Discriminating between barley genotypes using ...

Discriminating between barley genotypes using microsatellite markers

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Joanne Russell, John Fuller, George Young, Bill Thomas, Graziana Taramino, Malcolm Macaulay, Robbie Waugh, and Wayne Powell

Abstract: Eleven microsatellite loci were used to survey 24 barley genotypes representing 23 cultivars and a breeding line in official trials. Three separate combinations of four microsatellites had overall probabilities of identity of less than 1 in 1000 and could distinguish between all 24 barley genotypes. It is shown that the microsatellites could distinguish genotypes with the same pedigree and also that patterns of discrimination were different from those obtained from botanical descriptors. The stability of microsatellites across different generations was demonstrated by a retrospective analysis of the pedigree of Golden Promise. One of the parents of Maythorpe, the immediate ancestor of Golden Promise, was shown to be Irish Goldthorpe rather than Goldthorpe, thereby resolving conflicting published pedigrees. Key words: barley, microsatellites, cultivar identification, stability, Golden Promise.

RCsumC : Onze microsatellites ont Ctk utilisks afin de distinguer 24 gknotypes d'orge (23 cultivars et une lignCe d'amkliorateur) dans le cadre d'essais officiels. Trois combinaisons distinctes de quatre microsatellites rksultaient en une probabilitC globale d'identitC infkrieure i une sur ZOO0 et permettaient de distinguer chacun des 24 genotypes. I1 a CtC montrC que les microsatellites permettaient de distinguer des gknotypes ayant le meme pedigree et que ces distinctions diffkraient de celles obtenues sur la base des descripteurs botaniques. La stabilitC des microsatellites a kt6 dkmontrke sur plusieurs gCnCrations par l'analyse rktrospective du pedigree de Golden Promise. L'autre parent de Maythorpe, I'ancetre immCdiat de Golden Promise, s'avkre &re Irish Goldthorpe plut8t que Goldthorpe mettant ainsi fin B la confusion rksultant de la publication de pedigrees diffkrents. Mots cle's : orge, microsatellites, identification variktale, stabilitC, Golden Promise. [Traduit par la RCdaction]

Introduction There is a recognized need to reliably distinguish varieties of crop plants and establish their purity. A number of factors have driven this need, including the introduction of plant variety rights, seed certification, and the associated requirement to protect proprietary germplasm. Reliable methods for discriminating between varieties would also allow more accurate estimates of gene-pool variation to be determined and would promote genetic diversity in breeding and agriculture. The application of biotechnology, particularly genetic transformation, to plant breeding could also allow rapid improvement of one or a small number of traits. This issue has raised questions over the ownership of an earlier produced variety in relation to a derived variety. Such genotypes have been termed essentially derived varieties (EDV) and places greater pressures on breeders and legislators to accurately describe plant germplasm. Corresponding Editor: G.J. Scoles. Received December 13, 1996. Accepted March 4, 1997.

J. Russell, J. Fuller, G. Young, W. Thomas, M. Macaulay, R. Waugh, and W. ow ell.' Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, Scotland, U.K. G. Taramino. E.I. DuPont de Nemours and Co., DuPont Agricultural Products, Biotechnology Research Experimental Station, Wilmington, DE 19880-0402,U.S.A.

'

Author to whom all correspondence should be addressed (e-mail: [email protected]).

Genome, 40: 442-450 (1997)

Traditionally, morphological characters have been used to evaluate distinctness, uniformity, and stability (DUS) and to establish a description of a genotype (Jarman and Pickett 1992). Such methods are subjective and are often influenced by environmental conditions. Furthermore, examination of morphological characters is labour intensive, for example, over 80 separate morphological characters are examined for a barley genotype (Cooke 1984). For these reasons a great deal of attention has been paid to the development of laboratorybased methods for cultivar identification. Electrophoresis of seed storage proteins has been used extensively to identify cereal varieties (Jarman and Pickett 1992). Biochemical tests offer significant advantages over morphological methods for variety identification in that they are rapid, inexpensive, eliminate the need to grow plants to maturity, and are largely unaffected by the growth environment. Polymorphic isozyme and storage-protein systems have been investigated for classification of a wide range of crops, including wheat (Cooke 1989), maize (Cardy and Kannenberg 1982), soybean (Cardy and Beversdorf 1984), and perennial ryegrass (Ferguson and Grabe 1986). The use of electrophoresis techniques for barley varietal identification has been proposed by a number of authors (Almgard and Landegren 1974; Fedak 1974; Bassiri 1976; Anderson 1982; Nielsen and Johansen 1986) who have identified the need for unambiguous classification of barley varieties. Hordein protein separation by polyacrylamide gel electrophoresis (PAGE) is currently the only electrophoretic technique that has been adopted for commercial classification 01 997 NRC Canada

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Table 1. Spring and winter barley cultivars evaluated with microsatellites together with information on their pedigree, breeder, and percentage of U.K. certified seed area (1995). % U.K


Cultivar Winter barley Angora Fighter Halcyon Intro Linnet Manitou Marinka Melanie Muscat Pastoral Puffin Regina Spring barley Alexis Chariot Cooper Dandy Derkado Hart Livet Optic Prisma Riviera Tankard Tyne

Pedigree

seed area

Breeder

BR30la x Wei5907 RPB77/5 155 x Marinka Warboys x Maris Otter P30 x SEC527EHI Mogador x NRPB8 115233 1055 x Gerbel (Alpha x SVP6714) x Malta BR30la x Wei5907 Plaisant x Gaulois Igri x Matador (Athos x Maris Otter) x Igri Labea x Marinka

Breun, Germany Nickersons, U.K. Plant Breeding Institute, U.K. Zelder, The Netherlands Nickersons, U.K. Secobra, France Cebeco, The Netherlands Breun, Germany CPB Twyford, U.K. Secobra, France Zeneca, U.K. Breun, Germany

Br1622D x Trumpf Dera x CSB626112 (Corniche x Force) x Troop Egmont x Atem Lada x Salome Egmont x Atem 22746Co41 (Dera x Digger) x TSS3 11/54 (TS421315 x Apex) Chad x (Corniche x Force) Trumpf x Cambrinus) x Piccolo Stanza x Cebeco833 1 (Corniche x CSBA 1096/1022) x (Heritage x Chariot) (Goldmarker x Athos) x (Goldmarker x Magnum)

Breun, Germany Plant Breeding International Cambridge, U.K. New Farm Crops, U.K. Welsh Plant Breeding Station, U.K. Nordsaat, Germany Plant Breeding International Cambridge, U.K. Scottish Crop Research Institute, U.K.

of barley varieties (Shewry et al. 1979; Cooke and Morgan 1986). However, the level of resolution is insufficient to uniquely discriminate between cultivars (Jarman and Pickett 1992), and the techniques of DNA fingerprinting (Ainsworth and Sharp 1989) have therefore been considered. Various DNA profiling methods are currently available (for a recent review see ~ a f a l s k et i al. 1996) and fall into two main categories: those using defined primers that require sequence information from the species under study and those using generic primers that can be used on any template DNA. The most informative polymorphic marker system currently available is microsatellites or simple sequence repeats (SSRs; Tautz and Renz 1984). Variation in the length of the repeat motifs between individuals is revealed by amplifying genomic DNA with two unique oligonucleotide primers that flank, and hence define, the microsatellite locus. Microsatellites are particularly attractive for distinguishing between cultivars, since the level of variation detected at microsatellite loci is higher than that detected with any other molecular assay (Saghai-Maroof et al. 1994; Becker and Heun 1995; Powell et al. 1996; Bowers et al. 1996). However, the deployment of microsatellites requires that the sequences flanking the repeat motif be determined to allow for the design of primers. In this

New Farm Crops, U.K. Wiersum, The Netherlands Plant Breeding International Cambridge, U.K. Plant Breeding International Cambridge, U.K. Scottish Crop Research Institute, U.K.

Fig. 1. Pedigree of the spring barley Golden Promise. Two different genotypes (denoted by ?) have been published as having been crossed with Maja to produce Maythorpe. English Landrace

Unknown Austrian cv.

Local cv. (Gotland) Sweden

I

I

I

4

Chevalier

4

Hanna

I

Gull

Binder

+

1

Goldthorpe? Irish Goldthorpe?

Maja

I Golden Promise

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Fig. 2. An example of the polymorphism detected among 24 barley genotypes by microsatellite BMS02.

manuscript we describe both database- and library-derived microsatellite primers and demonstrate their utility to uniquely discriminate between current barley cultivars.

Materials and methods Barley cultivars Twelve winter barley and 12 spring barley cultivars were chosen for the study. With one exception, all the cultivars were derived from the 1996 National Institute of Agricultural Botany (NIAB) Recommended List (Anonymous 1995) and thus were already established as being morphologically distinct from one another. The exception was Livet, a new spring barley bred by the Scottish Crop Research Institute (SCRI), which has since been found to be morphologically distinct and has been placed on the U.K. National List. The genotypes are listed in Table 1, together with the breeders and the approximate percentage of seed available for sowing in 1995-1996 from the L1.K. seed certification scheme (Agricultural Supply Industry 1995). The genotypes were chosen to represent a range of popular and new genotypes, including two winter barley and two spring barley cultivars with common pedigrees.

Germ line stability of microsatellites To investigate the stability of microsatellites over generations, a retrospective analysis of the genotypic composition of the cultivar Golden Promise, whose pedigree is shown in Fig. 1, was undertaken. There was uncertainty over the parentage of Maythorpe, with Maja x Goldthorpe being indicated (Anonymous 1961) and Maja x Irish Goldthorpe also having been published (Aufhammer et al. 1958). Both these potential parents, along with the other genotypes in the pedigree, were included in a genotyping exercise.

Microsatellite discovery and detection of polymorphism Two sources of SSRs were used in this study: database-derived repeats (described by Becker and Heun 1995; Liu et al. 1996) and repeats derived from an enriched genomic library. Isolation of microsatellite-containing clones, sequencing, and primer design were as described by Rafalski et al. (1996) and Powell et al. (1996). Microsatellite assays were performed as described by Morgante et al. (1994), except that annealing temperatures were optimized for each primer pair (Table 2). Allele sizes were determined by comparing the most intense band with the M13 DNA sequence marker.

Statistical analysis The numbers of alleles detected by each microsatellite were estimated for each genotype. These numbers were converted into a numeric scale ranging from one to the number of different microsatellite alleles detected over all 24 genotypes. Average linkage cluster analysis of the allele numbers was then canied out using the city-block method

of estimating distances between genotypes (Digby and Kempton 1989), and the levels of differentiation between barley types were calculated using the RsTstatistic (Slatkin 1995).From the frequencies of the 1-n alleles detected by each microsatellite diversity indices were estimated as: diversity index = 1 -

1p i

(Weir 1990); probabilities of identity (I) as:

(Paetkau et al. 1995); and polymorphic information content (PIC) as:

i

n-l

n

i=l

;=i+l

&: 1 1 2p:p;

PIC= 1 -

-

1

(Weber 1990); where pi and p, are the frequencies of the ith and jth alleles in a given population.

Results Cultivar identification The distribution of allele sizes for the 11 microsatellites across the cultivars evaluated is given in Table 3. The microsatellite BLYRCAB detected the greatest number of alleles (9) and also has the highest diversity index. Only two alleles were detected for BMS90 and HVCMA, but BMS32 has the lowest diversity index, as there were only four deviants from the most frequent allele. Null alleles were detected in five cases, three with the HVWAXY microsatellite, in which the absence of an amplification product for the cultivars Linnet, Chariot, and Tyne was confirmed by several independent amplifications. An example of the polymorphism detected with BMS02 is shown in Fig. 2. Probabilities of identity (I)were quite variable, as were PIC values (Table 4), reflecting the range and frequencies of alleles detected by each microsatellite. However, for BMS02, BMS40, HVBKASI, BLYRCAB, and HVWAXY, I < 0.2 and PIC > 0.5. An examination of the allele-size distribution in Table 3 reveals that the following combinations of microsatellites uniquely discriminate between all the cultivars: BMS32, BMS40, BLYRCAB, and HVBKASI; BMS32, BMS40, BLYRCAB, and BMS90; and 0 1997 NRC Canada

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BMS32, BMS40, BLYRCAB, and HVWAXY, with overall probabilities of identity (Paetkau et al. 1995) of 1.72 x lo4, 3.46 x lo4, and 1.02 x lo4, respectively (assuming no linkage between loci).

Genetic differentiation and relatedness The levels of variability detected in the spring barley and winter barley gene pools with 11 microsatellites are given in Table 5. Overall there are no significant differences in the genetic variability observed in the two gene pools (winter barley and spring barley). However, two microsatellites, BMS64 and HVCMA, are monomorphic in the spring barley genotypes but detected two or more alleles in the winter barley genotypes, and one, HVLEU, is monomorphic in the spring barley genotypes but detected two alleles in the winter genotypes. This is reflected in the RsT statistic, which measures the levels of differentiation between the two groups based on microsatellite length variation. To examine relationships between cultivars further, principal coordinate (PCD) analysis of the microsatellite alleles was undertaken (Fig. 3). The first three PCOs account for 54% of the variation. From Fig. 3 it can be seen that the spring barley genotypes were generally characterized by negative P C 0 1 scores and positive PC02 scores. While the reverse was generally true for the winter barley genotypes, Linnet and Puffin tended to group with the spring barley genotypes. In the case of Puffin, this might reflect the contribution of alleles from a spring barley grandparent, and Linnet does not have the hairy leaf sheath characteristic of most winter barley cultivars (Jarman and Pickett 1993). Overall, the spring barley genotypes were more similar (average similarity 81%) than the winter ones (average similarity 62%). Figure 3 shows genotype groupings from the first three PCOs. The microsatellites used in the study do not discriminate between feed and malting barleys, nor do the groupings reflect any other obvious differences between the genotypes. The lack of any obvious associations of the groupings with phenotype indicates that the panel of microsatellites used in the current study should be ideally suited for cultivar discrimination. The average similarity of the winter malting barley genotypes (72%) was less than that of the spring ones (78%). No statistical significance can be attached to this difference, but coupled with the greater scatter of the winter malting barley types in Fig. 3, it does suggest that there is more diversity in winter malting barley compared with spring malting barley. This may reflect less breeding effort having been placed on the winter crop and also suggests that further improvements in malting quality may be possible in this group. In fact, progress in developing winter malting barleys made so far has produced an increase in the yielding ability of malting barley genotypes, with little, if any, advance having been made in hot water extract, the main component of malting quality, since the introduction of Maris Otter. Considerable advance has been made in hot water extract in spring malting barley in the same period, and the greater similarity may indicate limited opportunity for further progress here.

nnnn-nn

zzzzzzz

nnnnnnn

zzzzzzz

ctzcccc cszcscc

Germ-line stability of microsatellites Nine of the 11 microsatellites evaluated on the genotypes implicated in the pedigree of Golden Promise were informative and detected polymorphism (Table 6). There was no evidence of microsatellite instability, and polymorphisms 0 1997 NRC Canada

0

3

4

\D \D

2

"Indicates null allele. b~xcludingnull alleles.

Diversity indexb

Number of allelesb

Winter barley Angora Fighter Halcyon Intro Linnet Manitou Marinka Melanie Muscat Pastoral Puffin Regina Spring barley Alexis Chariot Cooper Dandy Derkado Hart Livet Optic Prisma Riviera Tankard Tyne 3

0.53k0.04

0.7M.07

BMS18

6

BMS02

8

BMS40

0.29f0. 11 0.83f0.04

3

BMS32

0.37f0.11

3

BMS64

0.49f0.03

2

BMS90

Microsatellite

0.38f0.09

2

HVCMA

0.62f0.09

4

HVBKASI

0 . 2 8 s . 10

2

HVLEU

0.86f0.02

9

BLYRCAB

Table 3. Number of alleles detected and their sizes in base pairs, together with the diversity index, for 24 barley cultivars evaluated with 11 microsatellites.


0.71f0.08

6

HVWAXY

0

@

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Table 4. Probabilities of identity (Z) and polymorphic information content (PIC) for 11 microsatellites based on allele frequencies detected among 24 barley genotypes.


Microsatellite

I

Table 5. Number of alleles (n), diversity index (DI) and level of differentiation (RsT)detected in 12 spring barley and 12 winter barley cultivars with 11 microsatellites. Spring barley cultivars

PIC

BMS02 BMS18 BMS32 BMS40 BMS64 BMS90 HVCMA HVBKASI HVLEU BLYRCAB HVWAXY

Winter barley cultivars

Microsatellite

n

DI

n

BMS02 BMS18 BMS32 BMS40 BMS64 BMS90 HVCMA HVBKASI HVLEU BLYRCAB HVWAXY

5 2 2 4 1 2 1 3 1 5 3

0.76 f 0.05 0.44 f 0.09 0.15f0.13 0.69 f 0.12 0 0.44 f 0.09 0 0.53 f 0.13 0 0.76 f 0.05 0.34 f 0.18

4 3 3 5 4 2 2 4 2 5 5

DI 0.56 f 0.15 0.57 f 0.06 0.40f0.15 0.78 f 0.06 0.58 f 0.07 0.50 f 0.00 0.50 f 0.00 0.65 f 0.09 0.44 f 0.09 0.72 f 0.07 0.79 f 0.02

RST 0.035 0 0.009 0 0.274 0 0.303 0.088 0.164 0 0.022

Fig. 3. Plot of the first three principal coordinates from city-block analysis of allele numbers detected by 11 microsatellites in 24 barley genotypes.

U II Winter Malting @

Winter Feed

detected at HVWAXY and BLYRCAB demonstrate that Irish Goldthorpe is one of the parents of Maythorpe rather than Goldthorpe and, therefore, the pedigree published by Aufhammer et al. (1958) is correct. The transmission of alleles was distorted in one instance. The cultivar Gull contributed all

eight alleles to Maja where polymorphism was detected between it and Binder with the 1 1 microsatellites tested. In contrast, there were five polymorphisms between Maja and Irish Goldthorpe, with the latter contributing three alleles to Maythorpe (Table 6). 01997 NRC Canada

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Discussion and conclusions These results demonstrate that it is possible to discriminate between closely related elite barley cultivars using four microsatellite markers; indeed, the probability of identical genotypes is less than 1 in 1000. Within both groups of cultivars evaluated (winter and spring barleys), examples exist of cultivars that are derived from the same parental mating (Table 1). Thus, Angora and Melanie together with Hart and Dandy are examples of siblings that can be distinguished using microsatellites. Such cultivars would be classified as identical on the basis of their pedigrees. As to their botanical descriptions, Angora differs from Melanie for two botanical characters, shows slight differences for nine others, and is placed in hordein group 2.9, as opposed to group 2.7 for Melanie (Jarman and Pickett 1993, 1994). Dandy differs from Hart for nine botanical characters and shows a further seven slight differences, but is a mixture of two hordein biotypes, one of which is identical to Hart's (Jarman and Pickett 1992). This gives the impression that Dandy and Hart are less related than Angora and Melanie, whereas from the microsatellite analysis, each is its sibling's nearest neighbour and the similarities between the two pairs are 92 and 90%, compared with 82 and 9 1% for the morphological characters. This illustrates the high PIC values of microsatellites, which reflects the number and frequency of alleles detected. A further advantage of the use of microsatellites is the ease and reproducibility of genotyping, since the method is PCR based and also amenable to automation. Microsatellite markers have also been used to unequivocally identify grapevine (Thomas and Scott 1993), soybean (Rongwen et al. 1995), and wheat (Plaschke et al. 1995) genotypes. From the cluster analysis of the microsatellite data, Prisma and Tankard are the most similar genotypes (98.7%). This contrasts with differences in 23 of 38 botanical descriptors for the two genotypes (Jarman and Pickett 1992, 1995). Clearly, similarity between genotypes is a function of the number and distribution of loci being examined. The chromosomal locations of the microsatellites cover six of barley's seven chromosomes. The genetical distribution of loci controlling the botanical descriptors is, however, unknown. Microsatellites, in common with other genetical markers, offer the advantages of being able to assay variation at known regions of the genome, which could be targeted to the key regions controlling economically important characters as more information is gathered from quantitative trait locus mapping. Bailey (1983) originally identified four basic criteria for methods used to identify varieties: (i) distinguishable intervarietal variation, (ii) minimal intravarietal variation (iii) environmental stability, and (iv) experimental reproducibility. All these criteria are clearly satisfied by the use of microsatellites. The extent of intravarietal variation is related to the mechanism responsible for generating polymorphism in the assay being deployed. Thus in the case of microsatellites, where slipped-strand mispairing (Levinson and Gutman 1987) is thought to be responsible for generating length variation, it is important to establish the germ-line stability of microsatellites over time and through the development of new cultivars. In this study we have used microsatellites to analyse retrospectively the transmission of microsatellite alleles through the pedigree of Golden Promise. Based on this data, the only poly01997 NRC Canada


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morphism observed was that associated with intergenotype variation, with no evidence of microsatellite germ line instability. This observation, together with the multi-allelic properties of microsatellites, provides new opportunities for integrating cultivar identification with a retrospective analysis of germplasm development. Although our data are based on allelic variation at nine informative microsatellite loci used in the germ line stability study, these results indicate some distorted transmission of alleles that may reflect conscious or unconscious selection for favourable alleles during the creation of new barley cultivars. Retrospective analysis of germplasm development will allow the transmission of alleles through a breeding programme to be correlated with plant phenotype data. This approach has been used with soybean and restriction fragment length polymorphism markers (Lorenzen et al. 1995), but the greater resolving power of microsatellites will dramatically improve the efficiency of this approach and provide enhanced value to the genotyping of cultivars in multigeneration pedigrees.

Acknowledgements The authors thank the Scottish Office Agriculture, Environment and Fisheries Department for funding this work. Support from the North American Treaty Organization (CRG940005) is gratefully acknowledged.

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