Phaseolus reference map. All the lines belonged to commercial seed type classes that are widely grown in the USA and include both dry bean and snap beans for the fresh and processing markets. Through population structure, principal components analyses, cluster analysis, and discriminant analysis of principal components (DAPC), Andean and Mesoamerican genotypes as well as most American commercial type classes could be distinguished. The genetic relationship among the commercial cultivars revealed by the SSR markers was generally in agreement with known pedigree data. The Mesoamerican cultivars were separated into three major groups—black, small white, and navy accessions clustered together in a distinct group, while great northern and pinto clustered in another group, showing mixed origin. The Andean cultivars were distributed in two different groups. The kidney market classes formed a single group, while the green bean accessions were distributed between the Andean and Mesoamerican groups, showing inter-gene pool genetic admixture. For a subset of 24 SSR markers, we compared and contrasted the genetic diversity of the commercial cultivars with those of wild and domesticated landrace accessions of common bean. An overall reduction in genetic diversity was observed in both gene pools, Andean and Mesoamerican, from wild to landraces to advanced cultivars. The limited diversity in the commercial cultivars suggests that an important goal of bean breeding programs should be to broaden the cultivated gene pool, particularly the genetic diversity of specific commercial classes, using the genetic variability present in common bean landraces.Progress in common bean breeding requires the exploitation of genetic variation among market classes, races and gene pools. The present study was conducted to determine the amount of genetic variation and the degree of relatedness among 192 selected common bean advanced cultivars using 58 simple-sequence-repeat markers (SSR) evenly distributed along the 11 linkage groups of the  Phaseolus vulgaris L.) is a crop plant cultivated worldwide and one of the most important grain legumes in terms of total yield and cultivated area (Food and Agriculture Organization of the United Nations (FAO) http://www.fao.org). It is grown for its green pods and immature and/or dry seeds and is a primary source of protein in the human diet in both developing and developed countries. According to FAO data (http://www.fao.org/faostat/en/#home), common bean world production in 2016 was estimated at 27 million metric t for dry bean production, and at 23.5 million t for green bean. In the United States, dry bean is grown on about 630,743 ha with a total annual production of 1,269,916 t and an average yield of 2.01 t ha-1, while green bean is grown on about 11,330 ha with a total annual production of 41,640 t and an average yield of 3.67 t ha-1 (http://www.fao.org/faostat/en/#home).Common bean  or medium (25–40 g 100 seed weight-1) seeds, with phaseolin patterns as either the “S” or “B” types; these characteristics are different from those of the of the large seeds (>40 g 100 seed weight-1) of the Andean gene pool with “T”, “C”, “H” and “A” phaseolin types , which is also the source of the Mesoamerican genome reference sequence , in whicSeeds were grown in a greenhouse at the University of California in Davis. After 15 days, the primary leaves were harvested and stored overnight at– 80°C.–1 for polymerase chain reaction (PCR) amplification. The amount of genetic diversity in the 192 samples was then assessed with molecular marker analysis. A set of 58 SSR markers were selected based on their wide distribution over the Phaseolus genome and their high polymorphism information content (PIC) values [The frozen leaf tissue samples were lyophilized for around 48 hours using VirTis Sentry 2.0. and ground to a fine powder. Genomic DNA was then extracted from the young leaf tissue using the Qiagen DNeasy Plant Kit , and following the protocols provided by the manufacturer. DNA was quantified with a DyNA Quant 200 fluorometer  and diluted to a concentration of approximately 10 ng μL) values –29. MoreTGTAAAACGACGGCCAGTATGC) was added to the 5’ end of each forward SSR primers. The fluorescent dyes, 6-FAM, PET, and VIC, were attached to the 5’ end of the complementary (TGTAAAACGACGGCCAGT) M-13 universal primer sequence. For amplification, PCR reaction consisted of about 30 ng of genomic DNA, 200 μM dNTP (New England Biolabs), 0.04 μM forward primer with M-13 universal sequence tail, 0.16 μM reverse primer, 0.16 μM M-13 labeled fluorescent dye (Sigma Life Science), one unit of standard ThermoPol (Taq) reaction buffer with 2 mM MgSO4, and one unit of Taq polymerase (New England Biolabs). The PCR program consisted of 5 minutes at 94°C, 30 cycles of 30 seconds at 94°C, 45 seconds at 56°C, and 45 seconds at 72°C followed by 8 cycles of 30 seconds at 94°C, 45 seconds at 53°C, and 45 seconds at 72°C with a 10 minutes final extension period at 72°C. After dilution to a standard concentration, the amplified DNA samples were separated and sized in multiplex fashion depending on their expected size variation and were analyzed on Applied Biosystems 3730 DNA automatic analyzers.The SSRs analysis was conducted using an economical fluorescent tagging method described by Schuelke  in whichhttps://doi.org/10.25338/B8G30V.Genotypes of markers were determined using the GeneMarker program . When markers produced more than one peak, the peaks with clearly separated size ranges were scored independently as a different locus. This was noticed for three of the SSRs . For each SSR locus and for the whole set of accessions, the total number of alleles observed were recorded and reported in a data set. Missing data were recorded when there was no detectable peak in the target size region for the marker. The data set was converted into Powermarker  and STRUo), the observed (Ho) and the expected (He) heterozygosity values and PIC values were calculated across the total sample using Powermarker software version 3.25 [a), the mean effective number of alleles per locus (Ne), the total number of private alleles (Npa), the Shannon's information index (I), the observed (Ho) and the expected (He) heterozygosity were also calculated for each different market classes as defined according to the pedigree data using the GenAlEx 6 software [Based on SSRs profiles defined among the 192 studied advanced cultivars, the total number of observed alleles (Nion 3.25 . The totsoftware . As the software ) was comsoftware , a methosoftware .The genetic relationship among all accessions was first analyzed in two dimensions by principal coordinates analysis based on an individual-by-individual (N x N) genetic distance matrix using the program GenAlEx 6  and plothttp://taylor0.biology.ucla.edu/struct_harvest/, was used to calculate the Delta K statistical test together with the likelihoods (posterior probabilities) of each K. To assign accessions to each different population, results from simulations with the highest likelihood among each K simulations were chosen. Potential hybrids accessions were identified if the population membership coefficient was less than 0.7. All population memberships for K = 2, K = 3, K = 5 and K = 8 are reported in Using the model-based (Bayesian clustering) method implemented in STRUCTURE 2.3.1 software , the degGenetic distance between accessions were calculated using the Chord distance . This meFst measurements were calculated according to Weir and Cockerham [To estimate the divergence between the different population, pairwise ockerham  using Geockerham . Analysiockerham . AMOVA aockerham ). Two leTo further confirm cluster analysis and genetic structure inferred from Bayesian clustering, a discriminant analysis of principal components (DAPC), using the R package ADEGENET v2.0.0  was conde) and alleles (ΔRs) was calculated according to Vigouroux et al. [http://www.statistixl.com).In addition, we used a dataset published in Kwak and Gepts  in orderx et al. . WilcoxoIn this study, 58 SSR markers distributed on the 11 genetic linkage groups were genotyped in 192 common bean advanced cultivars. Markers BMd-1, PVag004, and BM188 produced two very clear peaks in the expected sizes over all the samples. Therefore, they were scored as a multi-locus marker, BMd-1a, PVag004a, and BM188a and BMd-1b, PVag004b, and BM188b. According to Blair et al. , Yu et ao = 22) while the next highest allele numbers were found for BM200 (No = 20) and GATS91 (No = 18), respectively. All of them were genomic SSR markers . In contrast, the gene-based SSR markers were less polymorphic; a total of 10 markers produced only two alleles in the gene-based markers while only 3 did so in the case of the genomic markers. Hence, the average number of alleles per marker was higher for the genomic SSR (No = 7.00) when compared with the gene-based SSR (No = 3.57).The total number of alleles identified in the entire study was 343 with an average of 5.6 alleles per locus with all the SSR markers analyzed being polymorphic having from two to 22 alleles . The mare) of individual markers ranged from 0.046 to 0.860 (mean 0.453) for gene-based SSR and from 0.021 to 0.897 (mean 0.616) for genomic markers. The SSR markers that presented the highest expected heterozygosity (higher than 0.800) were BM53, GATS91, BM200, PV-at007, and BM187 located on linkage groups 11, 02, 01, 09, and 06 respectively. The SSR markers, which showed the lowest expected heterozygosity (lower than 0.300), were PVBR139, BMd26, BMd53, PV-atcc002, PV-atcc003, and BMd44, located on linkage groups 02, 04, 05, 07, 07, and 08, respectively (o) was low, ranging from 0.000 to 0.099 and averaging 0.006 across all markers. The markers with higher observed heterozygosity were PV-at007 and BMd20 (gene-based) and PVBR107 and BM188b (genomic) (Expected heterozygosity (Hectively . Observegenomic) . The obsThe PIC values, a reflection of allele diversity and frequency, were 0.496 for all the microsatellites, and ranged from a low 0.020 (BMd44) to a high 0.888 (BM53) .a) for each commercial market class varied between 1.28  and 3.30 (pinto). Dark red kidney, light red kidney, green bean, navy, black and great northern showed a very similar total number of alleles, while white kidney and small white showed a lower total number of alleles compare to the other market classes . Similarly, the mean effective number of alleles per locus was lower for white kidney and small white  compared to the other market classes, and was higher for green bean (Ne = 1.81) . After size standardization, the sample of green beans still had the most alleles per locus (Rs = 1.35). The number of private alleles was computed considering all the commercial market classes and using an allele frequency threshold of 5% in order to reduce chances of confounding allele classification with sampling error [e) varied from 0.137  to 0.343 (green bean). The observed heterozygosity (Ho) was very similar among the commercial market classes and ranged from 0.000 (green bean) to 0.012 (black) .Genetic diversity parameters were calculated for each of the races and commercial market classes (the latter based on pedigree data) using both the gene based and the genomic SSR markers . Overallng error . Green bPCoA, Bayesian model-based clustering, and NJ tree based on genetic distance were used to investigate the genetic relationship among the different commercial advanced cultivars and to test for population structure. The PCoA approach based on a genetic distance matrix is shown in In Population structure of the 192 commercial cultivars was further assessed using a Bayesian model-based clustering method implemented in STRUCTURE program. The number of subpopulations (K) was identified according on maximum likelihood and Delta K values . The DelFor K = 3, a finer subgrouping corresponding to the three major eco-geographic races used in common bean breeding programs in the USA was obtained: the Nueva Granada race, made up of large-seeded kidney and green beans; the Mesoamerican race including the small seeded navy, black and small white; and the Durango race including the medium-seeded pinto and great northern. At K = 5, five clusters that correspond to the broad commercial seed classes that are grown in the USA were clearly separated. The first cluster  included the following 18 SSRs: Bmd10, GATS91, PVBR107, BM210, BMd41, BM188B, BMd47, PVBR54, BM53, BMd20, BMd37, PV-ctt001, BMd25, BMd28, BM171, BM200, BM114, BM141.AMOVAs were conducted to determinate the variation explained by races  and market class groups . The resFST statistic estimated from pairwise comparisons as a measure for genetic distance between races and market classes. Within each race, the degree of genetic differentiation was very large, typical of inbreeding species . In general, FST values between subgroups within gene pools were generally low compared to FST values of subgroups between gene pools. Low genetic differentiation was found between pinto and great northern groups and between navy and black beans. Moreover, in the Andean gene pool green beans were less differentiated compared to the kidney groups and closer to the Mesoamerican gene pool.Genetic variation between races and market classes was also tested using the We validated maximum likelihood-based clustering results from STRUCTURE analysis using the Discriminant Analysis of Principal Components (DAPC) method, which is considered free of Hardy-Weinberg and linkage disequilibrium assumptions . Model sa = 3.67), number of effective alleles (Ne = 1.88), allelic richness (Rs = 3.16), Shannon's information index (I = 0.73), and expected heterozygosity (He = 0.394) than the landrace samples  . For the Andean gene pool, the total reduction in diversity in terms of number of alleles (ΔNe), allele richness (ΔRs), and genetic diversity (ΔHe) attributable to post-domestication was 0.33, 0.39, and 0.17, respectively. This loss of diversity is significantly greater than the loss of diversity attributable to domestication   .a = 5.04), number of effective alleles (Ne = 2.38), allelic richness (Rs = 4.09), Shannon's information index (I = 0.83), and expected heterozygosity (He = 0.418) than the domesticated samples  . The total reduction in diversity in terms of number of alleles (ΔNe), allele richness (ΔRs), and genetic diversity (ΔHe) attributable to post-domestication for the Mesoamerican gene pool was 0.27, 0.32, and 0.16, respectively . This increase in diversity is because green beans where included in this group. Indeed, some green beans originated in the Mesoamerican gene pool, showing admixture origin. If we analyze the loss of genetic diversity in race Nueva Granada without including the green bean group the genetic diversity (ΔHe) attributable to post-domestication was 0.25.If we compare the Andean and Mesoamerican advanced cultivars, there was a clear difference in the level of genetic diversity: the Andean gene pool showed a substantially lower level of genetic diversity than the Mesoamerican gene pool for all of the genetic diversity estimates . Comparee = 0.34; ΔHe = 0.23). The limited diversity in the commercial cultivars has serious consequences for bean breeding, and suggest that an important goal of bean breeding programs should be to broaden the cultivated gene pool.Race Mesoamerica showed a marked reduction in genetic diversity between the landraces descendants and their respective commercial advance cultivars . Although number of alleles may not be the best statistic to compare genetic diversity of different samples, in general, our sample presented a lower number of alleles than the sample of 44 genotypes (parents of mapping populations) used in the study of Blair et al. . Allele e) was 0.546 (0.601 for genomic SSR markers and 0.466 for gene–based markers), indicating that the common bean advanced cultivars displayed a substantial genetic diversity. Since estimates of expected heterozygosity are not affected by differences in sample size [The expected heterozygosity value Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 TableFST  and Nei Distances  values between all pairwise combinations of common bean races. 6b) Genetic differentiation based on FST  and Nei Distances  values between all pairwise combinations of common bean market class.6a) Genetic differentiation based on (XLSX)Click here for additional data file.S1 FigSTRUCTURE estimation of the number of subpopulations for K ranging from 2 to 12 by mean likelihoods (A) and Delta K values (ΔK) (B).(XLSX)Click here for additional data file.


Rangifer tarandus caribou) populations across their distribution in Ontario/Manitoba (Canada) to assess changes in genetic diversity and connectivity in areas of high and low anthropogenic activity. Using data from >1,000 caribou and nine microsatellite loci, we assessed population genetic structure, genetic diversity, and recent migration rates using a combination of network and population genetic analyses. We used Bayesian clustering analyses to identify population genetic structure and explored spatial and temporal variation in those patterns by assembling networks based on RST and FST as historical and contemporary genetic edge distances, respectively. The Bayesian clustering analyses identified broad‐scale patterns of genetic structure and closely aligned with the RST network. The FST network revealed substantial contemporary genetic differentiation, particularly in areas presenting contemporary anthropogenic disturbances and habitat fragmentation. In general, relatively lower genetic diversity and greater genetic differentiation were detected along the southern range limit, differing from areas in the northern parts of the distribution. Moreover, estimation of migration rates suggested a northward movement of animals away from the southern range limit. The patterns of genetic erosion revealed in our study suggest ongoing range retraction of boreal caribou in central Canada.With increasing human activities and associated landscape changes, distributions of terrestrial mammals become fragmented. These changes in distribution are often associated with reduced population sizes and loss of genetic connectivity and diversity  which may further diminish a species' ability to respond to changing environmental conditions and lead to local population extinctions. We studied threatened boreal caribou ( We tested for genetic bottlenecks and mating among closely related individuals  and estimated recent migration rates. Under the hypothesis that recent anthropogenic activities increase the potential for genetic erosion, we predicted that (a) recent anthropogenic activities will cause contemporary genetic differentiation to differ from historical differentiation, (b) lower genetic diversity and connectivity and greater amounts of inbreeding and bottlenecks will be linked to populations at the southern range limit, and (c) caribou will exhibit a northward migration trend. A combination of these genetic measures is then used to identify areas at greatest risk of future population decline or extirpation.22.1The study area consists of the boreal region in Ontario and Manitoba Figure , includiWe used the microsatellite DNA genotypes generated by Klütsch et al.  sampled 2.2Na), number of effective alleles (Ne), average observed heterozygosity (Ho), average expected heterozygosity (He), sample‐size weighed expected heterozygosity (uHe), and inbreeding coefficient (FIS) were calculated. We used the software HP‐RARE  and private allelic richness  to correct the observed number of alleles for sample‐size differences among groups by rarefaction. Finally, we measured Euclidean distance from the center of each sampling location to the closest point along the current southern range margin to test for associations between genetic diversity values and proximity to the range margin using both Pearson's and Spearman's rank correlation coefficients. Only sampling locations with ≥10 individuals were used in the analyses.We examined genetic variation in the sampling locations by calculating a suite of genetic diversity statistics. Using the program GenAlEx v. 6.5  using the programs BOTTLENECK  ranging from 1 to 10 and the burn‐in length and number of MCMC repetitions set to 500,000 and 1,000,000, respectively. We evaluated the second‐order rate of change (ΔK) in likelihood values  ranging from 2 to 10 and the number of MCMC iterations set to 50,000 and a burn‐in length set to 40,000. TESS calculates the deviance information criterion (DIC), a measure of both model fit and model complexity with smaller DIC values indicating a better fit of a particular model  in TESS, with a linear trend a total of 50 times with the same number of iterations and burn‐in length as above to determine the proportion of each individual's ancestry that belonged to the inferred number of groups identified by the no‐admixture model  using SPAGEDI  across sample comparisons  structure  was tested for a significant difference from zero based on 10,000 permutations, which is the equivalent of carrying out a Mantel test  with the largest modularity score. We used 10 replicate runs with a burn‐in of 100,000 iterations, a sample size of 50,000 iterations, and a thinning interval of 100. Each run was preceded by 20 pilot runs of 1,000 iterations in an attempt to obtain acceptance rates between 25 and 45 percent. The run with the lowest Bayesian deviance (Dassign) was selected to extract parameter values, including the mean, mode, and 95% highest posterior density interval (HPDI) values.We used the program BIMr  and a surface of contemporary genetic differentiation based on FST calculated among all caribou sampled areas  to identify regions exhibiting characteristics of genetic erosion.We used the Genetic Landscapes GIS Toolbox  across sampling locations was 7.09  and private allelic richness (ARP) were lowest in North Interlake (4.21) and Kenogami (0.00), respectively, whereas both richness values were greatest for Attawapiskat  was 3.54 and was lowest for Kenogami (2.41) and greatest for Naosap–Reed , expected (He), and sample‐size weighted expected heterozygosity (uHe) across all sampled areas were 0.67, 0.69, and 0.70, respectively. Ho and uHe were lowest in Kenogami  and greatest in Attawapiskat , while expected heterozygosity was also lowest in Kenogami (0.57), but greatest in Cochrane  based on Pearson's correlation ; AR also exhibited a significant association based on Spearman's rank correlation  ranged from −0.16 for Kapuskasing to 0.15 for Wabakimi, where larger values suggest greater inbreeding; there was not a significant association between FIS values and distance to the range margin  or two‐phase mutation model (TPM)  of 0.031 (p = 0.185), suggesting mutations did not contribute significantly to genetic differentiation at the sampling‐site level and none of the 351 pairwise permutation tests were significant after a sequential Bonferroni adjustment , suggesting that mutations partially explained genetic differentiation among genetic clusters. Additionally, 2 of the 3 pairwise comparisons were significant after sequential Bonferroni adjustment . When individuals were grouped based on the four TESS local clusters  and a significant difference occurred between TESS local clusters 1 and 3, with an observed RST of 0.028 and pRST of 0.007 (p = 0.008), when considering pairwise comparisons. The results suggested that mutations indeed contributed to genetic differentiation in the study area, meaning that historical processes partially shaped contemporary genetic differentiation.The global (observed) nt Rice, . When innt Rice, , the glors Table , the glo3.43.4.1RST values ranged from 0.000 for 48 comparisons of sampling locations to 0.117 between Berens and The Bog , the three TESS regional clusters , or the four TESS local clusters , suggesting isolation by distance was not an important factor contributing to historical genetic structure.Mantel tests indicated that no correlations existed between 3.4.2FST ranged from 0.000 for six comparisons of sampling locations to 0.095 between Norway House and North Interlake  than among clusters , suggesting contemporary differentiation was less aligned with the clusters than differentiation based on RST. Similar to RST, no correlation was detected between FST and geographic distance for the sampling locations , the three TESS regional clusters , or the four TESS local clusters , indicating that isolation by distance did not explain the genetic differentiation patterns observed.ke Table . The AMOrs Table . Similar3.53.5.1RST was thinned based on a Dpe of 0.029 and revealed one large connected component with a large number of edges connecting Ontario and Manitoba sampling locations , whereas the remainder of sampling locations consisted of individual disconnected components . Yet, because the 10 groups represent contemporary patterns of genetic structure, we argue that pooling of sampling locations represents the most appropriate delineation for exploring recent migration rates. We chose the multilevel community detection algorithm over other community detection techniques because it produced the largest modularity score  indicated that erosion was occurring in the southern and western portions of the study area  and spruce (Picea spp.) forests  suggested that some of the differentiation may be the result of phylogeographic processes. One possibility is that the eastern migratory ecotype, which most likely diverged after an earlier introgression between barren‐ground caribou (Rangifer tarandus groenlandicus; Figure Historical differentiation contributed to genetic structure of boreal caribou in Ontario and Manitoba, but at the level of STRUCTURE and regional and local TESS clusters. This was supported by pairwise tests evaluating the effect of mutations on genetic structure, which were significant when caribou individuals were grouped by the TESS regional and local clusters. Similar to contemporary causes of structure, it is unlikely that the historical structure is the result of isolation by distance as shown by our analyses. Instead, three lines of evidence (i.e., pairwise tests, community detection techniques, and AMOVA for RST network identified similar patterns as our Bayesian clustering results, delineating an Ontario group and either a Manitoba group or western and southwestern Manitoba groups (Table Alternatively, vicariance may explain the historical structure patterns seen. The mitochondrial DNA study by Klütsch et al.  found thps Table . Howeverps Table . Additiops Table . Klütschps Table  detectedFIS values were found in some sampled areas within 100 km of the range's southern edge (e.g., Atiko and Nipigon; Table Similar to genetic differentiation, there were associations between genetic diversity and distance to the southern range margin Table , an areaM‐ratio test, we assumed a smaller proportion of one‐step mutations (ps = 0.80; see Appendix Evidence of genetic bottlenecks was found only in the Kenogami area and only for small prebottleneck effective population sizes Table . HoweverOur results also supported our final prediction that recent migration rates, as inferred through recent proportions of immigrant genes in subdivided populations, would show a movement pattern away from the southern range limit. These results are consistent with animals emigrating from lower quality habitats (Andreasen, Stewart, Longland, Beckmann, & Forister, 5Our findings illustrate recent genetic erosion and increased inbreeding as well as decreased connectivity in the contiguous southern distribution of boreal caribou in Ontario and Manitoba suggesting ongoing range retraction. A northward migration trend suggests that animals partially react with avoidance to disturbed areas. These findings are consistent between two regional differences in population history: Ontario into the east side on Lake Winnipeg and the remaining distribution of Manitoba. These regions demonstrate different histories that contribute to different levels of baseline genetic structure and contact with the eastern migratory ecotype, yet the signatures of genetic erosion are consistently evident. As a result, our study demonstrates that fine‐scale genetic analysis, when accounting for historical processes, is valuable to assess the impact of human‐induced landscape changes on genetic diversity and connectivity in wildlife species.Our research shows provincial and federal recovery efforts would best be focused in areas with healthy and sustainable populations to either restore connectivity among herds or ensure that existing connectivity is maintained. Further, this work has implications for conservation and land protection, particularly for caribou groups that may be important for contemporary gene flow. Thus, consideration of impacts to caribou connectivity and the protection of distinct genetic biodiversity is essential when proposing development plans.None declared. Click here for additional data file.


FST analysis, inbreeding coefficient analysis, principal component analysis, and population structure analysis were carried out. The results showed that Nanjiang camel and Beijiang camels grouped together, and the other five Bactrian camel populations gathered into another branch. It may be because the mountains in the northern part of Xinjiang and the desert in the middle isolate the two groups from the other five groups.Restriction site‐associated DNA sequencing (RAD‐seq) is one of the most effective high‐throughput sequencing technologies for SNP development and utilization and has been applied to studying the origin and evolution of various species. The domestic Bactrian camels play an important role in economic trade and cultural construction. They are precious species resources and indispensable animals in China's agricultural production. Recently, the rapid development of modern transportation and agriculture, and the deterioration of the environment have led to a sharp decline in the number of camels. Although there have been some reports on the evolution history of the domestic Bactrian camel in China, the origin, evolutionary relationship, and genetic diversity of the camels are unclear due to the limitations of sample size and sequencing technology. Therefore, 47 samples of seven domestic Bactrian camel species from four regions  were prepared for RAD‐seq analysis to study the evolutionary relationship and genetic diversity. In addition, seven domestic Bactrian camel species are located in different ecological zones, forming different characteristics and having potential development value. A total of 6,487,849 SNPs were genotyped. On the one hand, the filtered SNP information was used to conduct polymorphism mapping construction, LD attenuation analysis, and nucleotide diversity analysis. The results showed that the number of SNPs in Dongjiang camel was the highest, the LD coefficient decayed the fastest, and the nucleotide diversity was the highest. It indicates that Dongjiang camel has the highest genetic diversity. On the other hand, the filtered SNPs information was used to construct the phylogenetic tree, and  In this paper, 47 samples of seven domestic Bactrian camel species from four regions  were prepared for RAD‐seq analysis to study the evolutionary relationship and genetic diversity. In addition, seven domestic Bactrian camel species are located in different ecological zones, forming different characteristics and having potential development value. Thus, the camel is very important for studying the livestock production in ancient northern China, and economic and cultural exchange between China and the West. With the rapid development of modern agriculture and transportation tools, the number of camels in China has dropped from 373,000 in 1994 to 250,000 today. Therefore, it is necessary to study the genetic diversity of Bactrian camels to clarify their phylogenetic relationship and lay the foundation for the protection of their biodiversity  are ideal molecular markers for genetic mapping and population diversity assessment  and to identify the SNPs of each sample. The study is beneficial to protect the genetic diversity and exploit the potential value of Bactrian camels. Camels are now more than a means of transportation. With the need of domestic animal products , especially the anticancer activity of camel milk  and column‐purified. Samples were sequenced on an Illumina HiSeq 3000 using 100 bp paired‐end reads.RAD‐seq libraries were constructed following a modified protocol  with the settings “mem 4 ‐k 32 ‐M,” −k is the minimum seed length, and −M is an option used to mark shorter split alignment hits as secondary alignments  was used to align the clean reads from each sample against the reference genome  for statistical analyses. The difference between any two averages, such as its absolute value ≥ LSDα, is significant at the level of α.Statistically, comparing two of the multiple averages to each other is called multiple comparisons. There are many methods for multiple comparisons. In this study, multiple comparisons were made between SNPs of seven camel populations by using the least significant difference method (LSD method). The procedure of the least significant difference method is to calculate the least significant difference LSDα with a significant level of α under the premise that the 2.5The population relationship based on individual sample strategies was used to analyze the differentiation, gene exchange, and evolutionary history of seven domestic camel populations. Polymorphism map construction, LD attenuation analysis, and nucleotide diversity analysis were used for camel population genetic analysis.2.5.1For each group, in order to ensure the reliability of the population SNP, for the sites where the SNP exists, each individual in the group needs to ensure that the site information exists, and missing phenomenon does not exist  between two points in a range of sequence . The LD coefficient r2 represents the correlation of two points, which varies within the interval of 0–1. If r2 is 0, there is no correlation between the inheritance of the two locus. If r2 is 1, it means that the site correlation is the largest. We used the “LD attenuation distance” to evaluate the speed of LD decay  is also called as allelic association. It refers to a nonrandom association between different locus alleles within a population. After sequencing, 6,487,849 SNPs were obtained. We estimate the LD decay trend by calculating the LD coefficient , population structure analysis, etc., were used to analyze the evolutionary relationship among different groups on different dimensions . After F value of each individual was obtained, the average was obtained within the population.The inbreeding coefficient refers to the correlation coefficient between two gametes forming an individual, that is, the ratio of the pair of genes from the common ancestor in all relative genes of the individual. Inbreeding coefficient was calculated using Plink 1.9 , and a total of 1,000 replicates generated the Bootstrap values. Moreover, the phylogenetic tree was constructed by the maximum likelihood (ML) method and default parameters were set. By analyzing the phylogenetic tree constructed by the two methods, we can find the evolutionary relationship between populations.2.6.4In genetics, PCA mainly converts multiple differences into a few independent factors and analyzes the differences among different groups by the degree of difference among these factors to classify different populations . We predefined the number of genetic clusters from K = 2 to K = 6 , and each K value was repeated three times. After the STRUCTURE software run was completed, web used the POPHELPER software (https://www.ncbi.nlm.nih.gov/pubmed/26850166) to calculate the ∆K value and the CLUMPP software (https://www.ncbi.nlm.nih.gov/pubmed/17485429) to merge the results of the three repetitions. After the combination, we used the POPHELPER software to illustrate it  in the transversion and 4,217,102 loci (65%) in the transition. The ratio of transition to transversion was nearly 2:1, the transition frequency between purine and pyrimidine was basically the same, and the transversion frequency of each type was also substantially flush.3.23.2.1p > .05; Figure The vcftools software was used to extract SNPs from each population, and there were differences in SNPs among different domestic camel populations. The number of SNPs in the seven domestic camel populations varied from 828,619 in the Beijiang camel to 1,004,857 in the Dongjiang camel, but the differences between the populations were not significant (3.2.2The rate of LD attenuation varied greatly among different species or among different subgroups of the same species. The faster the LD coefficient decays, the higher the genetic diversity of the population is. LD attenuation analysis was performed on seven domesticated camel populations in four regions. It can be observed from the figure that the decay rate of the LD coefficient was different in different populations, and the attenuation speed was Dongjiang camel > Sunite camel > Beijiang camel > Nanjiang camel > Qinghai camel > Alashan camel > Hexi camel Figure .3.2.3Nucleotide diversity represents the genetic diversity of population to some extent. It can be seen from Table 3.33.3.1FIS between Hexi camel, Qinghai camel, and other populations was lower, indicating that the genetic distance was far from other populations.For an individual, the probability of getting a gene from the parent is 1/2, and the probability of getting a gene from the grandparent is 1/4; that is, the probability of getting the same gene from a common ancestor is reduced by 1/2 every other generation. Therefore, the closer the kinship is, the greater the inbreeding coefficient is. As can be seen from Table 3.3.2FST values between different populations were calculated to study the genetic diversity among different populations. It can be seen from Table FST value between Dongjiang camel and other camel breeds was 0.1594, which was the lowest among all the average values. It indicated that its genetic distance was close to other populations, and the genetic difference with other populations was not significant. The average value of FST between Hexi camel, Qinghai camel, and other populations was the highest, indicating that the genetic distance was far from other populations.The 3.3.3The filtered SNPs information was used to construct phylogenetic tree by the ML method Figure  and the 3.3.4FST statistical analysis. Two PCA maps showed that Sunite camel and Alashan camels were clustered together, and there was genetic communication between two camel breeds. They had a close genetic relationship, and it was consistent with the results of the phylogenetic tree. Dongjiang camels and Beijiang camels gathered together, that showed genetic communication and relatively close genetic relationship. It was consistent with the results of the phylogenetic tree.The key information was extracted from millions of SNPs, and the PCA of seven breeds of domestic camels was conducted Figure . On the 3.3.5K value, we performed cross‐validation to determine which K value best fitted the true differentiation history of the population. In Figure K = 5. At K = 3, the Qinghai camel and the Hexi camel were clearly separated from other populations of camels, indicating that the Qinghai camel and the Hexi camel were far away from the camels of other populations, which was consistent with the results of the FST statistical analysis. At K = 5, the Alashan camel and the Sunite camel shared a common genetic ancestry, and there was genetic communication between two populations of camels, which was consistent with the results of the PCA. Some individuals of the Dongjiang camel shared an ancestral genetic background with the Beijiang camel, which was consistent with the results of the evolutionary tree. The ancestral background of Nanjiang camel was very pure and had a genetic ancestry. Dongjiang camel, Qinghai camel, and Sunite camel had a variety of genetic ancestry, but there was a main genetic ancestry.The STRUCTURE analysis software was used to analyze the population structure of the domestic Bactrian camels and the ancestral population of each breed Figure . When pe4FST statistical analysis, inbreeding coefficient analysis, principal component analysis, and population structure analysis were employed to analyze the population genetic relationship. The results showed that the number of SNPs in Dongjiang camel was the highest, the LD coefficient decayed the fastest, the nucleotide diversity was the highest, and the genetic diversity was the highest, which may be due to the preservation of genetic diversity of ancestors (Abdulla et al., The genetic diversities and evolutionary origins of domestic Bactrian camels in China have been a fascinating source for decades (Chen, Ren, et al., In the study, RAD‐seq was first applied on camels. RAD‐seq technology includes DNA sequence data from multiple loci in the genome at a lower cost, simpler library preparation process, no prior knowledge of any locus DNA sequences, management of data from simplified genomes, and well‐developed pipelines for data treatment and analysis to retrieve orthologous sites for comparison (Eaton & Ree, Male‐specific region of Y chromosome in mammals does not recombine with X chromosome during meiosis. It has low mutation rate and is easy to form specific haploid. It follows strict paternal inheritance, so it is an important genetic resource for studying paternal genetic diversity (Cao et al., None declared.Zhanjun Ren and Chenmiao Liu designed the study and wrote the manuscript, Huiling Chen collected the samples, and Chengdong Zhang and Xuejiao Yang contributed to the data analysis. All authors read and approved the manuscript.


Carya cathayensis and Juglans nigra. A total of 77 ISSR and 19 SSR primers were prescreened; 10 ISSR and eight SSR primers were selected, yielding a total of 94 amplified bands (100% polymorphic) in the range of 140–1,950 bp for the ISSR and 70 amplified bands (100% polymorphic) in the range of 50–350 bp for SSR markers. Genetic diversity analyses indicated Chinese-grown pecan cultivars and fine plants had significant diversity at the DNA level. The dengrograms constructed with ISSR, SSR or combined data were very similar, but showed very weak grouping association with morphological characters. However, the progeny were always grouped with the parents. The great diversity found among the Chinese cultivars and the interesting germplasm of the fine pecan plants analyzed in this study are very useful for increasing the diversity of the pecan gene pool. All 77 accessions in this study could be separated based on the ISSR and SSR fingerprints produced by one or more primers. The results of our study also showed that ISSR and SSR techniques were both suitable for genetic diversity analyses and the identification of pecan resources.Pecan is an important horticultural nut crop originally from North America and now widely cultivated in China for its high ecological, ornamental and economic value. Currently, there are over one hundred cultivars grown in China, including introduced American cultivars and Chinese seedling breeding cultivars. Molecular markers were used to assess the genetic diversity of these cultivars and to identify the pedigrees of fine pecan plants with good characteristics and no cultivar-related data. A total of 77 samples grown in China were studied, including 14 introduced cultivars, 12 domestic seedling breeding cultivars, and 49 fine pecan plants with no cultivar data, together with  Carya illinoensis) is a North American deciduous tree that belongs to the Juglandaceae family, which includes hickories, walnuts and the Carya genus, which comprises approximately 25 species of large trees. In North America, the pecan tree is native to the Mississippi River Valley and its tributaries, and its natural distribution extends approximately from latitude 26° to 42° and longitude 84° to 103°, primarily along rivers. The range of cultivation extends from North Carolina to Southwest California [Pecan  markers for the genetic studies of pecan [et al. have constructed the first linkage map of pecan, using RAPD and AFLP markers [et al. used RAPD to analyze the population genetic diversity of 30 introduced American pecan cultivars, although Chinese cultivars were not investigated [In previous works, the genetic diversity of pecan cultivars was assessed in different ways. Several isozyme systems had been developed and used for studying the genetic diversity of pecan populations ,5,6,7,8 of pecan ; 19 SSR  markers . In Chinstigated ,15. FromBoth inter-simple sequence repeat (ISSR) and SSR markers based on the polymerase chain reaction (PCR) are commonly used for measuring genetic diversity ,17 and fCarya cathayensis Sarg. and Juglans nigra Linn., by screening 77 ISSR and 19 SSR markers. Using 10 ISSR and eight SSR markers, we addressed three objectives: (1) to detect the genetic diversity and genetic variation among the introduced American cultivars, Chinese cultivars and fine pecan plants; (2) to identify (or fingerprint) different cultivars and fine plants; and (3) to discuss the genetic relatedness between the ISSR and SSR markers. Our long-term goal is to select suitable varieties for cultivation in China. These results should provide useful data for further breeding programs.An understanding of the genetic relationships of the pecan germplasm is difficult because of the inherent difficulties of working with a large perennial tree, but it is vital for continuing any breeding program that endeavors to increase the genetic diversity of new cultivars. In this study, we fingerprinted 77 pecan samples grown in China, including 14 introduced cultivars, 12 domestic seedling breeding cultivars, 49 fine pecan plants with no cultivar data, and Carya cathayensis and Juglans Nigra. A list of the samples investigated is given in The following 77 plant samples were used in this study: 14 cultivars introduced from America, 12 Chinese seedling breeding cultivars, 49 fine pecan plants with no cultivar data, Juglans nigra”).A screen of the 77 accessions using 10 selected ISSR primers  yielded Carya cathayensis”). In addition, the 80-bp band amplified by the SSR-4 primer, the 350-bp band amplified by the SSR-7 primer, the 210- and 160-bp bands amplified by the SSR-8 primer, the 260- and 200-bp bands amplified by the SSR-9 primer and the 110- and 100-bp bands amplified by the SSR-19 primer were only detected in S77 (“Juglans nigra”).Of the 19 SSR primers tested, eight producing clear and reproducible bands were chosen for further study . A totalBased on the different origins of the germplasm, the 77 accessions were divided into four groups, as follows: the AC group comprising 14 cultivars introduced from America, the DC group comprising 12 Chinese seedling breeding cultivars, the FP group comprising 49 fine pecan plants with great characteristics and no cultivar data, and the OH group comprising two other hickory genotypes. With the purpose of detecting the extent of genetic diversity of the pecan accessions in this study more accurately, the four groups were organized into the following four clusters: Cluster I, which included only one group (AC); Cluster II, which included two groups (AC and DC); Cluster III, which included three groups (AC + DC + FP); and Cluster IV, which included all four of the groups (AC + DC + FP + OH). And with the purpose of discuss the genetic relatedness between ISSR and SSR, genetic parameters were analyzed using the ISSR and SSR markers separately and were listed in et al. in 2003 using a native pecan genotype “Halbert” and were evaluate for the genetic studies of 48 pecans and other hickory spp. [In ory spp. . Grauke’Ae) was 1.46, Nei’s gene diversity (H) was 0.27 and Shannon’s information index (I) was 0.42 [Ae) was 1.42, Nei’s gene diversity (H) was 0.26 and Shannon’s information index (I) was 0.41. These results indicated that a high genetic variance existed among the accessions. The ISSR and SSR markers both expressed a high level of polymorphism in distinction of the accessions. ISSRs were revealed as more efficient for pecan diversity evaluation compared with SSRs except with American introduced cultivars. The genetic variance analysis using the ISSR markers showed that the coefficient of gene differentiation (Gst) was 0.9742 and the gene flow (Nm) was 0.0133, whereas the genetic variance analysis using the SSR markers indicated that the coefficient of gene differentiation (Gst) was 0.9694 and the gene flow (Nm) was 0.0158. The coefficient of gene differentiation results showed that 97.42% and 96.94% of the differences existed among the cultivars and 2.58% and 3.06% of the differences existed within the cultivars, indicating that the pecan cultivars had significant diversity at the DNA level. The pecan is monoecious, that is, the male (catkin or staminate flower) and female (pistillate flower) flowers are borne separately at different locations on the same tree. However, within a pecan cultivar, pollen shedding usually does not closely overlap with the period when the stigma is receptive, which tends to ensure cross-fertilization rather than self-fertilization. Our results are consistent with this character of pecans and the results of previous studies [When analyzing the genetic diversity of all 77 of the accessions (Cluster IV), the ISSR results showed that the effective number of alleles  and group II (containing 50 accessions). The cultivars and fine plants were mixed together and scattered in two groups, but some patterns remained. The UPGMA cluster analysis based on the SSR data also revealing a structure of two clusters: Juglans nigra and the other accessions. The other 76 accessions were divided into three groups: group I (containing 73 accessions), group II (containing one accession) and group Ⅲ (containing two accessions).The UPGMA cluster analysis was firstly conducted using only the ISSR data and showed a two cluster structure: Juglans nigra exhibited lower genetic identity than the pecan cultivars, ranging from 0.59 for “Mang 1” to 0.48 for “Mahan”. The average genetic identity among the American cultivars (0.79) was higher than the Chinese cultivars (0.75), indicating that the Chinese cultivars had a higher genetic diversity. Genetic variation may be caused by factors such as different locations, climates, and cultivation methods. The Chinese cultivars originated from the American cultivars, and, after introduction into China, the cultivars were affected by the local climate and cultivation methods. The most suitable cultivars were propagated and developed a great many characters. Thus, these cultivars have added abundant genetic diversity to the pecan germplasm. This result also highlights the role of the growing locality on the genetic diversity of pecan.We then combined the ISSR and SSR data because the combined data permit a more thorough analysis of the genetic variations . The NeiJuglans nigra can be easily identified by many primers that it presented a lot of bands that all other accessions lacked. Other six accessions—Carya cathayensis, Sanber, Kanza, L1, IIW13Lv, and IVW28—could be identified through the presence of a single ISSR or SSR band that all other accessions lacked. All other accessions required at least two bands to be scored for an identification to be made. Therefore, ISSR and SSR markers have good potential for use in fingerprint pecan.All 77 accessions in this study could be separated based on the ISSR and SSR fingerprints produced by one or more primers. The dendrograms constructed with ISSR, SSR or combined data were very similar, but with some differences which led to some better representation of the genetic relationship for cultivars and fine plants. The dendrogram constructed from both the ISSR and SSR similarity data showed a relatively indistinct grouping model among the different accessions . HoweverA large number of Chinese pecan cultivars and fine plants are of unknown or questionable pedigree. This is because many were selected from seedling pecan plants that lacked a cultivar record and neither parent was known, or they were produced early in the century before efficient means of pollination control of this wind-pollinated species were established . The appCarya cathayensis shares the same genus with pecan (Carya Nutt. species) and has a relatively close relationship with the pecan accessions, whereas Juglans nigra is of a different genus (Juglans species), very far away from the other accessions.The dendrogram analysis reveals a definite gap between pecan and other hickories, as was expected on the basis of known levels of relatedness. The cultivars used in the present study were obtained from America and China and had been cultivated in China for at least 2 years. The cultivars analyzed in this study were maintained in the scientific orchards of the Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, China.Total genomic DNA was extracted from young leaves collected in early spring using a DNAsecure Plant kit . The quality of the total DNA was verified by gel electrophoresis (1% agarose gel) and quantified by spectrophotometry . The DNA samples were stored at −20 °C. This genomic DNA was used for both the ISSR and SSR-PCR amplifications.et al. The PCR was conducted in a 20 µL reaction volume containing 1× PCR buffer, 40 ng genomic DNA, 0.2 mM dNTP, 0.2 mM Mg2+, 0.4 mM primer and 1 U Taq DNA polymerase [−1 ethidium bromide (EB) in 1× Tris-acetate-EDTA (1× TAE) buffer; the gels were then photographed under ultraviolet light .A total of 77 ISSR primers  were prescreened using two cultivars; 10 primers were selected based on polymorphism, quality and the reproducibility of the amplifications. The procedure for the ISSR marker amplification was modified from that of Zhao lymerase . The PCRet al. using eight primer pairs selected from among the 19 SSR primer pairs that were developed for pecan by Grauke et al. [2+), 0.3 mM forward and reverse primers and 1 U Taq DNA polymerase. The SSR amplification were conducted with an initial denaturation at 94 °C for 3 min, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at the specific temperature (53 to 59 °C) shown in The SSR assays were performed as described by Grauke e et al. . The preN), the percentage of polymorphic loci (P), the observed number of alleles (A), the effective number of alleles (Ae), Nei’s gene diversity index (H), Shannon’s information index of genetic diversity (I), the coefficient of gene differentiation (Gst), and the gene flow (Nm).Only distinct, well-resolved fragments were scored as present (1) or absent (0) for each of the ISSR and SSR markers in the 77 accessions. Two different matrices of the ISSR and SSR data were analyzed among the four clusters composed of different accessions using POPGENE Software version 1.31 . The folClustering analysis was conducted using the unweighted pair group method with arithmetic average (UPGMA) and dendrograms were constructed for the ISSR, SSR and combined data, respectively, using the scorable fragments (The dendrograms of ISSR and SSR are showed in the In summary, the genetic diversity analyses indicated that a high genetic variance existed among the 77 studied accessions. Pecan cultivars and fine plants had significant diversity at the DNA level. Perhaps due to the growing locality, Chinese cultivars had a higher genetic diversity than American introduced cultivars.The dengrograms constructed with ISSR, SSR or combined data were very similar but showed very weak grouping association with morphological characters. However, the progeny were always grouped with the parents and in accordance with pervious research. Using data obtained from this experiment may not fully identify the genetic pedigree of fine plants, but provided us a lot of useful data for understanding their genetic backgrounds. Some interesting fine plants were identified for their unique genetic relationship with other accessions. The great diversity found among the Chinese cultivars and the interesting germplasm of fine pecan plants indicated that the Chinese cultivars and fine plants comprise variable sources of pecan genes for use in breeding programs. Thus, it is necessary to search among the Chinese pecan cultivars and fine plants with the goal of diversifying the available pecan gene pool.All 77 accessions in this study could be separated based on the ISSR and SSR fingerprints produced by one or more primers. The results of our study also showed that ISSR and SSR techniques are both suitable for genetic diversity analyses and the identification of pecan resources.To the best of our knowledge, we report here for the first time the genetic variation of Chinese-grown pecan cultivars and fine plants. The results reported here could have practical uses and may be useful for future studies.


Eucalyptus regnans F. Muell., a foundation tree species of montane forests in south‐eastern Australia. We used these data to determine the extent of hybridization with another species, Eucalyptus obliqua L'Hér., and investigate how admixture influences genetic diversity parameters, by estimating metrics of genetic diversity and examining population genetic structure in datasets with and without admixed individuals. We found hybrid individuals at all sites and two highly introgressed populations. Hybrid individuals were not distributed evenly across environmental gradients, with logistic regression identifying hybrids as being associated with temperature. Removal of hybrids resulted in increases in genetic differentiation (FST), expected heterozygosity, observed heterozygosity and the inbreeding coefficient, and different patterns of isolation by distance. After removal of hybrids and introgressed populations, mountain ash showed very little population genetic structure, with a small effect of isolation by distance, and very low global FST(0.03). Our study shows that, in plants, decisions around provenancing of individuals for restoration depend on knowledge of whether hybridization is influencing population genetic structure. For species in which most genetic variation is held within populations, there may be little benefit in planning conservation strategies around environmental adaptation of seed sources. The possibility for adaptive introgression may also be relevant when species regularly hybridize.Conservation management often uses information on genetic population structure to assess the importance of local provenancing for ecological restoration and reintroduction programs. For species that do not exhibit complete reproductive isolation, the estimation of population genetic parameters may be influenced by the extent of admixture. Therefore, to avoid perverse outcomes for conservation, genetically informed management strategies must determine whether hybridization between species is relevant, and the extent to which observed population genetic patterns are shaped by interspecific versus intraspecific gene flow. We used genotyping by sequencing to identify over 2,400 informative single nucleotide polymorphisms across 18 populations of  The existence of hybrids between E. regnans and the frequently co‐occurring Eucalyptus obliqua L'Hér. (messmate stringybark) has long been known  describe how identification of admixture using genomic data may influence our understanding of population genetic structure and (c) consider how these factors would influence current management strategies in eucalypts. We address these aims using genotyping by sequencing to obtain large numbers of genomewide genetic markers on individual samples across the natural geographic range of the species. We predict that (a) some individuals and populations will show greater levels of admixture with E. obliqua, (b) levels of admixture will be driven in part by local environmental variables and (c) the inclusion or exclusion of hybrid individuals in population genetic analyses will lead to different strategic outcomes for management. If these predictions are true, there are implications for future studies of population genetic structure and the planning of restoration plantings and assisted gene flow.Given the importance of understanding population genetic structure for conservation, and the knowledge that hybridization in eucalypts is a widespread and common phenomenon , before storage at −18°C to await DNA extraction.Samples were ordered randomly, and whole genomic DNA was extracted in plate format by following the kit (Stratec Invisiorb DNA Plant HTS 96) instructions. Library preparation for genotyping by sequencing included (a) digestion using PstI restriction enzyme , (b) ligation using T4 DNA ligase , (c) a purification step (Qiagen MinElute 96‐well PCR purification kit), (d) PCR amplification using two GBS primers (Integrated DNA Technologies), (e) postpurification quantitation using microfluidic capillary electrophoresis (PerkinElmer LabChip GX II), (6) pooling of 12 ng DNA per sample using an automated robotic liquid handling machine (PerkinElmer NGS Express) and (f) a final purification step (Sigma‐Aldrich Genelute PCR Clean‐Up Kit).E. regnans sequencing experiments) of an Illumina HiSeq 2500 machine using a 100‐base paired‐end read.Size fractionation, 250–450 base‐pair gel cutout, and sequencing was conducted at the Australian Cancer Research Foundation Biomolecular Resource Facility (BRF) at the John Curtin School of Medical Research  on portions of four lanes (grouped with other 2.4E. regnans and 21 E. obliqua), sequencing resulted in nearly 1.49 billion read pairs. We demultiplexed reads using exact matches and combinatorial index mode with Axe  reads at both ends, and NextGenMap  and minor allele frequency (MAF ≥ 0.01), retaining 2,192 SNPs. Samples missing more than two‐thirds of these loci were removed from any further analysis, retaining 380 samples. Next, we used an eigen‐analysis approach to investigate individual ancestries, using the snpgdsAdmixProp function of the “SNPRelate” package  is often used as an initial method of removing outlier samples  Spatial Portal , and 15 environmental variables at each point were extracted. Environmental variables used in the ALA were collated or derived from various sources  prior to fitting any models.The location of all 359 putative To identify whether any predictor variables showed nonlinearity on the logistic scale, we fitted a binomial generalized additive model in R and plotted the component smooth functions for each variable on the scale of the linear predictor. The MAXTEMP variable showed signs of nonlinearity and so was transformed with the inverse reciprocal, which improved linearity substantially.glmer function of the “lme4”  using the “MuMIn” Barton,  package.2.7HWChisqStats function of the “Hardy–Weinberg”  was removed from further analysis. In addition, the snpgdsLDpruning function in the “SNPRelate” , minor allele frequency (MAF ≥ 0.01) and observed heterozygosity (≤0.5). The likelihood that each SNP does not deviate from Hardy–Weinberg equilibrium (HWE) was checked using the E. obliqua samples) and (b) pure E. regnans individuals . In the admixture‐inclusive group, 2,474 SNPs were retained. For the pure group, 2,481 SNPs were retained. Any samples with more than 50% missing data were removed from each dataset, leaving 323 samples and 228 samples in the admixture‐inclusive and admixture‐free groups, respectively. Visual inspection of hierarchical clustering dendrograms, created using the hclust function on a Euclidean genetic distance matrix, showed that all biological replicates were closely paired in both datasets  all samples including hybrids , genetic differentiation (FST), expected heterozygosity (HE) and observed heterozygosity (HO) were calculated across all loci and plotted as bar charts.Standard population genetic parameters were calculated for all loci in both groups, using the  Goudet,  package.df2genind and genind2genpop functions in the “adegenet”  and log(geographic distance), respectively, to allow for linear interpretation  of pairwise population genetic distances as well as through isolation by distance. Pairwise population Euclidean genetic distances were calculated by first converting genotypes to genpop objects using the Jombart,  package, Vavrek,  package.Rousset, .2.8mantel.rtest function in the R package “ade4” , number of effective alleles (AE), HO, HE and FIS for each of the 15 populations. We then calculated the pairwise genetic distance between all individuals in these populations using the “Dch” method of the genet.dist function. This distance matrix was then read into GenAlEx to conduct an analysis of molecular variance (AMOVA) with 999 permutations to determine the amount of genetic variation explained within and among sites.To investigate population genetics within 33.1r = 0.94, p < 0.001) and SNPRelate , with bar plots showing near‐identical patterns between methods . Excluding the reference E. obliqua samples, SNPRelate, STRUCTURE and NGSadmix identified 59, 130 and 190 hybrid individuals (>10% admixture with E. obliqua), respectively. All hybrid samples identified in SNPRelate were also identified using STRUCTURE, but a small proportion of samples identified as hybrids in SNPRelate and STRUCTURE were not identified as such by NGSadmix. After calculating the mean value of the E. obliqua admixture coefficient for the three methods, 170 samples were identified as hybrids. Of these, 75 samples had E. obliqua admixture coefficients between 0.1 and 0.4, five had coefficients between 0.4 and 0.6, 11 had coefficients between 0.6 and 0.9, and 16 had coefficients of greater than 0.9.Despite NGSadmix using a different approach  and much larger number of loci, there was a very strong correlation of ancestry coefficients computed using that method and both STRUCTURE  were able to be easily identified due to their separation from the bulk of the r Figure . UnfortuE. obliqua ancestry coefficient of a site was 0.11 (±0.21), with sites varying considerably in the amount of admixture  was 0.24. Not a single site was completely free of hybrids, but seven sites had just one hybrid. The mean e Figure . Samples3.2Model selection showed that hybrid individuals were not randomly distributed across all environmental variables. Of the 11 top models (ΔAICc < 2), MINTEMP and MAXTEMP were identified in all 11, suggesting that these two variables had the strongest effects on the probability of hybrid occurrence. Sites with a high MAXTEMP (hot summers) and sites with a low MINTEMP (cold winters) had lower probabilities of hybrid occurrence, whereas sites with a high MINTEMP and sites with a low MAXTEMP had higher probabilities of hybrid occurrence Figure . Variabl3.3HE, HO, FST and FIS increasing from 0.087, 0.092, 0.024 and −0.012 in the admixture‐inclusive dataset, to 0.094, 0.097, 0.03 and −0.005 in the admixture‐free dataset.The removal of hybrid individuals from the dataset modified the values of the genetic parameters investigated Figure , with thFST values between this and other sites, leading to a reduction in fit of the isolation‐by‐distance model when this site was included in the analysis.Removal of hybrids led to greater resolution of geographic population structure in the PCoA of pairwise population genetic distances and a stronger pattern of isolation by distance from the Mantel test Figure . In the 3.4r intercepting zero at 108 km. A Mantel test, comparing the logarithm of geographic distance with Nei's genetic distance for all pairs of samples, showed that there was a relatively small but significant  positive effect of isolation by distance.After removing all hybrids and discounting sites that had <10 samples, 200 individuals from 15 sites were retained. The spatial genetic structure analysis in GenAlEx identified weak but significant autocorrelation  between genotypes at pairwise distances of up to 90 km, with the autocorrelation coefficient A, AE, HO, HE, or FIS. Most sites had higher OH than EH, and all sites had negative FIS values, implying that outbreeding is the common condition throughout the species distribution. Global FST was very low (0.03), and approximately equal to the mean pairwise FST between sites (0.028), despite some large (>600 km) pairwise geographic distances , to 0.063, between the geographically distant Errinundra Plateau and Gellibrand River (489 km).Within‐population genetic structure at the 15 sites was very similar  Voss and Picea engelmannii Parry ex Engelm. have been shown to utilize adaptive introgression as a way to maximize fitness in a changing climate  do not explicitly address the presence of hybridization in their study species, it is plausible that many studies are influenced by this issue. We propose that future studies always be explicit in acknowledging the potential for hybridization between their species of interest and other species, as gene flow between some species is clearly a common, and possibly evolutionarily significant, phenomenon  to pure specimens, with morphological approaches now generally regarded as a poor way of identifying hybrids  is likely due to their being located on the periphery of suitable climatic conditions for this species.In the case of 4.2FST values that we observed between sites are low but comparable to those found in other eucalypts  results show very little population structuring. Chloroplast DNA is highly conserved, with genetic structure typically reflecting historical patterns of dispersal and colonization. Further, only a very small proportion of chloroplast variation is typically contained within coding regions  of a stand, selection may be acting to promote particular genotypes within a generation, as environmental conditions filter out particular alleles. There is a steep reduction in the stem density within 4.3Seed used for native vegetation restoration activities has historically been collected from small local geographic areas  dominate the majority of Australian ecological restoration schemes , intermediate (FST > 0.05 < 0.1) or distant (FST > 0.1 < 0.2) provenances. Under this definition, the entire range of E. regnans would be considered local provenance. Because most of the genetic variation of the species is already contained within local geographic areas, the source of seed used for restoration activities is not likely to be as important as previously considered. While we acknowledge that reciprocal transplant experiments show a strong effect of provenance in some species . A CSV file containing location data and called genotypes from ANGSD for all individuals are available at the Dryad Digital Repository:  Click here for additional data file.


Togaviridae, Alphavirus) is a highly pathogenic mosquito-borne arbovirus that circulates in an enzootic cycle involving Culiseta melanura mosquitoes and wild Passeriformes birds in freshwater swamp habitats. Recently, the northeastern United States has experienced an intensification of virus activity with increased human involvement and northward expansion into new regions. In addition to its principal role in enzootic transmission of EEE virus among avian hosts, recent studies on the blood-feeding behavior of Cs. melanura throughout its geographic range suggest that this mosquito may also be involved in epizootic / epidemic transmission to equines and humans in certain locales. Variations in blood feeding behavior may be a function of host availability, environmental factors, and/or underlying genetic differences among regional populations. Despite the importance of Cs. melanura in transmission and maintenance of EEE virus, the genetics of this species remains largely unexplored.Eastern Equine Encephalitis (EEE)  characterize the genetic diversity of Cs. melanura at EEE virus foci across eastern North America, 2) investigate the occurrence of genetic structure among populations of Cs. melanura, and 3) examine patterns of gene flow among these populations. We generated a draft genome of this species as a reference for population studies, identified evidence of significant genetic differentiation and fine-scale genetic structure among populations, and found evidence of gene flow among northeastern populations. This study provides the molecular basis for future investigations on the causes and consequences of the genomic variation in Cs. melanura on the risk of human and equine infection with EEE virus.Eastern equine encephalitis (EEE) is a highly pathogenic mosquito-borne virus responsible for outbreaks of severe disease in humans and equines, causing high mortality and neurological impairment in most survivors. In the past, human disease outbreaks in the northeastern United States occurred intermittently; however, recently, this region has experienced a recurring seasonal intensification of EEE virus activity with expansion into more northerly locales. Eastern equine encephalitis virus is maintained in a transmission cycle involving the ornithophilic mosquito,  Alphavirus, Togaviridae) causes severe disease in humans and equines with high case mortality and persistent neurologic impairment in survivors [st century, this region has experienced a recurring seasonal intensification of EEE virus activity [Culiseta melanura (Coquillett) (Diptera: Culicidae) and passerine birds [Cs. melanura breeds [Eastern equine encephalitis (EEE) virus  characterize the genetic diversity of Cs. melanura in EEE virus foci across eastern North America, 2) investigate the occurrence of genetic structure among populations of Cs. melanura, and 3) examine patterns of gene flow among these populations.The apparent flexibility in host choice exhibited by  regions ,15,17–19Culiseta melanura from a laboratory colony, originally collected in Cape May, New Jersey [Female w Jersey  and mainExtracted DNA was used for library construction and sequencing on the PacBio RSII instrument  at the Yale Center for Genome Analysis (YCGA), where standard Pacific Biosciences 20Kb library construction was carried out according to the manufacturer’s instructions. The resulting library was loaded onto a total of forty SMRT Cells and sequenced with P6-P4 chemistry.https://www.pacb.com/support/software-downloads/). Briefly, raw reads were mapped back to the genome assembly using BLASR, and high-quality consensus base calls were made with both Quiver and Arrow, resulting in two polished assemblies.Resulting raw reads were error-corrected and assembled using Canu version 1.6 . Defaultwww.vectorbase.org, [Aedes albopictus , Anopheles gambiae , Culex quinquefasciatus , Glossina fuscipes , and Lutzomyia longipalpis . BUSCO results were visualized in R with the ggplot2 package [Benchmarking Universal Single Copy Ortholog (BUSCO) Analysis  was usedase.org, ) for com package .Culiseta melanura were collected from ten locations in eastern North America, ranging from Florida to Canada  methods –33 is th20. Adaptor mixes were then heated at 97.5°C for 10 minutes, then cooled 2°C every minute to 4°C.The constituent oligo stubs that comprised Read 1 and Read 2 adaptors , 1 μl of 10 μM read 1 adaptor, 2 μl of 10 μM read 2 adaptor, 1.5 μl of 10μM rATP , and 100 units of T4 DNA Ligase. Ligation reactions were incubated at room temperature for 30 minutes, then heat shocked at 65°C for 10 minutes, then cooled 2°C every minute to 4°C. The I5 index containing degenerate bases was then annealed to individually barcoded samples in a 50 μl reaction containing 22 μl of adapter-ligated sample, 2.5 μl of 10 μM I5 oligo, 0.3mM of each dNTP, 10 μl of 5X KAPA HiFi Fidelity Buffer, and 0.5 units of KAPA HiFi Hotstart DNA Polymerase . Samples were incubated at 95°C for 2 minutes, 98°C for 20 seconds, 61°C for 15 seconds, 72°C for 30 seconds, and 72°C for 5 minutes. Following incubation, samples were cleaned with magnetic beads. Next, samples were enriched in 50 μl reactions containing 22 μl of sample, 2.5 μl of 10 μM P5 primer, 2.5 μl of 10 μM I7 oligo containing either the “A” or “B” index  under a “tight” setting at 440 base pairs. Libraries were sequenced at the YCGA on the HiSeq 4000 platform  in 150 base pair paired-end mode. To improve sequence quality and increase the complexity of sequencing lanes, ddRAD libraries were spiked with another library.Resulting reads were demultiplexed initially by I7 index, and raw reads were contained in two paired end files (hereafter read 1 and read 2), as well as a third set of reads for the 8 degenerate bases in the I5 index in the appropriate phase for each paired end read. To remove PCR duplicates, the degenerate bases of the I5 index were concatenated to the end of read 1 using a custom script; and then, both paired end reads were passed to clone_filter in Stacks. With default settings, clone_filter removes reads that are exactly duplicate across both pairs of reads; as PCR duplicates would contain identical I5 indices (now concatenated to the end of read 1), as well as identical read 1 and read 2 sequences, they would be discarded by this filter. Following clone filtering, Trimmomatic  was usedde novo in Stacks using the subset strategy defined in Rochette and Catchen [de novo Stacks catalog with parameters m and n equal to 5, and variants were called for all samples from this catalog.Following removal of PCR duplicates, Stacks version 1.46 ,37 was uVariants were called with Stacks’ population module, requiring that loci were present in 75% or more of samples (parameter r set to 0.75), and filtering minor alleles at a frequency below 0.01 (flag–min_maf 0.01). The effect of specifying the population parameter, p, was also evaluated by requiring that loci be present in 75% of samples in 2, 6, or 10 populations. For all analyses except for fineRADstructure analysis (see below), linked SNPs were filtered with PLINK version 1.9  in a 50 Cs. melanura populations. Isolation by distance among sampling sites was assessed by correlating Nei’s genetic distance, implemented in the function dist.genpop from the R package adegenet [Several methods were used to assess genetic differentiation in adegenet , with geadegenet . An analadegenet  was usedadegenet , consideadegenet , and theNext, to assess the number of distinct genetic clusters, a least-squares approach was used: sparse non-negative matrix factorization (SMNF), implemented in the function smnf from the R  package FineRADStructure , a pipelTwo multivariate methods were also used to visualize genetic structure across sampling locations: principal component analysis (PCA) and discriminant analysis of principal components (DAPC), both implemented in the R package adegenet ,49. A peFollowing the identification of an unexpected genetic cluster at sampling sites in the northeast see , two froR version 3.4  was usedSequencing of forty SMRT Cells yielded a total of 4.2 million raw reads with an average read length of 9 kilobases (kb). These raw reads were assembled to produce an unpolished draft assembly of 1.278 gigabases (Gb) across 25,500 contigs, with a contig N50 of 93.23 kb. Subsequent polishing provided modest increase to assembly size and contig N50. The Quiver-polished assembly was 1.279 Gb, with a contig N50 of 93.29 kb, while the Arrow-polished assembly was a total of 1.281 Gb, with a contig N50 of 93.36 kb. Although polishing provided only minor improvements to assembly size and N50, improvement to the results of BUSCO analyses were more substantial. The unpolished genome assembly had evidence of 61.3% of expected complete single copy orthologs, with 22.4% missing entirely. More than 70% of complete single copy orthologs were detected in both polished genomes, with the Arrow-polished assembly performing the best in BUSCO analyses; BUSCO results for this assembly found more than 75% of expected single copy orthologs, and in total, at least partial evidence for 88.7% of expected single copy orthologs  of reads across libraries. Of these, 71.9% (SD = 10.7%) were single duplications, although some reads were duplicated hundreds of times Fig C in . Followide novo assembly of loci. The results presented below are for the variants called from the reference-aligned dataset, and without a specification of the population parameter p, which contained a total of 40,384 SNPs following the filtering of minor alleles and linked loci; specification of the population parameter to different values resulted in qualitatively similar results in downstream analyses, as did the de novo-assembled dataset (see Supporting Information for examples).Datasets varied in number of SNPs and genotyping rates . DatasetCs. melanura sampled, ranging from 0.007 to 0.05 when excluding five mosquitoes belonging to an unexpected and highly divergent genetic cluster  analysis found evidence of multiple genetic clusters shared across datasets. For the reference-aligned dataset, regardless of the specification of the population parameter p, the K value with the lowest mean cross entropy was K = 2. However, because both K = 3 and K = 4 were close to K = 2 in cross entropy, all three values of K are presented here.9,104 = 4.68, p<0.001, Table F in At all values of K investigated and regardless of dataset, an unexpected genetic cluster was detected by SNMF in the northeast. This cluster was comprised primarily of four individuals from New Hampshire and one from Maine, hereafter Cluster A . This geIn addition to this unexpected genetic cluster, both datasets had substantial evidence for additional genetic clusters. Assuming K = 3 and K = 4, southern populations  of this mosquito species formed a genetic cluster with >75% ancestry for all individuals  tree Fig G in . Cluster9,113 = 12.3, R2 = 0.51, P<0.001). Subsequent pairwise randomization MANOVAs found significant differences among the majority of populations across the five principal components retained  to their population from which they were sampled with greater than 50% membership probability , far outDue to the degree of genetic differentiation detected in Cluster A, genomic diversity in these mosquitoes was assessed separately from their geographic sampling location and presented alongside statistics for each population. Mean heterozygosity was similarly low across all populations sampled , with quCs. melanura prior to DNA extraction for population genomics. The sequence alignment of Cs. melanura from this study resulted in pairwise nucleotide identity of >99% for all Cs. melanura samples, including individuals belonging to Cluster A , desequenced –67, and equenced –70.de novo variant calling with Stacks  and south (9-VA and10-FL) were more akin to one another than to populations in other regions , as welCs. melanura such as heterogeneities in host choice across regions [Cs. melanura have been identified in populations across the eastern United States, including from mosquitoes trapped near several locations utilized in this study, albeit at low frequencies  and southern  populations. A lack of isolation by distance Click here for additional data file.