Setareh Mirzavand?Karim Sorkheh?Mohammad Reza Siahpoosh

Abbreviations

PAL Phenylalanine ammonia-lyase

PCRs Polymerase chain reactions

PAGE Polyacrylamide gel electrophoresis

PIC Polymorphism information content

RP Resolving power

SI Shannon’s information index

AMOVA Analysis of molecular variance

CCC Cophenetic correlation coefficient

UPGMA Unweighted pair group method arithmetic

PCA Principal component analysis

PCoA Principal coordinate analysis

NTSYS Numerical taxonomy multivariate analysis system

MCMC Markov chain Monte Carlo

SCoT Start codon targeted

IRAP Inter-retrotransposon amplified polymorphism

MI Marker index

PP Percentage polymorphism

UTR Untranslated region

Introduction

PAL(EC 4.3.1.5)is the primary enzyme in the phenylpropanoid pathway.PAL catalyzes the non-oxidative deamination of phenylalanine to trans-cinnamate and is thought to be a key regulator for redirecting carbon flow from primary to secondary metabolism in the phenylpropanoid pathway(Jones 1984;Dixon and Paiva 1995;Fraser and Chapple 2011).The enzyme,a member of a large superfamily of enzymes,carries out a variety of roles in cells,including scavenging reactive oxygen species created during biotic and abiotic stresses(Hiraga et al.2001;Mittler et al.2004;Gill and Tuteja 2010;Zhang et al.2013)and at the beginning of a constitutive defense response of plants against pathogens(Schopfer 2001;Passardi et al.2005),cell wall lignification and suberization(Herrero et al.2013),auxin catabolism,wound healing,senescence of leaves and plant–microbial symbiosis(Passardi et al.2005).

In all studied plants,PAL is encoded by a large,diverse multi-gene family.The number of PAL gene copies varies among plant species.For example,Arabidopsis thaliana(L.)Heynh.(Raes et al.2003)and tobacco(Fukasawa-Akada et al.1996;Basha and Chatterjee 2007;Reichert et al.2009)have four,poplar has five(Hamberger et al.2007),cucumber seven(Shang et al.2012),rice nine(Hamberger et al.2007),watermelon 12(Dong and Shang 2013),and tomato 26(Chang et al.2008).

An individual PAL gene may respond differentially to biotic or abiotic stress,and its expression is developmentally and spatially controlled.In poplar,organ-specific expression of PAL genes has been evaluated;two poplar PAL genes are expressed in lignifying tissues:one is involved in lignin formation,and the other is specifically targeted to reduce tannin synthesis(Kao et al.2002;Campos et al.2004).A third poplar PAL gene is linked with flowering,although its function still needs to be established(Hamberger et al.2007).In Arabidopsis,expression studies of AtPAL genes have shown that AtPAL3 is expressed only at basal levels in stems(Mizutani et al.1997;Raes et al.2003).In contrast,AtPAL1,AtPAL2,and AtPAL4 are expressed at relatively high levels in stems through late development,while AtPAL2 and AtPAL4 are both expressed in seeds,and AtPAL1 expression has been localized to vascular tissue(Raes et al.2003;Rohde et al.2004).Of the four AtPALs,only AtPAL1 and AtPAL2 are stimulated in response to diminished nitrogen and low temperatures(Olsen et al.2008).In contrast to the case in Arabidopsis and poplar,～26 PAL genes have been identified in tomato;nevertheless,only a single gene is robustly expressed in all tissues,while the other PAL genes appear to be silenced(Chang et al.2008).

The expansion of the PAL gene family in plants is probably due to gene duplication,including tandem duplication,segmental duplication,and whole-genome duplication(Cannon et al.2004).For instance,seven PAL genes occur in tandem in two duplication blocks in cucumber,signifying that the PAL gene family may have extended in the cucumber genome through tandem duplications(Shang et al.2012;Jeong et al.2012).In contrast,more than 20 PAL genes are widely separated in the tomato genome,with no clustering,demonstrating an unusual number of duplications(Chang et al.2008).

The genus Pistacia,a member of the Anacardiaceae family,includes 11 or more species(Zohary 1996);P.vera L.is the most important economically.Iran is the world’s largest producer and the most significant center of genetic diversity of pistachio(Pistacia spp.);over 44%of world production(Esmail-pour 2001;Razavi 2006;Iranjo et al.2016;Sorkheh et al.2016)is grown on 350,000 ha,which yields more than 300,000 tons/year(FAO 2006).Wild species of Pistacia has great potential as a germplasm resource for improving P.vera,but the wild populations have been insufficiently characterized so far,and molecular investigations are needed to elucidate the genetic relationships and diversity among wild Pistacia species(Sorkheh et al.2016).

Because the PAL gene family is so large and diverse and the number of copies can vary widely among species,PAL sequences might be useful as functional DNA markers to study genetic polymorphism in the Pistacia genome.Up to now,however,there have been no reports on using PAL sequences as DNA markers in any plant species.In the present study,we revealed high genetic variability for PAL markers among populations of Pistacia species,which should be very useful for phylogenetic analyses,genetic structure determination,heterozygosity analysis,and identification of population subgroups.This study also describes the procedure for using PAL sequences as DNA markers for genetic analysis in plant species and a customized protocol for a PAL marker system.

Materials and methods

Plant materials

A geographically diverse germplasm collection was selected for study,and 100 accessions of 10 wild Pistacia species(P.atlantica,P.khinjuk,P.mutica,P.vera,Pistacia eurycarpa,Pistacia palastina,Pistacia terebinthus,P.chinensis,P.falcata and Pistacia integerima)were also collected(Supplementary materials,Table S1).The number of populations per collection site varied from 1 to 10,depending on environmental diversity and ease of collection.The distance between samples was 200 m,whereas the pairwise distance between the most important areas was 100–500 km.Areas were chosen for sampling to cover the natural distribution of wild Pistacia species in Iran according to Esmail-Pour(2001)and Sorkheh et al.(2016).Specific permission was not required since these locations are outside protected areas,nor does leaf collection harm the sampled individuals.The sampled stands also were selected to give maximum representation of the ecological conditions of the area.Collected leaves were stored at-80°C until DNA extraction.

Preparation of nucleic acids

Total DNA was isolated from the young leaves collected in the spring,using a DNeasy Plant kit(Fermentase,Germany)according to the instructions with minor alterations(Sorkheh et al.2007;Iranjo et al.2016)and adjusted for wild Pistacia species(Sorkheh et al.2016).The purity of the total DNA was evaluated by gel electrophoresis and confirmed using a spectrophotometer(BioPhotometer Eppendorf,Germany).

PAL polymorphism

Four primer sequences from tomato(Solanum lycopersicum L.;Chang et al.2008),48 from tobacco(Nicotiana tabacum;Reichert et al.2009)and 24 from watermelon(Citrullus lanatus;Dong and Shang 2013;Supplementary materials,Table S2),were used for the PCRs.Amplification with 39 primer combinations resulted in a distinctive banding pattern and was employed for advanced genetic analysis.The 25-μL PCR mixture,based on that of Satya et al.(2014)with minor modifications of Iranjo et al.(2016),consisted of 50 ng of template DNA,0.2 mM dNTPs,0.5 μM of each primer pair,0.5 μL of Taq DNA polymerase(3 U),and 1× PCR buffer containing 0.5 μL MgCl2(2.5 mM).PCR thermocycling(BioRad,USA)conditions were as follows:hot start at 95°C for 5 min;45 cycles of denaturation at 95°C (30 s),1 min at the annealing temperature for every primer,and 72°C for 1 min;a final extension at 72°C for 10 min.Annealing temperature for PAL primers was determined by PCR at a temperature gradient of 38–43 °C.Distinct,reproducible amplicons were acquired when PAL primers were annealed at 39–40 °C.For PAL primers,amplicon separation in PAGE(6%)resulted in better resolvability than in agarose gel(0.8–2.5%).All PCR products were resolved in 6%PAGE according to Satya et al.(2014)with minor modifications according to Sorkheh et al.(2016).Bands were viewed using a silver staining method(Creste et al.2001).Well-resolved,reproducible bands were scored as present(1)or absent(0)for each locus for the PAL marker systems.

PIC values for PAL markers were considered for each locus as 1-p2-q2(Satya et al.2014)and averaged over loci according to Anderson et al.(1993),where p is the frequency of a band and q is the frequency of no band.RP of each marker was estimated following the method of Prevost and Wilkinson(1999).The average RP was calculated by averaging the total number of bands amplified for every marker.

Genetic statistical inferences

Percentage polymorphism,the observed(Na)and effective number(Ne)of alleles,SI,and expected heterozygosity(He)were estimated in every population group(Ramakrishnan et al.2016).The correlation among the Hevalues for PAL polymorphism was analyzed using Spearman’s rank order correlation.Population diversities were tested for each statistic using Student’s t test.Genetic similarity between populations was estimated using Nei’s pairwise genetic distance(D)and genetic identity(I)(Nei 1987).All calculations were done in GenALEx ver 6.5 using 1000 permutations(Peakall and Smouse 2006).

Within-accession diversity(HS)and total gene diversity(HT)(Nei 1973)were calculated among major groups,using the POPGENE software(Yeh et al.2000).

AMOVA analysis

AMOVA was used to partition total genetic difference among and within population groups following Excoffier et al.(1992).AMOVA was completed using GenALEx software version 6.5(Peakall and Smouse 2006),a nonparametric permutation and standard permutation method with 1000 pairwise-permutations;these were used to approximate the total molecular variance among the populations and within populations.

Statistical fitness analysis

To confirm the cluster analysis and genetic structure in accordance with Ramakrishnan et al.(2016),the CCC was computed using UPGMA,and the distribution of populations was analyzed using PCA.PCoA was carried out using NTSYS-pc version 2.1 software package(Exeter Software,Setauket,NY,USA;Rohlf 1998).The number of signif icant components to interpret from the PCA was established using the Jolliffe cut-off value and the broken stick model(Jolliffe 2002;Legendre and Legendre 1998).

Population structure analysis

Population structure was investigated by using the MCMC algorithm in the program structure,a tool for population genetic analysis(Pritchard et al.2000,2010)following the methods illustrated for dominant markers by Falush et al.(2007).We used admixture and non-admixture models and acquired the optimal number of clusters(K)through determination of posterior log likelihood(ln K)and second order rate of change in the likelihood function(ΔK)as recommended by Evanno et al.(2005).The structure program was then run at desired K values with a burn-in period of 100,000 and MCMC model with 100,000 repetitions.

Phylogenetic analysis

For UPGMA average analysis,binary data were analyzed with the NTSYS-pc version 2.1 software package(Exeter Software,Setauket,NY,USA;Rohlf 1998).Then,a similarity matrix was constructed based on Jaccard’s similarity coefficient,which considers only one to one matches between two taxa for similarity(Jaccard 1908).The similarity matrix was used to construct the UPGMA dendrogram to determine genetic relationships among the germplasm studied.To test the goodness of fit for the GS matrix to cluster analysis,first,used the COPH module to transform the tree matrix to a matrix of ultrametric similarities,then the MXCOMP module to compare this ultrametric similarity matrix with the similarity matrix produced.This procedure is called the Mantel test(Mantel 1967).

Results and discussion

Amplification of the PAL markers yielded distinct,reproducible banding patterns after 6%PAGE,but smeared,overlapping bands in agarose.Four PAL primer combinations,PAL3BpET29/PAL4BpET29,PAL2-F-Seg3/PAL2-R-Seg3,ClPAL1-F/ClPAL1-R and ClPAL4-F/ClPAL4-R amplified fewer loci(only 4)than other primer combinations(Table 1).The PAL primers generated 133 polymorphic loci(varying from 48 to 755 bp,mean 345.3 bp),with an average PIC value of 0.9747.Primer pair PAL1/4Ande/PAL2/3Ande and PAL3BpET29/PAL4BpET had the highest and lowest total resolving power(24.35;1.25)and mean resolving power per locus(4.05;0.31),respectively.

Of the 313 marker systems,PAL markers(100%)generated the highest polymorphism,in wild Pistacia species.In the wild population,the highest number of alleles detected was generated by PAL markers in P.falcata(1.94).Significant differences(P＜0.01)for Naand Ne,h,SI,and unbiased expected heterozygosity(He)were found among the Pistacia species populations studied(Table 2).SI was determined to be 0.43 for PAL,revealing high diversity within and among populations.Hefor PAL marker was 0.32(range 0.22–0.38).The sum of gene diversity across all accessions(HT)was 1.286,and the within-accession gene diversity(HS)was 1.121(Table 2).Because of the gene diversity among groups,it was possible to classify these wild Pistacia into four main groups:group 1 consisted of accessions of P.vera,P.khinjuk;group 2 included P.atlantica,P.mutica and P.eurycarpa;group 3 contained accessions of P.palastina and P.terebinthus;and group 4 included accessions of P.chinensis,P.falcata and P.integerrima(Table 2).The values for HTand HSfor group 1 were the highest among the wild Pistacia species studied,indicating that group 1 contains greater genetic variation both among and within accessions than in the other groups.Thus,relative,but not absolute,diversity estimates from the present study are considered reliable.Our results agree with those of Iranjo et al.(2016).

We also tested the correlation among the Hevalues of PAL polymorphism using Spearman’s rank order correlation.Significant association(r=0.89,P＜0.001)was found between Hevalues between PAL polymorphism.

Multiple copies of plant PAL gene families have been reported from many plant species(Cui et al.1996;Duroux and Welinder 2003;Chang et al.2008;Gonzalez et al.2010;Bagal et al.2012).The primers developed for amplification of PAL sequences in tomato,tobacco and watermelon exhibited high allelic polymorphism and resolving power in wild Pistacia species in the present study,demonstrating cross-species transferability of these markers.Many reports indicate that Pistacia species are very diverse phenotypically and genetically(Iranjo et al.2016;Sorkheh et al.2016);thus,it is expected that many of these loci(Table 1)will be amplified in Pistacia species.Genetic polymorphism generated by the PAL marker system can therefore be used as efficient tools for discriminating genotypes and elucidating phylogenetic diversity,and evolutionary relationships and for other genomic studies in Pistacia.Among DNA marker systems,AFLP and SSR are perhaps the most widely used in genetic diversity and population genetic studies in plants.The present study reveals great polymorphism and diversity generated by PAL markers in Pistacia species populations.

Previously,genetic analyses of five populations of Pistacia species based on SCoT and IRAP revealed polymorphism between the studied species(Sorkheh et al.2016).These observations further support that the PAL markers are reliable dominant marker systems for genetic analysis of population and genetic diversity studies in Pistacia species and may be used for genetic analysis in other crops.However,we observed more alleles for PAL using PAGE than agarose.

The AMOVA results are presented in Table 3.Signif icant variations among populations were obtained for PALpolymorphism(P＜0.01).Genetic polymorphism generated by the PAL markers indicated 81%within-population variation and 19%among-population variation.In the PCoA to obtain more information on interpopulation relationships,the first PCo(PCo1)accounted for 37.69%of the total variability,the second PCo(PCo2)for 49.46%of the variance,and the third PCo(PCo3)explained 56.58%of the variance(85.96%in total;Supplementary materials,Table S3).

Table 1 List of primers that yielded the most information(MI)and highest percentage polymorphism(PP)obtained among accessions of wild Pistacia species

Table 1 continued

Coefficients for unbiased genetic distance(D)and genetic identity(I)among the populations were estimated based on the normalized identity of PAL polymorphism following Nei(1987)for PAL polymorphism were 0.85(range 0.753–0.994) and 0.17 (range 0.005–0.283;Table 4).The highest genetic distance and lowest genetic identity based on PAL polymorphism was observed between P.khinjuk and P.chinensis;P.khinjuk and P.terebinthus;P.atlantica and P.chinensis;and Pistacia mutica and P.palestina.

From the outcome of the population structure analysis using PAL polymorphism,we observed a maximum value of ΔK at K=2,followed by K=3 and K=4,while the distribution of ln K stabilized at K=4(Fig.1).Thus,four genetic groups were identified in the population.Under the non-admixture model at K=4,the four clusters(I,II,III and IV)contained 30.9,67.3,and 31.8%of the population,respectively.At K=4,cluster I differentiated the wild P.vera,P.khinjuk,P.mutica and P.eutycarpa germplasm accessions.Under the admixture model,genetic admixtures were high at K=3 and K=4.At K=3,cluster I andcluster II exhibited high divergence(0.45).Cluster II differentiated the cultivars from P.palestina and P.terebithus and exhibited closer genetic association with cluster I.Genetic admixture was higher in the wild population.At K=4,clear population structure differentiation could be identified.Cluster III included the wild populations of P.chinensi s,P.falcata and P.integerrima.

Table 2 Numberofobservedalleles(N a),numberofeffective alleles(N e),Nei’s genediversity(h),Shannon’sinformation index(SI),and meanexpectedheterozygosity(H e)and group inthe hecluster analysisbased on PAL from100 accessionsofwild Pistacia species

On the basis of the molecular data,the results from Bayesian clustering analysis using structure software(Fig.1)confirmed the groupings we observed in UPGMA dendrogram and PCoA.The most likely value of K(as chosen by Evanno’s ΔK method)in Bayesian clustering analysis was four and indicates the division of variation into four clusters,indicating the most appropriate four main clusters within the wild Pistacia species populations studied,confirming the clustering of UPGMA dendrogram and PCoA.The first cluster(blue color)consisted of P.vera and P.khinjuk populations.P.atlantica,P.mutica and P.eurycarpa populations were placed into the second cluster(red color),while P.palestina and P.terebinthus were placed into the third cluster(green color).P.chinensis,P.falcata and P.integerrima were in the fourth cluster(yellow color).

Overall,we found an admixture model to be more effective than a non-admixture model for the population structure based on PAL polymorphism.This approach identified more structural groups in the population for PAL(K=4).Genomewide in silico analyses in plants indicate that allelic variation in POX sequences in monocots and dicots is much higher(52–196)than in PAL sequences(1–12;Rawal et al.2013).The rate of expansion of the POX gene family in comparison to the PAL gene family is much greater(Rawal et al.2013;Satya et al.2014),which may be the reason for the presence of more genetic groups in their structure analysis using POX genes.This classif ication also coincided well with an a priori grouping based on cluster analysis as well as geographical diversity.Our PAL-based structure analyses revealed four genetic groups,which exhibited good association with genetic distancebased clustering,but did not match well with geographical diversity.When results from all markers were pooled,the Bayesian analysis as well as the classification analysis of the structure of the Pistacia population revealed clear geographically and genetically isolated groups,suggesting that the use of more than one marker system may be beneficial to obtain a better estimation of population structure(Satya et al.2014).

PAL sequences are structurally and functionally conserved in plant species(Rawal et al.2013).While peroxidases act in diverse metabolic pathways,phenylalanine ammonia-lyase is restricted to the phenylpropanoid pathway catalyzing a single biochemical reaction that can lead to the synthesis of diverse phenolic compounds in the cell(Gulsen et al.2007,2010)by other enzymes.Although jute produces a high level of numerous phenolic compounds(Khan et al.2006),natural selection in geographically isolated populations of jute is expected to influence these downstream pathways more compared to upstream deamination of trans-cinnamic acid catalyzed by PAL.The escape of PAL sequences from stringent natural selection might be one reason behind the high allelic admixture in geographically isolated groups of Pistacia species.The present population structure and genetic diversity analyses using PAL markers clearly differentiated the Pistacia species.

Table 3 Analysis of molecular variance(AMOVA)for 100 wild Pistachio accessions based on 313 PAL DNA markers

Table 4 Nei’s unbiased measure of genetic distance(D;upper diagonal)and genetic identity(I;lower diagonal)among populations of Pistacia species based on PAL polymorphism

Considerations for conservation

The primary objective for the conservation of species is to preserve the evolutionary potential of a species by maintaining as much genetic diversity as possible.Thus,knowledge of the genetic variation between and within different populations of plant species is critical for designing appropriate strategies for conservation(Milligan et al.1994).According to our results,the genetic diversity of P.atlantica subsp.kurdica is relatively low compared to the other species examined,perhaps due to a severe decline in habitat,in addition to its over-collection and over-exploitation.The fruits of P.atlantica are used as edible nuts and for oil extraction(56%of the kernel and 30%of the total mass is composed of oil).In addition,physical and internal seed dormancy,low seed germination and low seedling vigor in the early stages make regeneration of this species difficult.Moreover,this species has experienced strong selection for higher resin production,which has resulted in genetic erosion(Esmail-pour 2001).Although further study is necessary,including for the other subspecies(P.atlantica subsp.,P.atlantica subsp.cabolica and P.atlantica subsp.mutica),the present analysis provides information that policymakers and scientists can use to improve the conservation and sustainable use of wild pistachio forests.The low genetic diversity of P.atlantica subsp.kurdica reveals its susceptibility to anthropogenic processes,environmental change and biotic stresses.Protection by in situ conservation and the management of seed and resin exploitation to prevent the loss of genetic diversity is required urgently.

The present analysis revealed that Iranian-cultivated germplasm is highly variable and genetically distinct from foreign accessions,likely as a result of different local genetic backgrounds,particular breeding pressures and limited interchange of genetic material.The apparently unique nature of the Iranian pistachio germplasm,revealed by our results,supports the case for the implementation of more intense characterization and conservation strategies.

Fig.1 UPGMA dendrogram of 100 accessions of Pistacia species populations based on Jaccard’s similarity coefficients.Bar graphs showing genetic diversity structure for 100 accessions of Pistacia species as assessed using structure software.Each group is represented by a different color(blue,red,green and yellow)

Conclusion

Protocols for PAGE-based separation and analysis of PAL markers and development of a customized protocol for a PCR marker system were established.High genetic variability for PAL marker alleles was identified among Pistacia species.Population structure and genetic relation among a diverse collection of wild Pistacia species were determined using the PAL markers.This is the first study on population structure analysis using the PAL marker system in wild Pistacia species populations or any other plant species.The system could be extended to other crop species to gain further insight into evolutionary changes and genetic differentiation,population structure,etc.to identify rich germplasm resources for plant breeding in these loci.Similar approaches may also be followed using other functional marker systems in Pistacia or in other species.

AcknowledgementsWe thank the Iranian Pistachio Research Institute,Rafsanjan,Iran for providing some samples of the accessions of wild Pistacia species.We also thank two anonymous reviewers for constructive suggestions that greatly helped to improve the manuscript.

Author’s contributionsAll authors contributed equally to this work.

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