Vulpes vulpes) that colonized Zurich, Switzerland. Through use of genome‐wide single nucleotide polymorphisms and microsatellite markers linked to the major histocompatibility complex (MHC), we expanded upon a previous neutral microsatellite study to assess population structure, characterize patterns of genetic diversity, and detect outliers associated with urbanization. Our results indicated the presence of one large evolutionary cluster, with substructure evident between geographic sampling areas. In urban foxes, we observed patterns of neutral and functional diversity consistent with founder events and reported increased differentiation between populations separated by natural and anthropogenic barriers. We additionally reported evidence of selection acting on MHC‐linked markers and identified outlier loci with putative gene functions related to energy metabolism, behavior, and immunity. We concluded that demographic processes primarily drove patterns of diversity, with outlier tests providing preliminary evidence of possible urban adaptation. This study contributes to our overall understanding of urban colonization ecology and emphasizes the value of combining datasets when examining evolutionary change in an increasingly urban world.Urbanization is driving environmental change on a global scale, creating novel environments for wildlife to colonize. Through a combination of stochastic and selective processes, urbanization is also driving evolutionary change. For instance, difficulty in traversing human‐modified landscapes may isolate newly established populations from rural sources, while novel selective pressures, such as altered disease risk, toxicant exposure, and light pollution, may further diverge populations through local adaptation. Assessing the evolutionary consequences of urban colonization and the processes underlying them is a principle aim of urban evolutionary ecology. In the present study, we revisited the genetic effects of urbanization on red foxes ( The authors concluded that fox colonization of Zurich likely occurred through two founder events , and neutral demographic processes subsequently shaped patterns of genetic diversity.To explore the genetic consequences of these observations, Wandeler, Funk, Largiadèr, Gloor, and Breitenmoser  used 11 Echinococcus multilocularis transmission cycle within Zurich city foxes  that were separated by Lake Zurich, the Limmat River, and the dense Zurich city center  were selected from within a 20 km radius of Zurich's city center to represent the surrounding rural fox population. We only included individuals believed to be resident foxes based on sampling location, season, sex, and age to avoid erroneous inclusion of dispersing juveniles or males traveling through multiple territories during mating season. We found the methods described by Wandeler et al. (2) of foxes sampled around Zurich and the restricted movement observed between habitat types . Sample selection is detailed in Wandeler et al. , but brir Gloor, . Three rr et al.  sufficieDue to sample availability and quality requirements, we analyzed a subset of the 128 fox samples used in the original Wandeler et al.  study. O2.2Genomic DNA was previously extracted with a standard phenol chloroform protocol  to select fragments with the ligated barcode and eluted selected DNA in 55 μl low TE. Libraries were then prepared following standard recommendations for NEBNext Ultra ll DNA Library Prep Kit, where we used Agencourt AMPure XP magnetic beads for library purification and size selection. We standardized final libraries to 10 nM and used paired‐end DNA sequencing (2X150nt) on an Illumina HiSeq 2500.To generate genome‐wide SNPs, we conducted restriction‐associated DNA sequencing (RADseq) on all samples that passed DNA quality standards, using a dual‐adapter/barcode‐ligated library preparation method as described by Ali et al. . DNA wasSTACKSv1.42  set to the default parameter 3. SNPs were further filtered with populations, where we retained only the first SNP per locus (‐‐write‐single‐snp flag) and removed loci with missing data for more than 10% of foxes (‐r 0.90). After SNP genotyping, we additionally removed individual foxes with missing data for >10% genotyped loci. Lastly, we filtered for statistical linkage disequilibrium (LD) in PLINK with ‐‐indep‐pairwise 50 5 0.3 flag. We evaluated this final, filtered SNP dataset for outliers and aberrant genotypes by implementing principal component analysis with flashPCA to confirm final sample selection  which put all forward and reverse reads with a restriction enzyme cutsite into a single file. We then used 2.3C. familiaris) after successful cross‐species amplification in red foxes , Class II (n = 8 loci), and Class III (n = 2 loci) genes. Multiplex PCRs were conducted in 10 μl reactions containing 5 μl Qiagen Multiplex PCR Master Mix , 1 μl primer mix, 2.1 μl deionized water (diH2O), 0.4 μl bovine serum albumin , and 1.5 μl template DNA (standardized to 5 ng/μl with diH2O). In each multiplex, forward primers were marked with one of four dye labels , and primer mixes consisted of 84 μl diH2O mixed with 2 μl 100 μM dye‐labeled forward primer and 2 μl 100 μM reverse primer for each primer pair included. Cycling conditions consisted of initial denaturation 95ºC for 5 min followed by 28 cycles of 95ºC for 30 s, 60ºC for 90 s, and 72ºC for 30 s and a final extension 60ºC for 30 min.We selected twelve MHC‐linked microsatellites designed for domestic dogs . We shipped these diluted ready‐to‐run samples to the Biotechnology Resource Center at Cornell University Institute of Biotechnology for fragment analysis. Genotypes were assigned by visual inspection of fragment analysis peaks in  Kearse, .R package Genepop  in and around Zurich. Briefly, we used (a) genetic assignment tests in STRUCTURE to determine the number of evolutionary clusters based on shared ancestry, (b) Mantel tests in the R package ecodist to evaluate spatial genetic structure within the entire sampling area, (c) principal component analysis (PCA) in flashPCA to identify the primary drivers of individual clustering, (d) discriminate analysis of principal components (DAPC) in the R package adegenet to explore the relationship between sampling location and population substructure, and (e) estimates of pairwise genetic differentiation (FST) and combined private allelic richness to consider genotype differentiation and allele sharing between the groups identified in the previous analyses. Use of multiple analyses enabled us to consider population substructure in a variety of diverse yet complementary analytical frameworks. This increased confidence that observed substructure patterns resulted from true signal rather than statistical relicts of any singular method.As traditional methods often fail to detect fine‐scale structure in urban populations  spanning 1–10 , with 10 independent runs at each K value. Each run had 10,000 burn‐in length and 25,000 Monte Carlo Markov Chain repetitions. We determined the optimal K value based on evaluation of log probabilities. Given the geographic proximity of our five sampling areas, we ran this model with sampling location given a priori using LOCPRIOR. This parameter setting aids detection of weak structure without forcing erroneous evolutionary clusters , PCA‐based approaches rely on ordination. This allowed us to consider the variables underlying emergent clusters without including prior assumptions about sampling location. To later incorporate geographic information, we used Spearman's rank correlation tests to compare PC1 with the Swiss coordinate system's X‐ and Y‐coordinates  tree with our genetic distance matrix comparing all foxes in the R package ape  with our genome‐wide SNP dataset using the linkage disequilibrium method implemented in NeEstimator v2.1, although these estimates were restricted to “urban” and “rural” foxes  due to small sample sizes , observed heterozygosity (OH), expected heterozygosity (EH), number of alleles , nucleotide diversity , and inbreeding coefficient (FIS). We then performed nested ANOVAs using base functions in R to compare diversity statistics between subpopulations .We next calculated summary and per‐population metrics of diversity with the ADZE v1.0  while retaining the majority of loci. For microsatellite data (where more foxes were genotyped at fewer loci), we set the maximum standardized sample size to 200 and the missing data tolerance to one, in order to retain all loci for analysis.Due to sample size differences in both datasets, we used a rarefaction approach to estimate allelic richness detected in each subpopulation with increasing sample size in R package detectRUNS  in each subpopulation with the 2.6pcadapt to detect outliers in clusters identified through previous structure analyses  to obtain a vector of z‐scores. Outlier loci are identified from these vectors by calculating Mahalanobis distance (D) test statistics, which measure the multidimensional distance of each point from the mean. We determined significance by transforming p‐values into q‐values with the R package qvalue . qvalue: Q‐value estimation for false discovery rate control. R package version 2.12.0. http://github.com/jdstorey/qvalue), retained SNPs with q < 0.05, and focused attention on outlier SNPs detected in multiple analyses.We first used the genome scan method implemented with the GEMMA to identify outlier loci that may be associated with urban fox colonization  while accounting for population stratification and designated covariates. We calculated a centered relatedness matrix from the SNP dataset using the ‐‐gk 1 flag in GEMMA and included sex and subpopulation as covariates. We applied a modified FDR to adjust the 5% significance threshold to correct for multiple testing  compares observed homozygosity to that expected under neutral conditions. Significantly negative FND values indicate balancing selection, as observed homozygosity is lower than expected homozygosity. This result suggests that genetic diversity is actively maintained. Alternatively, significantly positive FND values indicate directional selection, as observed homozygosity is higher than expected. This result suggests maintenance of a few particular alleles that may confer selective advantage. For this analysis, we considered both statistically significant results and general trends as potentially biologically relevant, given constraints of sample size.For MHC‐linked markers, we implemented the Ewens–Watterson homozygosity test of neutrality in 33.1process_radtags in STACKS. Lastly, an average of 10% of reads per individual (6%–36%) were removed as PCR duplicates with clone_filter. Our final dataset consisted of 10,149 SNPs filtered for LD in 31 rural and 19 urban foxes. This served as our final SNP dataset in all subsequent analyses.A total of 72 foxes passed quality control screening and were prepared for RADseq, 50 of which retained enough quality reads to be included in downstream analyses. Overall, we sequenced a total of 258,360,568 paired‐end reads and retained 172,305,248 (66.7%) after removing reads without a barcode. Of these, another 5.8% of sequenced reads were removed due to poor quality with 3.2i.e., missing data >30% following Heppenheimer et al., Given lower DNA quality requirements for microsatellites, we genotyped 115 foxes at 12 MHC‐linked microsatellite loci. We discarded three markers  due to monomorphism, leaving nine polymorphic loci for downstream analyses. We then removed individual foxes that failed to amplify three or more loci . In total, 44 alleles were amplified across all nine loci, with a minimum of 2 alleles detected for C2_BF_1, C2_BF_2, and CFA12‐19 and a maximum of 13 alleles detected for CFA12‐17.Rural and urban foxes reported similar numbers of successfully amplified loci  with no significant difference between them  and a subdivided dataset of intergenic sites , with the overall Mantel test suggesting moderate correlation across the full range of sampling distances .Within this evolutionary cluster, the overall Mantel test and Mantel correlogram supported patterns of spatial genetic structure  clustered to the left and those east of the three landmarks (Ueast + Reast) clustered to the right. The rural population sampled north of the city (northR) fell in the center. The component explaining most variance (PC1) was significantly correlated with the Swiss X‐coordinate (easting) in the Spearman's rank correlation test , with no association detected between PC1 and the Swiss Y‐coordinate . Plotting PC1 against the Swiss Y‐coordinate recapitulated the geographic sampling area of Zurich foxes  and west (Rwest and Uwest) of Lake Zurich, the Limmat River, and Zurich's city center further emerged in this analysis, with large branches of the NJ tree broadly corresponding to this geographic subdivision across the lake and river  after correcting for multiple testing, with the exceptions of Rnorth + Reast, Rnorth + Rwest, and Reast + Ueast  occurred between the two urban subpopulations, Ueast + Uwest  and lowest for two pairings separated by the center city barriers  foxes and 5,915.5 for rural (Reast + Rwest + Rnorth) foxes. Though Ne estimates should not be mistaken for projected census sizes, they do suggest far greater numbers of foxes outside of the city limits.Estimates for ADZE v1.0 to calculate allelic richness at standardized sample sizes , urban foxes reported higher observed heterozygosity and lower inbreeding coefficients than the rural subpopulations. For heterozygosity, nested ANOVA reported a significant effect of habitat , with an insignificant effect of subpopulation . For inbreeding coefficients, both habitat  and subpopulation  were statistically significant.Heterozygosity deviated from this trend of reduced urban diversity Table . Though F = 7.820, p = 0.006), with an insignificant effect of individual sampling area . Mean number of alleles was similarly reduced in urban foxes, although neither habitat nor sampling area had statistically significant effects (p > 0.05). Across standardized sample sizes, rarefaction of allelic richness showed fewer alleles in urban foxes when compared to rural foxes , with specific sampling area insignificant .Analysis of ROH by subpopulation revealed similar patterns of decreased diversity in urban foxes Figure . Median s Figure a. This tReast, Rwest,Ueast with 12–13 foxes each; Rnorth, Uwest with six foxes each) and observed that both urban subpopulations consistently possessed more ROH than rural foxes, with Ueast exhibiting the global maximum in each length class. As with the sum of ROH, nested ANOVA of the number of ROH reported a significant effect of habitat  with subpopulation effect insignificant .A similar pattern emerged in total number of ROH observed per length class Figure b. It is 2r = 0.918), with urban foxes (particularly Ueast) more densely concentrated in the upper right quadrant of the plot than rural foxes  and west (Rwest + Uwest) of Lake Zurich, the Limmat River, and Zurich's city center separately in pcadapt. We excluded Rnorth from this analysis due to its intermediate position between Reast and Rwest in the PCA and DAPC analyses. For both runs of pcadapt, we regressed the SNP dataset  against the first two PCs, since K = 1–2 captured the relevant population structure in this and previous (DAPC) analyses. Using a significance threshold of q < 0.05, we detected 514 outliers in east subpopulations and 508 outliers in west subpopulations, with 42 loci appearing as outliers in both analyses. These overlapping SNPs included 17 annotated as intergenic, 27 as intronic, three as exonic, and two near promoters (note that some SNPs have multiple annotations). We queried genic outliers significant in both analyses , using GEMMA to fit a univariate linear mixed model with sex and sampling area as covariates. We further controlled for population structure by including a relatedness matrix of all foxes sampled. We analyzed all 10,149 SNPs and adjusted our likelihood ratio test (lrt) significance threshold using the modified FDR (adjusted p = 0.005). This analysis produced 91 SNPs significantly associated with the urban phenotype, with 48 annotated as intergenic, 42 as intronic, 11 as exonic, and three near promoters . Although no SNPs overlapped with outliers identified in pcadapt, possible gene functions once again related predominantly to immunity and metabolism (among other cellular processes), and VEP analysis included “low impact,” “moderate impact,” and “modifier” annotations.We next examined SNPs associated with urban versus rural habitats in the full fox dataset , which suggested the presence of balancing selection at loci linked to MHC Class I and II genes. Though remaining loci were not significantly positive or negative, we considered trends as potentially biologically relevant, as small sample sizes may have limited our ability to detect statistically significant relationships  exhibited positive FND values in subpopulations polymorphic at those markers, which may suggest positive selection.To identify outlier loci in the MHC‐linked microsatellite dataset, we implemented the Ewens–Watterson homozygosity test of neutrality in 4In the present study, we revisited the city‐fox phenomenon in Zurich, Switzerland, to examine the genetic effects of urban colonization and the evolutionary processes that shaped them. Through concurrent analysis of genome‐wide SNPs and MHC‐linked microsatellites, we addressed the following questions: (1) Do we observe subpopulation structure between urban and rural foxes in Zurich? (2) What patterns of genetic diversity characterize urban fox colonization? (3) Can we identify evidence of selection at MHC‐linked markers or outlier SNPs associated with urban colonization?C. lupus; Fabbri et al., C. latrans; DeCandia et al., Etheostoma fonticola; Olsen et al., Propithecus perrieri; Salmona et al., Considered together, our results suggested the presence of one evolutionary cluster subdivided into smaller groups clustered by geographic sampling area. We observed significant differentiation across natural  and anthropogenic  barriers that were consistent across multiple data‐types and complementary analytical frameworks. These results matched previous radio‐tracking data that suggested smaller home range sizes and localized movement of foxes inhabiting rural and urban areas around Zurich Gloor, . They fuRegarding genetic diversity, this study builds upon the results reported by Wandeler et al.  by showiSORT1 and NNMT; Shi & Kandror, NNMT; Aksoy, Szumlanski, & Weinshilboum, CD22 and ATG16L1; O'Keefe, Williams, Davies, & Neuberger, 1996; Chu, NAV2; Peeters et al., RAI1; Walz et al., P. leucopus; Harris & Munshi‐South, Turdus merula; Mueller et al., Fundulus heteroclitus; Reid et al., J. hyemalis; Whittaker et al., L. rufus; Serieys et al., We further detected outlier loci that may provide preliminary evidence of urban adaptation during colonization. Although we observed no overlap between outlier SNPs using different outlier detection methods, we did observe considerable overlap in possible gene functions. Recurring annotations were related to metabolism (e.g., These results should be interpreted with caution, due to the small sample size, minimal overlap of specific outlier sites, and ongoing debate on the use of RADseq data for detecting genomic outliers (Catchen et al., Through examination of genome‐wide SNPs and MHC‐linked microsatellites, this study expanded upon the results reported by Wandeler et al.  to proviNone Declared.ALD, KEB, and BMvH designed the study; GC, PW, and CD contributed samples; ALD, KEB, and CC conducted the laboratory work; ALD and KEB processed the raw data; ALD analyzed the data; ALD, KEB, EH, and BMvH provided analytical assistance; ALD, KEB, and BMvH prepared the manuscript; all authors contributed to and approved the final manuscript. Click here for additional data file. Click here for additional data file.


The adaptation of organisms to changing environments is self-evident, with the adaptive evolution of organisms to environmental changes being a fundamental problem in evolutionary biology. Bees can pollinate in various environments and climates and play important roles in maintaining the ecological balance of the earth.Apis cerana (A. cerana) specimens from 31 populations in 11 regions and obtained 39 representative morphological features. We selected 8 A. cerana samples from each population and performed 2b-RAD simplified genome sequencing. A total of 11,506 high-quality single nucleotide polymorphism (SNP) loci were obtained. For these SNPs, the minor allele frequency (MAF) was > 1%, the average number of unique labels for each sample was 49,055, and the average depth was 72.61x. The ratios of the unique labels of all samples were 64.27–86.33%.We performed an analysis of 462 A. cerana. Using genomics to assess population structure and genetic diversity, we found that A. cerana has a large genetic difference at the ecotype level. A comparison of A. cerana in North China revealed that some physical obstacles, especially the overurbanization of the plains, have isolated the populations of this species. We identified several migration events in North China and Central China. By comparing the differences in the environmental changes in different regions, we found that A. cerana has strong potential for climate change and provides a theoretical basis for investigating and protecting A. cerana.Using 39 morphological characteristics as the data set, we proposed a method for the rapid classification of  Adaptation to a changing environment is a fundamental problem in evolutionary biology. Understanding the impact of the environment on biological genetic diversity can not only clarify the course of evolution but can also provide information on how to protect the ecological environment , 2. BeesApis contains 10 different species, most of which are distributed throughout Asia [A. cerana is an Asian honeybee species with a wide geographical distribution. Previously, A. cerana was divided into five or six local categories based on a comprehensive study of mitochondrial DNA and microsatellite DNA, and the A. cerana species in China belonged to a subspecies [A. cerana was defined as one of the most important pollinators in China, domesticating the region for more than 2000 years [A. cerana in China have classified A. cerana into different ecological types only by morphometric measurements. However, the results were variable due to different measurement indicators [A. cerana in China, including Hainan, the Yunnan-Guizhou Plateau, Tibet, Aba, Changbai Mountain, southern Yunnan, North China, South China, and Central China [A. mellifera, and the conclusions were obtained from no more than 12 traits; therefore, the unique features of A. cerana were likely missing from the analysis [Apis mellifera (A. mellifera) [A. cerana continued to improve until 2015, when the reference genome was published [A. cerana in most parts of China, which paralleled the simple hierarchical division and proposed that physical barriers (such as islands and mountains), rather than physical distances, lead to population differentiation. In other words, these barriers are the main obstacles leading to population exchange [A. cerana, even in the same region in China, can be highly variable [out Asia . A. cerabspecies , 7. A. c00 years . The vardicators , 10. It al China . Howeverllifera) , 13–17. ublished . Recentlexchange . Other svariable , which hA. cerana uses small-scale nectar plants effectively. This species also has a strong harvesting ability, a long honey-collecting period and adaptability, strong disease resistance, and low consumption of feed, which are highly suitable for changing landscapes. The number of A. cerana has fallen sharply in recent decades [A. cerana has unique economic and ecological values in agriculture in China. In recent years, due to the continuous increase of China’s population, A. cerana has helped to maintain a balance between demand and production by contributing to high yields of grain. On the other hand, A. cerana is at the center of research in evolutionary biology, which attempts to understand how the population responds to climate change or environmental insults, thereby providing basic knowledge of the evolution and adaptation of A. cerana. decades , with cl decades . On the A. cerana genome [A. cerana can also be used to determine the genetic variation of the adaptive and economic shape, thereby providing an in-depth understanding of the genetic structure of A. cerana as a whole. We conducted a more comprehensive measurement of North China and analyzed the effects of topographical and environmental changes, including human activities, by combining morphological characteristics and genomic differences. We identified genetic variations, proposed a rapid classification method, explored the population structure and factors affecting differentiation, and screened the A. cerana genes that adapted to the local environment, which provides evidence of genetic diversity for future research investigating A. cerana.In this study, we collected samples from regions of different topography, environment, and climate and carried out a comprehensive morphometric determination, with the a genome  serving A. cerana samples included: (1) Bee right front wing: length of bee right forewing cubital vein a (a), length of bee right forewing cubital vein b (b), width of bee right forewing (FB), length of bee right forewing (FL), angle A4, B4, D7, E9, G18, J10, J16, K19, L13, N23, O26 of bee forewing , bee index number of cubital vein (Ci); (2) Bee right hind wing: Bee branches midrib (NT), Number of bee hindwing hamule (Nh); (3) Bee tergum: bee length of tergum 3,4 , bee width of tomentum on tergum 5 (T5); (4) Bee sternum: (bee length of sternum 7 (L7), bee width of sternum 7 (T7), bee length of sternum 4 (S4), bee distance of bee wax mirror on sternum 4 (WD), bee length of bee wax mirror on sternum 4 (WL), bee width of bee wax mirror on sternum 4 (WT); (5) Bee hind leg (length of femur of bee hind leg (Fe), length of bee hind leg basitarsus (ML), width of bee hind leg basitarsus (MT), length of tibia of bee hind leg (Ti); (6) Color of the bee: bee pigment of scutellum B,K area , bee pigment of tergum 2,3,4 , bee pigment of clypeus (Pc), bee pigment of labrum (PL), and bee pigment of scutellum Sc area (Sc) .The morphological measurements of the collected A. cerana from 31 populations collected from 11 regions in China (Mengyin (MY), Yiyuan (YY), Rizhao (RZ), Qingdao (QD), Linqu (LQ) and Zaozhuang (ZZ) Chongqing (WL), Sichuan (QC), Anhui (LA), Shanxi (HZ) and Hainan (WC)) and used the average of the morphological data of A. cerana from the 11 regions for the cluster analysis. Figure A. cerana interregional relationships. At a threshold of 12, A. cerana from the 11 regions was divided into 4 groups, in which YY and MY were grouped together, LA and WC were in separate groups, and the remaining seven regions were clustered into one large group. According to the Chinese recognized ecotypes of A. cerana, YY, MY, LA, QD, ZZ, RZ, and LQ were from the North China ecological type; WC was sampled from the Hainan ecological type; and HZ, WL, and QC were from the Central China ecological type [We divided 462 A. cerana from the 11 regions into three groups as follows: YY, MY, and LA formed the first group; ZZ, LQ, QC, and HZ fell into the second group; and WC, RZ, WL, and QD formed the third group. This finding was notably different from the results we had used to classify all the trait data. In particular, RZ, LQ, QD, and WC were relatively close in the four regions of the third group. We found that these regions were located in coastal areas, which seemed to be related to the color of the bees. According to the results of body size clustering, there was a significant difference in the size of the Hainan Bee (WC) compared to other bees, whereas clustering according to the angle of right forewing showed no difference between the 12 indicators of wing geometry and the total 39 traits.We clustered the 39 traits into three categories—body size, color type, and angle of right forewing—for cluster analysis Fig. . We founA. cerana ecological type of the sampling area. The northern ecological type was divided into two regions, the larger region and the smaller region that overlapped with the central ecological type. The central and south ecological types were nearby, but the division was clear (4A). When the bees were divided according to the sampling region, the bees in the 11 regions grouped together more obviously. The distribution pattern was consistent with the morphometric measurement of 39 traits. RZ, ZZ, LQ, and QD, which belong to North China, are close to central China  scatter plot of principal factor 1 (variation 29%) and principal factor 2 (variation 20.21%) further supported the patterns  formed its unique pedigree composition with LA, and most of YY (YY1-YY7) formed a cluster. LQ and RZ formed a cluster; MY, ZZ, and QD showed different degrees of pedigree, and approximately one-half of the MY area (MY1 and MY2) showed a special lineage with clear differences in the area. When the K value was 5, the differentiation of MY, ZZ, and QD was further emphasized. MY was split into three areas, ZZ was split into two areas, and RZ was split into two areas, showing a highly mixed state. These results were further supported by the phylogenetic tree of the SNP data, as analyzed with Tessal 5.0 [K values ranging from 3 to 5. ΔK was determined by the Harvester method [K value was 3, and all regions were divided into 4 genetic components; blue region (WC), green region , red region , and a mixed area of red and green .We used STRUCTURE 2.3.4 for cluster analysis   to 0.257 (AH and WC), with an overall mean of 0.132, indicating moderate genetic differentiation. The states (0.05 < 0.132 < 0.15) in which WC, LA, and LQ were highly differentiated  were consistent with the overall heterogeneity of the population structure and gene flow. Compared with A. mellifera  [A. cerana was more highly differentiated at the level of genetic differentiation . The Fst difference between the different regions of the bee was large, showing rich species diversity at the ecotype level [A. cerana  in the central mountainous region had the lowest Fst distribution , and WC had the highest differentiation state . The region of North China  showed variable differentiation states, with most being in a low differentiation state, although LA and LQ were in a highly differentiated state. We found that the mountainous regions  were higher than the other regions. Given the lower average Fst of 0.166, we calculated the Fst  < 0.01 were excluded. Finally, only biallelic genes  and SNP loci with t, 0.10) , A. cerape level , 31. A. Pic), effective allele number (Ne), nucleic acid diversity (Pi), heterozygosity (Ho), and expected heterozygosity (He) of each SNP locus in the population were separately calculated . Among these regions, the QC region  has the lowest Pic at 0.209, whereas the average Pic of the QD region  was the highest at 0.274. The more isolated populations had lower genetic polymorphisms  with an average Pic of 0.214, which is consistent with the distribution of Pi. Nucleotide diversity is an indicator of diversity within or between populations. The Pi distribution of YY, HZ, WL, and QC was similar with average Pi values of 0.281, 0.275, 0.253, and 0.266, respectively, which are lower than the average (the average Pi = 0.306). Furthermore, the WC region surpassed the mean polymorphic information (Pi = 0.321 > 0.306), and there was high differentiation (mean Fst = 0.216) and low genetic variation . At the same time, Fis < 0 indicated that the Wenchang area was in a closed island, and it had a large surface area, which caused A. cerana in the WC area to have more biodiversity and heterozygosity than other areas. There were significant differences among heterozygosity (He), variance (Pic), and diversity (Pi) (P < 0.01) in MY, among which MY2 and MY3 had higher heterozygosity, variation, and diversity, and MY1 and MY4 had lower heterozygosity, variation, and diversity. A comparison of the STRUCTURE stacking map with a K value of 3 . In addition, a large gene flow was observed between MY1 and MY2 (Nm = 18.1). MY2 had higher heterozygosity (He = 0.364), whereas MY1 remained relatively stable (He = 0.28), suggesting that the genes flowed from MY1 to MY2. Overall, we found that Ho was greater than He at the population level and that the inbreeding coefficient was generally less than zero. We also calculated all sampled groups with an average observed heterozygosity (Ho) of 0.3368, which was higher than the expected heterozygosity (He) of 0.2865. The QD region  has the highest Ho, He and Pic  indicated that the population heterozygosity was high, which could be affected by the combined effects of selection, mutation and genetic drift.The polymorphism information content . The first migration showed that the bloodline of QC was 18.1% for HZ (w = 18.1%). The second migration showed that the ancestors of HZ, QC, and WL were the ancestors of QD, RZ, and LQ (w = 26.5%). We evaluated the residual model using the 31 populations without migration to reveal the nonstrict hybrid events. All reported migration edges had P-values < 0.01. The three-population test was performed based on the “f3 structure” .Treemix was used to construct the maximum likelihood tree with 1 and 2 migration events between regions in our study  using thmap Fig. a, b, whiQ w = 26.%. We evaFst is one of the most common methods for assessing the spatial communication of the population structure [Fst were tested by Mantel [P = 0.008). We also used PASSaGE for repeated tests and obtained the same result (P = 0.0093). There was a significant correlation between physical distance and genetic distance, and the correlation degree was r = 0.34493. We calculated this value for A. cerana in North China. The results showed that there was a weak correlation between geographic distance and genetic distance (P = 0.051), and the correlation degree was reduced to r = 0.273. This finding may be related to the high plains in North China and low altitude.The difference between the genetic distance and geographical distance calculated by the paired tructure –36. We utructure , and they Mantel , 36. We Fst and Manchester correlation of A. cerana in North China , the population similarity was higher  in the first segment. When the distance was 156.4 Km, the population similarity decreased to 0 and then changed to a negative value, indicating that the population is not genetically similar. To make it easier to observe the Manchester correlation graph, we simultaneously calculated the Fst value at each node and created an interference graph .North China has a rich terrain and belongs to the temperate monsoon climate. To further understand the changes in the correlation between genetic distance and geographical distance, we separately calculated the A. cerana according to the Arlequin stratification method and identified 121 candidate SNPs at a significance level of 1%  analysis and the related candidate genes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, 20 significantly enriched GO terms and three significantly enriched KEGG pathways were selected Table , in whicila fins , 42. In aptation , and a s species . Metabol species .For the enriched GO terms, adaptive terms, such as “response to stimulus”, “signal transduction”, “locomotion”, and “biological regulation”, were significant  showed that human-mediated gene flow led to the management of honey bee colonies High genetic diversity [The phenotypes of ZZ, RZ, QD, and LQ in North China were similar to those in the central region, which seems counterintuitive. We performed a genome-level analysis, and the STRUCTURE results showed that there was considerable genetic diversity in ZZ, RZ, QD, and MY. At iversity , 47, andFst value of population differentiation, which showed a large difference between WC and the inland region (average Fst = 0.216). The Fst value was previously calculated for A. cerana at the subspecies level between the more isolated populations , for which the average Fst differentiation was 0.162 in the range of 0.099 to 0.228 [Fst between MY, YY, LA and WL, HZ, and QC between 0.6 and 0.9, but the morphological data show that it belongs to a different ecological type. Therefore, we believe that the Fst range of A. cerana should be between 0.06 and 0.228, while the Fst range for the A. mellifera subspecies of the same lineage was 0.05 to 0.15 [A. mellifera, A. cerana has a richer genetic diversity.Genetic variation is critical for the survival of bees in changing climates. For bees, high genetic diversity at the population level can increase the adaptability of colonies, as bee colonies with higher diversity exhibit a more stable ethnic balance , 49, areto 0.228 . We calc to 0.15 . ClearlyA. cerana, especially in the vast plains of North China, which are particularly conducive to urban construction. However, complex terrains are more resistant to human activities, which could be the reason for the higher degree of differentiation of A. cerana in ZZ, RZ, QD, and LQ. We believe that the isolation of A. cerana by human urban agglomerations is more stringent than the physical isolation caused by mountains.Although ZZ, RZ, QD, and LQ may have undergone mixed population events, they are currently in a state of equilibrium. Furthermore, different mixed regions have gradually formed relatively independent ecological types. Previous studies have suggested that bees migrate rapidly in areas without strong physical barriers, which can promote gene flow and reduce genetic differentiation. The rapid spread of bees in Australia and the Americas can better illustrate the potential for the rapid migration of bees –55. The A. cerana shows the potential of using all three strategies. Research has described a method to identify the performance of bee populations based on outliers [A. cerana.Researchers believe that the survival of a species through climate change, habitat loss, and ecosystem changes is due to their physiological tolerance limits and resilience, ecological characteristics , and genetic diversity . A. ceraoutliers , 60. In outliers . The socoutliers , 63. Furoutliers . Geneticoutliers . We furtA. cerana shows good potential for climate change, but the effects of stress, such as pesticides, pollutants, pathogens, parasites, and limited flower resources caused by human activities, are posing a larger threat to A. cerana in China [In summary, as a wide-range species, in China , 67. In A. cerana species, as well as morphological characteristics and genomic methods, to provide insights into the differentiation and adaptation of the species in China. We proposed a method for the rapid identification of the morphology of the wing and found some historical migration between the North and Central regions. A. cerana in China exhibits high genetic diversity, and physical barriers, rather than distance, are the driving factors for the differentiation of this highly migratory species. Human activities, such as urbanization, have a great impact on the differentiation of A. cerana. We screened for abnormal SNP loci and obtained related genes, performed enrichment analysis and gene ontology categories to identify candidate genes. The results of this study may help to elucidate the evolution of A. cerana in different environments and promote our understanding of how bee populations will respond to increasing climate change and how to protect bees from current and future challenges.Our study utilized the wide-range A. cerana germplasm conservation areas or traditional breeding sites in 11 provinces and municipalities, such as Chongqing (WL), Sichuan (QC), Anhui (LA), Shanxi (HZ) and Hainan (WC) , Yiyuan (YY), Rizhao (RZ), Qingdao (QD), Linqu (LQ) and Zaozhuang (ZZ), in Shandong (SD) Province and WC) Fig. . To obtaes Table . All fraA. cerana [This test was carried out in accordance with the indicator project of the honeybee morphology researcher , 69 and . cerana . First, A. cerana was randomly selected from each of the sampled sites for sequencing, and a tag sequencing library of A. cerana samples was constructed by the 2b-RAD technique. All samples were constructed using standard 5′-NNN-3′ linkers. To obtain high quality reads, both the library and quality-controlled libraries were subjected to paired-end sequencing data filtering on the HiSeq X Ten platform, and SOAP2 was used to compare the sequencing data to the genome [p-values less than 0.05. A total of 11,504 SNP loci were obtained for all samples  was performed. Then, we used the first two main factors of PCA (cumulative variability reached 57.4) and constructed different scatter plots. Finally, we use the hierarchical cluster function in SPSS 22, select Ward’s method to perform hierarchical clustering, and combine the most similar samples according to the degree of closeness between the different indicators. The sequential aggregation method classified all samples to obtain an intuitive understanding of the population structure.We used SPSS 22 to analyze the morphological data of 462 F), expected heterozygosity (He), and observed heterozygosity (Ho) were calculated using PLINK2 [Pic) was calculated using a custom Perl script. The Fis, Fst, and Fit values of the SNP locus in 243 samples were statistically analyzed using Genepop software (version 4.2.2) [Fst matrix and distance matrix was performed using the ade4 package in R [Prior to population genetic analysis, VCF tools were used to rigorously obtain the most informative SNPs . The inbg PLINK2 . The ratn 4.2.2) . The Manage in R . We usedage in R  to inferage in R . The metK, and the variable ancestor ratio was determined by the allele frequency of the population. This approach allowed the use of mixed bees to characterize ancestral populations [K from one to ten for 11,506 SNPs to run on STRUCTURE. The analysis was performed without prior knowledge of the demographic identity by simulating 50,000 preburning steps and 100,000 iterations of the MCMC algorithm per run. Ten independent runs were performed for each K to estimate the most reliable different genetic clusters using the probability of posterior probability (LnP(N/K)) [K partition. The posterior probability variation with respect to K between the different runs was designated as the method for determining the true K value [K was based on the network software STRUCTURE HARVESTER [PCA of the genetic and morphological traits of different individuals, respectively, enabled us to visualize the correlations between individual bees in individuals/regions on a multidimensional scale.A model-based Bayesian clustering method was used to characterize the different genetic clustering patterns between the different regions with STRUCTURE 2.3.4 . The genulations . We usednP(N/K))  and the  K value . The mosARVESTER  and EvanARVESTER , which wARVESTER  and SPSSFst matrix and distance matrix with the ade4 software package in R [Fst of the set “distance level” was calculated separately to generate a polyline “interference graph” that was combined with the Manchester correlation map for a more intuitive view.The Mantel test was performed using the age in R . To descage in R , accordiFst and heterozygosity. A locus with an Fst value higher than the 0.99 limit of the neutral distribution was considered to be a putative outlier under divergent selection [Fst values were considered to be neutral SNPs. All procedures reduced bias and maintained highly differentiated loci between ecotypes individuals. We chose Fst values that were higher than the expected neutral distribution as the directional selection sites and Fst values that were lower than the expected neutral distribution as the balanced selection sites [A coalescence-based simulation was used to detect deviating SNP sites. With these methods, we expected to detect low-level differentiation sites under balanced selection  and high-level differentiation sites under directed selection (differentiation loci). The layering method we used was a modification of the FDIST method that was performed with Arlequin ver 3.5.2.2 , 79.. Weelection . The remon sites .https://www.ncbi.nlm.nih.gov/assembly/GCF_001442555.1). A 50-base sequence upstream and downstream of the extraction site was sequenced and aligned with the A. mellifera sequence to obtain the most recent genes. Enrichment analysis was based on their orthologs in Drosophila melanogaster. The genes were assigned to GO and KEGG pathways. The functional enrichment of gene IDs was performed using GeneMania and g: Profiler [P-values to identify clusters of significantly enriched terms.SNP loci were screened using high-quality SNP loci , 80, andProfiler , 82 withProfiler  and BenjAdditional file 1: Figure S1. Maximum likelihood tree with one migration event.Additional file 2: Table S1. The 39 morphological measurements of A. cerana.Additional file 3: Table S2. Abbreviation table.Additional file 4: Table S3. The Fis, Fst, and Fit of each SNP locus.Additional file 5: Table S4. The Fst table between all groups.Additional file 6: Table S5. The gene flow table between all group.Additional file 7: Table S6. Three population tests for admixture.Additional file 8: Table S7. The Fst value table and distance table in North China.Additional file 9: Table S8. Mantel test table.Additional file 10: Table S9. Details of 121 candidate SNP loci.Additional file 11: Table S10. GO term enrichment result.Additional file 12. SNP data after filtering.


Etlingera elatior) collected from seven states in Peninsular Malaysia were evaluated for their molecular characteristics using ISSR and SSR markers to assess the pattern of genetic diversity and association among the characteristics. Diversity study through molecular characterization showed that high variability existed among the 57 torch ginger accessions. ISSR and SSR molecular markers revealed the presence of high genetic variability among the torch ginger accessions. The combination of different molecular markers offered reliable and convincing information about the genetic diversity of torch ginger germplasm. This study found that SSR marker was more informative compared to ISSR marker in determination of gene diversity, polymorphic information content (PIC), and heterozygosity in this population. SSR also revealed high ability in evaluating diversity levels, genetic structure, and relationships of torch ginger due to their codominance and rich allelic diversity. High level of genetic diversity discovered by SSR markers showed the effectiveness of this marker to detect the polymorphism in this germplasm collection.Fifty-seven accessions of torch ginger ( Etlingera elatior), a member of Zingiberaceae, is a multifunctional crop but no information is available on its genetic resources. Torch ginger is commonly propagated by rhizomes . It takes about 12 months after planting to start flowering but a longer time is needed when seeds are used  and 2 μl β-mercapto-ethanol using vortex. An equal volume of chloroform/isoamyl alcohol, CIA (24:1 v/v), was added and the mixture was centrifuged at 14,000 rpm for 30 sec to separate leaf residues. The supernatant was collected into a new tube and the step with CIA was repeated twice. The supernatant was transferred again into new 1.5 mL tube and added with 800 μl absolute ethanol. The mixture was mixed well by gentle shaking and centrifuged at 14,000 rpm for 3 min. After discarding the supernatant, the DNA pellet was washed by adding 1 mL 70% ethanol at -20°C, dried, and dissolved in TE buffer . RNase enzyme (50 μg/mL) was added and incubated at 37°C for 1 hour. For purification, ethanol precipitation was done by adding potassium acetate (5.0 M) with two volumes of isopropanol at -20°C, mixed well 1-2 min by shaking, and centrifuged at 12,000 rpm (4°C) for 10 min. The DNA was precipitated and washed twice by adding 1 mL 70% ethanol at -20°C. The DNA was pelleted by centrifuging at 10,000 rpm for 10 min, dried, and dissolved in 100 μl of TE buffer. The DNA solution was measured to check the concentration and quality with Nanodrop BioPhotometer . The quality of DNA extracted was also checked by running the electrophoresis  of DNA samples. DNA samples with ratio absorbance 260/280 of more than 1.8 were considered good to proceed for the next steps. DNA template was diluted to final concentration of 60 ng/μl. The DNAs were stored at -20°C until further use.DNA was extracted from young leaves following the modified method of Zheng et al. . Young lOut of 100 ISSR primers, 11 sets of primers  were cho E. elatior DNA for reproducible amplification of 57 accessions. Only six primers  were able to show amplification on 57 accessions for SSR analysis , forward and reverse primers, DNA template, and nuclease-free water. The total amplification cycle was performed in a thermocycler programmed to start at 94°C for 5 min, 10 cycles at 94°C for 1 min, 58°C for 1 min (with a decrease of 1°C per cycle), and 72°C for 1 min plus 30 cycles at 94°C for 40 s, 48°C for 40 s, and 72°C for 1 min, as well as final extension at 72°C for 10 min. The amplification products were separated on Fragment Analyzer and evaluated using the software package ProSize 2.0 . The amplified bands were scored according to the size of DNA ladder (1kb Plus). Each band fragment size was recorded in Microsoft Excel for analysis.A total of 21 microsatellite primers developed by Goncalves  were inianalysis . The rem E. elatior was examined by assessing the marker informativeness through the bands scoring. Primer banding characteristics such as number of total bands (TB), number of polymorphic bands (PB), and percentage of polymorphic bands (PPB) were obtained. In order to analyze the suitability of marker for genetic profile evaluation, the performance of ISSR markers used was measured using three parameters: polymorphic information content (PIC), marker index (MI), and resolving power (RP). The PIC value for each primer was calculated as described by Roldan-Ruiz et al. [i = 2fi (1-fi), where PICi is the polymorphic information content of the locus i, fi is the frequency of the amplified allele, and 1-fi is the frequency of nonamplified allele. The frequency was calculated as the proportion between the number of amplified alleles at each locus and the total number of accessions. The PIC of each primer was calculated using the average PIC value from all loci of each primer. Marker index for each primer was calculated as product of polymorphic information content and effective multiplex ratio according to Varshney et al. [ n x β, where n is the average number of alleles amplified by accession to a specific system marker (multiplex ratio) and β is estimated after considering the number of polymorphic loci (PB) and nonpolymorphic loci (MB); β = PB/ (PB+MB). Resolving power is the ability of a primer to distinguish genotypes, which was calculated as RP = ∑Ib, where Ib represents the informative bands [i∣), where pi is the ratio of accessions comprising the ith band.Primarily, the potential of the marker for estimating genetic variability ofz et al. ; PICi = y et al. ; MI = PIve bands . The Ib  I = -∑pi ln pi, where pi is the allelic frequency of the ith allele in question for the specific accession; (2) Nei's genetic diversity (h) according to Nei [ h = 1 - ∑pi2, where pi is the frequency of the ith allele at the locus. Shannon's information index and Nei's gene diversity with other genetic diversity parameters such as the observed number of alleles per locus (na) and the effective number of alleles per locus (ne) were calculated with the aid of the POPGENE software version 1.32 [The genotype and allelic frequency data were used to compute the genetic diversity indices: (1) Shannon's information index (I) by Shannon and Weaver ; I = -∑pg to Nei ; h = 1 -ion 1.32 .a), number of effective alleles per locus (Ne) = 1/(p2 +q2), Shannon's information index (SI) = -1(p Ln(p) + q Ln(q)), the expected heterozygosity (He) = 2pq, the unbiased expected heterozygosity (UHe) = (2N/(2N-1)) He, and percentage of polymorphic loci (%P).GenAIEx 6.5 software  was utilThe binary data matrix was converted into genetic similarity coefficient between pairs of accessions using Dice coefficient by NTSYS-pc version 2.10 . The disGenetic diversity was evaluated using POWERMARKER Ver. 3.25 . The gen E. elatior accessions. The ISSR effective multiplex ratio (EMR) may be influenced by the fraction of polymorphic loci. The highest EMR (28.73) was detected with the primer UBC888 and the lowest was shown by the primer UBC830 (11.88), with a mean EMR of 15.19 per primer. General usefulness of the system markers used was determined by the calculation of marker index (MI) for each ISSR primer. The highest MI is shown by the primer UBC888 (14.35) and the lowest in the primer UBC830 (3.83) with a mean MI of 5.86 per primer. The resolving power (RP) is the ability of a primer to differentiate between genotypes. The average RP was 8.72 per ISSR primer. The highest RP value was detected with the primer UBC885 (12.72) and the lowest with the primer UBC811 (5.51). Primer UBC817 showed the highest number of effective alleles per locus (1.54) and the lowest alleles were observed in UBC811 with the value of 1.36 , effective multiplex ratio EMR, marker index (MI), and resolving power (RP) . High PI of 1.36 . Nei's ie) showed that Pahang population possessed greater level of variability with value of 0.20 as compared to other populations which ranged from 0.10 to 0.20. Shannon's information index among populations ranged from 0.14 to 0.31 with the highest value observed in the Pahang population. The pairwise population matrix of Nei's genetic distance of seven states was estimated  to 0.79% (Terengganu) with average of 0.52% . Geneticstimated . The maxThe genetic relationship of 57 torch ginger accessions was obtained from the scoring data using Dice similarity coefficient. Cluster analysis was conducted to group genotypes into a dendrogram. The dendrogram was constructed using Dice similarity coefficient. The 57 accessions were grouped into seven major clusters at a coefficient value of 0.47  and the The PCA analysis was performed to determine the dissimilarity of the accession and to verify the clustering pattern from the dendrogram. Based on PCA analysis, 57 accessions were also grouped into seven groups as shown in the two-dimensional (2D) plots . The resSix primers were chosen based on their ability to generate polymorphic and scorable amplification products. High polymorphism was observed in all the six amplified loci, Eela2, Eela4, Eela5, Eela17, Eela18, and Eela21. A total of 363 alleles from six SSR markers were distinguished across all 57 accessions. The number of alleles per primer pair (locus) ranged from 54 (Eela2 and Eela4) to 70 for Eela17 with an average of 60.5 . PIC valThe genetic distance between torch ginger accessions is displayed in Similarity matrices of all the 57 accessions were generated using NTSYS-pc version 2.10. The allelic diversity data was used to produce a dendrogram to explain the genetic relationships among the accessions . All genA principal coordinate analysis was presented as a complementary idea of the relationships among torch ginger accessions . The resThe values of Nei's genetic distance among seven states based on ISSR markers were low compared to SSR markers . HoweverThe evaluation of genetic diversity is crucial for the effective management and conservation of available genetic variability. The discovery of genetic dissimilarities and the interpretation of genetic associations among genotypes are very important for species protection and the sustainable use of plant genetic resources . MoleculIn the most recent years, many researches revealed that PCR-based techniques (SSR and ISSR) are effective to study the relationship or diversity between different species. Predominantly, they have been used to study the similarity between different varieties of ginger. In the present study, both ISSR and SSR markers were effective to characterize and differentiate between the accessions of torch ginger. They were capable of detecting the polymorphic and monomorphic alleles of accessions. Moderate-to-high level of genetic diversity among the torch ginger accessions was detected by ISSR and SSR markers. et al. [ et al. [ et al. [In ISSR, all screened primers resulted in 11% polymorphism. These primers were dinucleotide repeats and this is in line with earlier report which discovered high polymorphic potential of dinucleotide  through  et al.  and Pand[ et al. , 44 for [ et al.  who deteThe use of ISSR primers is considered highly informative with the PIC value more than 0.30 . However et al. [ Curcuma varieties. Besides that, the range of Nei's gene diversity and its average  of Shannon's information index  was comp et al.  for Curcge 0.26;  also is   et al.  who foun[ et al.  who disce) values, population from Kelantan and Melaka showed a slightly lower genetic diversity. Meanwhile, three populations, namely, Pahang (0.31), Terengganu (0.30), and Perak (0.30), presented the highest genetic heterogeneity through Shannon's information index  and  populations in Peninsular Malaysia. However, this result contradicts the report by Noroozisharaf et al. [ Primula and Panahi and Neghab [Furthermore, using the ISSR marker, the accessions could be broadly grouped into seven clusters (I-VII) and one of the major clusters (I) was further classed into smaller subclusters . The acc et al.  to lembaf et al.  on Primud Neghab  on saffld Neghab . et al. [SSR primers such as Eela17, Eela18, and Eela21 showed polymorphism in all accessions studied with heterozygosity values above 70%  . Therefo et al. . Since gNei's genetic distance among seven states was also estimated using SSR markers to determine the level of population difference among torch ginger accessions. Nei's pairwise genetic distance among torch ginger accessions showed variable genetic distances . The pop et al. [ et al. [ et al. [ et al. [Besides that, SSR markers through UPGMA cluster analysis give a better explanation on the association among 57 torch ginger accessions. All tested accessions were grouped into 11 main clusters based on the dendrogram. The coefficient of similarity index showed most of the accessions shared 0 to 0.8 index value, indicating that the accessions were highly different in their genetic characteristics. Two accessions (KAN014 and KAN015) showed a very close relationship in cluster II, suggesting that these two accessions were highly similar in their genetic characteristics. This is due to the fact that they were collected from the same district (Terengganu). However, most of the accessions from seven states were clustered separately and part of those was often mixed with others from different state. The results emphasized that genetic diversity among torch ginger accessions is not influenced by their geographical origin. Besides that, same state could be different in terms of environmental characteristic within it. On the other hand, this indicated little or no location specificity among the torch ginger accessions. This finding also is in agreement with Distefano et al. , Liang e[ et al.  who stud[ et al.  suggeste et al. [Consequently, this germplasm would enhance the local gene pool and offer additional information for crop improvement programs in the future . Pradhan et al.  opined t E. elatior accessions using molecular markers in Malaysia. Genetic diversity revealed the existence of a considerable degree of genetic variation among accessions of torch ginger as discovered by ISSR and SSR markers. The detection of high polymorphism and resolving power of marker system used in this study are of substantial consequence. The amplification of large number of polymorphic bands suggested that the primer sets used in this study could be of significance for the measurement of genetic diversity in torch ginger accessions. The combination of different molecular markers offered reliable and convincing information about the genetic diversity of torch ginger germplasm. Based on data generated from the two molecular markers, SSR marker was more informative compared to ISSR in terms of gene diversity, PIC values, and heterozygosity. SSR also revealed high ability in evaluating diversity levels, genetic structure, and relationships of torch ginger due to their codominance and rich allelic diversity. Generally, this study provides an initial scientific basis of data for torch ginger improvement and conservation programs in the future.This is the first report on the assessment of genetic variation in


Despite rapid expansion of public bicycle share programs (PBSP), there are limited evaluations of the population-level impacts of these programs on cycling, leaving uncertainty as to whether these programs lead to net health gains at a population level or attract those that already cycle and are sufficiently physically active. Our objective was to determine whether the implementation of PBSPs increased population-level cycling in cities across the US and Canada.We conducted repeat cross-sectional surveys with 23,901 residents in cities with newly implemented PBSPs , existing PBSPs  and no PBSPs  at three time points . We used a triple difference in differences analysis to assess whether there were increases in cycling over time amongst those living in closer proximity (< 500 m) to bicycle share docking stations in cities with newly implemented and existing PBSPs, relative to those in cities with no PBSPs.Living in closer proximity to bicycle share predicted increases in cycling over time for those living in cities with newly implemented PBSPs at 2-year follow-up. No change was seen over time for those living in closer proximity to bicycle share in cities with existing PBSPs relative to those in cities with no PBSP.These findings indicate that PBSPs are associated with increases in population-level cycling for those who live near to a docking station in the second year of program implementation. Public bicycle share programs (PBSP) make bicycles available for rent throughout a city. As of 2014, there were over 855 public bicycle share programs operating in cities around the world . These pDespite rapid expansion of PBSPs, there are limited evaluations of the population-level impacts of these programs on cycling, leaving uncertainty as to whether these programs lead to net increases in cycling at a population level or attract those that already cycle and are sufficiently physically active . The eviMixed results are reported from two pre-post evaluations of PBSPs in Canada. In Montreal, a study showed a greater likelihood of cycling in the second season of program operation for those who lived near a bicycle share docking station compared to those who did not . A similEvidence across multiple cities and contexts is needed to better understand the impacts of PBSPs on health , 6. It iIn the current study, we used data from 8 major North American cities to estimate the impact of PBSPs on population-level cycling from 2012 to 2014 as part of the International Bikeshare Impacts on Cycling and Collisions Study (IBICCS) . Cities n = 23,901). We used online repeated cross-sectional surveys at three time points  to collect data on cycling behaviour, sociodemographic characteristics, self-reported health, and residential location. Fall data collection is consistent with Household Travel Behaviour Surveys and is timed to ensure participants were engaged in regular bicycle commuting behaviour. The Centre de Recherche du Centre Hospitalier de l’Université de Montréal and Toronto Public Health granted ethics approval for all IBICCS study procedures and survey respondents provided informed consent.IBICCS is a quasi-experimental non-equivalent groups study designed to evaluate the health impacts of PBSPs. The study protocol is published elsewhere . In brieThe IBICCS sample included data from residents in 8 cities, with varying population sizes and land areas Table . The proThe outcome was a binary measure of self-reported cycling for any purpose (transportation or leisure) for at least 10 min in the past week or not. We derived the binary measure from the long version of the validated International Physical Activity Questionnaire (IPAQ) transport physical activity module . Respondn = 43 stations) and only 48 participants were assigned as exposed when using 500 m buffers, which was not sufficient for our modelling approach. There were three city types: newly implemented, already existing, and no PBSP. Newly implemented cities had a PBSP implemented mid-way through the study period, already existing PBSP cities had a bicycle share program in place for the duration of the study period, and control cities did not have a PBSP during the study period.The primary independent variables used in the difference in differences analysis were time , exposure to the PBSP service area , and city type . For respondents in cities with PBSPs, we assigned exposure to the PBSP service area based on whether they had one or more bicycle share docking stations within a 500 m road network buffer of their home. We selected a distance of 500 m because it represents a reasonable distance to walk to a docking station and has been used in previous studies to define service areas , 8, 16. We identified covariates a priori based on socio-demographic characteristics and environmental factors that have been used in previous evaluations of PBSPs , 8 and tWe used census data to apply post-stratification weights on age and gender to adjust the sample to better represent the general population. We trimmed survey weights at 0.2 and 10 .To assess if PBSP had an impact on cycling, we used a triple difference in differences analysis , 20. Then = 284) or were missing socio-demographic data (n = 594). Our final sample included 23,023 respondents , resulting in a weighted population of 22,164.The pooled sample included 23,901 respondents with 7829 respondents in 2012, 7979 in 2013, and 8093 in 2014. Cooperation rates, which is the proportion of eligible respondents who agree to participate, were 12, 9, and 4%, respectively. Of the 23,901 respondents, 878 were excluded because they did not provide a home postal code or zip code  or a city that had an existing PBSP . Exposure to PBSP did vary by year, with fewer respondents exposed in 2013  compared to 2012 (42.9%) and 2014 (39.5%) (Table Approximately two-thirds of the sample were from a city that implemented PBSP during the study period (%) Table .Weighted logistic regression models examining the odds of cycling over time for exposed and unexposed respondents in cities with PBSP and control cities are shown in Table In the unadjusted model, there was over two-fold greater odds of past-week cycling for those living near a docking station in cities with newly implemented PBSPs at the first follow-up  and second follow-up , relative to those in cities with no PBSP. The effect size was attenuated when adjusting for socio-demographic factors and Walk Score in residential neighbourhood but remained significant at the second follow-up point . There was no differential change in cycling over time for those living near a docking station in cities that had an existing PBSP, relative to those in cities with no PBSP. The results of the sensitivity analysis excluding Detroit  compared to women in cities with no PBSP. This association was also in the positive direction in the adjusted model, but the confidence interval crossed 1 . This trend was not sustained into the second year for women living near to a docking station. Conversely, the odds of past-week cycling for men living nearer to a docking station at the first follow-up point was not different relative to men in cities with no PBSP, but increased at the second follow-up. The odds were two times greater for men living nearer to a docking station in the unadjusted model  relative to the reference group, but when adjusting for covariates, the confidence interval crossed 1 .Figure This large-scale multi-city study examined whether PBSP increased population-level cycling in cities with newly implemented and existing PBSPs. Overall, we found that PBSPs were associated with an increase in self-reported cycling for those living near to a docking station in cities with newly implemented PBSPs at 2-year follow-up relative to those in cities no PBSP. On average, residents living within 500 m of a bicycle share docking station had 1.8 times the odds of reporting past-week cycling at 2-year follow up, compared to residents living in comparable areas in cities without PBSPs. Examining the effects for women and men separately showed that PBSPs may be associated with a greater likelihood of cycling for women living near to a docking station in cities with newly implemented PBSBs 1-year into program implementation and for men 2-years into program implementation.The observed increase in cycling could be from both the use of PBSP bicycles and personal bicycles. In these samples, the proportion that had ever used a PBSP bicycle increased from 9.0% in 2012 to 14.3% in 2014. PBSP can make cycling more convenient by allowing for one-way trips by bicycle, eliminating the concern of bicycle theft, facilitating the first and last miles of transportation trips, and by providing access to bicycles for those who do not own their own bicycle , 21, 22.We hypothesized that the greatest increases in cycling would be observed in cities with newly implemented PBSPs, but we also anticipated that there would be increases in cycling in cities with existing PBSPs relative to cities with no PBSPs. It may be that the gains in population cycling level off after the first few years of a PBSP’s implementation. For instance, ridership of BIXI bicycles in Montreal increased from when it was first implemented in 2009 to 2011 but stabilized between 2012 and 2014 , which cAn important contribution of the current analysis is that we investigated the impact of PBSP on cycling for men and women separately. In countries with low cycling rates, there remains a significant gender gap in cycling , 26, 27.This study surveyed almost 24,000 people in 8 cities across 3 time-points to estimate the impact of a population-wide intervention on cycling. We focus on population-level cycling as an outcome. This is a common goal of bike share programs [This study has limitations common to natural experiment studies including bias from residual confounding, selection bias, exposure assignment, the unpredictable nature of real-world interventions, and challenges of multi-country studies . There cFinally, the measure of cycling that we used for our outcome was a binary measure of whether the respondent self-reported cycling in the past week. Future studies may wish to include a measure for frequency and duration of cycling to determine whether PSBPs increase the volume of cycling at a population level.Using a large-scale quasi-experimental multi-city study, we observed that PBSPs were associated with increases in population-level cycling for those who live near to a docking station in the second year of program implementation in cities with newly implemented PBSPs. This finding suggests that PBSPs can contribute to increases in cycling at a population-level.


Artemia urmiana, has progressively desiccated over the last two decades, resulting in a loss of 80% of its surface area and producing thousands of hectares of arid salty land. This ecological crisis has seriously affected the lake’s native biodiversity. Artemia urmiana has lost more than 90% of its population during the decade from 1994 (rainy period) to 2004 (drought period) due to salinity increasing to saturation levels (∼300 g/l). We studied the influence of this ecological crisis on the genetic diversity of A. urmiana in Urmia Lake, based on one cyst collections in 1994 and 2004. AMOVA analysis on ISSR data demonstrated a 21% genetic variation and there was a 5.5% reduction of polymorphic loci between samples. PCoA showed that 77.42% and 68.75% of specimens clustered separately in 1994 and 2004, respectively. Our analyses of four marker genes revealed different genetic diversity patterns with a decrease of diversity at ITS1 and an increase for +/K+ ATPaseNa. There was no notable difference in genetic variation detected for COI and 16S genes between the two periods. However, they represented distinctly different haplotypes. ITS1 and COI followed a population expansion model, whereas +/K+ ATPaseNa and 16S were under demographic equilibrium without selective pressure in the 1994 samples. Neutrality tests confirmed the excess of rare historical and recent mutations present in COI and ITS1 in both samples. It is evident that a short-term ecological disturbance has impacted the genetic diversity and structure of A. urmiana.Urmia Lake, the largest natural habitat of the brine shrimp  Its historical water surface area has ranged from 4,750 to 6,100 kmectively . It is aively  via a paved road . AdditioArtemia cysts and biomass in 1994–1995, Artemia urmiana cyst production in the upper 50 cm of the lake’s water column ranged from 4,200 to 4,500 tonnes/year (dry weight)   over the past six decades (from 1955 to 2015). Based on the first resource assessment of  weight) . Analysi weight) . The wat weight)  Fig. 1)Artemia c300 g/l) . In the 300 g/l) . The lak300 g/l) . No livestuaries . Now Urmstuaries , at an estuaries .Triticum dicoccoides) in response to ecological change. A similar pattern was observed in slender oat (Avena barbata), followed by environmental variations (Betula pendula), which showed different genotypes in warm and cool years   .Artemia has lost more than 90% of its reproductive potential and population size, and reproduction has stopped in the main body of Urmia Lake . The samples were obtained from the upper 50 cm of the water column  were extracted following the Chelex® 100 Resin method . The embryos were crushed via a sterilized pipette tip, incubated for 2.5–3 h at 60 °C (tubes were shaken by vortex every 30 min) and eventually for 10 min at 80 °C. The tubes were centrifuged at 10,000 rpm for 1 min and the supernatant phase was directly used in the PCR reaction . The extA. urmiana samples collected in 1994 (31 specimens) and 2004 (32 specimens) was evaluated using inter-simple sequence repeats (ISSRs). ISSRs were amplified from genomic DNAs with two universal primers (GA)8T , 1 µl template DNA and 1 µl of primer. The PCRs were carried out separately using the following conditions: 94 °C denaturation for 1 min, 35 cycles of 46–48 °C annealing for 50 s and 72 °C extension for 2 min. The final cycle was followed by a 7-min extension at 72 °C (Nuclear genotype variation between s (GA)8T  and (AG))8T  was determined for each year and population genetic information was computed separately. Genetic relationships among ISSR genotypes were established by principal coordinate analysis (PCoA) using GenAlex version 6.5 . The parNa+/K+ATPase and ITS1) and two mitochondrial markers (COI and 16S) were amplified. PCRs were carried out in a total volume of 15 µl containing 6 µl of ddH2O, 7.5 µl Taq polymerase , 0.3 µl template DNA and 0.6 µl of each primer. Sequencing was performed by TsingKe CO. (China).Two fragments of nuclear markers , the complete sequence of internal transcribed spacer 1 (ITS1) and a partial sequence of the 5.8S ribosomal RNA (5.8S) genes, was PCR-amplified using the primers 18d-5′/R58  gene was performed using the invertebrate universal primers LCOI 490/HC02198  was amplified using the primers 16S-SP/12S-SP  were computed using p-distance in MEGA ver. 6.00. To estimate the genealogical relationships among haplotypes for each gene, a maximum-parsimony haplotype network was inferred using the software TCS version 1.21 , average number of nucleotide differences (K) and neutrality tests  were computed using DnaSP v.5.10 program  was calculated using Arlequin v.3.5  sites (S), total number of mutations (M), number of haplotypes (H), haplotype (gene) diversity (Hd), differentiation of haplotype frequencies (DHF), nucleotide diversity ( program . Fixatioin v.3.5 .Na+/K+ATPase α-1 subunit with the exception of a single specimen collected in 1994 which showed a heterozygous pattern (T-G). Our phylogenetic trees (ML and BI) for COI showed that all analyzed specimens clustered with the reference sequence of A. urmiana (HM998991)  in the last valine codon using the M998991) . Only onA. urmiana for all observed ISSRs loci between 1994 (rainy period) and 2004 (drought period) is listed in A. urmiana  for the 1994 and 2004 samples (The  samples . Among tITS1 sequences of 60 specimens showed 50 haplotypes (H1–H50). There were three groups of haplotypes  which were shared by 13.4% (8/60), 1.6% (1/60) and 1.6% (1/60) of specimens, respectively. H1 included two specimens from 1994 and six from 2004. With the exception of four haplotypes  that shared genotypes between sampling years, other haplotypes were only found in one sampling year (The ing year .COI sequences for 60 specimens contained 43 haplotypes (H1–H43). Haplotype 1 was the major haplotype that was found in ten (16.7%) specimens. H12 and H23 were found in two and four specimens from 2004, respectively. H31 and H43 were shared by two specimens belonging to the two sampling years, while all other haplotypes came from a single sampling year , which showed high variation in comparison with the other markers. The central haplotype (H1) covered only two specimens (3.5%) including a single specimen from each year. With the exception of H39 that was shared by two specimens from 2004, other haplotypes were unique to a single specimen  demonstrated lower values in 2004 (drought period). The mitochondrial COI marker revealed a reduction of polymorphic sites, total number of mutations and number of haplotypes in 2004. In contrast, the number of polymorphic sites, total number of mutations and number of haplotypes of the 16S marker showed lower values in 1994. Similar to COI there was no notable dissimilarity for the haplotype diversity, nucleotide diversity and average number of nucleotide differences in the 16S marker between the two periods. Haplotype frequencies of all mitochondrial and nuclear markers represented non-significant difference between rainy and drought periods. Though there was no significant difference in the amount of genetic variation of COI and 16S markers between rainy and drought periods, each marker presented different distinct of haplotypes. 16S presented higher expected heterozygosity in 1994 while ITS1 and COI showed higher values in 2004. The values of the pairwise genetic differentiation index (FST) were not significant. The minimum and maximum between-group distances were detected in Na+/K+ATPase (0.001) and 16S (0.011), respectively. Neutrality tests yielded negative values with different significant and non-significant levels.Genetic indices and allele frequency estimated for the aforementioned four markers are presented in Daphnia populations. The impact of salinity changes on genetic variation has been considered less frequently in aquatic organisms  was significantly reduced after 10 years of an increase of experimentally-driven intra-annual precipitation variation. Stipiturus mallee by reducing population size. Similar studies in zooplankton species such as Artemia have not been done. Environmental instability directly affects the FST (genetic differentiation among populations) through its impact on immigration and genetic drift combined with population reduction . The smaller cysts and thicker chorion produced during the dry period were attributed to decreasing food availability and to an acclimation mechanism, respectively, to increase the survivorship of the diapausing embryo under ecological crisis  had lower mortality but higher RNA content than those from 2003 . Our ISSR fingerprint analysis on samples collected in 1994 and 2004 showed that each group had a single unique ISSR band. AMOVA analysis showed that 21% genetic variation occurred between the two periods; the drought period had lost 5.5% of polymorphic loci in comparison with the rainy period . In contrast, the genetic diversity of COI and 16S was not significantly different between the two periods. Additionally Na+/K+ATPase revealed a remarkable increase in variation in the drought period. These conflicting results might be attributed to the difference in the potential of gene variability that might be confirmed by further experimental evidence.Theoritically a decreasing population size in response to unfavorable ecological changes is expected to lead to a reduction of genetic diversity . But in D value for both examined periods in COI and ITS1 (D should be referred to the demographic expansion of these markers in both ecological periods with regard to developed haplotype networks of ITS1 and COI markers. Additionally, Fu and Li’s D* and Fu’s Fs tests showed a negative departure from the neutrality test. Given that Fu and Li’s D * test and Fu’s Fs test recognize an excess of rare historical mutations (COI and ITS1 during the rainy and drought periods. Consequently, the results of neutrality tests of Fu and Li’s D* and Fu’s Fs could explain the patterns of haplotype networks and population expansion of ITS1 and COI.Our study showed a negative and significant Tajima’s and ITS1 , which iand ITS1 . The negutations , and rarutations , respectNa+/K+ATPase and 16S markers. Neutrality tests resulted in a non-significant value for Na+/K+ATPase in the rainy period, which supported the demographic equilibrium. While significantly negative Tajima’s D, Fu and Li’s D* strongly supported a demographic expansion and an excess of rare historical mutations in the drought period. These results are consistent with the pattern of haplotype distributions developed during this period. In addition, the non-significant value of Fu’s Fs suggested the absence of recent mutations in Na+/K+ATPase in both periods.The major influence of short-term ecological disturbance was observed in the demographic history of 16S structure. Tajima’s D and Fu and Li’s D* were non-significant in the rainy period which could indicate 16S marker was at demographic equilibrium without selection in the rainy period. In contrast, a negative and significant neutrality value and expanded haplotype network indicated that 16S is involved in recent expansion in the drought period (Fs test suggested the excess of new mutations in the gene pool of 16S in both normal and drought periods.Another major alteration was observed in the t period . The negArtemia urmiana shows dissimilar responses to environmental changes. Consequently, changes in genetic diversity and the pathway of variation are controlled by interaction between ecological conditions and the ability of genes to vary. Artemia urmiana genetic structure, especially reducing genetic diversity, which ultimately could risk the survival of this crustacean.Overall, our results have demonstrated that ecological disturbance should be considered in hypotheses about effects of short-term environmental changes on genetic variation. The rapid genetic changes that we found has also been demonstrated in some other species of animals and plants experiencing environmental crises . This co10.7717/peerj.7190/supp-1Figure S1Click here for additional data file.10.7717/peerj.7190/supp-2Supplemental Information 1Click here for additional data file.10.7717/peerj.7190/supp-3Supplemental Information 2Click here for additional data file.10.7717/peerj.7190/supp-4Supplemental Information 3Click here for additional data file.10.7717/peerj.7190/supp-5Supplemental Information 4Click here for additional data file.


As genetic testing is becoming more widely commercially available for Parkinson's disease (PD) and may have implications regarding clinical outcomes for deep brain stimulation (DBS) and other therapies, we aimed to determine patient knowledge and attitudes towards genetic testing.  A sample of 88 PD subjects with bilateral STN-DBS completed a Genetic Attitudes Questionnaire (GAQ). Knowledge and attitudes towards genetic testing were assessed.  The mean percent of correct responses regarding genetic testing knowledge was 58.5%. Nearly 90% of subjects were unfamiliar with Genetic Information Nondiscrimination Act (GINA). The most important reasons subjects cited in deciding whether to undergo genetic testing included (1) to be a candidate for clinical trials if positive, (2) to learn that they do not carry a mutation, and (3) because a healthcare provider had recommended it. Individuals who influence decision-making include spouses and children. About 88% of subjects would share results with spouses, children, and siblings.  These results reveal that there is a major knowledge gap regarding genetic testing in PD and the implications of testing results on treatment, work, insurance, and privacy. Also, subjects would mainly seek genetic testing to participate in clinical trials, with spouses and children being the key stakeholders in decision-making. Approxin (PRKN) . In genen (PRKN) . GBA, a pulation . Series pulation .To our knowledge, genetic testing is not part of routine clinical care at the present time for PD as it does not influence clinical decision-making. This is true of our center and other specialty centers throughout the world . HoweverLRRK2 G2019S mutation carriers have greater improvement from DBS compared with nonmutation carriers [GBA mutation carriers with DBS have more significant cognitive impairment and reduced quality of life compared with nonmutation carriers with DBS. In fact, the effects of STN-DBS in GBA mutation carriers are currently being investigated in a prospective longitudinal clinical trial assessing cognitive, motor, and quality of life outcomes . There are also ongoing clinical trials aimed at using pharmacologic agents to alter the progression of GBA-associated PD, and similar trials will be starting for LRRK2-associated PD [As genotype-phenotype correlations become more clear, it is possible that genetic mutation status may soon play a role in clinical decision-making for treatments and interventions such as DBS . For inscarriers  have repiated PD . This isWith these observations and the growing interest in gene-DBS interactions and gene-based treatments, it is critical to understand PD patients' knowledge base regarding genetic testing and their expectations regarding how this genetic information may or may not impact their treatment. We assessed knowledge and attitudes towards genetic testing in a consecutive sample of PD subjects who had already undergone STN-DBS.Approval for the study was obtained from the Rush University Medical Center Institutional Review Board, and all patients signed informed consent for study participation. Consecutive PD patients with bilateral STN-DBS were recruited from the Movement Disorders clinic of Rush University Medical Center in Chicago, Illinois. The main inclusion criteria were as follows: (1) clinical diagnosis of idiopathic PD, (2) implantation with bilateral STN-DBS, (3) agreement to attempt completing a Genetic Attitudes Questionnaire (GAQ), and (4) English speaking to ensure comprehension of the GAQ. Patients were not given any specific information regarding genetic testing either before or after their surgery as the goal was to obtain their baseline level of knowledge and attitudes towards genetic testing. Furthermore, genetic testing is not part of routine clinical care of PD  at our cDemographic data including current age, sex, age at onset of PD symptoms, disease duration, family history of PD, and ethnicity were collected. The GAQ has been previously described , 13 and One hundred subjects were enrolled in the study, and GAQ data were available for eighty-eight subjects (88%). The remaining 12 who were recruited but not included in the final analysis were lost to follow-up for completion of the GAQ despite multiple attempts to make contact via telephone. Demographic characteristics for the remaining 88 subjects with complete data are summarized in For the entire group, the mean percent of correct responses regarding genetic testing knowledge was 58.5%. Approximately 64% of subjects were aware that genes have been identified that confer a higher risk of developing PD . The majOver 50% of subjects listed the following factors as very important factors regarding their desire for genetic testing: “to be a candidate for clinical trials if positive,” “to learn that I do not carry the mutation,” “my healthcare provider thought I should have genetic testing,” “to psychologically prepare myself for lies ahead if I am a mutation carrier,” and “I am worried about losing my disability insurance” . When suOver 50% of subjects noted that the following individuals were influential in their decision-making: spouse (76%) and children (47%) . Over 88Genetic testing provides the opportunity to correlate individual genotype with clinical outcome of therapies such as DBS . Before 23andme” [GBA gene. Mutation in GBA is the most common genetic risk factor for PD. Explaining that heterozygous mutations predispose an individual to an increased risk of PD and homozygous mutations cause yet another disease, Gaucher's disease [GBA and the implications of testing for this gene will be particularly important for patients and families to understand as genetic testing becomes more widely available and more of these mutation carriers are identified.The mean percent of correct responses regarding genetic testing knowledge was 58.5%, which is comparable to percent of correct genetic testing knowledge questions regarding breast cancer amongst Caucasians . Approxi23andme”  that do  disease , is a laWe acknowledge that the data provided here are from a single medical center. However, we posit that the knowledge gap seen in our patients may be reflective of the general PD population. This is likely given that there are currently no standardized set of tools that are used systematically by clinicians to educate patients regarding genetic testing in PD. Patients typically rely on web-based resources, patients' associations, and their clinicians to provide them with information regarding PD genetics, but these resources certainly vary in their availability, quality, and comprehensiveness. Therefore, PD patients and their families would likely benefit from development of educational tools and resources regarding genetic testing.The most important reason subjects cited in deciding whether to undergo genetic testing included being a candidate for trials if they carry a mutation. Gupte et al.  also repApproximately 52% of subjects would opt for genetic testing if it could predict side effects of a treatment and 58% of subjects would opt for genetic testing if it could predict treatment benefit. We had anticipated that the vast majority of subjects would have wanted genetic testing if it could help maximize their outcomes. Limitations for this study include the fact that all subjects in our study already had longstanding DBS implantation which may bias our sample as these subjects may have been satisfied with their current level of functionality, so they may believe that genetic testing would not add more to their care. Indeed, satisfaction with DBS is high in patients with greater than 5 years of therapy  though tWe found that individuals who influence decision-making include spouses and children, and about 88% of subjects would share results with relatives, particularly with spouses, children, and siblings. In our study, we focused on knowledge and attitudes towards genetic testing in patients with PD, but it is also important to engage spouses, children, family members, and other key stakeholders in decision-making regarding genetic testing.PD patients and their families will likely benefit from development of educational tools and resources regarding genetic testing, given the clear knowledge gap identified in this study as results may have significant implications for work, insurance, and privacy. This will be particularly important if genetic testing becomes incorporated into the treatment algorithm for therapies such as DBS. Also, it is important for clinicians to engage the key stakeholders in decisions regarding genetic testing and the implications of such testing. There are efforts to make genetic testing more easily accessible to patients through organizations, such as the Michael J. Fox Foundation, since patients may qualify for targeted treatments in the form of clinical trials. It will be particularly important to counsel patients regarding the implications and meaning of genetic testing results in such cases as such gene-based trials become increasingly common in PD.TOR1A mutations typically respond better to pallidal DBS than individuals with THAP1 mutations or undetermined genetic causes [Lastly, the issue of genotype-phenotype correlations regarding DBS outcomes extends to other movement disorders as well, particularly dystonia. For instance, studies have suggested that individuals with c causes . As genoAs the field of Parkinson's disease and movement disorder genetics moves towards a precision-medicine approach to treatment of the disease, patients and key stakeholders require education regarding the implications of genetic testing in order to make informed healthcare decisions.