Cytological and Molecular Characterization of Genetic ...

RESEARCH

Cytological and Molecular Characterization of Genetic Diversity in Stenotaphrum Susana R. Milla-Lewis,* M. Carolina Zuleta, George A. Van Esbroeck, Kenneth H. Quesenberry, and Kevin E. Kenworthy

ABSTRACT St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] is a warm-season turfgrass broadly distributed across the southern United States. Here, we investigated genetic diversity and ploidy levels in publicly available plant introductions and cultivars of St. Augustinegrass as an aid to more effective use of these materials in breeding programs. Ploidy assignment of genotypes was problematic in some cases because of a lack of agreement between flow cytometry–inferred ploidy level and chromosome counts indicating that DNA content of higher ploidy genotypes was not a simple multiple of the diploid genome. Cytological investigations indicated five different ploidy levels (diploid, triploid, aneuploid, tetraploid, and hexaploid) with chromosome numbers ranging from 2n = 2x = 18 to 2n = 6x = 54. Principal coordinate and cluster analyses separated genotypes into distinct groups that were mostly congruent with ploidy levels. Moreover, analysis of molecular variance results based on amplified fragment length polymorphism genotyping indicated that 46% of the total variation could be explained by differences between ploidy levels. A clear positive correlation was observed between ploidy level and number of scored bands, with polyploids showing an increased number of bands. Variation in chromosome number is an important source of genetic variation in S. secundatum, and knowledge of the genetic relationships among accessions of this species can be an important consideration for the proper utilization of this germplasm in applied cultivar development.

S.R. Milla-Lewis, M.C. Zuleta, and G.A. Van Esbroeck, Dep. of Crop Science, Box 7620, North Carolina State Univ., Raleigh, NC 27695-7620; K.H. Quesenberry and K.E. Kenworthy, Agronomy Dep., Box 110500, Univ. of Florida, Gainesville, FL 32611-0500. Received: 11 Apr. 2012. *Corresponding author ([email protected]). Abbreviations: AFLP, amplified fragment length polymorphism; AMOVA, analysis of molecular variance; GS, genetic similarity; MI, marker index; PCO, principal coordinate analysis; PCR, polymerase chain reaction; PI, plant introduction; PIC, polymorphic information content; PP, primer pair; UPGMA, unweighted pair group method with arithmetic averaging.

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t. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] is widely adapted as a lawn grass in warm, tropical and subtropical regions of the world (Sauer, 1972). The grass is highly resistant to weed infestation (Busey, 2003), grows well in a broad range of soil conditions, and exhibits good performance under shade conditions relative to other warm-season grasses (Busey and David, 1991; Busey et al., 1982b). Broad leaf blades and rapid stolon production allow the grass to form a coarse-textured monostand that is well suited for sod production, home lawns, and commercial landscapes. All these characteristics make St. Augustinegrass a valued turfgrass in the southern United States. The genus Stenotaphrum is comprised of seven species, all indigenous to coastlines from East Africa to islands of the South Pacific (Busey, 1995; Sauer, 1972). Pembagrass [S. dimidatum (L.) Brongn.] is the most closely related species to St. Augustinegrass. Evidence of introgression from this species in some polyploid St. Augustinegrass introductions has been observed (Busey, 1993, 1995). The base chromosome number of S. secundatum is Published in Crop Sci. 53:296–308 (2013). doi: 10.2135/cropsci2012.04.0234 © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

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x = 9, with diploids (2n = 2x = 18), triploids (2n = 3x = 27), and tetraploids (2n = 4x = 36) reported (Long and Bashaw, 1961). Aneuploids (e.g., cultivars Floratam and FX-10) were reported by Busey (1979, 1993); however, the extent of aneuploidy in the genus has not been fully evaluated. Genome composition in the genus is also largely unknown, but some African polyploids were hypothesized to be allopolyploids (Busey, 2003). Classification of the genetic diversity present in St. Augustinegrass, based on morphological and performance traits (Busey, 1986, 1995, 2003; Busey and Zaenker, 1992; Busey et al., 1982a, 1993; Reinert et al., 1986), has revealed distinct clusters of similar genotypes. The most marked morphological and adaptive differentiation occurs between diploids and polyploids. Plant breeding efforts in St. Augustinegrass have emphasized, for the most part, the use of diploid materials; however, a limited number of germplasm evaluations have revealed that significant phenotypic variation exists among polyploid germplasm. For example, polyploid lines have been found to be more resistant than diploids against the southern chinch bug (Blissus insularis Barber) (Busey and Zaenker, 1992; Reinert et al., 1986), the St. Augustine Decline Strain of Panicum Mosaic Virus (Horn et al., 1973), the sting nematode (Belonolaimus longicaudatus Rau) (Busey et al., 1993), and Magnaporthe grisea, the causal agent of gray leaf spot disease (Atilano and Busey, 1983; Milla-Lewis et al., 2011b). Polyploids were also reported to exhibit increased water use efficiency as compared to diploids (Busey, 2003). The exploitation of the variation found among polyploids has been hindered due to sterility issues related to unbalanced chromosome complements, however. While the production of interploidy hybrids has been reported (Busey, 1993; Genovesi et al., 2009), success rates are low and often require the use of embryo rescue techniques. The study of genetic diversity and race classification in the species was based on morphological traits such as stolon length and stigma color (Busey et al., 1982a; Busey, 1986). While plant morphology can be useful to gauge levels of genetic diversity, morphological plasticity has been found to be more common in turfgrass than in other crop species (Bradshaw, 1965). Therefore, turfgrasses generally require multiple measurements in multiple environments for proper characterization. With the advent of DNA marker techniques, the level of resolution for detecting genetic variation in germplasm characterization studies has dramatically increased. In warm-season turfgrasses, a number of studies on the use of polymerase chain reaction (PCR)–based DNA fingerprinting techniques for assessing genetic diversity have been published for Cynodon (Gulsen et al., 2009; Kang et al., 2008; Wu et al., 2005, 2006), Zoysia spp. (Guo et al., 2008; Kimball et al., 2012; La Mantia et al., 2011; Tsuruta et al., 2005), carpetgrass [Axonopus fissifolius (Raddi) Kuhlm.] (Wang et al., 2010), and centipedegrass [Eremochloa ophiuroides (Munro) Hack.] crop science, vol. 53, january– february 2013

(Harris-Shultz et al., 2012; Milla-Lewis et al., 2011a; Weaver et al., 1995). In St. Augustinegrass, molecular information has lagged behind, with limited studies on the application of molecular marker techniques. In one study (Genovesi et al., 2009), buffelgrass [Pennisetum ciliare (L.) Link] expressed sequence tag–simple sequence repeats were used to confirm hybridity and assess genetic variation in 25 plants derived from interploidy crosses. In another study, amplified fragment length polymorphism (AFLP) markers were used to detect genetic variants among samples of cultivar ‘Raleigh’ collected from sod farms across the southern United States (Kimball et al., 2012). The only published study focusing on germplasm characterization was based on isozyme polymorphisms of a limited number of cultivars and breeding lines (Green et al., 1981). The AFLP technique (Vos et al., 1995; Zabeau and Vos, 1993) has been used for determining taxonomic relationships and assessing genetic variation in a range of crop species (Hill et al., 1995; Meudt and Clarke, 2007; Powell et al., 1996). The AFLP technique allows analysis of a large number of loci throughout the genome, has high reproducibility rates, and can detect high levels of polymorphism (Powell et al., 1996). Moreover, the technique is ideally suited for studying genetic diversity in genera such as Stenotaphrum for which little genomic information currently exists (Lu et al., 1996; Prabhu and Gresshoff, 1994). The duplication of genes during polyploidization has been suggested as a major force driving diversity in angiosperms (Leitch and Leitch, 2008). Duplicated genes may retain function, gain new function, or become silenced, all of which could result in increased genotypic and phenotypic diversity (Wendel, 2000). Gene diversification in polyploids could also result in higher levels of molecular marker polymorphism. In buffalograss [Buchloe dactyloides (Nutt.) Engelm.], Gulsen et al. (2005) and Budak et al. (2005) found greater frequencies of PCRderived fragments among plants with higher ploidy levels than among diploids. Gulsen et al. (2009) observed the same in the genus Cynodon, reporting that 38% of the variation in fragment frequency could be explained by differences in ploidy level. The presence of increased phenotypic variation among Stenotaphrum polyploids for a number of traits suggests that genome diversification through polyploidization also occurs in this genus. Up to this time, however, the relationship between polyploidy and allele frequency has not been investigated in St. Augustinegrass. Few studies have attempted to study the levels of intraand interspecific variation present in Stenotaphrum. A comprehensive assessment of the molecular and cytological diversity present in the genus would aid breeders in the use of this germplasm for population improvement, especially when dealing with the transfer of desirable traits from polyploid to diploid genotypes. In the present study, flow cytometry, chromosome counts, and AFLP marker

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analyses were performed to: (i) determine the extent of molecular variation present in different sources of St. Augustinegrass germplasm, (ii) establish ploidy levels in publicly available Stenotaphrum germplasm and determine the usefulness of the flow cytometry technique for such purposes, (iii) assess possible relationships between ploidy level and molecular diversity, and (iv) compare previously published taxonomic relationships based on morphological information to those revealed by molecular markers.

Materials and Methods Plant Materials

A total of 21 cultivars and 18 plant introductions (PIs) of St. Augustinegrass were evaluated in this study (Table 1). Additionally, two accessions of Pembagrass, a close relative of St. Augustinegrass, were analyzed. Samples from all cultivars, with the exception of ‘Polaris’ (Philley and Krans, 2010) and ‘Eclipse’ (Philley et al., 2009), were obtained from Dr. Kevin Kenworthy at the University of Florida (Gainesville, FL). Samples of Polaris and Eclipse were obtained from Mr. Wayne

Table 1. List of St. Augustine, Pemba, and Bahiagrass materials used in assessment of molecular diversity with amplified fragment length polymorphism markers and their nuclear DNA content and inferred ploidy level based on flow cytometry. Identity Amerishade Bitterblue Captiva Classic Delmar Deltashade Eclipse Floralawn Floratam Floratine Floraverde FX-10 Jade Mercedes Palmetto Polaris Raleigh Sapphire Seville Sunclipse TX Common PI 289729 PI 290888 PI 291594 PI 300129 PI 300130 PI 365031 PI 365032 PI 410353 PI 410355 PI 410357 PI 410360 PI 410361 PI 410362‡ PI 410363 PI 410364 PI 414079 PI 509038 PI 509039 PI 647924 PI 647925 † ‡

Type

Species

Source†

Mean DNA ( pg/2C )± SD

Flow cytometry–inferred ploidy

Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar Cultivar PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI

Stenotaphrum secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. dimidatum S. secundatum S. secundatum S. secundatum S. secundatum S. dimidatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum Paspalum notatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum S. secundatum

UF UF UF UF UF UF MSU UF UF UF UF UF UF UF UF MSU UF UF UF UF UF NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS NPGS

1.18 ± 0.07 1.81 ± 0.06 1.20 ± 0.05 1.17 ± 0.07 1.21 ± 0.06 1.19 ± 0.01 1.12 ± 0.06 2.29 ± 0.02 2.30 ± 0.01 1.76 ± 0.02 1.17 ± 0.02 2.41 ± 0.01 1.21 ± 0.03 1.17 ± 0.05 1.14 ± 0.04 1.19 ± 0.03 1.15 ± 0.04 1.19 ± 0.04 1.16 ± 0.02 1.22 ± 0.03 1.15 ± 0.01 3.46 ± 0.12 2.33 ± 0.02 2.32 ± 0.02 2.34 ± 0.07 2.34 ± 0.06 4.40 ± 0.06 1.20 ± 0.03 1.26 ± 0.00 1.26 ± 0.14 1.26 ± 0.06 1.22 ± 0.01 1.22 ± 0.04 — 1.24 ± 0.03 1.19 ± 0.05 1.16 ± 0.18 1.12 ± 0.03 1.18 ± 0.02 1.12 ± 0.03 1.11 ± 0.03

Diploid Triploid Diploid Diploid Diploid Diploid Diploid Tetraploid Tetraploid Triploid Diploid Tetraploid Diploid Diploid Diploid Diploid Diploid Diploid Diploid Diploid Diploid Hexaploid Tetraploid Tetraploid Tetraploid Tetraploid Heptaploid Diploid Diploid Diploid Diploid Diploid Diploid — Diploid Diploid Diploid Diploid Diploid Diploid Diploid

UF, University of Florida; MSU, Mississippi State University; NPGS, National Plant Germplasm System. Plant Introduction (PI) 410362 is listed as Stenotaphrum secundatum in NPGS, but is an accession of Paspalum notatum.

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Philley at Mississippi State University (Starkville, MS). The 20 PIs were obtained from the National Plant Germplasm System (S9 Germplasm Repository, Griffin, GA). All samples were received as vegetative plugs. They were planted into plastic pots filled with Fafard 4P potting mix (Conrad Fafard Inc., Agawam, MA) and placed in a greenhouse. Plants were mowed biweekly at a 7.62-cm (3-in) height and fertilized every 2 wk with Scotts Starter Fertilizer (The Scotts Company LLC, Marysville, OH).

Flow Cytometry Nuclear DNA content of the genotypes was determined using fresh leaf tissue taken from greenhouse-grown plants. Soybean (Glycine max Merr. ‘Roy’) and corn (Zea mays L. ‘Bicolor Sweet Frisky F1’) were used as internal standards. The nuclear 2C DNA content of the standards was assumed to be 2.5 pg for soybean and 5.43 pg for corn (Doležel et al., 2007). DNA extraction and propidium iodide staining were performed with a CyStain Propidium Iodide Absolute P Staining Kit 05-5022 (Partec North America, Swedesboro, NJ). Briefly, 500 μL of nuclei extraction buffer was added to a 5-cm petri dish containing the standard and sample. The sample leaf tissue and internal standard (200 mg of each) were co-chopped with a new razor for about 60 s and then filtered through a 30-μm filter into a 5-mL test tube. The solution was stained with 3 to 4 mL of Cystain Propidium Iodide Absolute P staining buffer (including Cystain Propodium Iodide and RNase) and incubated in the dark at room temperature for 60 to 90 min. Samples were then stored in the dark on ice until analysis was completed the same day. Analysis was performed at the North Carolina School of Veterinary Medicine (Raleigh, NC) with a FACSCalibur flow cytometer (Becton-Dickinson Biosciences, San Jose, CA). It was operated with a 15-mW argon laser (excitation at 488 nm) and propidium iodide fluorescence (FLA-2) was detected. Signal from subcellular debris was gated out and the position of the G1 histogram peaks measured using CellQuest Pro software (Becton-Dickinson Biosciences, San Jose, CA). Histograms

were based on 10,000 scanned particles (sample + standard). DNA content was calculated as: (sample histogram peak/standard histogram peak) × DNA content of the standard. When sample histogram peaks overlapped with the soybean standards, subsequent samples of those genotypes were performed using corn. On each sampling day, two samples of soybeans and corn were co-chopped and analyzed. In all cases, the ratio of soybean to corn G1 histogram peaks was within 98% of the value reported by Doležel et al. (2007). Each genotype was replicated three times (one on each of 3 d). Ploidy levels were determined by comparing mean DNA contents of each genotype to that of ‘Raleigh’ (Bateman, 1980), which is a known diploid St. Augustinegrass genotype (Arumuganathan et al., 1999).

Chromosome Counts Following DNA content analysis, chromosome numbers were determined for the extremes of each DNA content level, with the exception of diploids where six genotypes (lowest, highest, and four intermediates) were analyzed. Immature inflorescences were collected in 6:3:1 (v:v:v) 95% (v/v) ethanol:chloroform:glacial acetic acid, then transferred after 24 h to 70% (v/v) ethanol for storage. Entire spikes were stained overnight in Snow’s carmine (Snow, 1963). Spikes were removed from stain, rinsed in 70% ethanol, and individual florets were dissected from the spike. Immature anthers were then dissected from the florets on a microscope slide using a dissecting microscope. Anthers were mounted and stained in a drop of aceto-orcein stain and squashed by gentle tapping on the cover slip. Observations and photographs of pollen mother cells were made primarily at 250× and 500× magnification. The number of counts per accession ranged from 3 to 17 (Table 2), and may be mitotic or meiotic determinations.

DNA Extraction and AFLP Analysis Four young, unopened leaves were collected from each plant and bulked together for DNA extraction. The

Table 2. Cytological chromosome counts of selected Stenotaphrum accessions and comparison of inferred ploidy levels with those of previously published reports and flow cytometry. Entry Jade Captiva PI† 647925 Raleigh Amerishade PI 410357 Bitterblue PI 300129 PI 291594 Floratine PI 290888 PI 300130 FX-10 Floratam Floralawn PI 289729 PI 365031 †

No. observed

Chromosome count Absolute no.

Ploidy

Literature ploidy

3 17 5 6 3 5 9 10 16 7 5 8 14 6 12 5 12

2n = 18 2n = 18 2n = 18 2n = 18 2n = 18 2n = 18 2n = 27 2n = 27 2n = 27 2n = 27 2n = 28 2n = 30 2n = 30 2n = 32 2n = 32 2n = 36 2n = 54

Diploid Diploid Diploid Diploid Diploid Diploid Triploid Triploid Triploid Triploid Aneuploid Aneuploid Aneuploid Aneuploid Aneuploid Tetraploid Hexaploid

2n = 18 (Busey, 1995) 2n = 18 — 2n = 18 (Busey, 1995) — — 2n = 27 (Busey, 2003) — — 2n = 27 (Busey, 1995) 2n = 30 (Busey, 1990) 2n = 30 (Busey, 1990) 2n = 30 (Busey, 1990) 2n = c.32 (Busey, 1979) 2n = c.32 (Busey, 1995) — 2n = 54 (Busey, 1990)

Flow cytometry 2C value Ploidy 1.21 1.20 1.11 1.15 1.18 1.26 1.81 2.34 2.32 1.76 2.33 2.34 2.41 2.30 2.29 3.46 4.40

Diploid Diploid Diploid Diploid Diploid Diploid Triploid Tetraploid Tetraploid Triploid Tetraploid Tetraploid Tetraploid Tetraploid Tetraploid Hexaploid Heptaploid

PI, Plant Introduction.


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cetyltrimethylammonium bromide method of Stein et al. (2001) was used with the modification that a Fast Prep FP120 (Qbiogene, Carlsbad, CA) was used to grind the leaves. DNA quantifications were performed using a Hoefer fluorometer (Hoefer Scientific Instruments, San Francisco, CA). Subsequently, samples were diluted to 10 ng μL –1, and stored at 4°C. Labeled EcoRI + 3 primers were purchased from LI-COR Inc. (Lincoln, NE). All other AFLP primers and adapters were obtained from Sigma Genosys (The Woodlands, TX). The AFLP reactions and polyacrylamide gel electrophoresis were performed following the protocols of Milla et al. (2005). Two completely independent AFLP fingerprints were generated for three samples (Raleigh, PI 647924, and PI 647925) to evaluate the reproducibility of banding patterns. The mean reproducibility value for each primer pair (PP) was calculated as the correlation between the two repeats averaged across all three genotypes.

Genotypic Data Analysis The AFLP-Quantar 1.0 software package (KeyGene Products, 2000) was used to score bands as binary data (present = 1, absent = 0). Fragments of the same size in different genotypes were considered to be the same allele. Standard statistics were calculated for each PP including: total number of bands, number of polymorphic bands, percentage of polymorphic bands, and number of scored bands. The discriminatory power of each PP was assessed by calculating the polymorphic information content (PIC) and marker index (MI) values. The mean PIC value for n loci was calculated as:

å (1 - F PIC = n

2 aaj

j -1

1000 replications was used to evaluate the goodness of fit between the UPGMA clustering and the original similarity matrix by using the COPH and MXCOMP modules in NTSYS. To assess genetic relationships among genotypes, a principal coordinate analysis (PCO) was performed based on the distance matrix using the Dcenter and Eigen functions of NTSYS. The first three resulting principal coordinate scores were plotted for visualization. Additionally, an analysis of molecular variance (AMOVA) was performed using Arlequin version 3.0 (Excoffier et al., 2005) to partition molecular variation among and within germplasm type (cultivars, PIs, and wild relatives) and ploidy level (diploids, triploids, aneuploids, and higher ploidy).

RESULTS

Ploidy Levels Mean 2C nuclear DNA contents for the 40 Stenotaphrum accessions are listed in Table 1, and representative flow histograms are presented in Fig. 1. Nuclear DNA content for S. secundatum accessions ranged from 1.11 to 2.41, whereas for S. dimidatum accessions ranged from 3.46 to 4.40. Based on their nuclear DNA content, the accessions could be roughly classified into five ploidy levels: diploid, triploid, tetraploid, hexaploid, and heptaploid. Of the 40 accessions analyzed, 29 were diploid, two were triploid,

- Fan2 j )

n

where j is the jth locus, Faa is the frequency of the amplified allele, and Fan is the frequency of the nonamplified allele (Geuna et al., 2003). The MI was calculated as described by Varshney et al. (2007) as MI = PIC × n × b, where n is the total number of amplified fragments per PP, and b is the proportion of polymorphic fragments. To investigate linear, quadratic, and cubic associations between ploidy level and band frequency in the Stenotaphrum accessions, regression analysis using PROC REG (SAS Institute, 2008) was performed as described by Gulsen et al. (2009). Mainly, for each individual, the average frequency of present alleles was calculated as a/(a + b), where a = number of present alleles (1) and b = number of absent alleles (0), excluding missing values. Frequency of present alleles was then plotted against ploidy level. Genotypes were grouped by germplasm type (cultivars, PIs, and wild relatives) and ploidy level (diploid, triploid, aneuploid, and higher ploidy) and genetic similarity (GS) values were calculated for all pair-wise genotype combinations within and between groupings according to Dice (1945) using NTSYSpc v 2.2 (Rohlf, 2000). Average GS values were calculated for each group to compare levels of diversity among the different groupings. Genetic similarity values were also used to construct dendrograms using both the unweighted pair group method with arithmetic averaging (UPGMA; Sokal and Michener, 1958) and the neighbor-joining (NJ; Saitou and Nei, 1987) clustering procedures. The robustness of the phylogenetic trees was evaluated by comparing dendrograms obtained from both methods and by bootstrap analysis (Felsenstein, 1985). Additionally, a Mantel test (Mantel, 1967) with 300

Figure 1. Flow cytometry histograms showing relative G1 peaks as follows: (A) M1 for diploid (2n = 2x = 18) ‘Raleigh’, M2 for aneuploid (2n = 32) ‘Floratam’, M3 for tetraploid (2n = 4x = 36) Plant Introduction 289729, and M4 for control (corn); and (B) M1 for diploid Raleigh, M2 for triploid (2n = 3x = 27) ‘Bitterblue’, M3 for control (soybean), and M4 for hexaploid (2n = 6x = 54) PI 365031.

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seven were tetraploid, one was hexaploid, and one heptaploid with nuclear DNA contents of 1.11 to 1.26, 1.77 to 1.81, 2.29 to 2.41, 3.46, and 4.40, respectively (Table 1). The most common (73%) cytotype in Stenotaphrum germplasm was diploid. The accuracy of ploidy level determination based on flow cytometry was assessed by means of cytological chromosome counting. For diploid accessions, PIs 647925 and 410357, the individuals with the lowest and highest DNA contents, respectively, and four intermediate genotypes (Raleigh, ‘Amerishade’, ‘Captiva’, and ‘Jade’) were used for chromosome counts (Table 2 and Fig. 2). Eighteen chromosomes were observed consistently in all diploid samples, confirming the accuracy of flow cytometry estimations for the diploid group. For the polyploids, chromosome counts were performed on all accessions. While cytological observations confirmed

the ploidy levels inferred by flow cytometry on diploids and some triploids, this was not the case for all other polyploids where flow cytometry overestimated ploidy levels in all cases. All samples estimated to be tetraploids with flow cytometry were triploids and aneuploids ranging in chromosome number from 27 to 32 (Table 2). Plant Introductions 289729 and 365031 estimated as hexaploid and heptaploid, respectively, using flow cytometry were found to have chromosome numbers of 36 and 54, respectively. Previously published chromosome counts for some of these accessions were in agreement with our counts (Table 2) and were also in disagreement with flow cytometry–inferred ploidy levels for higher polyploids.

AFLP Polymorphism A total of 1793 fragments were generated using 15 PPs. Out of those, 564 distinct, polymorphic fragments ranging in size from 56 to 717 bp were scored. Standard statistics for all PPs are summarized in Table 3. The number of polymorphic scored fragments amplified per PP ranged from 19 to 57 with an average of 38. The range for PIC values was from 0.22 to 0.34 with an average of 0.29. The PP with the highest PIC and MI values was E-ACT/M-CGA, indicating that it was the PP with the most discriminatory power. Reproducibility values were very high and ranged from 94 to 100% with an average of 98% for the 15 PPs used (Table 3).

Relationship between Band Frequency and Ploidy Level Figure 2. Meiotic chromosome configurations in St. Augustinegrass: (A) diploid Plant Introduction 410357, diakinesis 9II, and (B) Floratam (2n = 32) AI showing 14–15 chromosome segregation with three lagging univalents.

The frequency of present bands in the Stenotaphrum germplasm studied varied from 0.25 to 0.50 with an average of 0.37. The diploids, triploids, aneuploids, tetraploid, and hexaploid had an average band frequency of 0.33, 0.49,

Table 3. Standard statistics for amplified fragment length polymorphism primer pairs (PP) used to assess genetic diversity among St. Augustinegrass germplasm. PP E-ACG/M-CAA E-ACG/M-CCG E-ACA/M-CCC E-ACA/M-CAG E-ACG/M-CGC E-AAT/M-CCA E-AGA/M-CAG E-ATG/M-CAT E-ATT/M-CGG E-ACC/M-CTA E-ACC/M-CCT E-ACT/M-CGT E-ACT/M-CGA E-AGG/M-CTC E-ATC/M-CAA Total †

TB† 125 117 106 95 132 121 147 145 105 116 94 133 143 104 110 1793

PB 99 97 88 78 110 97 122 105 90 103 86 123 123 99 104 1524

PPB % 79.20 82.91 83.02 82.11 83.33 80.17 82.99 72.41 85.71 88.79 91.49 92.48 86.01 95.19 94.55 85.00

SB 33 48 56 57 40 44 50 46 25 19 33 34 23 23 33 564

SRSB 98–610 80–513 60–717 76–644 72–558 82–522 97–614 80–544 113–694 168–650 99–561 93–547 99–499 87–458 56–688 56–717

PIC 0.28 0.27 0.22 0.27 0.34 0.31 0.25 0.31 0.27 0.31 0.28 0.28 0.34 0.33 0.33 0.29

MI 27.72 26.19 19.36 21.06 37.40 30.07 30.50 32.55 24.30 31.93 24.08 34.44 41.82 32.67 34.32 29.89

R % 100 97 100 99 100 100 98 98 100 96 96 100 94 97 98 98

TB, total number of bands; PB, number of polymorphic bands; PPB, percentage of polymorphic bands; SB, number of scored bands; SRSB, size range of scored bands; PIC, polymorphic information content; MI, marker index; R, repeatability.


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0.44, 0.36, and 0.41, respectively (Fig. 3). Regression analysis indicated that a cubic response was the most explanatory (adjusted R 2 = 0.64, P = 0.0007) for the association between ploidy level and band frequency.

Genetic Relationships and Principal Coordinate Analysis Average GS values for the different groupings are listed in Table 4. When looking at materials by ploidy level, diploids and triploids were the most and least diverse groups, respectively. While higher-level polyploids were the most distinct group, the level of diversity within this group was comparable to that of diploids. Regarding germplasm types, PIs were the most diverse group, followed by cultivars. The Dice GS values were used to generate dendrograms using the UPGMA and neighbor-joining methods. The genetic relationships obtained from both methods were similar except for inconsequential differences in a few topological rearrangements. Both dendrograms had the same main clusters. The dendrogram produced using the UPGMA method is presented (Fig. 4). The 41 accessions fell into six distinct groups that were based on ploidy level. Clusters I through III included all diploid genotypes. Specifically, Cluster I included all diploid commercial cultivars, Cluster II all PIs from diverse geographical origin, and Cluster III PIs collected from South Africa. While the first two clusters were not supported by high bootstrap values, the clustering of African PIs was strongly supported with a bootstrap value of 99%. Clusters IV and V, with bootstrap values of 100 and 98%, respectively, comprised all triploid and aneuploid accessions. Cluster VI included both accessions of Pembagrass and had a bootstrap value of 100%. Plant Introduction 410362 did not fall into any of the previously listed clusters and appeared to be distantly related from all other accessions. After visual examination of this accession, it was determined that it was an accession of Bahiagrass (Paspalum notatum Flügge) and had been misclassified in Germplasm Resources Information Network. The cophenetic correlation (Mantel test) was found to be very high (r = 0.95), indicating that the UPGMA clustering summarized the similarity matrix very well.

Principal coordinate analysis was also used to evaluate genetic relationships among Stenotaphrum germplasm. The first two axes of the PCO accounted for 72% of the variation with the first and second eigenvalues explaining 64% and 8%, respectively. The first axis separated among species, clearly differentiating among Pemba, St. Augustine, and Bahiagrass accessions (Fig. 5). The second axis separated ploidy levels, discriminating diploids from higher ploidy accessions. The PCO separated accessions into the same distinct groups as the UPGMA dendrogram. All diploid PIs and cultivars grouped together with the exception of the African PIs that formed their own tight cluster. Triploids and aneuploids formed two subgroups containing a mix of both ploidy levels. The two accessions of Pembagrass formed their own group, clearly differentiated from St. Augustinegrass accessions as in the dendrogram.

Analysis of Molecular Variance Results of the AMOVA test indicated that significant differences existed among and within ploidy levels and germplasm types (Table 5). Variation among ploidy levels

Figure 3. Distribution of amplified fragment length polymorphism fragment frequencies and ploidy levels in 40 Stenotaphrum accessions assessed for genetic diversity. # obs. = number of observations.

Table 4. Average genetic similarity values (GS) within and between groups of Stenotaphrum materials studied for amplified fragment length polymorphism diversity organized according to their inferred ploidy level or their germplasm type. By ploidy level Diploid Triploid Aneuploid S. dimidatum By germplasm type Cultivars Plant introductions Wild relatives

302

No. individuals

Diploid

Triploid

Aneuploid

S. dimidatum

29 2 7 2

0.71 0.57 0.55 0.36

0.76 0.74 0.44

0.72 0.44

0.72

21 17 2

0.72 0.62 0.38

0.64 0.38

0.72

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accounted for 46% of the total variation, whereas the within-group component accounted for 54%. For germplasm types this difference was more marked and the among and within components of variance accounted for 25 and 75% of the variation, respectively. While both the among- (Va) and within-groups (Vb) components of variance were highly significant (p < 0.0001) for both grouping schemes, group differentiation seems to be greater for ploidy level. This observation is supported by results from the cluster and PCO analyses.

DISCUSSION This study represents the first comprehensive assessment of genetic diversity at the molecular and cytological levels among public sources of Stenotaphrum germplasm. Regarding cytological variation, five different ploidy levels (diploid, triploid, aneuploid, tetraploid, and hexaploid) were identified with chromosome numbers ranging from 2n = 2x = 18 to 2n = 6x = 54. Our results indicate a lack of concordance between ploidy level as inferred by flow cytometry and actual chromosome numbers. Flow

cytometry has been used for the determination of ploidy levels in an array of plant species, including turfgrasses such as zoysiagrass (Schwartz et al., 2010) and bermudagrass (Wu et al., 2006; Gulsen et al., 2009), because of the many advantages of the technique (summarized in Doležel et al., 2007). Use of the technique is only recommended when differences in chromosome size among groups are not expected to be large, however (Emshwiller, 2002). Lack of correlation between DNA contents and chromosome numbers have also been reported in Triticeae (Vogel et al., 1999), Capsicum (Moscone et al., 2003), and Rosa (Yokoya et al., 2000), among others. Changes in DNA contents after polyploidization can be explained by the loss or gain of entire chromosomes (De Wet, 1979) or by changes in chromosome size (Das et al., 1998). While allotetraploidy has been proposed as the simplest cytological origin for the African polyploids (Busey, 2003), no information is available about differences in chromosome size or the existence of different genomes in Stenotaphrum. Our findings that flow cytometry was inaccurate at inferring ploidy levels for higher polyploids

Figure 4. Unweighted pair group method with arithmetic averaging dendrogram of 40 Stenotaphrum and one Bahiagrass genotypes constructed using 564 amplified fragment length polymorphism markers. Numbers in parentheses after the entry name indicate inferred ploidy level. Aneuploids are labeled as 3–4X. Bootstrap values >50% are displayed. Plant Introduction 410362 had been misclassified as St. Augustinegrass and is an accession of Bahiagrass. crop science, vol. 53, january– february 2013

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Figure 5. Principal coordinate plot of 40 Stenotaphrum and one Bahiagrass genotypes for the first two principal components estimated with 564 amplified fragment length polymorphism markers.

Table 5. Results of the analysis of molecular variance for Stenotaphrum accessions analyzed for amplified fragment length polymorphism diversity grouped by inferred ploidy level and by germplasm type. Source of variation

df

Sums of squares

Variance components

Variation accounted for %

Ploidy level (diploid, triploid, aneuploid, S. dimidatum) Among ploidy levels 3 Within ploidy levels 36 Total 39 Germplasm type (cultivars, plant introductions, wild relatives) Among germplasm types 2 Within germplasm types 37 Total 39

1137.32 2285.45 3322.77

42.44 (Va)*** 63.48 (Vb)***

42.77 57.23

657.39 2673.61 3331.00

23.69 (Va)*** 72.26 (Vb)***

24.69 75.31

*** Significant at P < 0.001.

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suggests that these genotypes arose from the hybridization of diploids with different DNA contents or that they underwent chromosomal changes after polyploidization. Additionally, several of the polyploids analyzed were aneuploids with chromosome numbers ranging from 2n = 3x = 27 to 2n = 32. Discrimination of small differences in chromosome number might be difficult to distinguish using flow cytometry (Emshwiller, 2002). An additional factor that could have contributed to the lack of concordance between flow cytometry and chromosome counts is the presence of varying levels of anthocyanin or other cytosolic compounds in the different genotypes analyzed. Anthocyanins are known to potentially interfere with propidium iodide staining and can cause inaccuracies in genome size estimations for many plant tissues and taxa (Bennett et al., 2008; Price et al., 2000). This appears particularly true when trying to detect small differences in DNA content as was the case of our study. Based on our results, it appears that until genome sizes are defined in Stenotaphrum, use of flow cytometry in this genus should be restricted to discrimination of diploids from polyploids rather than as a true estimator of ploidy level. More than 1700 loci were scanned with 15 AFLP primer pairs. All PIs and cultivars could be uniquely identified and the average pair-wise genetic similarity value was relatively low at 0.63. Furthermore, the repeatability of the AFLP technique was very high, averaging 98% across the 15 PPs used. Overall, our results indicate that AFLP markers constitute an efficient and reliable technique for fingerprinting purposes in St. Augustinegrass. Separation of accessions based on molecular data supported and expanded the current classification based on morphological data. Results from both PCO and cluster analyses showed welldefined separation of accessions by ploidy levels. Moreover, results from the AMOVA indicated that separation of genotypes by ploidy level rather than germplasm type provides a much stronger differentiation among groups. The clearest delimitation was that between secundatum and dimidatum materials, followed by that between diploids and polyploids. The separation of accessions by ploidy level agrees with that of morphological studies that classified St. Augustinegrass germplasm into “groups” and “races” (Busey, 1986; Busey et al., 1982a). Under this system, diploids can be classified into the Breviflorous and Longicaudatus races and polyploids into the Bitterblue and Floratam groups. The Breviflorous race can be further divided into the Gulf Coast group and the Dwarf group. Cultivars Texas Common, Raleigh, and Palmetto, previously classified in the Gulf Coast group, did group together within the diploid cluster. Cultivars Seville and Jade, previously classified in the Dwarf group, also clustered together within Cluster I. All PIs were well separated from commercial cultivars. The clustering of African PIs in the UPGMA dendrogram illustrates that these materials form a distinct crop science, vol. 53, january– february 2013

group (bootstrap value = 99%) and that they are clearly separated from the other diploid accessions (bootstrap value = 84%). Little is known about this germplasm other than that it was collected from KwaZulu-Natal in South Africa (USDA-Germplasm Resources Information Network, 2012). Based on inflorescence morphology, they most likely correspond to the Natal-Plata deme of Sauer (1972) and the Longicaudatus race of Busey (1995). The morphological peculiarities of this group have been proposed as an indicator of introgression from S. dimidatum (Sauer, 1972). Moreover, some of the members of this group have been recently shown to have resistance to Magnaporthe grisea (Milla-Lewis et al., 2011b), a trait that had been previously reported only in S. dimidatum (Atilano and Busey, 1983). This separation of diploids into two distinct groups provides some support to the hypothesis that St. Augustinegrass is not naturalized but native to the Gulf Coast states (Busey, 1989) and, therefore, may have two origins. All S. secundatum polyploids fell into two distinct groups. In the first group, cultivars Floratam (2n = 32) and Floralawn (2n = 32), previously classified by Busey et al. (1982a) in the Floratam Group, clustered together with a high degree of confidence (bootstrap value = 100%). These two cultivars are closely related (Horn et al., 1973; Dudeck et al., 1986) and, thus, clustered as expected. Likewise, cultivars Bitterblue (2n = 3x = 27) and Floratine (2n = 3x = 27), previously classified by Busey et al. (1982a) in the Bitterblue Group, clustered together with a bootstrap value of 100%. Clustering of cultivar FX-10 with PI 290888 and PI 300130 was also expected as these two introductions are in the pedigree of FX-10 (Busey, 1993). Chromosome numbers for genotypes in the second subcluster ranged from 2n = 3x = 27 to 2n = 30. Clustering of accessions in these subgroups did not correspond with ploidy level or germplasm type, but it is apparent from the cluster and PCO analyses that these groups are distinctly different. More research needs to be done to elucidate the possible genetic differences present in these groups. The PCO placed all secudantum polyploids more closely associated with the African diploids and the Pembagrass accessions. These results could provide some insight into the origins of the polyploids. Polyploidy in St. Augustinegrass could have originated through chromosome doubling (followed by chromosome loss) of the African diploids, or by interspecific hybridization between this group and Pembagrass. The latter hypothesis would seem more plausible given the abundance of aneuploidy among polyploids, odd chromosome pairing behavior during metaphase (Busey, 1979), and the possible differences in genome size inferred from the lack of correspondence between DNA content and expected ploidy level. Regression analysis was conducted to evaluate possible associations between ploidy level and band frequency. Sixtythree percent of the total variation in band frequency could be explained by its cubic relationship with ploidy level. While

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the cubic response explained a higher proportion of the variation than the quadratic response (53%), the evaluation of only one tetraploid and one hexaploid accession might have skewed results and a quadratic response might be a better fit. A quadratic relationship was previously observed for Cynodon (Gulsen et al., 2009). It is clear that there is a positive correlation between ploidy level and number of bands scored, with polyploids showing an increased number of bands and, therefore, being more polymorphic. The multiplication of DNA content created through polyploidization produces an array of genetic interactions that result in gene diversification (Wendel, 2000) and ultimately in increased adaptation allowing polyploid individuals to outcompete their parents and/or occupy new niches (Leitch and Leitch, 2008). In Stenotaphrum, polyploids are not only generally morphologically distinguishable as having coarser leaf blades and a more erect growth habit (Busey, 1995), but more importantly, they harbor significant genetic variation for an array of adaptive traits such as resistance to the southern chinch bug (Busey, 1990; Busey and Zaenker, 1992; Reinert et al., 1986) and to Magnaporthe grisea, the causal agent of gray leaf spot disease (Atilano and Busey, 1983; Milla-Lewis et al., 2011b), among others. While chromosome duplication creates instant barriers with diploid progenitors perpetuating genetic changes, interspecific hybridization promotes gene flow between populations and generates variation (Leitch and Leitch, 2008). The production of interploid hybrids in Stenotaphrum is difficult but possible (Busey, 1993; Genovesi et al., 2009). Thus, despite sexual incompatibility issues, the extensive variation present in the polyploid germplasm can be used in St. Augustinegrass breeding. Knowledge of the genetic relationships among accessions of Stenotaphrum can be an important consideration for the strategic utilization of this germplasm in cultivar development. Furthermore, knowledge of ploidy levels adds a key piece of information in the use of this germplasm as it provides breeders with an understanding of which accessions are more readily usable in terms of possible sexual incompatibility barriers. Further research on the genome origins of the polyploids is needed to expand our knowledge of this latter issue. Additionally, the use of a codominant marker system, such as simple sequence repeats, would increase our ability to estimate heterozygosity and expand our understanding of the population structure of the Stenotaphrum germplasm collection. Acknowledgments The authors would like to thank Mr. Wayne Philley at Mississippi State University and the National Germplasm System, for providing some of the germplasm used in this study. The help of Dr. Consuelo Arellano at North Carolina State University with parts of the statistical analysis is greatly appreciated. This research was supported in part by the Center for Turfgrass Environmental Research and Education at North Carolina State University. 306

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