rRNA unique haplotypes comprised three subclades that were 0.7–0.9% divergent (The Bayesian phylogeny of ivergent .P. b. brevicornis by longitude range distribution. Only one subclade combined four haplotypes from North America (Alaska and Canada (Yukon)), while others contained haplotypes from different geographical localities. The COI mean uncorrected pairwise p-distance between five geographical populations as a whole was 0.44 ± 0.17%. Genetic distances increased from east to the west in Eurasia, and the highest mean divergence value  was found between Northern European and Northeastern populations  than with those from Alaska . The median-joining network analysis using the short COI sequence dataset corresponded to the Bayesian phylogeny with closely related haplotypes among P. b. brevicornis from different localities of the northern range , and 11 COI haplotypes were determined for Eurasia, with eight unique haplotypes (72.7%). Only three COI haplotypes were shared between Nearctic and Palearctic populations of P. b. brevicornis: Hapl 6 in Canada and the Northeast Asia, Hapl 10 in all studied territories except Canada, and Hapl 15 in Alaska and Siberia. The most widespread haplotype (Hapl 10) was found in approximately half of the studied locations (12 locations) within North America and Eurasia  and in northern Europe  , with the highest variation found within population groups (51.99%) compared to the variation among population groups (48.01%).Overall, 16 COI haplotypes of  Eurasia . Unique , 46.7%) . The hig, 46.7%) . In comp, 46.7%) . Tests oP. b. brevicornis, the highest haplotype diversity (h > 0.7) was detected, yet there was also low nucleotide diversity (π < 0.6%). The studied samples of P. b. brevicornis from Siberia and Alaska were characterized by lower haplotype diversity (h < 0.7) and the highest nucleotide diversity (π > 0.6%). Lower values of both population parameters  were detected for P. b. brevicornis from Northern Europe and Northeast Asia . Specimens from the Taymyr Peninsula (Maksimovka River) and Vaygatch Island had similar population mean scores for pronotum PCs. The greatest distances between PC centroids of pronotum shape were detected on the first axis for populations from Chukotka (Pevek settlement) and Kanin Peninsula (Shoina settlement)  A. Reconstlement) A.For the second axis shape, changes of pronotum were not so obvious and slight asymmetry of sides and hind angle shapes for negative projections were observed A.P. b. brevicornis, the MANOVA including all five canonical components (mean scores for PCs) revealed more variance within than among population groups of Northern Europe and Siberia . A significant difference in aedeagus shape among the population groups of the studied territories resulted from a second canonical axis only . The population mean scores of aedeagus shape on the scatterplot for the second canonical axis were not completely separated in shape space between Northern Europe and Siberia . The results of correlations between distance matrices were different for the pronotum and aedeagus morphology of P. b. brevicornis . However, there was no significant correlation between morphological and genetic distance. The partial Mantel tests showed the same pattern where genetic differentiation did not correspond with aedeagus morphology . However, the mtDNA network, FST and uncorrected pairwise divergence analysis revealed an increase in genetic distances by longitude from Northeast Asia to North European populations. The haplotype network configuration had new haplotypes that were derived from low divergent haplotypes by one or two mutation steps that indicated a common population history with relatively recent mutation events [P. b. brevicornis of the Arctic islands shared COI haplotypes with adjacent mainland populations . Similar results were detected for other insect taxa with continuous ranges in the Arctic, such as the tiger moth Arctia tundrana , which has low genetic divergence among populations from Kolguev Island to Chukotka [Bombus pyrrhopygus Friese, 1902 from Novaya Zemlya, had a single COI haplotype with populations from Norway and Kamchatka [Bombus glacialis Friese, 1902 from Wrangel shared three unique COI haplotypes and was closely related to those inferred from samples from Novaya Zemlya [For detected . A highen events . The COIChukotka . The bumamchatka . The Arca Zemlya . The obsa Zemlya .P. b. brevicornis: four to nine haplotypes and 0.42–0.77 gene diversity. Lower genetic diversity was detected for the Northeastern  and European populations  of P. b. brevicornis. Higher genetic diversity was revealed for populations from West and Central Siberia, Alaska , and North Canada , which were likely associated with the ecological plasticity of these populations of P. b. brevicornis [Analysis of mtDNA haplotypes showed overall high genetic variability within the studied geographical populations of vicornis . P. b. brevicornis did not correspond with patterns of mtDNA variation. Both morphological structures had significant shape differences between local populations in Northern Eurasia, but only significant divergences were detected for the aedeagus shape between subdivided geographical populations of Northern Europe and Siberia. Correspondence between morphological distance and geographical distance was significant for the aedeagus but not associated for the pronotum. Genitalia are the fastest evolving characters in insects and have phylogenetic implications for Pterostichus species [Ohomopterus ground beetles, mechanical agents of reproductive isolation  provide fast species radiation without substantial ecological differentiation on the Japanese Islands [Carabus (Ohomopterus) beetles demonstrated that species diversification can follow the coevolution of genitalia between the sexes [P. b. brevicornis, the geographic structure of male genitalia can indicate such a pattern. However, to test this hypothesis, data samples from larger numbers of populations by circumpolar range were required. For both genetic markers, sequence divergences between North European and Siberian populations were not above any of the thresholds. Sexual dimorphism of the pronotum shape was not found for North Eurasian populations. According to Ball [P. b. brevicornis was divided into four classes by measures of side rounding (from not strongly rounded to strongly rounded) and sinuate hind angles (from feebly sinuate to markedly sinuate). The studied samples revealed pronotum shapes from the 1st to 4th classes with a predominating position of the samples at the gradient centre. In a previous revision, it was mentioned that there were a majority of second and third classes of pronotum shape within Northern Eurasia for specimens from Chukotka ), Central Siberia (Yenisey Basin), and Northern Europe (Vaygach Island and Novaya Zemlya) [P. b. brevicornis in Eurasia, and the marked variability of this morphological marker was confirmed statistically. Therefore, aedeagus shape was a stronger morphological structure for P. b. brevicornis taxonomy, and pronotum shape can hardly be used as a marker for distinguishing P. brevicornis subspecies.The pronotum and male genitalia morphologies of Northern Eurasian populations of  species . For Oho Islands . Additiohe sexes . In thishe sexes . For P.  to Ball , the pro Zemlya) . The resCulex revealed wing shape differences between populations, but genetic markers  did not corroborate the morphological variables [Lycaeides , where strong habitat and male genitalia structure partitions were detected but not by using mtDNA data [Carabus solieri  among populations in the southern Alps of France and the Ligurian Alps of Italy were less structured than genetic data (mtDNA), but the markers were congruent [Phyllophaga hirticula  from the eastern USA, female genitalia were more geographically structured than mtDNA and male genitalia [Previous research of one species or sister species populations of insects also confirmed that morphological markers were not more structured than genetic patterns and did not always correlate ,46,63. Aariables . A similDNA data . The proongruent . In the Pterostichus species: no significant sequence divergence within three nuclear markers and mtDNA for P. nigrita and P. rhaeticus were revealed [P. oblongopunctatus and northern populations of P. adstrictus was detected [Chiastocheta , RAD-seq-based phylogenies showed limitations for reconstructing interspecific relationships among recently diverged lineages (less than 1.6 Mya) [P. brevicornis with a relatively recent history of populations in the Arctic after LGP within Northern Europe and Western Siberia [P. brevicornis within North America mainland but did not divide them due to high morphological variability within populations rather between them [However, current research has shown the limitation of using DNA sequences for species identification if species pairs have very recent origins or hybridize . Such parevealed , and simdetected . In thisdetected , and thedetected ,69,70,71 Siberia ,72, nucleen them . This ageen them .Pterostichus b. brevicornis is a polymorphic subspecies with high genetic variability throughout the circumpolar range of North Eurasia and North America. The COI marker had more variation within, rather than among, population groups in addition to the morphology of the pronotum but not male genitalia.


Background and Aims: Quantifying genetic variation is fundamental to understand a species’ demographic trajectory and its ability to adapt to future changes. In comparison with diploids, however, genetic variation and factors fostering genetic divergence remain poorly studied in polyploids due to analytical challenges. Here, by employing a ploidy-aware framework, we investigated the genetic structure and its determinants in polyploid Alkanna tinctoria (Boraginaceae), an ancient medicinal herb that is the source of bioactive compounds known as alkannin and shikonin (A/S). From a practical perspective, such investigation can inform biodiversity management strategies.Methods: We collected 14 populations of A. tinctoria within its main distribution range in Greece and genotyped them using restriction site-associated DNA sequencing. In addition, we included two populations of A. sieberi. By using a ploidy-aware genotype calling based on likelihoods, we generated a dataset of 16,107 high-quality SNPs. Classical and model-based analysis was done to characterize the genetic structure within and between the sampled populations, complemented by genome size measurements and chromosomal counts. Finally, to reveal the drivers of genetic structure, we searched for associations between allele frequencies and spatial and climatic variables.Key Results: We found support for a marked regional structure in A. tinctoria along a latitudinal gradient in line with phytogeographic divisions. Several analyses identified interspecific admixture affecting both mainland and island populations. Modeling of spatial and climatic variables further demonstrated a larger contribution of neutral processes and a lesser albeit significant role of selection in shaping the observed genetic structure in A. tinctoria.Conclusion: Current findings provide evidence of strong genetic structure in A. tinctoria mainly driven by neutral processes. The revealed natural genomic variation in Greek Alkanna can be used to further predict variation in A/S production, whereas our bioinformatics approach should prove useful for the study of other non-model polyploid species. Polyploids are very frequent in flowering plants as at least 35% of extant species are of recent polyploid origin . DespiteGenotype likelihood-based methods  across most of its distribution area in mainland Greece. In addition, as a potential outgroup species, we included the closely related A. sieberi A.DC  How much genetic diversity is present in A. tinctoria in Greece and how is this diversity distributed? (3) What are the factors shaping the observed genetic structure? Given the medical relevance and historical importance of A. tinctoria our population genomic and cytogenetic appraisal serves as a valuable foundation for understanding its genetic and phenotypic variability.In the current study, we used a ploidy-aware likelihood-based genotyping to quantify genetic diversity and to investigate the population structure of the polyploid plant eri A.DC , a rare ountries . Howeverountries , Bulgariountries , and Hunountries , A. tincnin A/S; . The rednin A/S; . Severalnin A/S; . Althougstigated . We emplA. tinctoria with a wide range in Greece and A. sieberi, as the potential outgroup species, with a very restricted range . On Crete, the two species have partly overlapping distributions : ibutions . Both spibutions .A. tinctoria across three mainland regions of Greece , as well as from additionally two A. sieberi localities found on the island of Crete , Thessaloniki, Greece, with specific International Plant Exchange Network (IPEN) accession numbers  per sampling locality  were col numbers .Total DNA was extracted from 40 to 50 mg of powdered leaf tissue using the method described in A. tinctoria was collected from three geographic regions of Greece , while entire plants of A. sieberi individuals were collected from two sampling localities  in Otto’s isolation buffer  for 1 h at room temperature in darkness. Root meristems were then squashed in a drop of 60% acetic acid under a cover slip, and the preparations were analyzed using Axioplan light microscope  equipped with a CCD camera. Images were captured using ZEN software .Chromosome numbers were analyzed for two individuals of n = 8–11 per sampling locality, average 9.3; PstI, except for repeats where between 75 and 100 ng of starting DNA was used. After ligation of P1 adapters to digested samples overnight at 16°C, samples with different P1 barcodes were pooled together and sheared via sonication with a Bioruptor Pico (Diagenode) using three cycles of 45 s ON and 60 s OFF at 4°C. Illumina HiSeq sequencing as single-end 100 bp reads has been performed at the NGS Unit of Vienna Biocenter Sequencing Facility  with default options. Further demultiplexing into individual samples based on inline barcodes used process_radtags  with a maximum of one mismatch, and discarding reads with low-quality scores (−q) and any uncalled bases (−c). As no reference genome is available to date for Alkanna, we first assembled the RAD loci with Stacks. To optimize the de novo assembly, we followed n) to maximize the number of obtained polymorphic loci, including a maximum of ten SNPs, and that were recovered for at least 80% of individuals. The assembly parameters were optimized on a subset of 60 individuals. The final assembly parameters chosen based on the criteria described above to produce the final catalogue were m = 3, M = 1, and n = 4. The RAD-seq loci from the catalogue have been extracted with the EXPORT_SQL.pl module of Stacks. They have been further used as individual contigs to generate a synthetic reference in FASTA format.Raw reads were first demultiplexed into sub-pools based on index reads using BamIndexDecoder (v.1.19) from Illumina2bam ] and inbreeding coefficient  in GENODIVE v.3.0 (n + 1)/n] following n is the number of individuals in the relevant group.The summary statistics for each sampling locality was assessed by estimating within-population genetic diversity [Hs, analog to the expected heterozygosity . For FST estimation between K groups, we only included those individuals where the individual assignment to respective groups was greater than 0.8 at the optimal value of K.To quantify the strength of genetic differentiation among all sampling localities as well as among the A. tinctoria, we first identified the most important climatic variables for our target species using a gradient forest (GF) analysis in the R package gradientForest v.0.1–17  and log-transformed geographic or environmental distances. Partial Mantel test was performed by controlling the respective geographical or environmental distance matrices. These analyses were carried out using GENODIVE with 999 permutations.Next, we performed simple and partial Mantel analyses to test whether geographical or environmental processes contributed to the observed genome-wide divergence among R2 (coefficient of determination), where the statistical significance of the effect of the predictor variable (βn) and R2 are estimated by randomized permutations of columns and rows of the dependent variable distance matrix . However, this approach cannot take into account the multi-collinearity among predictors which can affect the estimation of regression coefficients (βn), R2 and values of p (FST) while accounting for collinearity among explanatory variables. We ran MMRR using pairwise FST as a response variable and geographical and environmental distances as predictor variables (model = FST ~ GEO + ENV) with 1,000 permutations. Variance partitioning analysis was then performed using CA to quantify the common and unique effect of GEO and ENV using a R-script available at https://datadryad.org/stash/dataset/doi:10.5061/dryad.q573n5th7  that explicitly accounts for the confounding effect of population structure. To do so, BayPass first estimates the covariance matrix of population-level allele frequencies  and very conservative quantiles for this neutral simulation (XtX > 99.9% quantiles and BF > 99.9%) as thresholds to define outliers in the real dataset. All analyses were run using the standard covariate model (STD) and default parameters, and with scaled covariates, as suggested by In addition, we identified loci associated with environmental variables using BayPass v.2.2 . In a nuA. tinctoria was found to vary from 1.21 to 1.28 pg. , whereas greater variation was observed among the A. sieberi samples, with sizes from 1.08 to 1.21 pg.  of the reads mapped back to these contigs with a final average coverage across individuals of 16× (SD ± 6×). Filtering of variants obtained from the EBG pipeline based on missing data, and minor allele frequency yielded 16,107 high-quality SNPs. The distribution of tetraploid genotypic frequencies against their allelic frequencies (estimated from EBG genotypes) in A. tinctoria showed the modes of the distribution of heterozygous genotypes  to be of similar heights in agreement with the hypothesis of tetratomic inheritance  million high-quality reads per individual. The optimized He) revealed that the northern sampling localities harbor comparatively higher amount of diversity than the other sampled localities of A. tinctoria (FIS) estimated for the sampling localities were all relatively close to zero  to 0.409 ; however, one of the A. sieberi localities (AT27) showed lower differentiation to A. tinctoria populations than to the second (AT28) locality of A. sieberi  and even sometimes, more locally, between the different sampling sites , which showed the least relatedness to all A. tinctoria accessions , therefore suggesting interspecific admixture. One accession from A. tinctoria from South Greece (AT01) shows also increased co-ancestry with A. sieberi , and those of A. tinctoria from the North on one side and from the Southern-Central localities on the other. The individuals from the western Crete population (AT27), plus the accession from AT01 already identified as admixed based on the coancestry heatmap, were located between the A. tinctoria Southern-Central group and the cluster formed by A. sieberi accessions from AT28 , the clustering of individuals is consistent with all previously described analyses , including the likely interspecific admixed nature of AT27  with well-assigned individuals (q > 0.80). We observed a significant genetic divergence between the three groups (p = 0.001). Genetic differentiation was highest between AT28 and mainland groups  and lowest between Southern-Central and North group (0.14).Finally, to evaluate the strength of genetic differentiation between the identified groups, we estimated FST/1 − FST) between populations were strongly correlated with pairwise geographical distances . We also observed a milder, but still significant association between the genetic and the environmental distance matrices , whereas the association with environmental distances was weaker albeit significant . The multivariate model (MMRR), including both predictors (STF ~ GEO + ENV), explained 55% (R2 = 0.55) of the genomic variation within the Greek A. tinctoria , explaining 45% of the variation in the model . Among the seven non-collinear covariates tested with GF, the top three covariates were related to precipitation, including precipitation of coldest quarter (BIO19), precipitation of warmest quarter (BIO18), and annual precipitation BIO12; . We theninctoria . ConsistFST outlier scan and a genotype-environment association analysis. To identify non-neutral markers, we performed a classical genome scan using the XtX statistics, an FST analog which explicitly accounts for the confounding effect of population structure, including IBD. Using BayPass, we identified 107 SNPs  with conservative criteria, including 17 (0.11%) using a more conservative criterion. Then, under BayPass, we assessed associations of three top bioclimatic variables and identified between up to 0.14% of the SNPs with BF > 99.9% depending on the variable. Interestingly, among the 107 previously detected FST outliers, several SNPs were associated with precipitation: Six SNPs were associated with annual precipitation , including one SNP among the 17 strongest outliers. Similarly, six and four SNPs were associated with precipitation of warmest quarter (BIO18) and of coldest quarter (BIO19), including three and one SNPs among the 17 strongest outliers, respectively , previous microsatellite analyses where up to four alleles were observed per individual  derived from lineages/species with x = 7. Indeed, x = 7 is one of the widespread in Lithospermae  is expected to be significantly higher than other classes of heterozygous genotypes . At the other end of a continuum, autotetraploids with tetrasomic inheritance are expected to show the reversed trend. In A. tinctoria, we observed that triplex heterozygous genotype class  is approximately two-fold more frequent than the duplex heterozygous genotypes  probably due to a change of management practices , or due to expanding urbanization over natural habitats. Reduced connectivity of suitable habitats could lead to genetic isolation  estimated between these main genetic pools. Although investigating different regions and spatial scales, other studies also found evidence for significant genetic structure in other Alkanna species  phytogeographic region, whereas the majority of the southern-central localities pertain to the Sterea Ellas (StE), except two populations which were collected at the boundary between East-Central (EC) and StE (AT17 and AT19), and between Peloponnisos (Pe) and StE (AT07 and AT08). Botanical exploration and biosystematics studies have shown consistent discontinuities in species composition, richness, and endemism patterns between StE and NE  after excluding putatively admixed individuals. Phylogenetic and historical biogeographical studies have shown that the diversification in islands mainly occurred via vicariant speciation that is taxa become isolated owing to formation of barriers , as the later has been hypothesized for some Cretan (sub)species (Our investigation of genetic differentiation detected a high genetic differentiation between mainland barriers . Howeverbarriers . Due to )species . In the A. tinctoria and the Central population from Crete. We identified via traditional and Bayesian clustering that the investigated accessions from AT27 showed an admixed ancestry between the two species  in this important medicinal plant, prompting to future studies.In the present study, we provide evidence that only dysploid tetraploid https://www.ncbi.nlm.nih.gov/) under the accession number PRJNA705074.The raw sequence reads can be found at NCBI (MA, ES, CL, and OP planned and designed the research. NK collected the samples. ET and HW-S performed flow cytometry and chromosomal counts. MA prepared the RAD-seq libraries and analyzed the data with support from OP and TL. MA, ES, TL, and OP interpreted the results. MA and OP wrote the manuscript with the input from all authors. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The reviewer EZ declared a past co-authorship with one of the authors OP to the handling editor.


Fitted qpAdm-based two-way admixture models with ancestral sources from northern and southern East Asians demonstrated that Maonan people were an admixed population with primary ancestry related to Guangxi historical people and a minor proportion of ancestry from Northeast Asians, consistent with their linguistically supported southern China origin. Here, we presented the landscape of genetic structure and diversity of Maonan people and a simple demographic model for their evolutionary process. Further whole-genome-sequence–based projects can be presented with more detailed information about the population history and adaptative history of the Guizhou Maonan people.Guizhou Province harbors extensive ethnolinguistic and cultural diversity with Sino-Tibetan-, Hmong–Mien-, and Tai–Kadai-speaking populations. However, previous genetic analyses mainly focused on the genetic admixture history of the former two linguistic groups. The admixture history of Tai–Kadai-speaking populations in Guizhou needed to be characterized further. Thus, we genotyped genome-wide SNP data from 41 Tai–Kadai-speaking Maonan people and made a comprehensive population genetic analysis to explore their genetic origin and admixture history based on the pattern of the sharing alleles and haplotypes. We found a genetic affinity among geographically different Tai–Kadai-speaking populations, especially for Guizhou Maonan people and reference Maonan from Guangxi. Furthermore, formal tests based on the  FurtherMaonan people used the Maonan language belonging to the Dongshui branch in the Tai–Kadai language family , which wWe collected saliva samples from 41 unrelated Maonan individuals in Pingtang County in Guizhou Province, Southwest China . Particivia the smartpca program of the EIGENSOFT v.6.1.4 package   package  based onvia ADMIXTURE  using the default parameters, and this index was used for evaluating the shared genetic drift between Population 1 and Population 2 since their separation from the outgroup population of Mbuti. Then we also used the qp3pop to perform the admixture-f3-statistics in the form f3 to explore the admixture signals in Maonan samples with different East Asian and Southeast Asian ancestral source candidates. The value with |Z-score|>3 denoted that Source 1 and Source 2 could generate the potential admixture signal for the target population.We used ADMIXTOOLS  to compuqpDstat program in ADMIXTOOLS , which can be used to determine the signals and directions of admixture, and the primary source of gene flow to Guizhou Maonan and other modern and ancient reference East Asians.We used the MIXTOOLS  with defqpWave/qpAdm as implemented in the ADMIXTOOLS  in mitochondrial DNA and Y-chromosome. The haplogroup assignment was used as the in-house manuscripts followed by our recent publications .We generated genome-wide data in approximately 700,000 SNPs for 41 Maonan individuals from Guizhou Province, Southwest China. We first merged our data with modern and ancient published populations from the Human Origins dataset. Then we carried out a principal component analysis (PCA) to understand the general patterns of relatedness between Guizhou Maonan and reference populations . We obseWe carried out the model-based ADMIXTURE clustering analysis to dissect ancestral components and genetic similarity of our studied group with geographically close ancient and present-day populations. We used cross-validation to identify an “optimal” number of clusters (K = 6) . At optif3 values. Based on the Illumina Array dataset, we further explored the phylogenetic relationship with admixture among 16 Chinese populations belonging to Sinitic, Tungusic, Mongolic, and Tai–Kadai people , which is consistent with the identified genetic affinity based on the outgroup-i people . We founi people . We founWe further explored the fine-scale population structure between Maonan people and other East Asians based on the patterns of the sharing haplotypes. PCA based on the coancestry matrix showed that Han Chinese clustered together and separated from Pingtang Maonan people and Guizhou Manchu and Mongolic people, which showed that the Maonan people had a different genetic history compared with Han Chinese populations . Model-bvia outgroup-f3 and admixture-f3-statistics. We performed outgroup-f3 statistics in the form of f3, and found that Guizhou Maonan shared more genetic drift with southern Chinese populations, especially for Hmong–Mien-  and Tai–Kadai-speaking populations   to model possible sources for Maonan_Pingtang people  . Then weg people . Howeverf4. The identified statistically non-significant f4-values (absolute Z-scores less than 3) in f4 indicated that Maonan_Pingtang and Maonan_Huanjing have a close genetic relationship , which suggested that Guizhou indigenous populations and Hmong–Mien-speaking populations shared more alleles with Maonan_Pingtang than other Tai–Kadai-speaking populations  in f4  .f4. We observed significantly negative f4-values here, indicating that Maonan_Pingtang shared more alleles with Tai–Kadai- and Austronesian-speaking populations , which suggests studied population was influenced by gene flow from the north , indicating that Maonan_Pingtang shared more alleles with northern populations than BaBanQinCen in Guangxi. We observed BaBanQinCen shared more alleles with other ancient populations than Maonan_Pingtang via significant positive f4-values in the form of f4 , which showed that Sinitic-, Tai–Kadai-, and Hmong–Mien-speaking populations from southern China shared more alleles with Maonan_Pingtang than Austroasiatic-speaking populations , it was shown that Tai–Kadai-, Austronesian-, and Hmong–Mien-speaking populations shared more alleles with studied population than southern Tibeto–Burman-speaking populations   . We obseulations . Signifiulations . We foun, Mbuti) .qpWave/qpAdm methods to model the minimum number of ancestry sources and evaluated the corresponding ancestry coefficients. We used ancient northern populations  as the northern ancestral sources and ancient southern populations  as the southern ancestral sources to estimate the admixture proportions. Here, BaBanQinCen was the representative ancestral source in Guangxi Province, where many Tai–Kadai people lived. When we used ancient Yellow River farmers as the northern source, Southeast Asian ancestry related to the BaBanQinCen in Maonan people spanned from 70.2 to 86.9%  and statistically negative f4-values in f4 . Our results were consistent with previous reports based on the forensic markers. He et al. explored the genetic diversity and forensic features of Guizhou Tai–Kadai-speaking Gelao people and identified the population interplay between Gelao and neighboring Hmong–Mien-speaking populations  and prehistoric Longlin, Dushan, and Baojianshan people. Among all reported ancient Northeast Asians, including the inland and coastal Neolithic Northeast Asians from Shandong, Henan, Shaanxi, Gansu, Inner Mongolia in the Yellow River Basin, and Neolithic Siberian, we found a close genetic connection between Maonan and Bronze Age to Iron Age people from Henan Province, which suggested Maonan people might have obtained gene influxes from them. Indeed, we obtained statistically negative f4-values in the f4, which directly evidenced that compared with the genetically attested ancestors of Tai–Kadai-speaking populations from the Guangxi region, Maonan people shared additional genetic materials from Northeast Asians. This identified admixture process was further confirmed via the qpAdm-based two-way admixture models with one source from Guangxi historic people and the other sources from Northeast Asians. We also found that two-way admixture models of Hanben-Northeast Asians can also well-fit the genetic composition of studied Maonan, which suggests the genetic influence from the southeastern coastal Fujian ancient people in the gene pool of inland Tai–Kadai-speaking Maonan people. As we know, Tai–Kadai-speaking populations were widely distributed in South China, including Guizhou, Guangxi, and Hainan. Previous genetic analysis from Hainan Province also reported a relatively isolated genetic structure of the Hainan Tai–Kadai-speaking Hlai people  and a possible ancestor of Hmong–Mien-speaking populations (GaoHuaHua). BaBanQinCen was one meta-population from four archeological sites that lived in Guangxi Province 2000 years ago, and GaoHuaHua was also a meta-population from three archaeological sites that lived in Guangxi around 1,500 years ago . Here, wi people . Thus, df-statistics, qpAdm). Results from PCA and ADMIXTURE showed a close genetic relationship between Maonan and other geographically different Tai–Kadai-speaking populations, especially for the closest relationship between Guizhou Maonan and Guangxi Maonan. No-admixture signatures were identified via admixture-f3 statistics showed the unique genetic structure of Maonan people compared with geographically close Han people. Further analysis based on the outgroup-f3 statistics and f4-based analysis showed a close relationship between Maonan and Guizhou Sino-Tibetan and Hmong-speaking populations, as well as a close connection between Guangxi historic people and Guizhou Tai–Kadai-speaking populations, suggesting their admixture history with the sources from surrounding regions. The well-fitted two-way admixture models with ancient northern and southern East Asians demonstrated that Tai–Kadai-speaking populations derived primary ancestry related to 1500-year-old Guangxi BaBanQinCen people and additional genes from Northeast Asia.We reported the first batch of genome-wide SNP data of Tai–Kadai-speaking Maonan people from Guizhou Province and comprehensively explored genetic structure, origin, and admixture processes based on the descriptive analyses (PCA and ADMIXTURE) and qualitative measures (


Potamilus amphichaenus and Potamilus streckersoni. We then synthesize our molecular findings with details from field collections spanning from 1901 to 2019 to further elucidate distributional trends, contemporary status, and other factors that may be contributing to population declines for our focal species. We collected GBS and mtDNA data for individuals of P. amphichaenus and P. streckersoni from freshwater mussel collections in the Brazos, Neches, Sabine, and Trinity drainages ranging from 2012 to 2019. Molecular analyses resolved disputing number of genetic clusters within P. amphichaenus and P. streckersoni; however, we find defensible support for four CUs, each corresponding to an independent river basin. Evaluations of historical and recent occurrence data illuminated a generally increasing trend of occurrence in each of the four CUs, which were correlated with recent increases in sampling effort. Taken together, these findings suggest that P. amphichaenus and P. streckersoni are likely rare throughout their respective ranges. Because of this, the establishment of CUs will facilitate evidence‐based recovery planning and ensure potential captive propagation and translocation efforts are beneficial. Our synthesis represents a case study for conservation genomic assessments in freshwater mussels and provides a model for future studies aimed at recovery planning for these highly imperiled organisms.Population genomics has significantly increased our ability to make inferences about microevolutionary processes and demographic histories, which have the potential to improve protection and recovery of imperiled species. Freshwater mussels  represent one of the most imperiled groups of organisms globally. Despite systemic decline of mussel abundance and diversity, studies evaluating spatiotemporal changes in distribution, demographic histories, and ecological factors that threaten long‐term persistence of imperiled species remain lacking. In this study, we use genotype‐by‐sequencing (GBS) and mitochondrial sequence data (mtDNA) to define conservation units (CUs) for two highly imperiled freshwater mussel species,  Freshwater mussels  represent one of the most imperiled groups of organisms globally. In this study, we couple multiple molecular datasets with survey data to facilitate recovery efforts for two threatened species of freshwater mussels. Our synthesis represents a case study for conservation genomic assessments in freshwater mussels and provides a model for future studies aimed at recovery planning for these highly imperiled organisms. We set 22.1P. amphichaenus and P. streckersoni from focal drainages in Texas . Potamilus amphichaenus was collected from 24 localities  and P. streckersoni was collected from 22 localities in the Brazos River drainage . Briefly, DNA samples were processed in digestion and ligation reactions using the n et al.  but replReads were demultiplexed using the individual‐specific barcode sequence ligated to the samples. Reads were then processed using proprietary DArT Pty Ltd analytical pipelines  and P. streckersoni (Brazos = 34) were used in all GBS analyses . We calculated allelic richness (AR), observed heterozygosity (Ho), expected heterozygosity (He), and inbreeding coefficient (FIS) for each group using diveRsity v 1.9.90  in dartR. We also performed a discriminant analysis of principal components (DAPC) in adegenet v 2.1.0  was determined using k‐means.For all downstream GBS analyses, individuals were binned into four groups based on drainage of capture: (a) Jombart,  on the fFST values using the R package StAMPP v 1.5.1 , and (c) P. streckersoni only (n = 34). Monomorphic loci and loci under linkage disequilibrium were filtered after creating species‐specific datasets. We modeled K = 1–10 to assess population genetic structure in each dataset, and the chooseK.py script in fastSTRUCTURE was used to select the best K value to explain structure and maximize likelihood. TESS3 uses ancestry proportions distributed over geographic space, and distinct clines are estimated from both genetic and geographic data  was modeled using TESS3, and we illustrated the distribution of genetic variation at the hydrological unit code (HUC) 8‐level.We used traditional and model‐based methodologies to identify patterns of population structure in our genomic data. First, we calculated pairwise K = 2–4): (a) P. amphichaenus and P. streckersoni; (b) P. amphichaenus from the Neches + Sabine, P. amphichaenus from the Trinity, and P. streckersoni; and (c) P. amphichaenus from the Neches, P. amphichaenus from the Sabine, P. amphichaenus from the Trinity, and P. streckersoni. Each estimation was conducted using path sampling with 48 steps and 100,000 MCMC steps with a 10,000 preburn‐in  and the number of effective breeders (bN) for the four groups based on drainage of capture. The molecular coancestry  to assess genetic variation in the mtDNA genome. Primers used for PCR and sequencing were ND1 5′‐TGGCAGAAAAGTGCATCAGATTAAAGC‐3′ and 5′‐CCTGCTTGGAAGGCAAGTGTACT‐3′  gene P. amphichaenus  and P. streckersoni (Brazos = 46) were used in all mtDNA analyses , haplotype diversity (Hd), mean number of nucleotide differences (k), and mean nucleotide diversity (π) for the four groups used in GBS analyses. We calculated pairwise FST values and conducted an AMOVA in Arlequin v 3.5.2.2  2.5P. amphichaenus and P. streckersoni throughout their known ranges, we compiled available or generated data from freshwater mussel surveys that detected live specimens in the Brazos, Neches, Sabine, and Trinity River drainages  and P. streckersoni (34) were sequenced, and 14,142 of the total 65,465 polymorphic loci were retained after filtering . Raw reads are deposited in the SRA (BioProject ID: PRJNA663379), and sample accession numbers can be found in Table P. amphichaenus from the Sabine, P. amphichaenus from the Neches, P. amphichaenus from the Trinity, and P. streckersoni , and the second axis described 3.6% of the variance (populations of P. amphichaenus). k‐means supported the best number of clusters as K = 4, aligning with groupings depicted by PCoA. All clusters were strongly supported by DAPC, with all individuals having 100% membership probability when compared to designations by drainage.Estimates for AR, us Table . PCoA shi Figure . The firFST was much larger between P. streckersoni and all populations of P. amphichaenus than comparisons within P. amphichaenus populations  was resolved as the best value to maximize likelihood, while K = 3  was supported as the best value to explain structure. For P. streckersoni, K = 1 was supported as the best value to explain structure and maximize likelihood. The TESS3 analysis using all data supported K = 2 selected by cross‐entropy plot, representing P. amphichaenus and P. streckersoni  and K = 1 for P. streckersoni. The geographic distribution of K = 4  when compared to populations of P. amphichaenus (5.2–7.0). Estimates of eN were higher in P. streckersoni  when compared to P. amphichaenus from the Neches (538.3) but depicted wide confidence intervals , P. amphichaenus from the Neches (38), P. amphichaenus from the Trinity (23), and P. streckersoni (46). All ND1 sequences are deposited on GenBank, and accession numbers can be found in Table P. amphichaenus from the Neches + Sabine, P. amphichaenus from the Trinity, and P. streckersoni : h, Hd, k, and π for each group are reported in Table P. amphichaenus populations than in P. streckersoni, similar to GBS analyses. Genetic diversity was also greater in the Trinity and Sabine populations of P. amphichaenus when compared to the Neches population. Similar to GBS analyses, pairwise FST comparisons showed more divergence between (a) P. streckersoni and all populations of P. amphichaenus, and (b) P. amphichaenus from the Trinity and P. amphichaenus from the Neches or Sabine , while 2.61% was found within groups. The haplotype network showed genetic differentiation of three groups similar to FastSTRUCTURE results: P. amphichaenus from the Sabine + Neches, P. amphichaenus from the Trinity, and P. streckersoni  and 0.25 to 10.5 for P. streckersoni (49 surveys). Potamilus amphichaenus appears to be extirpated from the lower Sabine (downstream of Toledo Bend Reservoir) and lower Trinity drainages (downstream of Lake Livingston). In currently occupied reaches, P. amphichaenus is not abundant except for the lower Neches below Lake Steinhagen  indicating that general increasing trends may be due to increased sampling effort rather than population expansion  aligned well with results from mtDNA   Haag, , which ts) Haag, . The lacs) Haag, , which hs) Haag, .P. amphichaenus and P. streckersoni, both species are presumed to be host specialists, with glochidia only transforming on A. grunniens , which leads us to hypothesize that the observed increasing trend in distribution for P. amphichaenus and P. streckersoni is a result of increased survey effort rather than range expansion.The demand for water and hydropower, coupled with ongoing changing climate, has led to obvious reductions in streamflow, alteration of sediment transport, increased salinity levels, and exacerbated highly variable seasonal hydrological fluctuations  throughout the ranges of n Figure , but DPHn Figure ; Table 6n Figure , 2012. WP. amphichaenus and P. streckersoni is the logical next step in recovery planning, and we found defensible evidence for the delineation of four genetically diagnosable CUs: P. amphichaenus from the Neches, P. amphichaenus from the Sabine, P. amphichaenus from the Trinity, and P. streckersoni. We do recognize that divergence between P. amphichaenus from the Neches and Sabine is limited  to augment populations in the upper Neches River  could be an effective recovery option to improve resiliency of the CU with limited genetic consequence. While CUs offer protection at the drainage level, delineation of GMUs within each CU will allow for more robust investigations of population characteristics such as relative abundance, age‐class structure, and threats to long‐term sustainability, all of which should be considered in recovery planning.Currently, populations of freshwater mussels for conservation and management practices are typically defined as geographic management units (GMUs), or a unit that is geographically or otherwise identifiable by man‐made and natural barriers ; Data curation (lead); Formal analysis (lead); Investigation (lead); Visualization (lead); Writing‐original draft (lead). Nathan A. Johnson: Conceptualization (supporting); Resources ; Writing‐review & editing . Clinton R. Robertson: Resources ; Writing‐review & editing . Robert D. Doyle: Funding acquisition (lead). Charles R. Randklev: Conceptualization (supporting); Funding acquisition (lead); Resources ; Writing‐review & editing .


Thrips tabaci Lindeman 1889, host strain infesting Welsh onion. Cytochrome oxidase I (COI) sequences of the populations exhibited specific residues at conserved positions of thelytokous biotype . Phylogenetic tree analysis revealed that COI sequences of the onion thrips collected from different local populations infesting Welsh onion were clustered with L2 biotype populations. In the laboratory, the thelytokous reproduction was demonstrated because each single thrips produced only female progeny. Interestingly, these thelytokous populations collected from different localities showed a certain level of genetic diversity. However, the genetic distance was independent of the actual distance among different local populations. Results of this study indicate that T. tabaci infesting Welsh onion is a thelytokous biotype with genetic variation among local populations.Parthenogenesis is an asexual type of reproduction that usually occurs in thrips. Thelytokous parthenogenesis is a kind of reproduction that produces female progeny without mating. This study reports a thelytokous reproduction of the onion thrips, Thrips tabaci Lindeman 1889) infesting Welsh onion (Allium fistulosum) in several areas of Korea. To determine the reproduction mode of T. tabaci, thrips infesting Welsh onion were collected from different localities in Korea. Cytochrome oxidase I (COI) sequences were then assessed. Results showed that all test local populations had signature motif specific to a thelytokous type. These COI sequences were clustered with other thelytokous populations separated from arrhenotokous T. tabaci populations. In a laboratory test, individual rearing produced female progeny without any males. These results support that Korean onion thrips infesting Welsh onion have the thelytokous type of parthenogenesis. Local thrips populations exhibited significant variations in susceptibility to chemical and biological insecticides. Random amplified polymorphic DNA (RAPD) analysis indicated genetic variations of local populations. However, the genetic distance estimated from RAPD was independent of the actual distance among different local populations. These results suggest that genetic variations of T. tabaci are arisen from population subdivision due to asexual thelytokous reproductive mode.Parthenogenesis is not uncommon in thrips. This asexual reproduction produces males (arrhenotokous) or female (thelytokous). Only females are found in the onion thrips ( Thrips tabaci Lindeman 1889) (Thysanoptera: Thripidae) is an important insect pest of onions including Welsh onion (Allium fistulosum L.). Its larvae and adults feed on leaf tissues and remove chlorophyll, thus impairing photosynthesis [Pantoea agglomerans and P. ananatis known to cause bacterial stalk and leaf necrosis [The onion thrips  biotype and two leek-associated  biotypes [Onion thrips is a cosmopolitan species with a wide host range, allowing it to have genetic diversity due to different hosts in various local regions . For exaZawirska , who sugbiotypes ,10. Althbiotypes .T. tabaci causes serious direct feeding damage [T. tabaci performs both dispersal and migratory displacement, leading to its wide habitat range in Korea and other countries [T. tabaci. This narrow genetic variability might be detrimental to species. However, little is known about the Welsh onion populations of T. tabaci. Thus, the objective of this study was to determine the biotype of the Welsh onion populations and their genetic diversity. To test genetic diversity, different local populations of T. tabaci were assessed in their variation in insecticide susceptibility.Welsh onion is cultivated in most agricultural farming areas in Korea, where g damage . A flighountries . HoweverT. tabaci were collected from six different regions (See Results). Rearing conditions were temperature, 25 ± 1 °C; photoperiod, 16 h/8 h of light/dark; and relative humidity, 70 ± 5% according to Reiter et al. [Larvae and adults of r et al. . Fresh WT. tabaci caught by sticky traps, morphological characters  were used. To avoid any errors in the identification by contamination of Frankliniella occidentalis and F. intonsa, which are common in Korea, we used the morphological characters [Three fields  of Welsh onion were monitored in this study. Songcheon field cultured onions in greenhouses. Both Yongsang sites were open fields. However, Yongsang 1 was close to a greenhouse culturing Welsh onion. Soon after transplanting onions from the nursery to fields in early May, yellow sticky traps  were installed with three replications in each field because sticky traps and cards are used in both open fields and greenhouses for monitoring the early occurrence and change in population size during different seasons [aracters  to diagnL1 larvae were randomly selected and individually reared in small Petri dishes  until adult stage. For reproduction tests, adults were kept individually or in a group. Single parent test used 30 individuals (=replications). For four or ten parental tests, reproduction tests were replicated 10 times or 5 times, respectively. Test arena used small Petri dishes with fresh Welsh onion. Progeny larvae were counted at five days after the reproduction test. Adult females were counted by observing ovipositor at 10 days after the reproduction test.g for 5 min. The resulting supernatant (1–2 ng DNA/μL) was used as gDNA sample. For cytochrome oxidase I (COI) sequencing, genomic DNA (gDNA) was extracted from 5~6 adult thrips which was collected from field population of different regions according to the method described by Kim et al. . Seven d2, 0.2 mM dNTP, 4 pmol of each primer, and 1 unit of Taq DNA polymerase . PCR was performed on a MyCycler Personal Thermal Cycler (Bio-Rad) using the following cycling conditions: initial heating at 94 °C for 3 min; 35 cycles of denaturation at 94 °C for 1 min, annealing at 50 °C for 1 min, and polymerization at 72 °C for 10 min; followed by keeping at 4 °C. PCR products were cloned into a PCR2.1 cloning vector  and transformed into Escherichia coli TOP 10 chemical competent cells. Plasmids were obtained after cloning and used for bidirectional sequence analyses using M13F and M13R universal primers. Sequencing was performed by Macrogen .Amplification of the 5′-fragment (482 bp) of cytochrome oxidase 1 (CO1) gene was carried out by PCR with a pair of primers: C1-J-1718 5′-GGAGGATTTGGAAATTGATTAGTTCC-3′ and C1-N-2191 5′-CCCCGGTAAAATTAAAATATAAACTTC-3′ [www.megasoftware.net, accessed on 30 October 2021). Evolutionary distances were computed using the Poisson correction method. Bootstrapping values were obtained with 1000 repetitions to support branching and clustering.Before sequence analysis, DNA sequences were trimmed and aligned with EditSeq and ClustalW program of MegaAlign , respectively. According to Kim et al. , phylogeIn each local population, 30 individuals were randomly chosen for RAPD analysis. gDNA was extracted as described above. Two RAPD primers, N-8017 (5′-TGCTCTGCCC-3′) and N-8041 (5′-ATCGGGTCCG-3′) , were usBeauveria bassiana, was purchased from Hannong Farm  and cultured in potato dextrose broth . Its spore and conidial mixture were prepared by filtering with four layers of cheese cloth. For bioassay, a fungal suspension (1.17 × 106 conidia/mL) was used. Spinosad was purchased from Dongbang Agro . An insecticide suspension (50 ppm) was used for the bioassay. The insecticide suspension was applied by a spraying method (~500 µL). Randomly ten T. tabaci adult insects were used for each replication (three replicates). Circular breeding containers  were used to conduct this experiment. Mortality was taken every 24 h up to five days.A fungal pathogen, All studies were performed by one-way ANOVA using PROC GLM of SAS program . Means wT. tabaci was monitored once a week using yellow sticky traps in Andong, Korea (p < 0.0001). Peak capture was observed in mid-May~early July when the average temperature was 25–28 °C with relative humidity of 60–80%. However, its seasonal occurrence was different among field conditions . Among three different filed sites, the highest density was found in Welsh onion cultured under an open field condition. The number of total thrips captured from three places during the entire onion culture period was 1079. These were all females based on the presence of ovipositor  per year in Korea. Spring onions were transplanted from nursery to field in mid-May and cultured until late August. During this culture period, g, Korea . Adults g, Korea A. Capturipositor B.T. tabaci infesting Welsh onion had a thelytokous biotype (L2). To test this hypothesis, 15 thrips collected from other Welsh onion sites in Korea were assessed for their COI sequences  and a microbial insecticide, B. bassiana . However, local variation appeared to be independent of geographical distance as two Andong populations exhibited a significant difference in susceptibility to B. bassiana.To explain the genetic diversity of tibility . DiffereT. tabaci. These field populations were obtained from thrips infesting Welsh onion. To analyze the reproductive mode, COI sequence analysis and laboratory mating assay were performed. RAPD was used to investigate genetic variation of field populations. All these analyses indicate that T. tabaci infesting Welsh onion in Korea has a thelytokous type of parthenogenesis.This study analyzed reproductive modes and genetic variation for field populations of Thelytokous parthenogenesis was observed for field-collected adults using sticky traps. The monitoring was performed in three fields cultivating Welsh onion during May–August. A main peak occurred in June. However, population sizes were different among field conditions. Specifically, more thrips were collected by traps in an open field condition than in a greenhouse condition. This suggests that thrips frequently migrate in field conditions, consistent with a previous report by Kim et al. . ConsideT. tabaci infesting Welsh onion. The issue of cryptic species of T. tabaci was initially raised by Zawirska [T. tabaci had the following two biotypes: a ‘tabaci type’ and a ‘non-tobacco  type’. Later, host-plant transfer experiments and field surveys support the cryptic species hypothesis that T. tabaci is a heterogeneous taxon [Apis mellifera capensis) is known to exhibit alternative thelytokous reproduction to prepare pseudoqueens [T. tabaci remains to be identified to explain such reproductive mode change.In recent years, the study of the mitochondrial regions of DNA including COI, using molecular biology, has proved useful in understanding some biological aspects of onion thrips populations . The phyZawirska , who sugus taxon . With thus taxon  have cladoqueens , in whicT. tabaci. RAPD is a type of polymerase chain reaction (PCR) with a short primer (8–12 nucleotides) that can randomly amplify products depending on target genome variation [T. tabaci has also been assessed using COI sequences of 12 local populations [T. tabaci due to RGD. Rather, the variation may be arisen from reproductive isolation, which prevents gene flow among subpopulations. In addition, T. tabaci may maintain genetic diversity by polyploidy as seen in variation in competency to transmit tomato spotted wilt virus (TSWV) depending on different modes of reproduction [T. tabaci was detected using microsatellite DNA and might be arisen from apomictic parthenogenesis of the thelytokous reproductive mode to possess more alleles than diploidy [RAPD analysis indicated the existence of genetic diversity in six local populations of ariation . Our curulations . A totalulations . Thus, pulations . Reproduoduction . Tetrapldiploidy .T. tabaci infesting Welsh onion can be classified into L2 biotype characterized by thelytokous parthenogenesis, and that onion thrips populations have genetic variations probably arisen from reproductive isolation and polyploidy.In summary, this study reports that