Geographical patterns of genetic variation in rosemary ( Rosmarinus officinalis ) in the...

Molecular Ecology (2001)

10

, 1947–1958

© 2001 Blackwell Science Ltd

Blackwell Science, Ltd

Geographical patterns of genetic variation in two species of

Stylosanthes

Sw. using amplified fragment length polymorphism

M. C . SAWKINS,*† B . L . MAASS,‡ B . C . PENGELLY,§ H. J . NEWBURY,* B . V. FORD-LLOYD,* N. MAXTED* and R . SMITH¶*

School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK,

‡

Institute of Agronomy in the Tropics, Georg-August-University, Göettingen, Grisebachstr.6, D-37077, Göettingen, Germany,

§

CSIRO Sustainable Ecosystems, Indooroopilly, Qld 4068, Australia,

¶

The Royal Botanic Gardens, Kew, Richmond, Surrey, UK

Abstract

Understanding the extent and distribution of genetic diversity within a species is essentialfor the development of effective conservation strategies. The objective of this study wasto assess genetic variation using amplified fragment length polymorphisms (AFLP) in twospecies of the tropical legume genus

Stylosanthes

Sw. Annual,

S. humilis

(2

n

= 20) andperennial,

S. viscosa

(2n = 20) are found throughout tropical America, and are sympatric formuch of their range of distribution. One hundred and eleven accessions, covering a widegeographical range, were selected for AFLP analysis. Binary data matrices derived fromDNA banding patterns were analysed using the software programs

NTSYS

-

PC

and

ARLEQUIN

.Several accessions were found to be misidentified. Of the

S. humilis

accessions, the overallaverage similarity value was (0.72) slightly higher than the value obtained for

S. viscosa

(0.67). Cluster analysis and principal coordinate analysis grouped accessions from both speciesby geographical origin, with a few exceptions. Analysis of molecular variance (

AMOVA

) in

S. humilis

revealed 59.4% of the variation among groups formed from the cluster analysis.This was highly significant (

P

< 0.001). For

S. viscosa

AMOVA

also revealed more variationamong than within groups (66.5%). This was also highly significant (

P

< 0.001). The majorityof accessions of both species conserved

ex situ

are of Brazilian and Venezuelan origin. Thisstudy has identified areas in Central America and Mexico for which novel genetic variationmay be found and where conservation activities should be focused.

Keywords

: AFLP, conservation, genetic variation, geographical distribution,

Stylosanthes humilis

,

Stylosanthes viscosa

Received 19 January 2001; revision received 3 May 2001; accepted 3 May 2001

Introduction

Stylosanthes

(Aubl.) Sw. (Fabaceae, Papilionoideae, Aeschy-nomeneae, Stylosanthinae, Polhill & Raven 1981) comprises30–40 species and is found throughout the tropics andsubtropics of the Americas, Africa and South-East Asia.The genus consists of herbaceous or suffruticose perennialsand annuals up to a height of 1.5 m. Members of the genusare considered colonizers, found principally in open ground,along roadsides, grassland with low scrub and open woodland

(Edye 1987). Considerable research has been undertakeninto the genus since the discovery, over 50 years ago, of itsuse in improving pasture. The greatest impact has been theimprovement of pasture in dry tropical regions of the world(Edye 1987, 1997). Species have been used as cattle fodder,as a cover crop and a green manure (Gardener 1984; Gillard& Winter 1984; Thomas 1984).

The two species considered in this study are

Stylosantheshumilis

and


.

S. humilis

is an annual diploidspecies (2

n

= 20), found throughout tropical America, andis also adventive in Australia. In the Americas, it has adistribution similar to that of

S. viscosa

and is found fromMexico, Central America, through Colombia, Venezuela andBrazil. It is thought to originate primarily from Venezuela andCentral America (Williams

et al

. 1984). It has previously been

Correspondence: M. C. Sawkins. †Present address: Departmentof Ecology & Evolutionary Biology, 321 Steinhaus Hall, Universityof California, Irvine, CA 92697–2525, USA. Fax: +949 824 2181;E-mail: [email protected]

MEC1347.fm 947 Tuesday, July 24, 2001 5:14 PM

1948

M . C . S AW K I N S

E T A L

.

© 2001 Blackwell Science Ltd,

Molecular Ecology

, 10, 1947–1958

divided into two main groups on the basis of morphological

−

agronomic (M–A) characters (Edye

et al

. 1974). The first groupcontains individuals from Brazil (and those introducedinto Australia from Brazil). These are vigorous plants andhave large leaves, in contrast to those from the second groupfrom Venezuela, Costa Rica, Nicaragua and Mexico, which arefiner in appearance and have small leaves (Edye

et al

. 1974).The species occurs in semiarid tropical and subtropicalareas (Edye 1987). Historically important in pasture improve-ment, the use of

S. humilis

has now declined due to sus-ceptibility to anthracnose (

Colletotrichum gloeosporioides

), afungal disease. However, this species is a progenitor ofthe agronomically important allotetraploid,

S. hamata

(L.)Taubert (Kazan

et al

. 1993; Curtis

et al

. 1995).

S. viscosa

is a perennial diploid species (2

n

= 20) with awide distribution in tropical America. It occurs in a widerange of environments, from the humid tropics to thesemiarid tropics (Burt

et al

. 1971; Williams

et al

. 1984). Anumber of ecotypes has been documented for this species(Mohlenbrock 1958; Costa & Ferreira 1984) and Edye

et al

.(1974), using M–A characters, divided a small collection of

S. viscosa

plants into three main groups, based on the sizeof the loment, length of bristles on the stem, plus persistenceand vigour of the plants.

Over 900 accessions of both species are held by the genebanks of the Centro Internacional de Agricultura Tropical(CIAT), Colombia, the Commonwealth Scientific and IndustrialResearch Organization (CSIRO) Sustainable Ecosystems,Australia and the International Livestock Research Institute(ILRI), Kenya. The majority of accessions were collectedfrom Brazil and Venezuela (Hanson & Heering 1994).

Several techniques have been used to investigate diver-sity in the genus. Some of these have included the use ofrhizobial affinities (Date

et al

. 1979), M–A characters (Burt

et al

. 1971), seed protein analysis (Robinson & Megarrity1975; Robinson

et al

. 1976), isozymes (Stace 1982; Stace &Cameron 1984; Vithange & Chakraborty 1992), randomlyamplified polymorphic DNA (RAPDs) (Kazan

et al

. 1993;Liu 1997), restriction fragment length polymorphism (RFLPs)(Lui & Musial 1995; Gillies & Abbott 1996) and sequencingof the nuclear (nr)DNA internal transcribed spacer region(ITS-1) (Vander Stappen

et al

. 1998). Few studies have investig-ated levels of variation within species. Liu (1997) examinedgenetic variation within a collection of

S. scabra.

A more recentstudy examined levels of genetic variation in

S. humilis

fromMexico with the inclusion of a few individuals from SouthAmerica (Vander Stappen

et al

. 2000).Amplified fragment length polymorphism (AFLP) (Zabeau

& Vos 1993; Vos

et al

. 1995) has been shown to be a reliableand robust dominant genetic marker assay (Powell

et al

.1996). This technique is highly reproducible, can detecthigh levels of polymorphism in a single assay and does notrequire prior sequence knowledge (Jones

et al

. 1997). AFLPshave been proven to be of use in assessing genetic variation

and taxonomic relatedness in a large variety of wild andcultivated plant species (Sharma

et al

. 1996; Travis

et al

. 1996;Pakniyat

et al

. 1997; Paul

et al

. 1997; Roa

et al

. 1997; Winfield

et al

. 1998; Muluvi

et al

. 1999).The objectives of our study were to: (i) examine, using

AFLPs, levels of genetic variation in two wild species of

Stylosanthes

for which little information exists; and (ii) deter-mine whether this variation is geographically structured.This information would provide an insight into the spatialstructuring of genetic variation in both species that willbe useful in the formulation of conservation strategies andmay identify novel genotypes for use in the improvementand development of cultivars.

Materials and methods

Plant materials and DNA samples

Seed was obtained from the gene banks of CIAT andCSIRO, Sustainable Ecosystems, Australia. One hundredand eleven accessions were selected for analysis; 59 acces-sions of


and 52 accessions of

S. humilis

,to represent the known geographical distribution of bothspecies (Table 1). Accessions were also chosen on the basisof membership of groups obtained through hierarchicalclustering of climate data for tropical America (Sawkins 1999).It was not possible to include accessions of both speciesused in the study of M–A characters by Edye

et al

. (1974).Seeds were scarified with emery paper, sown on dampWhatman paper and placed in a growth room maintainedat a constant 26

°

C with a 16-h photoperiod for vegetativegrowth. Young leaves were harvested from 2-week-oldseedlings of each accession.

DNA extraction and quantification

The protocol for the isolation of genomic DNA developed byGawel & Jarret (1991) was followed with some modifications(Virk

et al

. 1995). Twenty milligrams of leaf material from10 seedlings of each accession were bulked and placed in a1.5-mL microfuge tube; tissue was then immersed in liquidnitrogen and homogenized using a polypropylene pestle. Thehomogenate was mixed with 700

µ

L of preheated (65

°

C)extraction buffer containing 4% CTAB, and then incubatedat 65

°

C for 1 h. Following this, 600

µ

L of chloroform/isoamylalcohol (24:1, v/v) was added to each tube. This was mixed byinverting the tubes for 5 min at room temperature and thencentrifuged at 12 000

g

in a microfuge for 5 min. Five hundredmicrolitres of the supernatants was removed and placedinto a new tube. This was then mixed with an equal volumeof ice-cold isopropanol to precipitate the DNA, which wasrecovered as a pellet by centrifugation at 12 000

g

for 5 min.After washing with 300

µ

L of 70% ethanol, and being driedunder vacuum for 20 min, the DNA pellets were dissolved

MEC1347.fm Page 1948 Tuesday, July 24, 2001 5:14 PM

G E N E T I C VA R I AT I O N I N

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1949


Molecular Ecology

, 10, 1947–1958

Table 1

Accessions of


and

S. viscosa

used in AFLP analysis

Accession No.*† Origin Latitude Longitude


CPI-33829 Veracruz, Mexico 18.83N 96.68WCPI-33830 Veracruz, Mexico 19.20N 96.25WCPI-49828 Guanacaste, Costa Rica 10.60N 85.53WCPI-34001 Puntarenas, Costa Rica 9.15N 83.35WCPI-67670 El Progresso, Guatemala 14.82N 89.93WCPI-67671 El Progresso, Guatemala 14.88N 89.72WCPI-55853 Chiriqui, Panama 8.40N 82.35WCPI-55854 Chiriqui, Panama 8.43N 82.43WCIAT-11153 Chiriqui, Panama 8.53N 82.75WCPI-55852 Cocle, Panama 8.10N 80.55WCPI-55850 Veraguas, Panama 8.13N 80.98WCIAT-11154 Veraguas, Panama 8.13N 80.97WCPI-38753B Cundinamarca, Colombia 4.33N 73.87WCIAT-2334 Casanare, Colombia 5.48N 72.13WCIAT-1352 Bolivar, Venezuela 7.45N 63.30WCIAT-1511 Bolivar, Venezuela 8.15N 63.55WCIAT-1536 Bolivar, Venezuela 8.17N 62.42WCIAT-1543 Bolivar, Venezuela 7.25N 62.17WCIAT-1546 Bolivar, Venezuela 7.75N 62.67WCIAT-1366 Portuguesa, Venezuela 9.52N 69.25WCPI-62159 Apure, Venezuela 7.73N 68.95WCPI-65374 Apure, Venezuela 8.05N 69.33WCPI-110204 Aragua, Venezuela 10.25N 67.65WCPI-57246 Falcon, Venezuela 10.95N 70.60WCIAT-1363 Guarico, Venezuela 9.22N 66.28WCPI-33503 Guarico, Venezuela 8.93N 67.42WCPI-65373 Guarico, Venezuela 8.97N 67.47WCPI-110072 Guarico, Venezuela 8.93N 67.42WCIAT-1529 Monagas, Venezuela 8.67N 62.08WCPI-33502B Monagas, Venezuela 9.78N 63.55WCPI-105684 Bahia, Brazil 14.88S 42.73WCIAT-2059 Bahia, Brazil 12.15S 43.35WCIAT-2064 Bahia, Brazil 12.32S 42.82WCPI-40275 Ceara, Brazil 6.37S 39.40WCPI-40278 Ceara, Brazil 4.13S 38.47WCPI-63464 Ceara, Brazil 5.10S 38.42WCPI-105681 Distrito Federal, Brazil 15.75S 47.95WCIAT-1300 Maranhao, Brazil 2.68S 44.27WCIAT-1302 Maranhao, Brazil 3.25S 44.38WCIAT-1304 Maranhao, Brazil 3.82S 45.23WCIAT-1744 Mato Grosso, Brazil 15.35S 52.18WCIAT-1408 Para, Brazil 2.30S 48.60WCIAT-2482 Paraiba, Brazil 7.18S 35.98WCIAT-2484 Paraiba, Brazil 7.32S 35.90WCPI-40265 Pernambuco, Brazil 8.28S 36.08WCPI-40266 Pernambuco, Brazil 8.28S 36.25WCPI-40267 Pernambuco, Brazil 8.42S 37.02WCPI-54832 Pernambuco, Brazil 8.38S 37.00WCPI-34926 Sao, Paulo, Brazil 20.83S 49.33WCPI-40283B Sao, Paulo, Brazil 23.55S 46.65WCIAT-2623 Tocatins, Brazil 9.65S 48.63WCIAT-2663 Tocatins, Brazil 8.10S 48.48W


CPI-33831B Tamaulipas, Mexico 22.41N 97.91WCPI-41212 Oaxaca, Mexico 16.18N 95.20WCPI-41216 Oaxaca, Mexico 16.36N 91.40WCPI-91311 Oaxaca, Mexico 16.41N 95.91W


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Molecular Ecology

, 10, 1947–1958

CPI-91330 Oaxaca, Mexico 16.33N 94.33WCPI-86155 Nayarit, Mexico 21.25N 105.08WCPI-67662 Cayo, Belize 16.85N 89.78WCIAT-1538 Bolivar, Venezuela 6.83N 61.75WCIAT-1544 Bolivar, Venezuela 7.25N 62.16WCIAT-1900 Bolivar, Venezuela 9.91N 63.60WCIAT-1908 Bolivar, Venezuela 7.75N 63.20WCIAT-2341 Casanare, Colombia 6.18N 71.78WCIAT-2425 Alagoas, Brazil 9.80S 36.15WCIAT-1051 Bahia, Brazil 12.18S 38.40WCIAT-1094 Bahia, Brazil 13.16S 39.43WCIAT-2060 Bahia, Brazil 12.30S 42.90WCIAT-2110 Bahia, Brazil 12.45S 41.08WCIAT-2123 Bahia, Brazil 12.51S 39.86WCIAT-2171 Bahia, Brazil 12.58S 38.91WCIAT-2368 Bahia, Brazil 14.90S 39.08WCIAT-2374 Bahia, Brazil 15.15S 39.05WCIAT-2380 Bahia, Brazil 14.60S 39.38WCIAT-2524 Bahia, Brazil 13.86S 39.61WCIAT-2904 Bahia, Brazil 12.53S 41.90WCIAT-2912 Bahia, Brazil 13.23S 41.40WCIAT-2922 Bahia, Brazil 12.26S 39.13WCIAT-2927 Bahia, Brazil 12.01S 40.15WCIAT-11599 Bahia, Brazil 11.43S 41.08WCIAT-11604 Bahia, Brazil 11.18S 40.46WCPI-105720 Bahia, Brazil 14.16S 42.66WCPI-40302 Bahia, Brazil 12.76S 39.50WCPI-55859A Bahia, Brazil 12.55S 40.90WCPI-55862 Bahia, Brazil 12.50S 39.53WCPI-40300 Ceara, Brazil 3.76S 38.56WCIAT-2001 Goias, Brazil 15.56S 47.16WCPI-92892 Maranhao, Brazil 6.00S 47.40WCIAT-1703 Mato Grosso, Brazil 15.71S 55.73WCIAT-1764 Mato Grosso, Brazil 16.56S 54.56WCIAT-1783 Mato Grosso, Brazil 15.26S 54.93WCIAT-10959 Mato Grosso, Brazil 15.20S 56.31WCIAT-1430 Mato Grosso, Brazil 20.50S 52.70WCIAT-2916 Minas Gerais, Brazil 17.86S 41.05WCPI-105715 Minas Gerais, Brazil 19.88S 43.80WCPI-105724 Minas Gerais, Brazil 16.33S 41.48WCIAT-2460 Paraiba, Brazil 6.58S 35.15WCPI-94408 Paraiba, Brazil 3.60S 47.60WCPI-Q10044 Paraiba, Brazil 7.85S 37.08WCPI-Q10045 Paraiba, Brazil 7.36S 36.50WCIAT-2443 Pernambuco, Brazil 8.06S 34.93WCIAT-2486 Pernambuco, Brazil 8.05S 36.06WCPI-92990 Parana, Brazil 25.80S 48.60WCPI-93126 Rio de Janeiro, Brazil 22.20S 42.80WCIAT-1435 Sao Paulo, Brazil 22.00S 51.63WCIAT-2230 Sao Paulo, Brazil 22.71S 47.63WCPI-100469 Sao Paulo, Brazil 22.21S 49.96WCPI-40296 Sao Paulo, Brazil 23.68S 47.45WCPI-61999 Sao Paulo, Brazil 22.81S 50.06WCPI-93013 Sao Paulo, Brazil 22.00S 50.00WCIAT-2609 Tocatins, Brazil 11.78S 49.11W

*CPI, Australian Commonwealth Plant introduction number. †CIAT = Centro Internacional de Agricultura Tropical, Colombia.

Accession No.*† Origin Latitude Longitude

Table 1

Continued


G E N E T I C VA R I AT I O N I N

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Molecular Ecology

, 10, 1947–1958

in 100

µ

L of sterile distilled water. A 0.7% (w/v) agarose gelwas run to assess the concentration of DNA in each acces-sion by comparison with standards (Sambrook

et al

. 1989).

AFLP analysis

The methodology followed is described in detail by Virk

et al

. (1998) and is based on the protocol described byVos

et al

. (1995) with some minor modifications. Totalgenomic DNA was restricted with

Eco

RI (Pharmacia) and

Mse

I (New England Biolabs, Inc.) restriction enzymes andligated to

Eco

RI adapters (5

′

-CTCGTAGACTGCGTACC-3

′

and 3

′

-CATCTGACGCATGGTTAA-5

′

) and

Mse

I adapters(5

′

-GACGATGAGTCCTGAG-3

′

and 3

′

-TACTCAGGACT-CAT-5

′

). Following full digestion and ligation, products werediluted 10-fold with sterile distilled water.

Pre-amplification was carried out using

Eco

RI-(EP; 5

′

-GACTGCGTACCAATTCA-3

′

) and

Mse

I-(MP; 5

′

-GATG-AGTCCTGAGTAAC-3

′

) adapter-directed primers, eachpossessing a single selective base (Vos

et al.

1995). Productswere then diluted 50-fold with sterile distilled water. Foreach species, selective amplification of the pre-amplificationproducts was carried out using the primer combinationslisted in Table 2. The

Eco

RI primers contained two or threeselective nucleotides at the 3

′

-end and were end-labelled with[

γ

33P]-ATP using T4 polynucleotide kinase (Pharmacia).The

Mse

I primers contained three selective nucleotides atthe 3

′

-end and were not labelled. The selective nucleotidesare underlined in Table 2. Five primer combinations wereused for

S. humilis

(E1:M1; E1:M2; E1:M3; E1:M4; E2:M3)and four were used for

S. viscosa

(E2:M2; E2:M3; E2:M5;E2:M6). These were selected on the basis of giving clearbanding patterns with high levels of polymorphism.

Two microlitres of the selectively amplified polymerasechain reaction (PCR) products were loaded onto a 5% denatur-ing polyacrylamide gel [5% acrylamide (ultra pure Accugel19 : 1; National Diagnostics), 1

×

TBE (Sambrook

et al

. 1989),7.5

m

urea] after the reaction was stopped by adding 25

µ

Lof formamide loading buffer, and after samples were dena-tured at 90

°

C for 5 min and immediately placed on ice. Elec-trophoresis was undertaken at a constant 50

°

C temperaturefor 2 h. The gel was transferred to Whatman 3MM chroma-tography paper and dried for 2 h at 80

°

C on a slab drier(Bio-Rad) and exposed to Kodak Biomax film for 4–5 days.

Data analysis

Presence or absence of bands was scored as 1/0 in a binarydata matrix. Only heavy bands were scored, faint bandswere rejected. Monomorphic markers were also scored butomitted from the subsequent analysis, which was carriedout using the program

ntsys-pc

(Rohlf 1997). Pairwisesimilarities were calculated among accessions within eachspecies using the Jaccard coefficient ( Jaccard 1908) andcombining the data sets of each species. The resultingmatrices were then used to construct dendrograms usingthe unweighted pair group method average (

upgma

) cluster-ing procedure. In both species, accessions were placed intogroups of similar genotypes by assigning an arbitrary cut-off point on each dendrogram. The cut-off points, and thusthe number of subsequent clusters, varied among the twospecies and depended on the number of accessions and thelevel of diversity within each taxon. To estimate the partition-ing of AFLP genotypic variation between and within groups,analysis of molecular variance (

amova

) was used with

arlequin

, Version 2000 (Schneider

et al

. 2000). The goodness-of-fit of the clustering to the data matrix was calculatedwith the

coph

and

mxcomp

procedures in

ntsys-pc

(Rohlf1997). The similarity coefficient of Nei & Li (1979) in which

Sij =

2

a/

(2

a

+

b

+

c

) was used to compare distance values(1

−

F

) in each species with that of Kazan

et al

. (1993). Theconversion to genetic distances

D

was achieved by theformula

Dij = 1 – Sij. Principal coordinate analysis (PCO)was performed with the decenter and eigen procedures inntsys-pc. Performing a PCO on the data can be consideredas a check of the clusters formed by the cluster analysis.

Results


Five primer combinations produced 417 bands, of which316 were polymorphic (75% polymorphism). The averagesimilarity among accessions using Jaccard’s coefficient was0.71, and the average genetic distance among accessionswas 0.17. This is slightly larger than values obtained byKazan et al. (1993). When ntsys-pc analysis was performedon each individual primer combination, major groups formedin the dendrograms are similar to groups formed in the

Stylosanthes humilis Stylosanthes viscosa

EcoRI (E1) 5′GACTGCGTACCAATTCAT3′ EcoRI (E2) 5′GACTGCGTACCAATTCACG3′EcoRI (E2) 5′GACTGCGTACCAATTCACG3′ MseI (M2) 5′GATGAGTCCTGAGTAACAG3′MseI (M1) 5′GATGAGTCCTGAGTAACAC3′ MseI (M3) 5′GATGAGTCCTGAGTAACTA3′MseI (M2) 5′GATGAGTCCTGAGTAACAG3′ MseI (M5) 5′GATGAGTCCTGAGTAACAT3′MseI (M3) 5′GATGAGTCCTGAGTAACTA3′ MseI (M6) 5′GATGAGTCCTGAGTAACTC3′MseI (M4) 5′GATGAGTCCTGAGTAACTT3′

Table 2 Amplification primers obtained fromOperon and used in AFLP study


1952 M . C . S AW K I N S E T A L .

© 2001 Blackwell Science Ltd, Molecular Ecology, 10, 1947–1958

dendrogram with the combined data set (data not shown).The cophenetic correlation value for the complete data setis 0.95, indicating a very good fit of the clusters to the data.upgma clustering reveals that at an arbitrary level of 75%similarity six groups are formed (Fig. 1). In general, clustersreflect the geographical localities from which accessionsare collected with some exceptions. For example accessionsCPI-38753B (Colombia), CPI-55854 (Panama) and CPI-49828(Costa Rica) group together in cluster 1, which containsmainly Brazilian accessions. Cluster 2 is mainly of Venezuelanorigin with one individual from Colombia (CIAT-2334),whereas cluster 3 is principally from Panama, with theaddition of individuals from Brazil (CPI-40283B), Costa Rica(CPI-34001) and Venezuela (CPI-57246). Cluster 4 containsa single accession, CIAT-2064, from Brazil. This resolves at alower similarity with cluster 5, which comprises accessionsfrom Mexico and one accession from Brazil (CPI-34926).Cluster 6 contains two accessions from Guatemala, whichresolve with the other Stylosanthes humilis accessions at only≈ 50% similarity and may be misidentified. The geographicaldistribution of the groups is shown in Fig. 2.

PCO analysis of the similarity data reveals similar rela-tionships among accessions. Figure 3 shows a two-dimensional PCO plot of the S. humilis AFLP data set. Thefirst principal coordinate represents 24% of the variation

and clearly illustrates the separation among the SouthAmerican accessions. Group 1 is primarily Brazilian, whereasgroup 2 is primarily Venezuelan, with one accession fromColombia. Group 3, comprising accessions from Panama,is also differentiated from the mainly South Americanaccessions by the first dimension. The second principalcoordinate accounts for ≈ 14% of the variation. It showsthat the Mexican and Guatemalan accessions (groups 5and 6) are clearly differentiated from the other groups. Italso shows that the other Central American accessions(Group 3) are placed midpoint between the mainly SouthAmerican and the Mexican (and CPI-34926 from Brazil) andGuatemalan accessions. Accession CIAT-2064 is similar togroup 5 on the first dimension and group 3 on the seconddimension. amova (Table 3) revealed that a greater part ofthe variation (59.4%) is found among the clusters thanwithin them (40.5%). This is highly significant (P < 0.001).


Four primer combinations produced a total of 373 bands ofwhich 312 were polymorphic (83% polymorphism). Theaverage similarity value among all accessions using Jaccard’ssimilarity was 0.67 (67%). The average genetic distance amongaccessions was 0.20. When ntsys-pc analysis was performed

Fig. 1. A dendrogram constructed for 52 accessions of Stylosanthes humilis, using Jaccard’s coefficient and UPGMA clustering.


G E N E T I C VA R I AT I O N I N S T Y L O S A N T H E S S P E C I E S 1953


on each individual primer combination, the major groupsformed are similar to those formed with the combined dataset (data not shown). The cophenetic correlation for thecombined data set is 0.96, which indicates a very good fit ofthe clusters to the data. Cutting the dendrogram at ≈ 78%similarity forms 10 clusters as shown in Fig. 4. As withS. humilis, the clusters generally reflect the geographical

localities from which accessions were collected, again withsome exceptions. Clusters 1 and 2 comprise accessions fromBrazil, although cluster 1 also contains one accession fromMexico (CPI-91330). These two clusters are very similar, asillustrated by the very short length of the branch that joinsthem. Cluster 3 contains one accession from Brazil (CPI-105724) which resolves at ≈ 69% similarity with the other

Fig. 2 Geographical distribution of Stylo-santhes humilis accessions represented by theclusters formed from the UPGMA clustering.

Fig. 3 A two-dimensional plot of the prin-cipal coordinates analysis of the AFLP datafor Stylosanthes humilis.


1954 M . C . S AW K I N S E T A L .


Brazilian accessions from clusters 1 and 2. Cluster 4 containsaccessions from Venezuela in addition to one Colombianaccession (CIAT-2341), whereas group 5 comprises the remain-ing Mexican accessions. One individual from Belize (CPI-67662) makes up cluster 6, which resolves with the Mexicanaccessions in cluster 5 at ≈ 70% similarity. Cluster 7 containsthree accessions from Brazil which, in turn, join one accession(cluster 8) from Brazil (CIAT-2060). The two remainingclusters, 9 and 10, are genetically dissimilar to all the otheraccessions, particularly accession CPI-93013 from Brazil. Thegeographical distribution of the groups is shown in Fig. 5.

PCO analysis of the data reveals similar relationshipsamong accessions. Figure 6 shows a two-dimensional PCOplot of the S. viscosa AFLP data set. Comparison between thePCO results for both species shows that there is not as cleara separation between groups as in S. humilis. This is shownin the spread of points within groups. The first principalcoordinate accounts for 18% of the variation and separates

groups 1 and 2 (Brazil) from groups 7 and 8 (Brazil). AccessionsCPI-Q10044, CPI-Q10045 (group 9) and CPI-93013 (group 10)are similar to groups 7 and 8. The second principal coordinateaccounts for 10% of the variation and separates the Venezuelan,Mexican, Belize and Colombian accessions (groups 4, 5 and6) from the Brazilian accessions in groups 1, 2, 3, 7 and 8.However accessions CPI-Q10044, CPI-Q10045 (group 9) andCPI-93013 (group 10) are more similar to the Mexican andCentral American group. amova (Table 4) reveals that amongclusters variation is higher (66.5%) than variation withinthe clusters (33.5%). This is highly significant (P < 0.001).

Discussion

Genetic variation

Our results demonstrate the utility of AFLP technologynot only in detecting genetic diversity within species of

Source of variation d.f. SSD Variance components % of total P-value

Among clusters 4 533.99 14.65 59.41 < 0.001Within clusters 45 450.44 10.00 40.59Total 49 984.44 24.65

Fig. 4 A dendrogram constructed for 59 accessions of Stylosanthes viscosa, using Jaccard’s coefficient and UPGMA clustering.

Table 3 Analysis of molecular variance(amova) for 50 individuals of Stylosantheshumilis. The hierarchy is based on the clustersformed in the dendrogram (Fig. 1)




Fig. 5 Geographical distribution of Stylo-santhes viscosa accessions represented by theclusters formed from the UPGMA clustering.

Fig. 6 A two-dimensional plot of the prin-cipal coordinates analysis of the AFLP datafor Stylosanthes viscosa.

Source of variation d.f. SSD Variance components % of total P-value

Among clusters 9 383.36 8.39 66.50 < 0.001Within clusters 49 207.26 4.22 33.50Total 58 984.44 12.62

Table 4 Analysis of molecular variance(amova) for 59 individuals of Stylosanthesviscosa. The hierarchy is based on theclusters formed in the dendrogram (Fig. 4)


1956 M . C . S AW K I N S E T A L .


Stylosanthes, but also in identifying individuals that may bemisclassified. The identification of species in Stylosanthesbased on morphological characters is not easy. AFLP analysisappears to have identified two accessions that were verydifferent to all others of S. humilis (CPI-67670, CPI-67671).Subsequent studies based on sequence similarity to the ITSregion of nrDNA and morphological characters (J. VanderStappen & S. Gama Lopez, personal communication) haveshown that CPI-67670 and CPI-67671 are in fact S. hamata,and not S. humilis. Nevertheless, the genetic variation inS. humilis (1 − F = 0.17) identified during this study wasgreater than that reported by Kazan et al. (1993) (1 − F= 0.105), although only four accessions of S. humilis wereexamined in that study with a diversity range of 0.08–0.16.Removal of these two misidentified accessions (CPI-67670,CPI-67671) in our study does not alter the average similarity(0.72) or distance (0.16) to any great extent. The two misidentifiedaccessions were also removed prior to running AMOVA.

The average genetic distance among accessions of S. viscosaexamined in this study with 1 − F was 0.20. Although Kazanet al. (1993) did not examine any accessions of S. viscosa intheir study, they do report a range of values between 0.04and 0.25 for four other species of Stylosanthes (i.e. S. scabra,S. hamata, S. guianensis and S. humilis). The value observed inthis study falls within the range obtained for these species.

Overall, a comparison of genetic variation among thetwo species in this study suggests that S. humilis is lessgenetically variable than that of S. viscosa. However, theuse of different primer combinations in both species mayhave been a contributory factor to this difference. In addi-tion, this difference may also be a reflection of the breedingsystem in these species. The annual S. humilis and perennialS. viscosa may differ in degrees of outcrossing and this mayexplain the observed difference in genetic similarity or dis-tance among the two species (Kazan et al. 1993). Levels ofoutcrossing have been quantified for a few species rangingfrom 1 to 2% in S. scabra to 20% in S. capitata (Stace 1984).Although levels of outcrossing in the species in this studyare not known, S. humilis is considered a highly inbreedingspecies, whereas some evidence exists for the formationof hybrids between Mexican and Brazilian accessions ofS. viscosa suggesting there is some outcrossing in thisspecies (Stace 1982, 1984).

Geographical distribution of genetic variation

Stylosanthes humilis. The S. humilis accessions used in thisstudy have been resolved into clusters that reflect theirgeographical origins. This was supported by the groupingsin the PCO analysis and the amova, which showed morevariation among clusters than within. AFLP genotypescould be divided into a Brazilian group, a Venezuelan group,a central American group and a Mexican group. Someaccessions did not conform to this geographical

demarcation. A possible reason could be long-rangedispersal events or introductions of genotypes from onearea to another by man. This is the situation that occurredwith the accidental introduction of S. humilis into Australia(Crowder & Chheda 1982). For example, cluster 5 (Mexico)contains one accession collected from Brazil (CPI-34926),which Stace & Cameron (1984) suggested, on the basis ofresults from intraspecific hybridization experiments, mayactually have originated from Mexico rather than Brazil.

The correlation between diversity based on AFLPs andgeographical origin suggests that Mexican accessions ofS. humilis may have a different evolutionary history fromthe Brazilian accessions, as the PCO and cluster analysisshowed that accessions from these countries were clearlydifferent to each other. It has been known for some timethat Mexican accessions are different to those from Brazil,but this study revealed that they are also genetically verydifferent. This suggests that during the evolution of thespecies, divergence between populations isolated oververy large geographical distances may have occurred. Thissupports the view of Vander Stappen et al. (2000) who founda clear discrimination between Mexican and some SouthAmerican accessions of S. humilis using AFLPs. Also, a studyof chloroplast DNA variation identified two sequencetypes, one from Mexico and the other from South America(Vander Stappen et al. 1999). Moreover, Edye et al. (1974),classified S. humilis into a number of geographical groups onthe basis of morphological agronomic characters, and Stace& Cameron (1984) found that F1 hybrids formed betweena Mexican and an Australian (ex Brazil) accession were lessfertile than F1 hybrids between one Brazilian and oneAustralian accession. On the basis of this evidence, VanderStappen et al. (2000) suggests the existence of two gene poolsin S. humilis, one in South America and a second in Mexico.

The greatest numbers of accessions in this study wereof Brazilian and Venezuelan origin, with some fromMexico and Central America. This is in contrast to theAFLP study by Vander Stappen et al. (2000), in which mostaccessions were Mexican in origin with few from SouthAmerica. Our study revealed new information concerninggenetic variation in S. humilis from Venezuela and CentralAmerica (Panama and Costa Rica), an area which has beenrather overlooked in studies of genetic diversity in Stylosanthes(Schultze-Kraft et al. 1984). Current work has shown thataccessions from these geographical areas were clusteredinto distinct groups and were genetically different to acces-sions from Mexico and Brazil. However, the relationshipsbetween these groups may change with the inclusion ofmore accessions from Mexico and Central America.

Stylosanthes viscosa. upgma clustering and PCO analysisof the AFLP fingerprint patterns for S. viscosa enabledthe genotypes to be allocated to a number of Braziliangroups, a Venezuelan group and a Mexican group, with




some exceptions. The possible reasons for this have beendiscussed earlier for S. humilis. In one case, accessions fromVenezuela and Mexico fall between the Brazilian accessionsas shown by the PCO (Fig. 6). This suggests that geneticvariation among the Brazilian accessions was not continuous,a feature that can be caused by isolation, genetic drift orselection (Miller & Libby 1991). A similar geographicalpattern was observed by Liu (1997), who examined geneticvariation using RAPDs in a collection of the allotetraploidS. scabra, of which S. viscosa is one of the diploid progenitors(Liu & Musial 1997) and which has a very similar geographicaldistribution to that of S. viscosa.

In contrast to S. humilis, very few accessions of S. viscosawere examined from Central America, so it is not possibleto obtain a clear picture of genetic variation in this region.The only Central American accession analysed was collectedfrom Belize and this was shown to be genetically similar toaccessions from Mexico. Also, the accessions from Venezuelawere found to be similar to those from Mexico.

Conclusion

AFLP fingerprint patterns for Stylosanthes humilis andS. viscosa revealed them both to have different degreesof genetic variation but generally showed similar pat-terns of geographical clustering. Geographical isolationand the processes of genetic drift and selection may haveled to the development of regional genotypes. Our studyand that of Vander Stappen et al. (2000) together providethe most detailed picture of genetic variation of S. humilisacross its distributional range to date. Similarly, this studyhas provided the most detailed information on levels andstructuring of genetic variation in S. viscosa to date.

The data presented have shown that although vari-ation exists in Brazil and Venezuela, novel variation islikely in Mexico and Central America. As the majority ofthe ex situ collections comprise Brazilian and Venezuelanaccessions, it would seem that existing variation in Mexicanand Central American accessions is less well represented.A conservation strategy formulated for these species shouldnot ignore these areas. If the primary goal of plant geneticresource conservation is to conserve the maximum geneticvariation present in a species then further collecting orstudy in these areas should certainly be considered. Asfew accessions were examined from Central America itwould be useful to examine more material to provide aclear picture of variation within this region and howthis variation is related to that known in Mexico andSouth America.

Acknowledgements

The authors would like to thank J. Donnelly (CSIRO), D.Debouck and C. Guevara (CIAT) for the supply of plant material.

M. Sawkins would also like to thank A. Gillies, University of St.Andrews, and E. Mace, University of Queensland for invaluablecomments on the manuscript and discussion on analyses.

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This research forms part of a PhD undertaken by Mark Sawkins.This was a collaboration between the University of Birminghamand The Royal Botanic Gardens, Kew. The overall objective of thePhD was the identification and use of tools to analyse collectiondata for effective germplasm conservation. Mark’s research interestsinclude the application of molecular markers to questions in plantgenetic resources, population genetics and genome evolution. BrigitteMaass is a lecturer at the Georg-August-University Göettingen. BrucePengelly is a Forage Legume Scientist at CSIRO Sustainable Eco-systems. Nigel Maxted, John Newbury and Brian Ford-Lloyd arelecturers at the University of Birmingham. Roger Smith is Head ofthe Seed Conservation Department, Royal Botanic Gardens, Kew.


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