Terminal restriction fragment length polymorphism data analysis for quantitative comparison of microbial communities

Terminal restriction fragment length polymorphism (T-RFLP) is a culture-independent method of obtaining a genetic fingerprint of the composition of a microbial community. Comparisons of the utility of different methods of (i) including peaks, (ii) computing the difference (or distance) between profiles, and (iii) performing statistical analysis were made by using replicated profiles of eubacterial communities. These samples included soil collected from three regions of the United States, soil fractions derived from three agronomic field treatments, soil samples taken from within one meter of each other in an alfalfa field, and replicate laboratory bioreactors. Cluster analysis by Ward's method and by the unweighted-pair group method using arithmetic averages (UPGMA) were compared. Ward's method was more effective at differentiating major groups within sets of profiles; UPGMA had a slightly reduced error rate in clustering of replicate profiles and was more sensitive to outliers. Most replicate profiles were clustered together when relative peak height or Hellinger-transformed peak height was used, in contrast to raw peak height. Redundancy analysis was more effective than cluster analysis at detecting differences between similar samples. Redundancy analysis using Hellinger distance was more sensitive than that using Euclidean distance between relative peak height profiles. Analysis of Jaccard distance between profiles, which considers only the presence or absence of a terminal restriction fragment, was the most sensitive in redundancy analysis, and was equally sensitive in cluster analysis, if all profiles had cumulative peak heights greater than 10,000 fluorescence units. It is concluded that T-RFLP is a sensitive method of differentiating between microbial communities when the optimal statistical method is used for the situation at hand. It is recommended that hypothesis testing be performed by redundancy analysis of Hellinger-transformed data and that exploratory data analysis be performed by cluster analysis using Ward's method to find natural groups or by UPGMA to identify potential outliers. Analyses can also be based on Jaccard distance if all profiles have cumulative peak heights greater than 10,000 fluorescence units.     

Use of 16S rRNA gene terminal restriction fragment analysis to assess the impact of solids retention time on the bacterial diversity of activated sludge

Terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes was used to investigate the reproducibility and stability in the bacterial community structure of laboratory-scale sequencing batch bioreactors (SBR) and to assess the impact of solids retention time (SRT) on bacterial diversity. Two experiments were performed. In each experiment two sets of replicate SBRs were operated for a periods of three times the SRT. One set was operated at an SRT of 2 days and another set was operated at an SRT of 8 days. Samples for T-RFLP analysis were collected from the two sets of replicate reactors. HhaI, MspI, and RsaI T-RFLP profiles were analyzed using cluster analysis and diversity statistics. Cluster analysis with Ward's method using Jaccard distance and Hellinger distance showed that the bacterial community structure in both sets of reactors from both experimental runs was dynamic and that replicate reactors were clustered together and evolved similarly from startup. Richness (S), evenness (E), the Shannon-Weaver index (H), and the reciprocal of Simpson's index (1/D) were calculated, and the values were compared between the two sets of reactors. Evenness values were higher for reactors operated at an SRT of 2 days. Statistically significant differences in diversity (H and D) between the two sets of reactors were tested using a randomization procedure, and the results showed that reactors from both experimental runs that were operated at an SRT of 2 days had higher diversity (H and D) at the 5% level. T-RFLP analysis with diversity indices proved to be a powerful tool to analyze changes in the bacterial community diversity in response to changes in the operational parameters of activated-sludge systems.     

Use of 16S rRNA Gene Terminal Restriction Fragment Analysis To Assess the Impact of Solids Retention Time on the Bacterial Diversity of Activated Sludge

Terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes was used to investigate the reproducibility and stability in the bacterial community structure of laboratory-scale sequencing batch bioreactors (SBR) and to assess the impact of solids retention time (SRT) on bacterial diversity. Two experiments were performed. In each experiment two sets of replicate SBRs were operated for a periods of three times the SRT. One set was operated at an SRT of 2 days and another set was operated at an SRT of 8 days. Samples for T-RFLP analysis were collected from the two sets of replicate reactors. HhaI, MspI, and RsaI T-RFLP profiles were analyzed using cluster analysis and diversity statistics. Cluster analysis with Ward's method using Jaccard distance and Hellinger distance showed that the bacterial community structure in both sets of reactors from both experimental runs was dynamic and that replicate reactors were clustered together and evolved similarly from startup. Richness (S), evenness (E), the Shannon-Weaver index (H), and the reciprocal of Simpson's index (1/D) were calculated, and the values were compared between the two sets of reactors. Evenness values were higher for reactors operated at an SRT of 2 days. Statistically significant differences in diversity (H and D) between the two sets of reactors were tested using a randomization procedure, and the results showed that reactors from both experimental runs that were operated at an SRT of 2 days had higher diversity (H and D) at the 5% level. T-RFLP analysis with diversity indices proved to be a powerful tool to analyze changes in the bacterial community diversity in response to changes in the operational parameters of activated-sludge systems.     

Analysis of T-RFLP data using analysis of variance and ordination methods: a comparative study

The analysis of T-RFLP data has developed considerably over the last decade, but there remains a lack of consensus about which statistical analyses offer the best means for finding trends in these data. In this study, we empirically tested and theoretically compared ten diverse T-RFLP datasets derived from soil microbial communities using the more common ordination methods in the literature: principal component analysis (PCA), nonmetric multidimensional scaling (NMS) with Sørensen, Jaccard and Euclidean distance measures, correspondence analysis (CA), detrended correspondence analysis (DCA) and a technique new to T-RFLP data analysis, the Additive Main Effects and Multiplicative Interaction (AMMI) model. Our objectives were i) to determine the distribution of variation in T-RFLP datasets using analysis of variance (ANOVA), ii) to determine the more robust and informative multivariate ordination methods for analyzing T-RFLP data, and iii) to compare the methods based on theoretical considerations. For the 10 datasets examined in this study, ANOVA revealed that the variation from Environment main effects was always small, variation from T-RFs main effects was large, and variation from T-RF × Environment (T × E) interactions was intermediate. Larger variation due to T × E indicated larger differences in microbial communities between environments/treatments and thus demonstrated the utility of ANOVA to provide an objective assessment of community dissimilarity. The comparison of statistical methods typically yielded similar empirical results. AMMI, T-RF-centered PCA, and DCA were the most robust methods in terms of producing ordinations that consistently reached a consensus with other methods. In datasets with high sample heterogeneity, NMS analyses with Sørensen and Jaccard distance were the most sensitive for recovery of complex gradients. The theoretical comparison showed that some methods hold distinct advantages for T-RFLP analysis, such as estimations of variation captured, realistic or minimal assumptions about the data, reduced weight placed on rare T-RFs, and uniqueness of solutions. Our results lead us to recommend that method selection be guided by T-RFLP dataset complexity and the outlined theoretical criteria. Finally, we recommend using binary or relativized peak height data with soil-based T-RFLP data for ordination-based exploratory microbial analyses.     

Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics

Background

Terminal restriction fragment length polymorphism (T-RFLP) analysis is a common DNA-fingerprinting technique used for comparisons of complex microbial communities. Although the technique is well established there is no consensus on how to treat T-RFLP data to achieve the highest possible accuracy and reproducibility. This study focused on two critical steps in the T-RFLP data treatment: the alignment of the terminal restriction fragments (T-RFs), which enables comparisons of samples, and the normalization of T-RF profiles, which adjusts for differences in signal strength, total fluorescence, between samples.

Results

Variations in the estimation of T-RF sizes were observed and these variations were found to affect the alignment of the T-RFs. A novel method was developed which improved the alignment by adjusting for systematic shifts in the T-RF size estimations between the T-RF profiles. Differences in total fluorescence were shown to be caused by differences in sample concentration and by the gel loading. Five normalization methods were evaluated and the total fluorescence normalization procedure based on peak height data was found to increase the similarity between replicate profiles the most. A high peak detection threshold, alignment correction, normalization and the use of consensus profiles instead of single profiles increased the similarity of replicate T-RF profiles, i.e. lead to an increased reproducibility. The impact of different treatment methods on the outcome of subsequent analyses of T-RFLP data was evaluated using a dataset from a longitudinal study of the bacterial community in an activated sludge wastewater treatment plant. Whether the alignment was corrected or not and if and how the T-RF profiles were normalized had a substantial impact on ordination analyses, assessments of bacterial dynamics and analyses of correlations with environmental parameters.

Conclusions

A novel method for the evaluation and correction of the alignment of T-RF profiles was shown to reduce the uncertainty and ambiguity in alignments of T-RF profiles. Large differences in the outcome of assessments of bacterial community structure and dynamics were observed between different alignment and normalization methods. The results of this study can therefore be of value when considering what methods to use in the analysis of T-RFLP data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0360-8) contains supplementary material, which is available to authorized users.     

Tools for T-RFLP data analysis using Excel

Background

Terminal restriction fragment length polymorphism (T-RFLP) analysis is a DNA-fingerprinting method that can be used for comparisons of the microbial community composition in a large number of samples. There is no consensus on how T-RFLP data should be treated and analyzed before comparisons between samples are made, and several different approaches have been proposed in the literature. The analysis of T-RFLP data can be cumbersome and time-consuming, and for large datasets manual data analysis is not feasible. The currently available tools for automated T-RFLP analysis, although valuable, offer little flexibility, and few, if any, options regarding what methods to use. To enable comparisons and combinations of different data treatment methods an analysis template and an extensive collection of macros for T-RFLP data analysis using Microsoft Excel were developed.

Results

The Tools for T-RFLP data analysis template provides procedures for the analysis of large T-RFLP datasets including application of a noise baseline threshold and setting of the analysis range, normalization and alignment of replicate profiles, generation of consensus profiles, normalization and alignment of consensus profiles and final analysis of the samples including calculation of association coefficients and diversity index. The procedures are designed so that in all analysis steps, from the initial preparation of the data to the final comparison of the samples, there are various different options available. The parameters regarding analysis range, noise baseline, T-RF alignment and generation of consensus profiles are all given by the user and several different methods are available for normalization of the T-RF profiles. In each step, the user can also choose to base the calculations on either peak height data or peak area data.

Conclusions

The Tools for T-RFLP data analysis template enables an objective and flexible analysis of large T-RFLP datasets in a widely used spreadsheet application.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0361-7) contains supplementary material, which is available to authorized users.     

Methodologically induced differences in oak site classifications in a homogeneous tree-ring network

Spatiotemporal variations in tree growth are induced by varying environmental conditions. Different methods like variants of the principal component analysis and the hierarchical cluster analysis are commonly applied in dendroecology to separate subsets of growth patterns within large tree-ring datasets. To seek for methodological differences in classification techniques and their specific characteristics, we compared three standard methods using a homogeneous oak (Quercus spp.) network from temperate forests in Central-West Germany. Classifications of the original dataset consisting of 46 oak ring-width sites, carried out with the varimax rotated principle component analysis, Ward's method and the average linkage method, reveal differences in the classification of approximately 20% of the sites. Analyses with modified datasets are calculated to evaluate effects of dataset extension, different time periods and different tree-ring detrendings. The application of the principal component analysis generally leads to the most stable site classifications, whereas the most sensitive response to changes in the dataset is obtained by Ward's method. The average linkage method separates single sites in the classification and thus emphasises outliers within the tree-ring network.     

An evaluation of terminal-restriction fragment length polymorphism (T-RFLP) analysis for the study of microbial community structure and dynamics

A systematic evaluation of the value and potential of terminal-restriction fragment length polymorphism (T-RFLP) analysis for the study of microbial community structure has been undertaken. The reproducibility and robustness of the method has been assessed using environmental DNA samples isolated directly from PCB-polluted or pristine soil, and subsequent polymerase chain reaction (PCR) amplification of total community 16S rDNA. An initial investigation to assess the variability both within and between different polyacrylamide gel electrophoresis (PAGE) runs showed that almost identical community profiles were consistently produced from the same sample. Similarly, very little variability was observed as a result of variation between replicate restriction digestions, PCR amplifications or between replicate DNA isolations. Decreasing concentrations of template DNA produced a decline in both the complexity and the intensity of fragments present in the community profile, with no additional fragments detected in the higher dilutions that were not already present when more original template DNA was used. Reducing the number of cycles of PCR produced similar results. The greatest variation between profiles generated from the same DNA sample was produced using different Taq DNA polymerases, while lower levels of variability were found between PCR products that had been produced using different annealing temperatures. Incomplete digestion by the restriction enzyme may, as a result of the generation of partially digested fragments, lead to an overestimation of the overall diversity within a community. The results obtained indicate that, once standardized, T-RFLP analysis is a highly reproducible and robust technique that yields high-quality fingerprints consisting of fragments of precise sizes, which, in principle, could be phylogenetically assigned, once an appropriate database is constructed.     

Parity among interpretation methods of MLEE patterns and disparity among clustering methods in epidemiological typing of Candida albicans

The typing of C. albicans by MLEE (multilocus enzyme electrophoresis) is dependent on the interpretation of enzyme electrophoretic patterns, and the study of the epidemiological relationships of these yeasts can be conducted by cluster analysis. Therefore, the aims of the present study were to first determine the discriminatory power of genetic interpretation (deduction of the allelic composition of diploid organisms) and numerical interpretation (mere determination of the presence and absence of bands) of MLEE patterns, and then to determine the concordance (Pearson product-moment correlation coefficient) and similarity (Jaccard similarity coefficient) of the groups of strains generated by three cluster analysis models, and the discriminatory power of such models as well [model A: genetic interpretation, genetic distance matrix of Nei (d(ij)) and UPGMA dendrogram; model B: genetic interpretation, Dice similarity matrix (S(D1)) and UPGMA dendrogram; model C: numerical interpretation, Dice similarity matrix (S(D2)) and UPGMA dendrogram]. MLEE was found to be a powerful and reliable tool for the typing of C. albicans due to its high discriminatory power (>0.9). Discriminatory power indicated that numerical interpretation is a method capable of discriminating a greater number of strains (47 versus 43 subtypes), but also pointed to model B as a method capable of providing a greater number of groups, suggesting its use for the typing of C. albicans by MLEE and cluster analysis. Very good agreement was only observed between the elements of the matrices S(D1) and S(D2), but a large majority of the groups generated in the three UPGMA dendrograms showed similarity S(J) between 4.8% and 75%, suggesting disparities in the conclusions obtained by the cluster assays.     

Genetic Diversity in Grapevine Germplasm Resources in the Coruh Valley Revealed by RAPD Markers

Random amplified polymorphic DNA analysis was carried out in 35 autochthonous table grapevine cultivars grown in Coruh valley. Fifty-five oligonucleotide primers were screened on cultivars, and among them, 12 primers showed clear polymorphic patterns. PCR amplification with 12 primers generated a total of 157 polymorphic bands. There was genetic variation among the cultivars with values of genetic diversity ranging from 0.19 to 0.72 using the Jaccard coefficient. UPGMA analysis of the distance matrix resulted in a dendrogram with two main clusters. The first cluster included 28 cultivars and the second 7 cultivars. The greatest genetic similarity was observed between cultivars Gah and Kolik, while the greatest dissimilarity was observed between cultivars Gah and Siyah Kus Uzumu. The dendrogram revealed that the cultivars present in Coruh valley can be distinguished to a relatively high degree.     

Semi-automated genetic analyses of soil microbial communities: comparison of T-RFLP and RISA based on descriptive and discriminative statistical approaches

Cultivation independent analyses of soil microbial community structures are frequently used to describe microbiological soil characteristics. This approach is based on direct extraction of total soil DNA followed by PCR amplification of selected marker genes and subsequent genetic fingerprint analyses. Semi-automated genetic fingerprinting techniques such as terminal restriction fragment length polymorphism (T-RFLP) and ribosomal intergenic spacer analysis (RISA) yield high-resolution patterns of highly diverse soil microbial communities and hold great potential for use in routine soil quality monitoring, when rapid high throughput screening for differences or changes is more important than phylogenetic identification of organisms affected. Our objective was to perform profound statistical analysis to evaluate the cultivation independent approach and the consistency of results from T-RFLP and RISA. As a model system, we used two different heavy metal treated soils from an open top chamber experiment. Bacterial T-RFLP and RISA profiles of 16S rDNA were converted into numeric data matrices in order to allow for detailed statistical analyses with cluster analysis, Mantel test statistics, Monte Carlo permutation tests and ANOVA. Analyses revealed that soil DNA-contents were significantly correlated with soil microbial biomass in our system. T-RFLP and RISA yielded highly consistent and correlating results and both allowed to distinguish the four treatments with equal significance. While RISA represents a fast and general fingerprinting method of moderate cost and labor intensity, T-RFLP is technically more demanding but offers the advantage of phylogenetic identification of detected soil microorganisms. Therefore, selection of either of these methods should be based on the specific research question under investigation.     

Population structure and genetic diversity in bottle gourd [Lagenaria siceraria (Mol.) Standl.] germplasm from India assessed by ISSR markers

Genetic diversity analysis was undertaken in 42 geographically distant genotypes accessions of bottle gourd (Lagenaria siceraria) from India northeastern (14) and northern region (28) using inter-simple sequence repeat (ISSR) markers. A total of 209 amplified bands were obtained from 20 ISSR primers used in this study, of which 186 were polymorphic with 89.00 % band polymorphism. Various parameters namely, observed number of alleles, effective number of alleles, Nei’s gene diversity/heterozygosity, resolving power, Shannon’s information index and gene flow were estimated under experiment. Jaccard’s similarity coefficient matrix was generated for pairwise comparisons between individual ISSR profiles and UPGMA cluster analysis based on this matrix showed clustering into six groups. Jaccard’s coefficient of similarity values ranged from 0.409 to 0.847, with a mean of 0.628 revealing a moderate level of genetic diversity. The Bayesian model-based approach to infer hidden genetic population structures using the multilocus ISSR markers revealed two populations among the 42 genotypes. This is the first report on the assessment of genetic variation using ISSR markers in this medicinal vegetable plant, and this study of diversity analysis will be helpful in analyzing future hybrid breeding strategy and devising effective germplasm exploration and conservation strategy.     

Molecular identification of fecal pollution sources in water supplies by host-specific fecal DNA markers and Terminal Restriction Fragment Length Polymorphism profiles of 16S rRNA gene

Specific fecal DNA markers were investigated for major pollution sources, cow, human, and pig, and occurrence of the identified markers was analyzed in river waters using Terminal Restriction Fragment Length Polymorphism (T-RFLP) techniques and sequencing of 16S rDNA of Bacteroides-Prevotella. The unique and specific DNA markers for cow and human were identified as a 222 bp and 60 bp peak in HaeIII T-RFLP profiles, respectively, and the pig-specific marker was not identified but the unique T-RFLP profile of pig could be used as a substitution. Human-specific marker was detected in most of the river waters tested (92.1%) and T-RFLP profiles of river waters were shown to be similar to those of human feces. Cluster analysis of T-RFLP data showed that the fecal sources were multiple (human plus cow and human plus dairy cow) in most of the river waters. The phylogenetic analysis for the clones recovered from the fecal and water samples showed that the clones from cow formed a discreet cluster from those of other sources. The other clones from human, pig, and river water formed two groups all together. The results of this study could be used to identify and control the fecal pollution source in the bodies of water in Korea.     

Informative SSR markers for commercial variety discrimination in watermelon (Citrullus lanatus)

SSR markers were used for variety discrimination and genetic assessment in watermelon varieties. Genetic characterization of 49 watermelon varieties was investigated using 30 SSR markers developed from melon and watermelon. A total of 121 polymorphic amplified fragments were obtained by using 30 SSR markers. The average polymorphism information content (PIC) was 0.502 ranging from 0.223 to 0.800. One hundred twenty one SSR loci were used to calculate Jaccard’s distance coefficients for unweighted pair group method using the arithmetic averages (UPGMA) cluster analysis. A clustering group of varieties, based on the results of SSR analysis, were categorized into 5 major groups corresponding to morphological traits. Inheritance mode of 2 SSR markers was investigated to F₁ plants and F₂ populations of 2 crosses. Parental alleles were transmitted from F1 plants and F2 populations. Therefore, these marker sets may prove to be effectively applicable to genetic assessment of germplasm, genome mapping, and fingerprinting of watermelon varieties.     

Differentiation ofLactobacillus spp. isolated from Chinese sourdoughs by AFLP and classical methods

TwentyLactobacillus strains isolated from sourdoughs that were used as starters for Chinese steamed bread were characterised by amplified fragment length polymorphism (AFLP) and classical methods. Twenty strains were divided into five clusters with AFLP profiles using similarity coefficient 0.60 (Jaccard coefficient) as a cut-off point, while three bio-clusters were formed with a numerical taxonomy classification based on phenotypic features, at a similarity level of 0.80 (Jaccard coefficient) and an average linkage algorithm (UPGMA) of clustering. A good correlation was observed between the two methods. The results suggested that the AFLP method is a useful taxonomic tool for typing of LAB, and the combination of the two methods may lead to obtain an improved understanding of the relationship between the phenotype and genotype of theLactobacillus spp. from the sourdough.     

Maturation of the murine cecal microbiota as revealed by terminal restriction fragment length polymorphism and 16S rRNA gene clone libraries

The maturation of murine cecal microbiota was determined by terminal restriction fragment polymorphism (T-RFLP) and 16S rRNA gene clone libraries. Cecal microbiota in specific pathogen free (SPF) mice aged four to 10 weeks were collected. The cluster of samples in 4-week-old mice was different from those of other ages based on T-RFLP profiles. The majority of clones obtained in this study belonged to the Clostridium coccoides (C. coccoides) group, the Bacteroides group or the Lactobacillus group. Phylogenetic analysis showed characteristic clusters composed of new operational taxonomic unit (OTU) of the C. coccoides and Bacteroides groups. The existence of a large number of yet unidentified bacteria inhabiting the murine cecum was demonstrated by 16S rRNA gene clone libraries. T-RFLP analysis data were more complex and more sensitive than the patterns generated by computer simulation of 16S rRNA gene clone library analysis data. T-RFLP revealed development with maturation of cecal microbiota including unidentified bacteria of SPF mice.     

应用ISSR技术分析不同分离方法获得的冬虫夏草菌株的遗传多样性

从60个引物中筛选出7个扩增条带清晰且多态性好的ISSR引物,并摸索合适的PCR反应条件,用于40株冬虫夏草的无性型——中国被毛孢菌株的PCR反应,共得到62条带,其中多态性条带38条,多态性百分率仅为61.29%,遗传相似系数范围在0.78¹.00之间。非加权配对算术平均法(UPGMA)聚类分析的结果表明:40株中冬虫夏草无性型菌株并没有完全按照不同的分离方法聚为3个类型;单子囊孢子分离法获得的菌株,明显区别于其他菌株而单独聚为一类,其他菌株则混合聚类。     

Genome and species relationships in genus<Emphasis Type="Italic"> Avena</Emphasis> based on RAPD and AFLP molecular markers

Species and genome relationships among 11 diploid (A and C genomes), five tetraploid (AB and AC genomes) and two hexaploid (ACD genome) Avena taxa were investigated using amplified fragment length polymorphisms (AFLPs) and random amplified polymorphic DNA (RAPD) markers. The two primer pairs used for the AFLP reactions produced a total of 354 polymorphic bands, while 187 reproducible bands were generated using ten RAPD primers. Genetic similarities amongst the entries were estimated using the Jaccard and Dice algorithms, and cluster analyses were performed using UPGMA and neighbor joining methods. Principle coordinate analysis was also applied. The highest cophenetic correlation coefficient was obtained for the Jaccard algorithm and UPGMA clustering method (r=0.99 for AFLP and r=0.94 for RAPD). No major clustering differences were present between phenograms produced with AFLPs and RAPDs. Furthermore, data produced with AFLPs and RAPDs were highly correlated (r=0.92), indicating the reliability of our results. All A genome diploid taxa are clustered together according to their karyotype. The AB genome tetraploids were found to form a subcluster within the A_s genome diploids (AFLPs), indicating their near-autoploid origin. The AC genome tetraploids are clustered to the ACD genome hexaploids. Finally, the C genome diploids form an outer branch, indicating the major genomic divergence between the A and C genomes in Avena.Communicated by J.S. Heslop-Harrison     

Study of genetic variation among parsley (<Emphasis Type="Italic">Petroselinum Crispum</Emphasis> (Mill.) Nym.) samples using RAPD and ISSR markers

RAPD and ISSR markers have been used to classify 32 samples of parsley (Petroselinum Crispum (Mill.) Nym. ex A. W. Hill) including the root and leaf plants. In total, 51 RAPD and 66 ISSR markers were amplified by five RAPD and six ISSR primers. On average, the ISSR and RAPD spectra had 11 and 10.2 bands, respectively. The matrix of genetic distances between the samples was constructed using Jaccard coefficients. The dendrogram constructed by the UPGMA method graphically shows the values of genetic distances. The distance between root and leaf forms of parsley was 0.292.