Genetic diversity of switchgrass and its relative species in Panicum genus using molecular markers

Biochemical Systematics and Ecology 39 (2011) 685–693

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Genetic diversity of switchgrass and its relative species in Panicum genus using molecular markers Lin-Kai Huang a, b, S.S. Bughrara b, *, Xin-Quan Zhang a, **, C.J. Bales-Arcelo b, Xu Bin c a

Department of Grassland Science, Animal Science and Technology College, Sichuan Agricultural University, Yaan 625014, China Department of Crop and Soil Science, Michigan State University, East Lansing, MI 48824, USA c Department of Horticulture, Virginia Tech, Blacksburg, VA 24060, USA b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 February 2011 Accepted 29 May 2011 Available online 13 July 2011

Switchgrass (Panicum virgatum), a warm season C4 grass, is a promising crop for bioenergy-dedicated biomass production. Understanding of genetic diversity within Panicum genus will facilitate switchgrass breeding. Genetic relationships of 22 Panicum species from six continents including ninety-one USDA germplasm accessions were investigated by Sequence-Related Amplified Polymorphism (SRAP) and Expressed Sequence Tags-Simple Sequence Repeat (EST-SSR) markers. Eight hundred and twenty-six markers from 28 pairs of SRAP and 25 pairs of EST-SSR Primers were used to differentiate between accessions of a bulk of 25 genotypes. The results showed that there was high genetic diversity found in Panicum species. Most genetic variation was present among the different species and cluster analysis indicated that all the Panicum accessions could be distinguished by SRAP or EST-SSR. Dendrogram results reflected the phylogenetic relationships between Panicum species and Panicum amarum was found to be the closest species to switchgrass. Comparison between molecular markers revealed that SRAP methods were considered more efficient than EST-SSR for screening Panicum accessions. Ó 2011 Elsevier Ltd. All rights reserved.

Keywords: Panicum virgatum Panicum amarum SRAP EST-SSR Genetic diversity

1. Introduction Switchgrass (Panicum virgatum L.) is a native perennial C4 grass adapted to the prairies of North America. Because of its potential for high biomass yield with minimal input, and its ability to grow on marginal land, switchgrass is considered as a prime candidate for large-scale biomass production for large-scale bioenergy-dedicated biomass production (Bouton, 2007). Identification and selection of useful germplasm for switchgrass breeding programs has been ongoing. Studies on genetic variation via molecular markers reported that upland and lowland ecotypes fell into their distinctive ecotype classes regardless of ploidy level (Missaoui et al., 2006) (Huang et al., 2003; Missaoui et al., 2006). Extensive genetic variations between and within upland and lowland switchgrass types were also observed (Missaoui et al., 2006). However, the genetic relationship between switchgrass and other Panicum species and the genetic diversity within Panicum genus have not been well studied using molecular markers. Panicum is a cosmopolitan genus with approximately 500 species widely distributed from wet shores to dry woodlands, grasslands and cultivated fields providing a vast genetic pool for switchgrass breeding (Sandra et al., 2003). Crossing between the two species usually only occurs between plants with close genetic relationship. Therefore, Panicum species, which have close genetic relationships with and are crossable to switchgrass, are particularly valuable for switchgrass breeding.

* Corresponding author. Tel.: þ1 517 432 8017; fax: þ1 517 353 5174. ** Corresponding author. Tel.: þ86 835 2882270; fax: þ1 835 2886080. E-mail addresses: [email protected] (S.S. Bughrara), [email protected] (X.-Q. Zhang). 0305-1978/$ – see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.bse.2011.05.025

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Molecular markers have been proved to be valuable tools in the characterization and evaluation of genetic diversity within and between species and population. Sequence-Related Amplified Polymorphism (SRAP) is recognized as a new and useful molecular marker system because of its reproducibility, low cost, and without the need of prior knowledge of target sequences (Li and Quiros, 2001). Microsatellites or Simple Sequence Repeats (SSR) was one of most used molecular marker, owing to its co-dominant results, polymorphic characteristics, reproducibility, low cost and simplicity. However, the development of SSR markers from genomic libraries is expensive and inefficient (Squirrell et al., 2003). Thanks to the availability of large EST (expressed sequence tags) datasets, it has become possible to systematically search for SSRs in EST datasets using bioinformatics tools (Kantety et al., 2002; Varshney et al., 2002; Gao et al., 2003; Omirshat et al., 2009). EST-SSR is now an efficient and low cost option for many plant species. Additionally, since these SSR are derived from an EST corresponding to the transcribed component of a gene unit, they have been shown to possess a high potential for inter-specific transferability (Cordeiro et al., 2001; Gupta et al., 2003; Thiel et al., 2003). Thus, Up to now, SRAP and EST-SSR have been successfully used for evaluation of genetic diversity (Sa et al., 2008; Huang et al., 2010) and genetic map construction (Lin et al., 2003; Graham et al., 2004). In this study, SRAP and EST-SSR are employed to examine the genetic diversity between switchgrass and selected Panicum species. These two techniques were further compared for their utilities of discriminating Panicum species. 2. Materials and methods 2.1. Plant materials and DNA extraction All plant materials including 22 Panicum species from six continents were obtained from USDA-GRIN (Table 1). Leaf tissues were collected from young seedlings and frozen in liquid nitrogen for DNA isolation. Approximately 200 mg of leaf tissue from 25 genotypes of each accession were extracted using the DNeasy Plant Mini kit (Qiagen Inc, Valencia, CA). The quality and concentration of the DNA were confirmed by electophoresis on 0.8% agarose gels by comparing the samples to the standardized lambda DNA size markers. 2.2. SRAP-PCR amplification Twenty-eight pairs of SRAP primers were used in the present study (Table 2 and Table 3), which were selected from 144 combinations of 12 forward and 12 reverse primers. These primer sequences were obtained from previous related studies (Li and Quiros, 2001; Ferriol et al., 2003; Lin et al., 2003). The protocol for SRAP analysis was based on Li and Quiros (2001). Each 20 mL PCR reaction mixture consisted of 40 ng genomic DNA, 0.2 mM dNTP, 2.5 mM MgCl2, 0.5 mM primer, 1  PCR buffer, and 1 unit of Taq polymerase. Samples were subjected to the following thermal profile: the first five cycles were run at 94  C, 1 min; 35  C, 1 min; and 72  C, 1 min, for denaturing, annealing and extension, respectively. Then the annealing temperature was raised to 50  C for another 35 cycles, followed by another extension step of 10 min at 72  C, and then followed by a 4  C holding temperature. PCR amplification products were analyzed on 2% agarose gel. The gel was stained in 0.75 mg/ml ethidium bromide (EB) solution and photographed under illumination with UV light using Quantity One. 2.3. EST-SSR amplification A total of 90 conserved grass EST-SSRs (CNL) developed by Kantety et al. (2002), and 176 switchgrass EST-SSRs developed by Tobis et al. (2005), were screened. From these, 25 primers (Table 4) were selected for the EST-SSR analysis based on reproducibility and clarity of bands. PCR amplification reactions were carried out in 20 ml volume, containing 1  PCR buffer (10 mM Tris-HC, pH 8.0; 50 mM KCl and 0.02% gelatin), 0.15 mM of each dNTP, 0.4 mM of each primer, 1.5 mM of MgCl2, 1 unit of Taq DNA polymerase and 40 ng of template DNA. PCR amplification was performed as follows: initial 5 min at 94  C followed by 35 cycles of 30 s at 94  C, 45 s at 52–58  C, 90 s at 72  C, and a final 20 min extension at 72  C. PCR products were separated on 6% denatured polyacrylamide gels. The gel was pre-run in 1.0  TBE buffer (with 0.75 mg/ml ethidium bromide) at 300 V constant voltage before the samples were loaded about 2 h. 2.4. Data analysis Only bands that could be unambiguously scored across all the sampled populations were used in this study. EST-SSR and SRAP amplified fragments, with the same mobility according to the molecular weight (bp), were scored manually for band presence (1) or absence (0). The resulting presence/absence data matrix was analyzed using POPGENE v. 1.31 (Yeh et al., 1999), assuming Hardy–Weinberg equilibrium, to estimate three genetic diversity parameters: the percentage of polymorphic bands (PPB) and Shannon’s Information Index of Diversity (I). The data matrix was then used to calculate the Genetic Similarity (GS) index as GS ¼ 2Nij/(Ni þ Nj), where Nij is the number of bands common to genotypes i and j, while Ni and Nj are the total numbers of bands observed for genotypes i and j, respectively (Nei and Li, 1979). Genetic relationships among Panicum accessions were estimated using the Unweighted Pair-Group Method with Arithmetic mean (UPGMA) cluster analysis of the GS matrix (Rohlf, 1997). In order to test for correlations between genetically similar samples based on SRAP and EST-SSR,

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Table 1 List of Panicum accessions. Number

PI Number

Geographic source

Species

2 3 4 7 8 9 10 11 12 13 14 15 17 20 21 22 23 24 25 26 27 28 29 30 33 34 35 36 37 38 42 43 44 45 47 49 53 54 55 57 58 59 60 61 62 64 67 68 69 71 72 73 74 75 76 78 80 81 82 83 84 85 86 87 90 91 92 95 97

PI 561721 PI 476814 PI 476815 PI 196337 PI 215647 PI 220026 PI 308603 PI 338608 PI 476289 PI 285216 PI 310031 PI 462240 PI 225995 PI 185546 PI 196361 PI 224985 PI 404632 PI 420892 PI 226085 PI 184776 PI 263605 PI 295647 PI 238345 PI 371932 PI 364951 PI 315726 PI 404359 PI 364956 PI 229051 PI 229052 PI 185560 PI 238346 PI 285219 PI 404803 PI 496387 PI 410261 PI 496372 PI 462241 PI 496395 PI 257775 PI 209196 PI 209244 PI 209391 PI 284153 PI 364348 PI 410237 PI 410276 PI 410277 PI 410278 PI 410278 PI 145794 PI 185547 PI 190327 PI 208014 PI 208247 PI 410233 Grif 16054 Grif 16407 Grif 16408 Grif 16409 Grif 16410 PI 204907 PI 315723 PI 315724 PI 337553 PI 414065 PI 414066 PI 414069 PI 421138

United States United States United States Australia India Afghanistan Italy Costa Rica United States Uruguay Brazil Uruguay Japan South Africa Botswana Zimbabwe Paraguay Pakistan kenya South Africa Australia Zimbabwe Australia Australia South Africa United States Brazil South Africa United States Mexico South Africa Zaire Uruguay Uruguay United States South Africa Argentina Uruguay Brazil Australia South Africa South Africa South Africa Cyprus Lesotho South Africa South Africa South Africa South Africa Sierra Leone South Africa South Africa South Africa South Africa South Africa South Africa United States United States United States United States United States Turkey United States United States Argentina United States United States United States United States

P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P.

amarum amarum var. amarumlum amarum var. amarumlum antidotale antidotale antidotale antidotale antidotale antidotale bergii bergii bergii bisulcatum coloratum coloratum coloratum coloratum coloratum coloratum var. coloratum coloratum var. makerikariense coloratum var. makerikariense coloratum var. makerikariense decompositym decompositym deustum dichotomiflorum dichotomiflorum dregeanum hallii hallii lanipes lanipes milioides milioides milioides natalense polygonatum prionitis prionitis queenslandicus schinzii schinzii schinzii schinzii schinzii schinzii sp. sp. sp. sp. staplianum staplianum staplianum staplianum staplianum subalbidum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum (continued on next page)

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Table 1 (continued ) Number

PI Number

Geographic source

Species

98 99 101 103 107 112 115 117 119 120 123 125 127 208 129 130 147 154 177 189 193 249

PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI

United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States Australia

P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P. P.

421520 421521 421999 422016 469228 476294 476297 478001 537558 549094 607837 636468 639129 642274 742191 742192 642210 642217 642242 642255 642259 257778

virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum virgatum whitei

a Mantel test was also performed with NTSYS-pc. Bootstrap analysis with 1000 replicates was performed to obtain the confidence of branches of the cluster tree using the Winboot software (Yap and Nelson, 1996). The analysis of molecular variance (AMOVA) was used to partition the total EST-SSR and SRAP variation into withinspecies and among species (Excoffier et al., 1992). Variance components, the sum of all squared differences, and analogs of F-statistics based on Euclidean distance between individuals was calculated to estimate the population differentiation (Wright, 1965). The input files for AMOVA were prepared with the aid of the DCFA1.1 program written by Zhang (2001). Marker utility is a function of information content per marker and the number of markers generated per assay. In this study, we employed Marker Index (MI), Effective Multiplex Ratio (EMR), and Average Band Informativeness (Ibav) to compare the utility of the two markers. Marker index was estimated as MI ¼ Ibav  EMR (Powell and Morgante, 1996). Average band informativeness (Ibav) was employed to estimate the information content per marker. Average band informativeness, with P a range from 0 to 1, was calculated as: Ibav ¼ 1=n 1  ð2j0:5  pi jÞ where, pi is the proportion of accessions containing the ith amplicon and n is the total number of amplicons (Milbourne et al., 1997; Archak et al., 2003). 3. Results 3.1. SRAP and EST-SSR polymorphism Twenty-eight SRAP primer pairs produced a total of 522 DNA markers, of which 505 were polymorphic (representing 96.74% of all bands), with an average of 18 polymorphic bands per primers and a range of 14–23 bands (Table 3). Twenty-five EST-SSR primer pairs selected from 266 EST-SSR primer pairs (Kantety et al., 2002; Tobis et al., 2005), were used in the study, based on reproducibility and clarity of bands. EST-SSR pairs produced a total of 304 DNA markers, of which 288 were polymorphic (representing 94.73% of all bands), with an average of 11.5 polymorphic bands per primers and a range of 4–18 bands (Table 4). Both the SRAP and EST-SSR fingerprints can distinguish Panicum species and intra-specific taxa.

Table 2 Primer sequences used in SRAP analyses of Panicum accessions. Forward primers

Reverse primers

me1 : 50 -TGAGTCCAAACCGGATA-30 me2 : 50 -TGAGTCCAAACCGGAGC-30 me3 : 50 -TGAGTCCAAACCGGAAT-3 me4 : 50 -TGAGTCCAAACCGGACC-30 me5 : 50 -TGAGTCCAAACCGGAAG-30 me6 : 50 -TGAGTCCAAACCGGTAA-30 me7 : 50 -TGAGTCCAAACCGGTCC-30 me8 : 50 -TGAGTCCAAACCGGTGC-30 me9 : 50 -TGAGTCCAAACCGGTAG-30 me10 : 50 -TGAGTCCAAACCGGTTG-30 me11 : 50 -TGAGTCCAAACCGGTGT-30 me12 : 50 -TGAGTCCAAACCGGTCA-30

em1 : 50 -GACTGCGTACGAATTAAT-30 em2 : 50 -GACTGCGTACGAATTTGC-30 em3 : 50 -GACTGCGTACGAATTGAC-30 em4 : 50 -GACTGCGTACGAATTTGA-30 em5 : 50 -GACTGCGTACGAATTAAC-30 em6 : 50 -GACTGCGTACGAATTGCA-30 em7 : 50 -GACTGCGTACGAATTCAA-3 em8 : 50 -GACTGCGTACGAATTCTG-30 em9 : 50 -GACTGCGTACGAATTCGA-30 em10 : 50 -GACTGCGTACGAATTCAG-30 em11 : 50 -GACTGCGTACGAATTCCA-30 em12 : 50 -GACTGCGTACGAATTATG-30

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Table 3 Amplification results of Panicum from 28 primer combination. Primer pairs bands

Total no. of polymorphic

No. of polymorphic bands

Percentage of polymorphic bands(%)

me1 þ em2 me1 þ em6 me2 þ em1 me2 þ em4 me2 þ em6 me2 þ em7 me2 þ em8 me3 þ em3 me3 þ em6 me4 þ em3 me5 þ em8 me6 þ em9 me7 þ em2 me7 þ em3 me7 þ em4 me7 þ em5 me7 þ em6 me7 þ em8 me7 þ em10 me8 þ em3 me8 þ em4 me8 þ em8 me9 þ em6 me9 þ em8 me10 þ em3 me10 þ em8 me10 þ em9 me10 þ em10 me1 þ em2

20 22 19 18 17 22 20 18 15 16 18 17 15 17 18 17 16 16 14 19 24 25 26 16 18 19 20 21 20

20 21 18 18 15 20 19 16 15 16 18 17 15 16 17 16 15 15 14 18 23 24 24 16 18 19 20 21 20

100.00 95.45 94.74 100.00 88.24 90.91 95.00 88.89 100.00 100.00 100.00 100.00 100.00 94.12 94.44 94.12 93.75 93.75 100.00 94.74 95.83 96.00 92.31 100.00 100.00 100.00 100.00 100.00 100.00

High genetic diversity in 22 species of Panicum was detected by both SRAP and EST-SSR (PPB ¼ 96.74%, I ¼ 0.463 based on SRAP data; PPB ¼ 94.73%, I ¼ 0.424 based on EST-SSR data). Shannon’s information index of diversity (I) based on SRAP and EST-SSR were 0.456 and 0.437 for the 57 Panicum accessions of different species or subspecies, whereas for the cultivated switchgrass accessions the index was 0.231 and 0.225. The mean GS index for the 57 Panicum of different species or subspecies was 0.433 while for the 34 cultivated switchgrass accessions the mean GS index was 0.813. These results suggest that the genetic diversity among relative Panicum species was more extensive than that among cultivated switchgrass. The AMOVA of the distance matrix for the 90 individuals permitted a partitioning of the overall variation into two levels:among species and among populations within a species. The results showed that most of the genetic variation existed among species. The proportion of variation attributed among species’ differences was 70.02% (revealed by SRAP), 73.35% (revealed by EST-SSR), and the remainder occurred among populations. 3.2. Comparing marker utility of SSR and SRAP Marker utilities of SRAP and EST-SSR are in Table 5. In this study, SRAP and EST-SSR revealed 96.74% and 94.73% of polymorphic bands, respectively, between 22 Panicum species (no significant difference found at P > 0.05). Ibav between SRAP and EST-SSR was also not significantly different (P > 0.05), suggesting that the two marker systems had similar discriminating power. However, EMR and the number of markers generated by each primer pairs of SRAP (18.12 and 18.75, respectively) were significantly higher than those of EST-SSR (11.52 and 12.16, respectively) at P < 0.01. MI was used to evaluate the efficiency of the two molecular marker systems, which depends on Ibav and the number of markers generated by each primer. In this study, MI of SRAP (4.20) was significant higher than EST-SSR (2.45 at P < 0.01). Additionally, we need screen more EST-SSR primers to select good primers than SRAP(Of the total 266 EST-SSR, only 25 can be used), because we use switchgrass’s EST-SSR primer to amplify panicum species. Therefore, SRAP was more efficient than SSR in the genetic diversity study of Panicum species. The correlation between the matrices of genetic distance values based on SRAP and EST-SSR data was high and significant (r ¼ 0.814, P < 0.01). 3.3. Cluster analysis Since the correlation between the matrices of genetic distance values based on SRAP and EST-SSR data was high and significant, both data were combined for UPGMA cluster analysis (Fig. 1). The results showed that accessions in a species were clustered together having high genetic similarities. At the genetic similarity coefficient value of 0.714, six groups were evident in Panicum accessions dendogram.Thirty-four switchgrass accessions and three Panicum amarum accessions were divergent from the other accessions and closely clustered into group I. The second group was formed by six accessions from the same

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Table 4 Amplification results of Panicum from 25 EST-SSR primer combinations. Primer name

Primers sequence

PVSSR123

F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R F R

PvSSR147 PvSSR259 PvSSR278 PvSSR280 PvSSR292 PvSSR497 PvSSR572 PvSSR753 PvSSR784 cnl35F cnl39F cnl42F cnl47F cnl51F cnl55F cnl61F cnl100F cnl101F cnl119F cnl130F cnl133F cnl144F cnl147F cnl152F cnl158F

GAACTGCCCCTGAAAACAAC GTTTCTTCCTGGTTGTTGGTGGGTACT CTCAATCCTCGGCAACAAGT GTTTCTTGGAGGTGCGTGTTCCAGTAG TCCATCCTCTCCCTTTGCTA GTTTCTTAGAACAATCGGATGTGGGAG GGTACCGGAAGAAGAGGAGG GTTTCTTATGTGGGTGAGGAAGACAGG GGAAGAAGGCCATGTACGAC GTTTCTTTCCATCATCACCAGCATCTC AGTGGCATTCCGGTCAATAG GTTTCTTGACAGGAGCCTCATCAGCTT AGCTCGTGCTGGACTACCTG GTTTCTTTCGCACTTGTTCAGATCGAC TACTACGACACGAGCGAACG GTTTCTTCTACAAGTGCGGCGAGGAG CAGGATGCAGGAAGGGATTA GTTTCTTGTTCTAGAGAGACACGCCCG ACCACAGAACCCTGCAAGTC GTTTCTTGTGCTGACTGCTGTAGGCTG AAGTGAGCACAACGACACGA CGATCCAAAGAAGCAAAGATG TACCTGTGCGGCGATGAAT CAGGAGCAGGAGAACGTGAA GTTGGTCTGCTGCTCACTCG CCGACGATGTTGAAGGAGAG GACTCGCACGATTTCTCCTC GCCAGACAACCAATTCAGGT CTAGGGTTTCCCACCTCTCA AATGTCCTTGGCGTTGCT GCTGATAGCGAGGTGGGTAG CTGCCGGTTGATCTTGTTCT CACGAGTGCAGAGCTAGACG ACAACAACCCGACTGCTACC CGTCGTCCTCTGCTGTGAG AGGTCGTCCATCTGCTGCT GCGGAGGAGAGAAAGCAAT AGGTCGTCCATCTGCTGCT ATCGTCTCCTCCTCCTCCA ATGCCTCGGTGGACTGGTA AAATGTTGAGCAACGGGAGCT ACTTCATAGGGCGGAGGTCT CAGGCAACAACCACCATTT GAACATGCCCTTCATCTGCT AGAAGGCGGCTCAGAAGAAG GCTCCAACTCAGAATCAACAA GGCTAGGGTTTCGACTCCTC AGATGGCGAACTCGACCTG ACAAAGGCTCACCGTGGAA GTCGGAGGCGATGAACTCT CTCATCCCACCACCACCAC CCCTGAAGAAGTCGAACACG

Total no. of polymorphic

No. of polymorphic bands

Percentage of polymorphic bands (%)

6

6

100.00

7

6

85.71

8

7

87.50

9

8

88.89

5

5

100.00

6

6

100.00

4

4

100.00

9

9

100.00

10

10

100.00

11

11

100.00

15

14

93.33

18

18

100.00

16

15

93.75

14

13

92.86

13

12

92.31

15

14

93.33

17

16

94.12

15

15

100.00

13

12

92.31

12

11

91.67

14

13

92.86

13

12

92.31

13

12

92.31

12

11

91.67

14

13

92.86

15

15

100.00

304

208

94.73

Table 5 Comparison of usefulness between SRAP and EST-SSR. Items

SRAP

EST-SSR

NO. of primers NO. of total loci NO. of average loci per primers Percentage of polymorphic bands (PPB) Average band informativeness (Ibav) Effective multiplex ratio (EMR) Mark index (MI)

28 525 18.75 0.97 0.23 18.12 4.20

25 304 12.16 0.95 0.21 11.52 2.45

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Fig. 1. UPGMA dendrogrm of 91 accessions of 22 Panicum ssp.

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species – Panicum antidotale. Group III includes two subgroups (IIIa, IIIb), of which IIIa included three accessions and IIIb included 10 accessions. In subgroup IIIa, there were two taxa, that is, Panicum decompositym and Panicum deustum. In subgroup IIIb, there were two species and two subspecies, namely, Panicum coloratum var. coloratum, P. coloratum var. makerikariense and Panicum dichotomiflorum. Group IV also includes two subgroups (IVa, IVb) where IVa included 23 accessions and IVb included five Panicum schinzii accessions. In subgroup IVa, there were nine taxa including Panicum bisulcatum, Panicum polygonatum, Panicum queenslandicus, Panicum dregeanum, Panicum lanipes, Panicum natalense, Panicum whitei, Panicum prionitis, Panicum milioides and four accessions of P. sp. The three Panicum bergii accessions and two Panicum hallii accessions were divergent from the other accessions and clustered into group VI, while five Panicum staplianum accessions were clustered into group V. 4. Discussion Panicum genus has approximately 500 species that have a wide distribution in the world, indicating a rich, but currently under-appreciated gene pool available for switchgrass breeding (Sandra et al., 2003). In this study, a higher genetic diversity among Panicum species than that among switchgrass ecotypes was detected by using SRAP and EST-SSR markers, echoing that related Panicum species can provide sufficient genetic resources for switchgrass breeding. Crossing between related species is one way to integrate desirable trait from one species to another. Species used for crossing should have different advantages and appropriate genetic distance to be crossable. P. amarum was the closest to switchgrass among the tested Panicum species. P. amarum grows perfect in coastal areas as well as inland gardens, as it is highly tolerant to heat, drought, and humidity (Ruiter et al., 2006). Within P. amarum species, P. amarum var. amarum and var. amarumlum are virtually indistinguishable in the southern part of their range. Cytological evidence indicated that P. amarum var. amarum (2n ¼ 54) is probably an autohexaploid derivative of P. amarum var. amarulum (2n ¼ 36) (Patricia, 1975). P. amarum var. amarum, P. amarum var. amarumlum and switchgrass are three representatives of six widely distributed Virgata-group Panicum species. Accessions from these three grass species vary widely in morphology ranging from bunched to rhizomatous and from decumbent to erect and tall (Patricia, 1975). Although specific elite agronomic traits of P. amarum are to be characterized, it has a great potential to serve as a breeding material for switchgrass. Although, both SRAP and EST-SSR distinguished Panicum species and infra-specific taxa with their great and similar discriminating power of Panicum, we considered SRAP more efficient than EST-SSR for screening large numbers of Panicum accessions, because SRAP produced more polymorphic bands per pair of primers than EST-SSR (Tables 2, 3, and 4). Only 25 out of the tested 266 EST-SSR primer pairs can be used in this study. Further screening effective EST-SSR primers is undergoing to facilitate future studies. On one hand, SSR may have disadvantages in studying genetic relationships between more than two species, because the sequences flanking SSR markers could vary in different species. The 15 EST-SSR primer pairs developed from conserved grass ESTs by Kantety et al. (2002) yielded 13.5 polymorphic bands per pair of primers in average, which was significantly higher than the ones developed from switchgrass ESTs by Tobis et al. (2005) (P < 0.01). On the other hand, EST-SSR has great potential for molecular breeding of switchgrass for it is a co-dominant marker, while SRAP is not. Therefore, these two molecular markers may complement each other for studies on genetic diversity and molecular breeding of Panicum. Acknowledgments This study was supported by The National Basic Research Program (973 Program) in China (No. 2007CB108907) and China Scholarship Council. References Archak, S., Gaikwad, A.B., Gautam, D., Rao, E.V.V.B., Swamy, K.R.M., karihaloo, J.L., 2003. Comparative assessment of DNA fingerprinting techniques (RAPD, ISSR and AFLP) for genetic analysis of cashew (Anacardium occidentale L.) accessions of India. Genome 46, 362–369. Bouton, J.H., 2007. Molecular breeding of switchgrass for use as a biofuel crop. Curr. Opin. Genet. Dev. 17, 553–558. Cordeiro, G.M., Casu, R., McIntyre, C.L., Manners, J.M., Henry, R.J., 2001. 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