Spartina densiflora Brongn. along the Pacific coast of North America from San Francisco Bay to Vancouver Island. Studied populations showed very low genetic diversity, high levels of phenotypic variability when growing in contrasted environments and high intrapopulation phenotypic variability for many plant traits. This intrapopulation phenotypic variability was especially high, irrespective of environmental conditions, for those traits showing also high phenotypic plasticity. Within‐population variation represented 84% of the total genetic variation coinciding with certain individual plants keeping consistent responses for three plant traits  in the field and in common‐garden conditions. These populations have most likely undergone genetic bottleneck since their introduction from South America; multiple introductions are unknown but possible as the population from Vancouver Island was the most recent and one of the most genetically diverse. S. densiflora appears as a species that would not be very affected itself by climate change and sea‐level rise as it can disperse, establish, and acclimate to contrasted environments along wide latitudinal ranges.Species can respond to environmental pressures through genetic and epigenetic changes and through phenotypic plasticity, but few studies have evaluated the relationships between genetic differentiation and phenotypic plasticity of plant species along changing environmental conditions throughout wide latitudinal ranges. We studied inter‐ and intrapopulation genetic diversity (using simple sequence repeats and chloroplast DNA sequencing) and inter‐ and intrapopulation phenotypic variability of 33 plant traits (using field and common‐garden measurements) for five populations of the invasive cordgrass  Cp‐DNA sequences  and potentially highly polymorphic nuclear SSRs were employed to explore genetic diversity among populations established along the Pacific coast of North America. Phenotypic variation within and among populations of S. densiflora was also evaluated through analysis of 33 morphological, physiological, and biochemical traits, on plants sampled in the field that were compared to plants maintained in a common‐garden. Five invasive populations of S. densiflora along the Pacific coast of North America from San Francisco Bay to Vancouver Island were analyzed to examine the mechanisms allowing this species to deal with changing environmental conditions and the relationships between these mechanisms. Analyzing the level of intrapopulation phenotypic variability and the phenotypic variation of many plant traits between populations of the same species invading contrasted environments and in a common‐garden experiment, together with knowledge of genetic diversity, would allow us to know the nature of the above‐mentioned phenotypic variation and its level of phenotypic plasticity  is highly sensitive to environmental conditions  22.1Spartina densiflora populations were sampled in summer of 2010 at five invaded salt marshes along the Pacific coast of North America, covering its entire latitudinal distribution in North America . See Castillo et al.  were randomly selected, separated by a minimum of 1 m in attempt to sample potentially different genotypes, and individually marked in each of the five populations. Due to the low genetic diversity of S. densiflora populations recorded previously in San Francisco Bay and Humboldt Bay . The trnT‐trnF chloroplast DNA (Cp‐DNA) region was chosen as it is well documented in Spartina sequence databases (and then useful for chlorotype comparison between samples from different species and geographic locations). This region was amplified by polymerase chain reaction (PCR) in a Mastercycle thermal cycler  and underwent denaturation for 2 min at 94°C, followed by 35 cycles at 94°C for 30 s, 54°C for 30 s, and 72°C for 1 min 30 s, followed by an extension phase at 72°C for 7 min. PCR products were purified using a NucleoSpin Gel and PCR purification kit (Macherey‐Nagel GmbH & Co) and sequenced directly (on both directions) by Sanger technique at Macrogen Europe sequencer . The amplification of the trnT‐F region was performed in two sections using the primer pairs a and b to recover the trnT‐trnL segment and primer pairs c and f to recover the trnL‐trnF segment . Chloroplast DNA sequences were analyzed and compared with corresponding sequences from GenBank, obtained on 2.3Spartina maritima genomic data obtained by Illumina sequence assemblies , using the MISA (MIcroSAtellite Identification Tool) software . For the first test, we selected 20 primer pairs considering those with the highest number of expected amplicon size and number of motif repetitions. PCR was performed as described above with these 20 primer pairs in S. densiflora nuclear DNA and analyzed by electrophoresis in agarose gel . Eight primer pairs of which amplification products produced unique and clear bands were chosen for further analysis  and separated by electrophoresis in an ABI PRISM 16‐capillary 3130xl Genetic Analyzer . Alleles were identified and binned using GeneMapper 4.1 software .2.4S. densiflora is a heptaploid species (2n = 7x = 70), so up to seven alleles may be expected per locus. As allelic dosage could not be ascertained from the obtained chromatograms, SSRs were treated as “dominant markers”  using the GenAlEx 6.502 software , and the different “genotypes”  were scored. The intrapopulation genetic diversity parameters, effective number of alleles, Shannon Information Diversity Index , analogous to Wright's F’ST for dominant data, was obtained following standardization  alive, (2) spiked, and (3) dead stem density (shoot per m2), shoot (4) length (cm) and (5) diameter (mm), number of (6) live and (7) dead leaves, (8) total nonstructural carbohydrates in rhizomes (mg/g), (9) root biomass (g/m2), (10) rhizome biomass (g/m2), (11) belowground biomass , (12) dead shoot mass (g/m2), (13) live shoot biomass (g/m2), (14) dead leaf mass (g/m2), (15) live leaf biomass (g/m2), (16) aboveground biomass , (17) AGB: BGB ratio, (18) leaf area index (LAI) (m2/m2), (19) maximum leaf wide (cm), (20) leaf length (cm), (21) leaf area (cm2), (22) specific leaf area (SLA) (m2/g), (23) leaf longitudinal adaxial rolling (%), (24) leaf elongation rate (mm/day), (25) leaf water content (LWC) (%), content of (26) chlorophyll (Chl) a (mg/g DW), (27) Chl b (mg/g DW), (28) Chl a+b (mg/g DW), and (29) carotenoids (Car) (mg/g DW), (30) Chl:Car ratio, and (31) Chl a: Chl b ratio, and foliar content of (32) carbon and (33) nitrogen (mg/g). Leaves traits were measured in flag leaves to minimize differences due to the foliar ontogeny. These plant functional traits were chosen as they together describe appropriately the leaf characteristics and the tussock architecture of S. densiflora, being key factors in shaping the responses of this clonal species to its surrounding environment. Detailed methods and values of these plant traits for the studied populations of S. densiflora were reported previously by Castillo et al.  in a common‐garden experiment in the glasshouse facility of the University of Seville, Spain . Pot bases were kept permanently flooded to a height of 2 cm and watered with 20% strength modified Hoagland's nutrient solution . Common glasshouse conditions included substrate redox potential of 234 ± 5 mV, pH 8.3 ± 0.2, electrical conductivity 0.5 ± 0.0 mS/cm, mean monthly air temperature 23 ± 2°C, and mean monthly air relative humidity 62 ± 2%. Light conditions of mean radiation of 700 μmol photon m−2 s−1 at canopy level and a daily photoperiod of 16 hr  400 W, giving a continuum spectrum) were set up to imitate those recorded at higher latitude sites during summer in relation to photoperiod and light intensity. Spartina densiflora is a facultative halophyte that can germinate, establish, and develop in freshwater conditions . Comparisons of the dissimilarity matrices described above were tested by Mantel's test for matrix correspondence  was calculated for each plant trait to evaluate differences between populations in phenotypic trait expression in the field and in the common‐garden experiment. PIv for each trait was quantified as the percentage of change in absolute high and low mean trait values . The overall mean intrapopulation variability in field and in the common‐garden experiment was calculated as the arithmetic average of the variability for every plant trait.Intrapopulation phenotypic variability index (IVI) was calculated also for each plant trait and population in the field and in the common‐garden experiment as the percentage of change in absolute high and low trait values: F‐test, p < .05) using the plant trait or the geographic location as the grouping factor, respectively. Dependent variables were tested for homogeneity of variance using Levene's test and for normality using Kolmogorov–Smirnoff test. The relationships between PIv and intrapopulation variability index in the field and in the common‐garden experiment were analyzed using Pearson's correlation coefficient (r) and linear regressions. Total intrapopulation variability and total phenotypic plasticity  were compared using paired‐samples t‐test. Deviations were calculated as standard error of the mean (SE). The α‐level of significance was p < .05 for all tests. These analyses were carried out using SPSS 12.0 .Intrapopulation variability was compared among traits and among populations using one‐way analysis of variance (ANOVA) (33.13.1.1trnT‐L (GenBank accessions MG869717 to MG869721) and trnL‐F (GB accessions MG869712 to MG869716) regions were identical in the five populations examined in this study. No difference was encountered between these sequences and those previously reported for S. densiflora samples from California , but the AMOVA showed that interpopulation variance contributed to only 16% of the total genetic variation, whereas within‐population variation represented 84% of the total variation , and leaf adaxial rolling and elongation. In contrast, those traits showing lower PIv in the field were related to shoot and leaf morphologies, leaf number per shoot, leaf water content, Chl:Car ratio, and foliar carbon content  and in the common‐garden experiment , with similar mean values for the five studied populations in the field (56 ± 3%) and in the common‐garden experiment (60 ± 2%)    . In contrast, total intrapopulation variability was higher than total interpopulation variability in the common‐garden experiment .On the other hand, those plant traits that had higher IVI and higher PId Figure b. Thus, r = .493, n = 20, p < .05; Car: r = .435, n = 20, p = .055; dead shoot mass: r = .328, n = 50, p < .05)  Figure . Moreove4Spartina densiflora gradually invading the Pacific coast of North America along 12° of latitude from the late nineteenth century when it was first introduced to Humboldt Bay, until recently with the discovery of a new invasion in 2005 at Vancouver Island, are genetically very similar according to the chloroplast DNA sequences and the nuclear microsatellite loci investigated. This low genetic variation may be accentuated through the founder effect  is in the range of those reported previously for other invasive species such as S. alterniflora in China  Trevis. in the Mediterranean  = 0.109, Moran et al., Mikania micrantha Kunth in China . Moreover, this intrapopulation phenotypic variability was especially high, irrespective of environmental conditions, for those traits showing also high phenotypic plasticity, suggesting that intrapopulation phenotypic variability in S. densiflora would be regulated through the same mechanisms as those regulating phenotypic plasticity. Ensuring high levels of intrapopulation phenotypic variability for key plant functional traits would allow S. densiflora to respond adequately to the changing environment  accumulating more Chl b and Car in the field and in the glasshouse and some individuals from high latitudes  showing the opposite response. Thus, although environmental conditions, hybridization, and polyploidy largely determined plant traits in S. densiflora, our results point to a genetic or epigenetic component influencing certain traits due to changing selection pressures along a wide latitudinal range . This result is in agreement with the slight but significant increase in genetic differentiation when increasing geographic distance. Thus, those individuals from lower latitudes showing higher values for Chl o et al.  recordedS. densiflora is carried out through hydrochorous propagules rafting on local and regional currents (Morgan & Sytsma, S. densiflora populations produce many viable seeds (‘Kittleson & Boyd, S. densiflora for key plant traits would promote seedlings to acclimate and to colonize new salt marshes with contrasted environmental conditions. S. densiflora started its invasion of the Pacific coast of North America in the late nineteenth century in Humboldt Bay (Spicher & Josselyn, S. densiflora appears as a species that would not be very affected itself by climate change and sea‐level rise as it can disperse, establish, and acclimate to contrasted environments along wide latitudinal ranges. Global climate change may even favor some polyploid taxa that can tolerate stressful environments due to greater phenotypic plasticity (Meyerson et al., Halophytes need to have efficient medium‐ and long‐distance dispersal mechanisms as they inhabit in salt marshes that are ephemeral ecosystems (Fagherazzi, S. densiflora that has invaded a broad latitudinal gradient along the Pacific coast of North America is characterized by low genetic divergence between populations, high phenotypic plasticity related to local conditions, and high and fixed intrapopulation polymorphism in some functional traits, which appears to be a key feature of this allopolyploid invasive species.In summary, our results show that None declared.J.M.C. and B.G.T. involved in the conceptualization, in the methodology, and in the investigation and wrote the original manuscript. E.F. involved in the conceptualization. B.J.G. involved in the conceptualization, in the methodology, and in the investigation and reviewed and edited the manuscript. D.V., H.R., J.K., O.L., S.D., and A.S. involved in the methodology. M.A. involved in the conceptualization, in the methodology, and in the investigation and reviewed and edited the manuscript.


Although the genetic structure of rice germplasm has been characterized worldwide, few studies investigated germplasm from Thailand, the world’s largest exporter of rice. Thailand and the International Rice Research Institute (IRRI) have diverse collections of rice germplasm, which could be used to develop breeding lines with desirable traits. This study aimed to investigate the level of genetic diversity and structures of Thai and selected IRRI germplasm. Understanding the genetic structure and relationships among these germplasm will be useful for parent selection used in rice breeding programs.Oryza species. The Thai accessions were selected from all rice ecologies such as irrigated, deep water, upland, and rainfed lowland ecosystems. The IRRI accessions were groups of germplasm having agronomic desirable traits, including temperature-sensitive genetic male sterility (TGMS), new plant type, early flowering, and biotic and abiotic stress resistances. Most of the InDel markers were genes with diverse functions. These markers produced the total of 127 alleles for all loci, with a mean of 6.68 alleles per locus, and a mean Polymorphic Information Content (PIC) of 0.440. Genetic diversity of Thai rice were 0.3665, 0.4479 and 0.3972 for improved cultivars, breeding lines, and landraces, respectively, while genetic diversity of IRRI improved and breeding lines were 0.3272 and 0.2970, respectively. Cluster, structure, and differentiation analyses showed six distinct groups: japonica, TGMS, deep-water, IRRI germplasm, Thai landraces and breeding lines, and other Oryza species.From the 98 InDel markers tested for single copy and polymorphism, 19 markers were used to evaluate 43 Thai and 57 IRRI germplasm, including improved cultivars, breeding lines, landraces, and 5 other Thai and IRRI germplasm were significantly different. Thus, they can be used to broaden the genetic base and trait improvements. Cluster, structure, and differentiation analyses showed concordant results having six distinct groups, in agreement with their development, and ecologies.The online version of this article (doi:10.1186/1939-8433-5-19) contains supplementary material, which is available to authorized users. Oryza sativa L.) have been studied worldwide . Howeves et al. ; Yu et as et al. ), and tos et al. ).http://www.fao.org/). By its shape and geography, Thailand can be divided into four regions: the mountains and forests of the North; the vast rice fields of the Central Plains; the semi-arid farm lands of the Northeast plateau; and the tropical islands and long coastline of the peninsula South. Each region has different rice-growing environments. The Northern region produces 25% of the total rice production where upland rice is grown on hilly areas, while lowland rice is grown in lower valleys and some terraced fields. The Central region produces 30% of the total rice production where rice is planted almost everywhere across the area in wet season, and in dry season rice is planted to irrigated area of about 450,000 ha. The Northeastern region produces 41% of the total rice mainly rainfed lowland rice. Only a small portion of the total rice is produced from the Southern region where rice is planted in the west and east coasts of the peninsula (http://www.irri.org).In Thailand, rice ecologies can be classified as irrigated, rainfed lowland, deep water, and upland ecosystems. Rainfed lowland is the majority of rice growing area, followed by irrigated, deepwater and upland. Different ecologies also results in different amount of rice production. The highest average rice yield was from irrigated ecosystem, followed by deep water, rainfed lowland, and upland ecosystems. The average rice yield in the wet season is constant at about 2 t/ha  and several ecotypes. Several efforts have been made to assess the genetic diversity within Oryza sativa at both phenotypic and molecular levels. To estimate genetic diversity among Oryza species, several types of molecular markers, particularly simple sequence repeats (SSR), have been used . Polymou et al. ; Provan u et al. ). Alternu et al. ). SSCP iu et al. ; Muangpru et al. ). Recentu et al. ), comparu et al. ), phylogu et al. ) and fitu et al. ). FurtheThe International Rice Research Institute (IRRI) has large collections of characterized rice germplasm. These germplasm could be used to develop breeding lines with desirable traits, and they are available to other countries. Several of IRRI germplasm have been used for improvement of rice breeding programs in Thailand. Understanding the genetic diversity and genetic relationships among Thai and IRRI germplasm is useful for parent selection to produce hybrids or to improve rice population (Moose and Mumm ). AlthouBy testing the 4 selected rice accessions with the 98 InDel markers, only markers that were presented as single copy and showed polymorphism in at least 3 out of the 4 rice accessions were selected for genetic analysis. A total of 19 InDel markers were used to evaluate genetic diversity in 101 rice accessions  to 12 alleles (Os07g27590), with the average of 6.68  as a representative for the tropical Japonica, five Thai and one IRRI accessions were grouped with Japonica rice lines by clustering closer to Azucena. All the Thai accessions in this group are upland rice. Group (G) II were clusters of Indica, which includes four sub-groups: GII-1, GII-2, GII-3, and GII-4, and additional two isolated single accessions. The GII-1 had 11 accessions which were all Thai landraces and Thai local breeding lines, except O. rufipogon, and one improved cultivars . KDML105 (No. 100), which is the famous Thai jasmine rice, was also sorted into this group by clustering with its derivative  and a Thai landrace . The GII-2 had eight accessions that were all TGMS types, with the exception of No. 29. The GII-3 was the largest group with 60 accessions, most of which were IRRI germplasm. It should be noted that seven of the Thai improved lines and three Thai breeding lines were in this group  was equal to six. The population structure based on the k = 6 showed similar results to the UPGMA tree , TGMS (green), deep water and mixtures (blue), IRRI germplasm (yellow), the other Orzya species (pink), and Thai landraces and breeding lines (light blue) . All Thai rice in this group was upland rice. The second group in green contained all TGMS lines with the Q-values ranged from 0.87 to 0.985. The TGMS line, tms2 KDML105 (No. 50), was not in this group but it had the highest Q value (Q = 0.369) with group of the other Oryza species. The third group in blue had the Q values ranging from 0.808 to 0.985. The majority of accessions in this group were Thai deep water rice. The fourth group was the largest group (shown in yellow) with Q values ranging from 0.812 to 0.984, most of which were IRRI germplasm, except three Thai improved cultivars from irrigated area. The fifth group in pink contained all the other Oryza species with their Q-values higher than 0.98, except for the O. rufipogon (No. 38) that was grouped with Thai landraces. The last group in light blue had the Q values ranging from 0.811 to 0.987. Four out of the eight accessions in this group were Thai landraces , while the remaining accessions were all Thai commercial lines from the Northeast.Using the data of 19 polymorphic InDel markers, the model-based method was performed to determine the genetic structure among all 101 samples. The Bayesian-based clustering method demonstrated that the highest log likelihood score was obtained when the number of populations  Figure . The firJaponica, TGMS, deep water and mixtures, IRRI germplasm, the other Oryza species, and Thai landraces and breeding lines were 0.256, 0.239, 0.303, 0.255, 0.565, and 0.355, respectively  were ranged from 4.8-14.0, 6.2-6.8 and 0.63-0.70, respectively . Small i et al. ). Similai et al. ) also shHere we showed that SSCP InDel markers can be used to study plant breeding. SSCP Indel gene-based markers are very specific and can utilize their known positions in the rice genome. In addition, SNP and InDel are abundant in rice  is higher than the genetic diversity of the 7 wild rice species (0.436) reported by Ram et al.  is the most divergent species among the other Oryza species, which is also in agreement with reports from previous studies  and Oryza latifolia No. 41, (CCDD genome) are grouped together, and separated from Oryza brachyantha, supporting that they are in the officinalis complex, including diploid CC and tetraploid CCDD genomes. Howeve et al. . Our rei et al. , Jacquemi et al. ; Lu et ai et al. ). Similai et al. ).The selected IRRI germplasm  showed lower genetic diversity than that of the Thai commercial cultivars (improved and breeding lines) and Thai landraces. The Thai breeding lines had the highest genetic diversity while the IRRI breeding lines had the lowest. Interestingly, genetic diversity of Thai landraces was lower than that of Thai breeding lines, possibly because the Thai landraces were selected only from the North and the Central parts of the country, while the breeding lines were from all over Thailand.Oryza sativa corresponding to the Indica and Japonica subspecies, similar to other studies , which is considered the progenitor of Oryza sativa, was most related to Oryza sativa. Interestingly, the famous Thai jasmine rice, KDML105 (No. 100) was grouped with Thai landraces and breeding lines, and O. rufipogon, which indicates that the strain is native to Thailand. Our analyses support the existences of five subpopulations of Oryza sativa, similar to earlier studies . Both cs et al. ; Zhao ets et al. , Ali et s et al. ; Chen ets et al. ). Severas et al. ), and clo et al. ) in thisJaponica rice. Deep water rice lines were planted in specific areas having high levels of water in the Central plain, and they were clustered together in a distinct group. Interestingly, three out of the four rainfed lowland rice lines from the South showed genetic structure that is similar to the deep water rice. In addition, groups that were sorted by population structure also displayed significant genetic difference among them.Although Thailand is quite small, 513115 sq. km. (approximately the same size as France), different ecologies and geography in distinct parts of the country could have some effects on our rice diversity. The first three of the four rice ecologies: irrigated, deep water, upland, and rainfed lowland ecosystems, showed distinct groups for both cluster and structure analyses. The irrigated rice lines, planted in irrigated areas in the Central plain, were grouped together and showed similar genetic structure to IRRI germplasm. Most of the tested upland rice lines were planted in hilly areas in the North, and they were grouped with tgms genes were grouped together by cluster analysis into one sub-group of Indica. Results from structure analysis also supported this information, with the exception of tms2 KDML105, which showed genetic structure similar to the group of the other Oryza species. Results from cluster and structure analyses indicated that tms2 KDML105 (No. 50) was quite distinctive from the other TGMS lines, and it contained several different genetic fragments, including the other Oryza species (Q = 0.369), TGMS (Q = 0.266), Thai landraces and breeding lines (Q = 0.141), and IRRI germplasm (Q = 0.101), in agreement with its genetic background containing some part of Japonica genome , and itm et al. ). C21489japonica rice, and genetic diversity is present in this set of the available germplasms. Differentiation analysis indicated that groups of IRRI germplasm were significantly different from Thai groups. Thus, these germplasm can be used to broaden the genetic base and trait improvements in rice breeding programs. Cluster and structure analyses showed concordant results having six distinct groups, and differentiation analysis supported that they were significantly different from each other. The results also indicate that TGMS lines which could be used as female parents were different from the other groups making them good candidates used to create rice hybrids having high yields. Genetic diversity and genetic relationship among these germplasms will be useful for parental line selection used in rice breeding programs and in hybrid production.Our study showed the utility of SSCP InDel markers for genetic analysis of Thai and IRRI rice germplasm, as alternative to SSR markers. The resulting genetic structure and differentiation of these samples were in agreement with their ecologies and their known information on their development. The results indicated that genetic diversity of Thai commercial rice lines  and Thai landraces were higher than that of the tested rice germplasms obtained from IRRI. Our molecular analysis indicated that some of our cultivars were Oryza species. The commercial cultivars were cultivars grown in all rice ecologies through out the country such as irrigated area, rain fed low land, up land, and deep water. These commercial cultivars were 11 improved and 16 local breeding lines. The improved lines were cultivars with high yielding and/or cultivars with agronomic desirable traits. The improved cultivars were classified by their development through crossing among local cultivars and/or with other genetic sources, and their recent pedigrees were known , new plant type, early flowering, and biotic and abiotic stress resistances , and Nipponbare were used in this study (Table  Tompson ).http://www.gramene.org/; and http://shenghuan.shnu.edu.cn/ricemarker, last accessed on December, 2011), primers were designed using the Primer 3 program (http://biowb.sdsc.edu/CGI/BW.cgi) to amplify regions of the genes containing at least two SNPs. To increase the possibility of identifying polymorphisms between rice accessions and to facilitate polymorphism observation using SSCP, sizes of the PCR products amplified from these primers were about 200–300 bp. The markers were first used to test polymorphism among 4 rice accessions  representing indica commercial Thai rice, landrace, japonica and other Oryza species. The markers show polymorphism in at least 3 rice accessions and shown the presence of only single copy gene were selected to test the whole set of rice samples. Details of the selected InDel markers used in this study were shown in Table A total of 98 InDel (Insertion-Deletion) markers were developed for the SSCP analysis, most of which were gene-based markers. Some of the 98 markers were reported by Pitnjam et al.  and SheOryza species}, and 6 {Thai landraces, Thai improved cultivars, Thai breeding lines, IRRI improved cultivars, IRRI breeding lines, and other Oryza species} sources of germplasm. In addition, pairwise genetic distances between rice accessions were calculated based on the similarity coefficients following Nei and Li ([k) required for accurate data interpretation without prior information on the number of groups of accessions at which the individuals were studied. The membership probabilities (Q) calculated from STRUCTURE ≥ 0.80 were used to assign rice accessions to clusters. Rice accessions with membership probabilities < 0.80 for all clusters were used to detect possible genetic exchanges among groups of rice accessions. In order to describe the population genetic structure and variability among populations, the Analysis of Molecular Variance (AMOVA) was performed using the ARLEQUIN 3.11 software  values calculated by AMOVA were used as inter-population genetic distance measurements as described by Huff  for each maker . The in and Li . The re and Li . Bayesi and Li  was perr et al. ). The toby Huff .


SWIO). This is epitomized by the lack of information for lethrinid fish, which support socioeconomically important fisheries in the region. This study combines comparative phylogeographic and population genetic analyses with ecological niche modeling to investigate historical and contemporary population dynamics of two species of emperor fish (Lethrinus mahsena and Lethrinus harak) across the SWIO. Both species shared similarly shallow phylogeographic patterns and modeled historical (LGM) habitat occupancies. For both species, allele frequency and kinship analyses of microsatellite variation revealed highly significant structure with no clear geographical pattern and nonrandom genetic relatedness among individuals within samples. The genetic patterns for both species indicate recurrent processes within the region that prevent genetic mixing, at least on timescales of interest to fishery managers, and the potential roles of recruitment variability and population isolation are discussed in light of biological and environmental information. This consistency in both historical and recurrent population processes indicates that the use of model species may be valuable in management initiatives with finite resources to predict population structure, at least in cases wherein biogeographic and ecological differences between taxa are minimized. Paradoxically, mtDNA sequencing and microsatellite analysis of samples from the Seychelles revealed a potential cryptic species occurring in sympatry with, and seemingly morphologically identical to, L. mahsena. BLAST results point to the likely misidentification of species and incongruence between voucher specimens, DNA barcodes, and taxonomy within the group, which highlights the utility and necessity of genetic approaches to characterize baseline biodiversity in the region before such model‐based methods are employed.Analysis of genetic variation can provide insights into ecological and evolutionary diversification which, for commercially harvested species, can also be relevant to the implementation of spatial management strategies and sustainability. In comparison with other marine biodiversity hot spots, there has been less genetic research on the fauna of the southwest Indian Ocean ( Combined demographic–genetic studies can reveal the spatial and temporal scale at which evolutionary forces are occurring Waples,  and, by The southwest Indian Ocean (SWIO), which forms a subdivision of the tropical Indo‐Pacific, is renowned for its diverse marine habitats and resources, including an ichthyofaunal richness  methods. To provide an additional historical context, we combined genetic studies with ecological niche modeling (ENM), which has been shown to provide novel insights into the influence of historical biogeography on genetic variation in marine species  and contemporary population genetic structure across the SWIO. As the Lethrinidae is one of the most important families of fish for artisanal, recreational, and subsistence fisheries  were collected from commercial or subsistence catches landed in seven locations across the SWIO between 2009 and 2012 Figure .c oxidase subunit I (COI) gene was amplified by polymerase chain reaction (PCR) with species‐specific primers  for a subset of individuals. PCRs were performed in a total volume of 20 μl, containing 4 μl template DNA, 2 mmol/L MgCl2, 0.5 μmol/L forward primer and 0.5 μmol/L of reverse primer, 0.2 mmol/L dNTP mix , 1× reaction buffer , and Taq polymerase . The PCR thermoprofile was: 180 s at 95°C, followed by 45 cycles of 30 s at 95°C, 45‐s annealing at 55°C for both primer sets, and 60 s at 72°C, followed by a final 5‐min extension at 72°C. PCR products were then purified using EXOSAPIT and sequenced from both directions on an Applied Biosystems 3500 platform using the respective PCR primers. Sequences were aligned using the Clustal W . To ensure robustness of genotypes, we employed a double genotyping as described by McKeown, Arkhipkin, and Shaw  and one trinucleotide (96RTE) microsatellite loci described by Van Herwerden, Benzie, Peplow, and Davies ; Van Herand Shaw .2.2L. mahsena and 104 L. harak samples. All analyses of mtDNA sequences were conducted in Arlequin 3.5.1.2 , in addition to indices of haplotype (h) and nucleotide (π) diversity , and observed (HO) and expected (HE) heterozygosities were calculated using GENALEX 6 , allelic richness  Slatkin, K = 1–6 (10 independent runs per K). Genetic relationships among samples were visualized using factorial correspondence analysis (FCA) in GENETIX , self‐classification tests  were employed in GENECLASS 2 , paleodistribution modeling was conducted. Post‐1950s species occurrence data were obtained from the Global Biodiversity Information Facility , along with the Ocean Biogeographic Information System (http://www.iobis.org), resulting in a total of 335 occurrences of L. harak and 152 of L. mahsena. Contemporary bioclimatic data, specifically generated for marine environments, were collected at 5‐min resolution from MARSPEC  of 33.1L. mahsena revealed the presence of two highly divergent clades within the SWIO, which were separated by 20 mutational steps ; however, BLAST searches of clade B individuals also identified 99% sequence similarity to L. mahsena voucher specimens from India ; this was followed by 97% sequence similarity to all available L. atkinsoni voucher specimens from Western Australia, the Philippines, and Taiwan . The average sequence divergence between clade A and clade B was 4.6% . This pattern was also supported by assignment tests which found complete self‐classification to clade with the exception of a single individual from clade A, which had a similar probability of assignment to both clades .BLAST searches of clade A individuals revealed a 99% sequence similarity to 3.2L. harak  and L. mahsena . Network representation of L. mahsena (excluding clade B) revealed a single haplogroup dominated by a single common haplotype present across all SWIO localities. Similarly for L. harak, a single haplogroup was dominated by two common haplotypes , pairwise tests revealed all significant values to be associated with two samples (Mauritius and Mozambique Pemba), with only the comparison between Mauritius and Mozambique Pemba remaining significant after Bonferroni correction , and although pairwise ΦST was high in many cases, they were all nonsignificant  nor Fu's Fs  tests detected global deviations from neutrality for L. harak. For L. mahsena Fu's Fs was significant , but Tajima's D was not . Mismatch analyses were compatible with expansions for L. mahsena  but not in L. harak .Owing to small sample sizes, demographic tests were conducted globally. Neither Tajima's 3.3L. harak from four sample locations and 72 L. mahsena individuals (excluding those belonging to clade B) from six sample locations were screened across nine and 10 microsatellite loci, respectively. Levels of intrasample genetic variability were similar in both species  than for L. harak (FST = 0.023) but highly significant in both cases. Pairwise FST estimates were also high and significant between all samples for both L. harak and L. mahsena  were higher for s Figure ; howevers Figure . For L. s Figure  supportes Figure .gq fell within the 95% confidence limits expected for panmictic populations for all samples of L. harak  and L. mahsena (79.56%)) but did identify related dyads within all samples for both species except Madagascar, Belo sur Mer for L. mahsena.Values of relatedness based on rk Figure ; howevera Figure . Maximuma Figure  and S5 i3.4SD = 0.003) and 0.980 (SD = 0.016) for L. harak and L. mahsena, respectively, indicating very good model performance. Present‐day models for both L. harak and L. mahsena appear to accurately reflect the known contemporary ranges of both species, with suitable habitats aggregated in coastal environments across the Indian and western Pacific Oceans  was in excess of even conservative thresholds of species‐level divergence  is in the gray zone of the species divergence continuum  have a greater similarity (99%) with L. lentjan voucher specimens from Iran, whereas supposed L. mahsena sequences from Japan (JF952782.1) exhibit greatest similarity (91%) to L. rubrioperculatus. In general, the meristic and morphological features of emperor fish are conservative  co‐occurring within samples all described initially as 4.2L. mahsena and L. harak during the LGM that would be expected to have decreased their range‐wide population sizes. Therefore, as for many other SWIO taxa including numerous reef‐associated fish  suggested a marked reduction in suitable habitat for both 4.3ST values were high for both species, pairwise comparisons between samples were largely nonsignificant. In contrast, highly significant nuclear (microsatellite) differentiation was reported among samples for both species. Such a pattern is compatible with the greater statistical power of the nuclear data set as estimated by POWSIM. Similarly, Muths et al.  were significant, including comparisons between nearby samples, with no clear geographical pattern or significant IBD . The structuring for both species was also significant upon conservative correction for null alleles  tests, the smaller sample sizes for L. mahsena may have inflated FST values  were found in all samples for both species. While the large number of dyads that could not be unanimously classified to a single relationship category  highlights the resolution threshold of the data, the results for both allele frequency and allele‐sharing analyses indicate that, even though sample sizes are small in some cases, the genetic heterogeneity cannot be dismissed as statistical noise but rather reflects some changes in the composition that may be a useful tool for better understanding recruitment dynamics and connectivity in these species . Differentiation of Mascarene populations has been observed for several other reef‐associated species , and limited mixing of larvae from genetically different sources . Facets of the genetic structure exhibited some congruence with known biogeographic boundaries and patterns of population isolation inferred from other species. For s et al. . Such ans et al. . The Mozs et al. . Such fes et al.  and may s et al.  may enhas et al.  and be es et al. . Berry, s et al.  reportedL. nebulosus in Australian waters (Berry et al., L. harak and L. mahsena reported similar historical modeled habitat occupancy and phylogeographic patterns, while resolved genetic patchiness points to similar recurrent population processes in both species. Therefore, while we agree that making sweeping predictions from alleged model organisms can be dangerous (Bird et al., Disentangling the exact roles of recruitment heterogeneity and restricted gene flow will require more sensitive genetic assays and would benefit from analysis of age‐segregated samples (Burford, Carr, & Bernardi, None declared.P.W.S. and N.J.M. gained funding for and conceived the project with input from A.J.E.H. and A.T.; data were collected and analyzed by A.J.E.H. and A.T.; and J.P. conducted the ecological niche modeling. A.J.E.H. and N.J.M led the writing of the manuscript, and all authors contributed to editing the manuscript.All data will be uploaded on DRYAD. Click here for additional data file.


Anolis lizard, Anolis distichus, to investigate whether adaptive trait divergence is consistently associated with speciation, whereby genetic divergence is observed with neutral markers, or whether locally adapted traits are maintained in the face of continued gene flow.Studies of geographic variation can provide insight into the evolutionary processes involved in the early stages of biological diversification. In particular, multiple, replicated cases of geographic trait divergence present a powerful approach to study how patterns of introgression and adaptive divergence can vary with geographic space and time. In this study, we conduct replicated, fine-scaled molecular genetic analyses of striking geographic dewlap color variation of a Hispaniolan We find instances where shifts in adaptive dewlap coloration across short geographic distances are associated with reproductive isolation as well as maintained in the face of gene flow, suggesting the importance of both processes in maintaining geographic dewlap variation.Our study suggests that adaptive dewlap color differences are maintained under strong divergent natural selection, but this divergence does not necessarily lead to anole speciation.The online version of this article (doi:10.1186/s12862-016-0763-4) contains supplementary material, which is available to authorized users. Geographic trait variation is widely found within species . The evoComparative studies of naturally replicated hybrid zones where adaptively divergent, closely related taxa come into contact and potentially interbreed can provide a powerful approach to study how patterns of introgression and adaptive divergence can vary with geographic space and time . In partAnolis distichus, provides an ideal system to investigate whether adaptive trait divergence consistently leads to the same genetic outcome. Across Hispaniola, A. distichus’ dewlap (an extensible throatfan) varies adaptively in response to heterogeneous environments, whereby dewlaps tend to be larger, orange and less bright in wetter habitats, while in drier habitats, dewlaps are smaller, yellow and relatively brighter  and A. bimaculatus [bimaculatus series]) [A. punctatus and A. occultus) [We investigated patterns of mtDNA differentiation along transects by obtaining mtDNA sequence data for all individuals sampled from sites along each transect (es e.g. –29). We . We N = series])  and two ccultus) . Our comccultus) , 20, 27 2, 2.5 μL of 0.5 mM dNTP solution, 0.125 μL of NEB Taq polymerase and 11.4 μL H2O. Our thermocycling protocol involved an initial denaturation at 95 °C for 4 min, followed by 30 cycles of 95 °C for 35 s, annealing at 52 °C for 35 s, and extension at 70 °C for 2 min 30 s. We sent successfully amplified PCR products to a commercial facility for purification and Sanger sequencing . We assessed each sequence chromatograph for quality in Geneious v4.6.1 ) ns (DPS) , calculans (DPS) . DPS hasilibrium , 51.K) [a priori information about where individuals were sampled. We ran analyses for 105 iterations following a burn-in period of 104 iterations for each value of K ranging from 1–15. We chose a maximum K value of 15 because we expected that there would be at least 8 different genetic clusters across our transitional transects if genetic differentiation is associated with adaptive dewlap color transition . We ran 10 independent runs of K to ensure consistent probability estimates and that particular runs were not trapped in different modes in the parameter space [K, we used log probabilities Pr(X|K) and calculated ΔK [K was 1.We conducted Bayesian clustering analyses using the program STRUCTURE v2.3.3, which uses a Markov chain Monte Carlo algorithm to probabilistically assign individuals to different genetic clusters (K) . We infeK) , and dider space . The avelated ΔK  using thlated ΔK . We alsolated ΔK , we assiWe interpreted results of distinct nuclear genotypic clusters at either ends of the transect to be evidence for neutral genetic divergence. We diagnosed how far along populations were in the speciation continuum by the frequency of admixed individuals. If geographic genetic structure was evident but the frequency of admixed individuals was high and widely spread across different populations, we considered this to reflect low levels of restricted gene flow, and that the populations were at an earlier stage in the speciation continuum. In contrast, a limited number or no evidence of admixed individuals indicated a strong reduction of gene flow, likely representing populations in the later stages of speciation.Along all transitional transects, we confirmed the presence of a phenotypic transition in dewlap color and pattern. At one side of each transect, males exhibited dewlaps that were completely yellow or had a small proportion of orange, while towards the other side of the transect, we found males with a higher proportion of orange in their dewlaps Figs.  and 2. TWe found similar dewlap phenotypes across each control transect. All males sampled along C3 had dewlaps with greater than 60 % orange, while individuals sampled along all other control transects had very little orange in the dewlaps; the two individuals at C2-1 that exhibited greater than 50 % orange in the dewlap was diffuse in coloration  and sites T1b-2 and 3  which were each at least 4 times greater than any other adjacent sites along the same transect, after correcting for differences in geographic distance  did not form monophyletic groups . Our finding that most A. distichus subspecies are non-monophyletic is inconsistent with other phylogenetic studies of the group [A. d. dominicensis that appear to be geographically structured; haplotypes from transect C1 in central Hispaniola are most closely related to haplotypes sampled from A. d. favillarum and Haitian A. distichus subspecies, while A. d. dominicensis haplotypes sampled from northern Dominican Republic  formed a separate group . These pairs differed between sites, except for DISTCC7 and DISTAH6, which showed significant LD in two sites along T4 (T4-1 and T4-3).The microsatellite loci exhibited significant deviations from HWE in 57 of 364 intrapopulation assessments  that, after correcting for differences in geographic distance, were at least 7 and 3 times greater respectively than that found along any other transect  while the other included some T1a and b populations   , whereby there was no evidence of genetic differentiation despite bimodal phenotypic variation. Patterns of mtDNA variation suggest that introgression is occurring and nuclear variation at microsatellite loci does not show evidence of any genetic structure. This is further supported by pairwise estimates of ΦST and DPS that indicate similar levels of pairwise genetic differentiation to that found along the control transects. Despite the homogenizing effects of gene flow, the maintenance of dewlap color variation at such a fine spatial scale suggests that strong divergent natural selection is acting on loci underlying dewlap color differences between spatially close sites while neutral regions of the genome are homogenized with gene flow. This also suggests that the genes underlying dewlap color likely have different evolutionary trajectories that is not reflected by the results of our analyses of neutral markers. Together, these results support the importance of divergent natural selection, rather than neutral processes, in driving and maintaining dewlap color variation along these transects. These transects are similar to previous studies that have shown that adaptive trait divergence between populations can be maintained in the face of gene flow (e.g. [Our study examining numerous transitions in adaptive dewlap coloration in ow e.g. –60), inc, incAnolow  exhibit similar levels to that found along transects that show no genetic differentiation . Mitochondrial haplotype structure has been shown to reflect historic geological events while the more quickly evolving microsatellite loci are more likely to reflect contemporary gene flow [A. d. dominicensis and A. d. ignigularis. While we know that these two subspecies along T1a were once isolated by a seawater channel that separated the Samaná Peninsula from mainland Hispaniola [We find patterns consistent with the expected signature of speciation along three transects  whereby adaptive dewlap color divergence is associated with genetic differentiation. The results of our control transects, showing no genetic differentiation where there was no change in dewlap color, further support the possibility of speciation occurring at these three transitional transects. The transects, however, exhibited differing levels of genetic differentiation and therefore likely represent different stages along the speciation continuum. T1a and b appear to be at an earlier stage along the speciation continuum relative to T2. Along T1a and b, phylogenetic and STRUCTURE analyses show distinct mtDNA clades and nuclear genetic clusters on either side of the transect, respectively. Both mtDNA and nuclear markers, however, suggest a low reduction in gene flow between the phenotypically divergent populations: mtDNA haplotypes prevalent on the western side of the transect were still found at a low frequency in the middle and other side of the transect, and nuclear markers showed evidence of admixed genotypes that decreased in frequency from the middle of the transect to the east. Furthermore, pairwise genetic distance estimates  whereby both parental genotypes and admixed individuals co-occur, and pairwise distance estimates between T2-2 and T2-2.5 are at least 3 times higher than that found along any other transect, despite closely related mtDNA haplotypes showing evidence of introgression. This pattern was also shown in Ng and Glor , but eviA. disitchus and that the dewlap does not serve as a ‘magic trait’ [A. distichus subspecies [A. d. favillarum along T4, which only differs in dewlap color, does not show genetic structure, despite exhibiting the most abrupt dewlap color shift of all transects.While three transects support the predictions of speciation, it remains unknown whether any of the transitional transects we investigated in this study will progress to speciation, or whether the current stages we observe represent stable states of migration-selection equilibria . The prec trait’ , 73. Forbspecies . Differebspecies , 74, 75.bspecies , this maA. distichus showed that geographic variation in adaptive dewlap color is associated with both local adaptation and speciation. At some transitional transects, there appears to be strong selection maintaining adaptive dewlap coloration in the face of gene flow. At other contact zones, we found signatures of speciation whereby adaptive dewlap divergence is associated with genetic differentiation, indicating some reduction in gene flow across the transects. Our results are consistent with previous work suggesting that within-island speciation in anoles is limited to the four large Greater Antillean islands [A. d. ravitergum and A. d. ignigularis across T2 [Our analysis of multiple replicates of dewlap color divergence in  islands . Despitecross T2 , 11, 68.


Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species . These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations . Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity . This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars.The availability of information on the genetic diversity and population structure in wheat ( Triticum aestivum L.) is a staple cereal crop for people worldwide. Bread wheat is an allohexaploid with three distinct genomes (AABBDD) , Oryza sativa L. (∼40 times), and Zea maize L. (∼60 times) (Wheat ((AABBDD) . The gen0 times) .(PstI/MspI) to greatly reduce genome complexity and create more homogeneous libraries for sequencing than the one enzyme protocol  and simple sequence repeats (SSRs) are the most common DNA marker for genetic studies.. . Howeverprotocol . The GBSprotocol .Puccinia graminus Pers.:Pers. f. sp. tritici Eriks. E. Henn.) resistance, exceptional winter hardiness and improved agronomic performance relative to existing cultivars. Generally, single and three-way crosses are used in this wheat breeding program to develop new breeding populations. At least one parent of the single cross will be a Nebraska-developed or adapted line and usually two parents of the three-way cross will be from Nebraska or Kansas and selected for good end-use quality  are grown in one location (Lincoln or Mead NE). The F3:5 lines are planted in an observation nursery at Lincoln and Mead NE for selection . Starting from the F3:6, lines are tested in eight locations in Nebraska in an augmented design as the preliminary yield trial. Based on traits such as plant height, grain yield, days to flowering, grain volume weight, resistance to disease and insects, end-use quality and genomic selection for yield, 57 lines are selected and advanced to the advanced yield trial (F3:7 Nebraska Triplicate Nursery). In the next growing season, approximately 25 F3:8 lines are advanced to the elite yield trial  where they continue to be tested until they are released or discarded. Nebraska breeding program uses this protocol each year to release the best line(s) which contain high levels of winter hardiness, disease resistance, agronomic performance, and good end-use quality.  consider how plant breeding and selection may have affected the genetic diversity and population structure.The objectives of this study were to (i) characterize the allelic and genetic diversity, and population structure of Nebraska winter wheat genotypes at the F3:6 lines (Nebraska Duplicate Nursery) were derived from 800 to 1000 crosses among Nebraska’s adapted cultivars or lines. The parents of these crosses are from wheat breeding programs in the Great Plains, and fewer crosses to globally important wheat lines. The breeding lines used in this study were derived from 80 crosses of the over 800 that were initially made. Pedigree information is presented in Supplementary Table 3:6 Nebraska Duplicate Nursery were grown in nine locations . Each year was the start of a new crossing, breeding, and selection cycle. Moreover, the F3:6 nurseries are genotyped using GBS each year.A set of 270 FDNA was isolated and purified from the wheat leaves of 2–3 young 2-week-old seedlings using BioSprint 96 DNA Plant Kits  following the manufacturer’s instructions. The GBS method was performed based on the protocol of The summary statistics of all 25,566 SNP markers such as gene diversity (GD), polymorphism information content (PIC), minor allele frequency (MAF), and observed heterozygosity were calculated using PowerMarker software V 3.25 . The PICij and Pik are the frequencies of jth and kth alleles for marker i, respectively.where Pk-values (an assumed fixed number of subpopulations) from 1 to 10 in the population. Three independent analyses were used for each k-value and the program was set on 100,000 as burn-in iteration, followed by 100,000 Markov chain Monte Carlo (MCMC) replications after burn-in (k for the current population was determined by STRUCTURE HARVESTER (A model-based (Bayesian) method with 25,566 SNPs was utilized to evaluate the possible number of subpopulations in the current lines. The analysis of population structure was performed using STRUCTURE 3.4.0 . Structu burn-in  and  was performed based on genetic distance among the lines. The genetic distance between markers was calculated using a simple matching coefficient by R-package ‘ade4’ . AdditioOn each chromosome, the markers having a PIC value from 0.20 to 0.37 were selected and a total of 7,842 SNPs were used for AMOVA. The number of subpopulations determined based on STRUCTURE results were used for AMOVA.h), unbiased diversity (uh), and Shannon’s Information Index (I) were calculated. The AMOVA and estimation of genetic indices were performed using GeneAlEx 6.41 , number of effective alleles (Ne), diversity index . The number of SNPs per chromosome ranged from 319 (chromosome 3D) to 2,370 (chromosome 3B). The lowest and highest number of SNPs identified per chromosome in each genome ranged from 700 (Chr. 5A) to 1575 (Chr. 2A), 706 (Chr. 6B) to 2,370 (Chr. 3B), and 319 (Chr.3D) to 1,220 (Chr. 5D) .The number of SNPs identified was, 8,753, 10,569, and 6,245 in genomes A, B, and D, respectively . A similar range of GD and PIC values were observed in the three wheat genomes. Most markers  had a minor allele frequency of 0.1 . The observed heterozygosity ranged from 0.1  to 0.7 (4 SNPs) .The GD and PIC value across all chromosomes varied from 0.1 (570 SNPs) to 0.5  with an average 0.3 and from 0.1  to 0.4  with an average of 0.25, respectively . In order to find the suitable value of K, the number of clusters (K) was plotted against ΔK which showed a sharp peak at k = 3 . Remarkably, a continuous-gradual increase was observed in the assessed log likelihood [LnP(D)] with the increase of K  and the best number of K which clearly defined the number of populations was K = 3, indicating that three subpopulations could include all the 230 of Nebraska winter wheat genotypes with the highest probability. Three subgroups  were identified and comprised 70, 130, and 30 genotypes in G1, G2, and G3, respectively (Table 2). The results of PCoA agreed with STRUCTURE analyses by clustering the 230 winter wheats genotypes into three clear groups .STRUCTURE analysis software was used to study the population structure of 230 genotypes from Nebraska Duplicate Nursery (Table 2). The highest value of expected heterozygosity was found in G2 with a value of 0.217 and the lowest value was found in G3 with a value of 0.174 while the G1 had a moderate expected heterozygosity with an average of 0.197. The Fixation index (Fst) was calculated to test the population substructure and it is considered the most efficient index for assessing the overall genetic variation among subpopulations. So, the Fst value were 0.107, 0,153, and 0.234 for G2, G3, and G1.A significant genetic divergence was observed among subpopulations and average distance (expected heterozygosity) among genotypes in each subpopulation  was within subpopulations. The haploid Nm was very high (5.621) indicating a high gene exchange among subpopulations. These results demonstrated that genetic differentiation among subpopulations was low and within subpopulations was high. The UPGMA based on genetic distance among all genotypes was performed again with the 7,842 SNPs  are provided in riation 9% was witFigure 5). The number of genotypes with private alleles were 26 (37%), 123 (95%), and 21 (70%) in G1, G2, and G3, respectively. The number of loci with private alleles ranged from 1 to 5 in G1 and G3 subpopulations, while, it ranged from 1 to 14 in G2 subpopulation.Of the 230 genotypes, 170 (74%) were found to possess several loci with private alleles (Table 4) were 1.898 and 1.480, respectively. Populations had average values of 0.433, 0.286, and 0.292 for I, h, and uh, respectively (Table 4). Of the three subpopulations, G2 population was the most diverse , whereas the sub-population G3 was the least diverse . The percentage of polymorphic loci per population ranged from 91.85% (G3) to 98.36% (G2) with an average of 95.69%.The mean value of different alleles (Na) and Number of effective alleles of the three subpopulations . The highest number of markers were found in B genome, while, the lowest were in the D genome indicating lower diversity in the D genome. T. aestivum came from the polyploid nature of its tetraploid ancestor. This result can be interpreted as at the nucleotide level of A and B genomes, the average diversity was estimated to be 30% of that existed in wild emmer. Hexaploid wheat was found to possess a larger portion of the natural gene diversity found in its tetraploid ancestor (AABB) than of the diversity found in Aegilops tauschii (DD)  . The conhii (DD) , SSRs (Rhii (DD) , RFLPs (hii (DD) , and AFLhii (DD)  in commooccoides . Our resFigure 2). -9) substitutions nt-1 year1 (-4)  . The lowar1 (-4) . The disar1 (-4) . The PICar1 (-4) .F3:6 Nebraska Duplicate Nursery in 2010 and 2011. They also found three subpopulations. As the 2010 and 2011 nurseries were separated by at least 6 years from the 2017 nursery and numerous crosses  were made between the nurseries, it was interesting to again find three subpopulations in each nursery from different years and different pedigrees. Presumably the role of breeder selection and the agroecological zones of Nebraska fostered the formation of the three subpopulations and the maintenance of this genetic diversity. Maintaining genetic diversity is critical for continued breeding advances.Population structure analysis is useful in understanding genetic diversity and association mapping studies. The Nebraska wheat lines were divided to three subgroups. The PCoA results were in a agreement with STRUCTURE results. Moreover, the dendrogram analysis (UPGMA) gave the same results . This result is probably due to G2 being the largest group and also most genetically diverse compared with the other two subgroups G1 and G3. The advantage of calculating private alleles was that it provided information on alleles that existed in only one subpopulation. G2 had 14 private alleles which was more than those found in G1 and G3 indicating the high genetic diversity that existed among the genotypes of G2. The private allele data provide useful information on unique genetic variability in certain loci and identifying highly -diverse genotypes that could be used in crop breeding programs as parental lines in order to maximize the allele richness in the population . Another and G3. P < 0.001). The selection for specific agronomic traits in the breeding program of the Nebraska winter wheat was considered the main reason for this high variation within groups. The low level of diversity among subpopulations was due to the high value of gene flow. (The results of AMOVA indicated high level of genetic diversity within-subpopulations. Although the variation among subpopulations was low (8%), it was significant according to the partitioning value . These main, hence common, parents were involved in many crosses each year in Nebraska breeding program. The progenies were elite lines and these parents were exposed to selection based on four criteria as described previously.The allelic pattern and genetic diversity indices provided useful information on genetic diversity in each subpopulation. Although the three subpopulations had observable diversity, G2 had the highest genetic diversity. The understanding of genetic diversity within the Nebraska winter wheat breeding program will be helpful for planning future studies and maintaining and monitoring genetic diversity in a breeding program.I, h, uh parentage of polymeric loci, and was the most diverse. Using this knowledge of population structure and genetic diversity are very important for future genetic analyses such as genomic selection studies, GWAS and marker-assisted selection which support the main objectives in Nebraska breeding program to genetically improve winter wheat.In this study, we employed high-throughput SNP genotyping to explore the utility of SNP markers for genomic analyses in elite wheat breeding lines. Although the elite genotypes were highly selected, they were genetically diverse. This level of genetic diversity can be used for future breeding progress to devlop new wheat cultivars with desirable characteristics such as high yield potential, tolerance to biotic and abiotic stress, and good end-use quality while being adapted to diverse environments. Moreover, our study identified three subpopulations which could be explained by their parentage and selection history. The G2 subpopulation has largest number of genotypes, exhibited the highest values for private alleles, SE conducted the experiments of this study, performed all the statistical analysis, and wrote the manuscript. AS designed the study, helped in the statistical analyses, and drafted the manuscript. VB performed the SNP calling and discussed the results. HE, AN, and KS helped in discussing the results and drafting the paper. JP performed the GBS for the population. PB designed the study, discussed the results, and helped draft the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Global fermented foods are classified into 9 major groups on the basis of substrates  used from plant/animal sources: fermented cereals, fermented vegetables and bamboo shoots, fermented legumes, fermented roots/tubers, fermented milk products, fermented and preserved meat products, fermented, dried, and smoked fish products, miscellaneous fermented products, and alcoholic beverages. Fermented foods are the hubs of consortia of microorganisms, which transform the chemical constituents of raw materials of plant/animal sources during Alkalibacterium, Carnobacterium, Enterococcus, Lactobacillus, Lactococcus, Leuconostoc, Oenococcus, Pediococcus, Streptococcus, Tetragenococcus, Vagococcus and Weissella. Species of Bacillus are reported for alkaline-fermented foods of Asia and Africa. The association of several species of Kocuria, Micrococcus (members of the Actinobacteria), and Staphylococcus (belonging to the Firmicutes) has been reported for fermented milk, fermented meat, and fish products. Species of Bifidobacterium, Brachybacterium, Brevibacterium, and Propionibacterium have been isolated from cheese and species of Arthrobacter and Hafnia from meat fermentation. Enterobacter cloacae, Klebsiella pneumoniae, K. pneumoniae subsp. ozaenae, Haloanaerobium, Halobacterium, Halococcus, Propionibacterium, and Pseudomonas, are also present in numerous fermented foods.Common genera of the lactic acid bacteria isolated from various fermented foods globally are Brettanomyces, Candida, Cryptococcus, Debaryomyces, Dekkera, Galactomyces, Geotrichum, Hansenula, Hanseniaspora, Hyphopichia, Issatchenkia, Kazachstania, Kluyveromyces, Metschnikowia, Pichia, Rhodotorula, Rhodosporidium, Saccharomyces, Saccharomycodes, Saccharomycopsis, Schizosaccharomyces, Sporobolomyces, Torulaspora, Torulopsis, Trichosporon, Yarrowia, and Zygosaccharomyces. Major roles of filamentous fungi in fermented foods and alcoholic beverages are mainly production of enzymes and also degradation of anti-nutritive factors. Species of Actinomucor, Amylomyces, Aspergillus, Monascus, Mucor, Neurospora, Parcilomyces, Penicillium, Rhizopus, and Ustilago are reported for many fermented foods, Asian non-food amylolytic starters and alcoholic beverages.Genera of yeasts reported for fermented foods, alcoholic beverages, and non-food mixed amylolytic starters are Direct DNA extraction from samples of fermented foods, commonly called culture-independent methods, is nowadays frequently used in food microbiology to profile both cultivable and uncultivable microbial populations from fermented foods. Amplified ribosomal DNA restriction analysis (ARDRA) and denaturing gradient gel electrophoresis (DGGE) techniques developed to profile microbial communities directly from fermented foods, and are based on sequence-specific distinctions of 16S rDNA or 26S rDNA amplicons produced by PCR.Application of next generation sequencing (NGS) such as metagenomic approaches by using parallel pyrosequencing of tagged 16S rRNA gene amplicons provide information on microbial communities as profiled in kimchi, a naturally fermented vegetable product of Korea, nukadoko, a fermented rice bran of Japan, narezushi, a fermented salted fish and cooked rice of Japan, and ben-saalga, a traditional gruel of pearl millet of Burkina Faso. A proteomics identification method based on protein profiling using matrix-assisted laser desorption ionizing-time of flight mass spectrometry (MALDI-TOF MS) is used to identify bacteria in fermented foods. NGS has revealed the new dimension of microbial ecology comprising both cultivable and uncultivable microorganisms in many ethnic fermented foods and beverages of the world.This e-book is a compilation of 15 originals and reviews papers written by 94 authors. We tried to represent the main Asian, African, European, and American fermented foods and alcoholic beverages.JT prepared a draft concept on Resource Topic of the present e-book and list of authors for papers, supplemented and corrected by WH, DS, and GF. JT was the main corresponding Editor, however, WH, DS, and GF also helped to provide the names of referrers, etc.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Gymnopithys rufigula) within and between two large reserves in central Amazonia. Analyses based on microsatellites suggested two genetically distinct populations and asymmetrical gene flow between them. Within a population, we found a lack of genetic spatial autocorrelation, suggesting that genotypes are randomly distributed and that G. rufigula may disperse longer distances than expected for antbirds. Analyses based on mitochondrial sequences did not recover two clear genetic clusters corresponding to the two reserves and indicated the whole population of the Rufous‐throated Antbird in the region has been expanding over the last 50,000 years. Historical migration rates were low and symmetrical between the two reserves, but we found evidence for a recent unilateral increase in gene flow. Recent differentiation between individuals of the two reserves and a unilateral increase in gene flow suggest that recent urban expansion and habitat loss may be driving changes and threatening populations of Rufous‐throated Antbird in central Amazonia. As ecological traits and behavioral characteristics affect patterns of gene flow, comparative studies of other species with different behavior and ecological requirements will be necessary to better understand patterns of genetic dispersal and effects of urban expansion on Amazonian understory antbirds.Amazonian understory antbirds are thought to be relatively sedentary and to have limited dispersal ability; they avoid crossing forest gaps, and even narrow roads through a forest may limit their territories. However, most evidence for sedentariness in antbirds comes from field observations and plot‐based recapture of adult individuals, which do not provide evidence for lack of genetic dispersal, as this often occurs through juveniles. In this study, we used microsatellite markers and mitochondrial control‐region sequences to investigate contemporary and infer historical patterns of genetic diversity and structure of the Rufous‐throated Antbird ( As the amount of genetic differentiation is inversely related to the dispersal of individuals, and hence to gene flow, estimating genetic structure among spatially isolated populations provides an indirect quantification of effective dispersal across a landscape  is an obligate army‐ant‐following bird that inhabits the understory of Amazonian lowland terra firme forests , G. rufigula is dominant at ant swarms in central Amazonia, suggesting it has more access to resources provided by army‐ants than other ant‐following species and thus may need to move shorter distances than subordinate species . Birds were captured with mist nets  at 29 sampling points systematically placed at intervals of roughly 1 km  of ve years 012–2013.m Figure . Rufous‐m Figure . Birds wG. rufigula  that were collected by other researchers between 2010 and 2011 in four locations within BDFFP , following the manufacturer's protocols. Individuals of Schlegel  using prSchlegel .2.5Ho and He), deviations from Hardy–Weinberg equilibrium (HWE), and performed exact tests of linkage disequilibrium between pairs of loci for DFR and BDFFP using Genepop Web v.4.2  among the sampled sites. Firstly, we used Structure v.2.3.4  to be tested was set between 1 and 8 with a correlated allelic frequency model. To assess the consistency of the results, we ran the MCMC 10 times and chose the best result based on the highest average posterior probability. In a second step, we ran 100 simulations using the same parameter settings as described above, with K fixed to the number of clusters inferred therein, to assign individuals to the clusters.Secondly, we used the spatially explicit cluster model implemented by the Geneland v. 4.0.5 package  over the last few generations . We used a full migration model and considered parameter estimates accurate when an effective sample size (ESS) >1,000 was observed  to those resulting from BayesAss (m), we multiplied M values by a commonly assumed microsatellite mutation rate of 5 × 10−4  of the inferred populations based on the linkage disequilibrium method corrected for sample size bias, using the monogamous mating model and lowest allele frequency = 0.050, as implemented in NeEstimator v.2.01 . PCR amplifications were performed in 25 μl total volume containing 16.8 μl double‐distilled water, 1 μl genomic DNA (10–20 ng/μl), 0.2 μl DreamTaq Green DNA polymerase, 5 U/μl and 2.5 μl DreamTaq Green buffer 10× , 2.5 μl dNTPs (2 mmol/L), 1 μl forward primer (10 mmol/L), and 1 μl reverse primer (10 mmol/L). Thermal cycling proceeded as follows: 95°C for 5 min; followed by 30 cycles of 95°C for 45 s, 58°C for 45 s, and 72°C for 60 s; finishing with 72°C for 2 min. PCR products were cleaned using NucleoSpin Gel and PCR Clean‐up Kit . Sequencing was carried out on an Applied Biosystems ABI 3730 XL by GATC Biotech . We used BioEdit v.7.2.5 to visualize, edit, and align DNA sequences Hall, . We used2.12Nucleotide (Pi) diversity and haplotype (Hd) diversity for each population were estimated using DnaSP v.5.10.01  with jModelTest2 v.2.1.10 .We scored 120 individuals at 14 loci. One locus (Gyru05) showed evidence for null alleles and was therefore removed from subsequent analyses  with asymmetrical gene flow between DFR and BDFFP: higher rates of dispersal occurred from DFR to BDFFP (0.32 [±0.02]) than the opposite (0.01 [±0.01]). Estimates of historical migration obtained from Migrate‐N indicated little and symmetrical gene flow between the two reserves: migration from DFR to BDFFP was = 0.013 [±0.004], and from BDFFP to DFR was = 0.007 [±0.004]. These results also suggest a recent increase in migration rates from DFR to BDFFP, but no overall change in migration rates from BDFFP to DFR.3.4Ne was 1,189 individuals . Both populations showed evidence of heterozygosity deficiency, indicating a recent expansion in their effective population size . However, when a TPM model was used, the multilocus probability of displaying a deficiency in heterozygosity appeared to be significant only for DFR .Harmonic‐mean estimates revealed an effective population size of 517 individuals  for DFR and 170 individuals for BDFFP (CIs = 118–287). The estimated overall 3.5r fell inside the 95% permuted confidence intervals, and bars of 95% bootstrapped estimates crossed zero at all distance classes, indicating no statistically significant spatial autocorrelation within DFR  showed that the autocorrelation coefficient R Figure .3.6t = 0.133, p = 0.899), vAIc , or FST  between sexes. However, FIS values were slightly greater for males . Within DFR, the correlograms comparing spatial autocorrelation between sexes showed that r values for males and females overlapped in both distance classes , but BDFFP had higher haplotype diversity . Only the most frequent haplotype was shared between the two populations; 12 were found only in DFR, and eight were recorded only in BDFFP . We found 21 haplotypes within the 79 sequences of The haplotype network did not reflect a separation into two distinct groups. Rather, it reflected a star‐like topology with a shared haplotype between the two reserves in the center, and rare variants radiating from the ancestral sequence, a pattern expected after range or demographic expansions Figure .3.8Analyses based on mitochondrial control‐region DNA sequences suggested demographic expansion for the whole Rufous‐throated Antbird population. Bayesian skyline plot estimates showed a signal of population expansion over the last 50,000 years Figure .4G. rufigula in the Manaus region form two distinct genetic clusters, which are undergoing an expansion in effective population size. Although the star‐like shape of the haplotype network indicates that both reserves shared an ancestral population whose structure cannot be distinguished from a panmictic population in expansion, the presence of haplotypes unique to each reserve suggests that the two areas have been undergoing a process of differentiation and that anthropogenic changes are likely to be driving recent changes in population dynamics.This is the first study to describe the population‐genetic structure of the Rufous‐throated Antbird. Currently, individuals of 4.1Although our results suggest the presence of two genetic clusters, these might just be segments of the same population that are isolated by distance. Nonetheless, the four sites within BDFFP are distributed over a maximum distance of ~ 40 km, which is roughly the same distance as between the DFR and BDFFP reserves  that run between DFR and BDFFP, as well as the urban sprawl of the city of Manaus, may be contributing to genetic differentiation between these local populations. Several studies have reported road avoidance by a wide range of vertebrates and showed that roads affect population‐genetic structure, not only by reducing the abundance of individuals and gene flow among populations, but also by increasing mortality risks  of E. burchellii are nomadic and widely spaced, obligate army‐ant‐following birds have developed a series of ecological and behavioral adaptations to effectively exploit army‐ant swarms as a food resource : 19,000–26,000 years ago (Clark et al., 4.8G. rufigula has a large distributional range and is thus considered as of least concern by the IUCN Red List (BirdLife International, G. rufigula, which is confined only to the Guiana Shield, northern Amazonia (Naka, Bechtoldt, Henriques, & Brumfield, Although its global population size has not been quantified, Given that the urbanization of the region around the two reserves may be driving genetic erosion in the population of Rufous‐throated Antbirds, more studies are needed to understand how environmental changes induced by human activities, particularly roads, affect Amazonian biodiversity. Moreover, taking into account that the Brazilian Amazon is rapidly undergoing extensive development and that 17.000 km of new roads are added every year to its road network (Ahmed, Souza, Riberio, & Ewers, Comparative studies of other Amazonian antbirds and sedentary understory species will be necessary to better understand patterns of genetic dispersal of Amazonian birds, given that ecological traits and behavioral characteristics affect gene flow and responses of species to fragmentation (Bregman, Sekercioglu, & Tobias, None declared. Click here for additional data file. Click here for additional data file.


Prosopis africana, an important sub-Saharan multi-purpose tree species. Availability of highly polymorphic genetic markers would be helpful for future genetic work.There is very limited genetic knowledge in Leaf samples from 15 trees were used to develop simple sequence repeat (SSR) markers. Size-selected fragments from genomic DNA were enriched for repeats and the library was analyzed on an Illumina MiSeq platform. Fourteen SSRs were selected and applied in two Burkinabe populations (40 adult trees each). The number of alleles varied from 4 to 20, evenness  averaged to 0.54 and unbiased heterozygosity ranged from 0.305 to 0.925 over all loci and populations. Null alleles were not detected.Due to the high level of polymorphism and lack of null alleles the developed SSRs can be effectively employed in population genetic studies.The online version of this article (doi:10.1186/s13104-017-2755-x) contains supplementary material, which is available to authorized users. Prosopis africana [Fabaceae: Mimosoideae]) is a valuable, medium-sized (up to 20 m height), multi-purpose tree in sub-Saharan Africa. It is the only species of the genus Prosopis native to Africa and occurs at sites with 600–1500 mm annual rainfall [African mesquite  were developed for other Prosopis species [Genetic knowledge of African mesquite is very scarce as only results from a single provenance trial with material originating from Niger and Burkina Faso are at hand. Survival, growth and wood density seem to be related to humidity of the seed source , 2. So f species –5. Unfor species  was not For primer development DNA was extracted from leaves collected from adult trees in two populations from Burkina Faso. Twelve individuals were selected as screening panel in Yeimzuro  and three in Padiali . An emphasis was put on selecting more trees in Yeimzuro due to its location in the North of Burkina Faso as less diversity is expected in that region as observed by Schmidt et al. at the species level [The polymorphism of the developed markers was tested and the population structure was estimated using leaves collected from 40 trees per site in two other populations: Raguitenga  and Bandougou . The former is located in the Sudano-Sahelian climatic zone with a savannah type of vegetation and tree density is low; in the latter, tree density is high and the site is located in the Sudanian climatic zone with dry forest vegetation type. These populations are separated by about 500 km, occurring in two different climatic zones, which were chosen to obtain a better genetic diversity estimate of the species over a larger area.DNA was extracted using the DNeasy Plant Mini Kit and the DNeasy 96 Plant Kit  following the manufacturer’s protocols. SSRs were developed by Ecogenics . Size-selected fragments from genomic DNA were enriched for SSR content by using magnetic streptavidin beads and biotin-labeled CT and GT repeat oligonucleotides. The SSR-enriched library was analysed on an Illumina MiSeq platform using the Nano 2 × 250 v2 format. After assembly, 3′635 contigs or singlets contained a microsatellite insert with a tetra- or a trinucleotide of at least 6 repeat units or a dinucleotide of at least 10 repeat units. Suitable primer design was possible in 2′232 microsatellite candidates by Ecogenics  using the Primer3 software ; for subStandard genetic parameters were estimated with GenAlEx 6.5 . Micro-CThe 14 newly developed primers were utilized for further analysis of two Burkinabe populations (Raguitenga and Bandougou). All the fourteen tested SSRs were polymorphic for 2-bp perfect tandem repeats and the number of alleles ranged from 6 to 14 in the screening panel. The characteristics of the developed markers are summarized in Table In both populations investigated to test the usefulness of these markers for genetic analysis (Raguitenga and Bandougou) all 14 loci were polymorphic Table . The numWhen the sample size was progressively increased from 10 to 80 , the number of alleles remained quite constant at four in the locus with the lowest number of alleles (Proafr_11069c), while this number ranged from 10 to 21 for Proafr_12199s, which was the locus with the largest number of alleles  showed significant deviation from HWE (Hardy–Weinberg expectation). While the Raguitenga population consisted of even-aged mature trees, in Bandougou different age classes were sampled; therefore we expected a higher number of deviations in Bandougou as in tree species with mixed-mating young cohorts often deviate more strongly from HWE  per locus ranged from 20 to 45 in Raguitenga and from 20 to 35 in Bandougou indicating the potential finding of additional alleles in other E .e/Na) which theoretically ranges from 0 (lack of evenness) to 1 (complete evenness) varied from 0.28 (Proafr_09196c) to 0.77 (Proafr_10663c) with an average value of 0.5 for each population. At least seven loci showed an evenness value above the average evenness. Loci with a high evenness and high number of alleles should be selected for the analysis when the number of loci is restricted [The evenness of the allele distribution  under the IAM and only Raguitenga under the SMM Table . Accordia and a high Na/Ne-ratio.All our 14 newly developed markers were highly polymorphic and no null alleles were detected. Using these SRRs, it was possible to quantify the genetic structure of two populations. These SSRs are very valuable for population genetic studies including the analysis of the mating system and gene flow parameters especially when markers which will be employed having a high N