This article was downloaded by: [Tel Aviv University] On: 25 April 2013, At: 02:54 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Canadian Journal of Plant Pathology Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tcjp20 Regional diversity of Russian populations of Puccinia triticina in 2007 Elena Gultyaeva a , Andrey Dmitriev a & Evsey Kosman b a All-Russian Institute for Plant Protection (VIZR), sh. Pobelskogo, 3, 196608, Saint Petersburg-Pushkin, Russia b Institute for Cereal Crops Improvement, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel Version of record first published: 03 Jan 2012. To cite this article: Elena Gultyaeva , Andrey Dmitriev & Evsey Kosman (2012): Regional diversity of Russian populations of Puccinia triticina in 2007, Canadian Journal of Plant Pathology, 34:2, 213-223 To link to this article: http://dx.doi.org/10.1080/07060661.2011.633562 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.tandfonline.com/page/terms-and-conditions This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.
Transcript
This article was downloaded by: [Tel Aviv University]On: 25 April 2013, At: 02:54Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK
Canadian Journal of Plant PathologyPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/tcjp20
Regional diversity of Russian populations of Pucciniatriticina in 2007Elena Gultyaeva a , Andrey Dmitriev a & Evsey Kosman ba All-Russian Institute for Plant Protection (VIZR), sh. Pobelskogo, 3, 196608, SaintPetersburg-Pushkin, Russiab Institute for Cereal Crops Improvement, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978,IsraelVersion of record first published: 03 Jan 2012.
To cite this article: Elena Gultyaeva , Andrey Dmitriev & Evsey Kosman (2012): Regional diversity of Russian populations ofPuccinia triticina in 2007, Canadian Journal of Plant Pathology, 34:2, 213-223
To link to this article: http://dx.doi.org/10.1080/07060661.2011.633562
PLEASE SCROLL DOWN FOR ARTICLE
Full terms and conditions of use: http://www.tandfonline.com/page/terms-and-conditions
This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form toanyone is expressly forbidden.
The publisher does not give any warranty express or implied or make any representation that the contentswill be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses shouldbe independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims,proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly inconnection with or arising out of the use of this material.
Regional diversity of Russian populations of Puccinia triticinain 2007
ELENA GULTYAEVA1, ANDREY DMITRIEV1 AND EVSEY KOSMAN2
1All-Russian Institute for Plant Protection (VIZR), sh. Pobelskogo, 3 196608, Saint Petersburg-Pushkin, Russia2Institute for Cereal Crops Improvement, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
(Accepted 12 October 2011)
Abstract: Four hundred and seventeen single-uredinial isolates of Puccinia triticina collected from wheat in seven regions of Russia in2007 were tested for virulence with 24 near-isogenic wheat differential lines and molecular variation with six RAPD and one UP-PCR DNAmarkers. Seventy-nine virulence phenotypes and 71 molecular genotypes were identified. The P. triticina isolates varied for virulence onresistance genes Lr1, Lr2a, Lr2b, Lr2s, Lr3a, Lr3bg, Lr3ka, Lr14a, Lr14b, Lr15, Lr16, Lr17, Lr18, Lr19, Lr20, Lr21, Lr24, Lr26, Lr28 andLrB. All isolates were virulent on Lr10, Lr11 and Lr30, and avirulent on Lr9. THTTTJ was the predominant phenotype in all regions withfrequency ranging from 25 to 63%. Diversity analysis of the regional collections demonstrated inconsistency of results obtained withvirulence and molecular markers. According to the virulence data, the North Caucasian and Central collections of P. triticina were the mostdistant from all the other regional populations. The most similar were collections from West Siberian and Ural regions, which may be a resultof growing genetically similar wheat cultivars. According to the molecular marker data, the Central, Central Black Earth, and Ural populationsclustered distinctly from the North Western, North Caucasian, and West Siberian collections.
Résumé: En 2007, 417 isolats mono-urédiniaux de Puccinia triticina, collectés sur du blé provenant de 7 régions de Russie, ont été testés,avec 6 marqueurs RAPD et 1 UP-PCR, pour leur virulence à l’égard de 24 lignées différentielles quasi-isogéniques et leur variationmoléculaire. Soixante-dix-neuf phénotypes de virulence et 71 génotypes moléculaires ont été identifiés. Sur le plan de la virulence, les isolatsde P. triticina variaient à l’égard des gènes de résistance Lr1, Lr2a, Lr2b, Lr2c, Lr3a, Lr3bg, Lr3ka, Lr14a, Lr14b, Lr15, Lr16, Lr17, Lr18,Lr19, Lr20, Lr21, Lr24, Lr26, Lr28 et LrB. Tous les isolats étaient virulents à l’égard de Lr10, Lr11 et Lr30, et non virulents à l’égard de Lr9.Le phénotype THTTTJ était le plus courant dans toutes les régions avec une fréquence variant de 25 à 63 %. L’analyse de la diversité descollections régionales a démontré la non-cohérence des résultats obtenus avec les marqueurs de virulence et les marqueurs moléculaires. Selonles données de virulence, les collections de P. triticina provenant du nord du Caucase et du Centre étaient les plus éloignées de toutes les autrespopulations régionales. Les plus semblables étaient les collections de l’ouest de la Sibérie et de l’Oural, ce qui peut découler du fait que, dansces régions, on utilise des cultivars de blé similaires. Selon les données obtenues avec les marqueurs moléculaires, les populations du Centre,du Centre-Terres noires et de l’Oural forment un groupe distinct de celles du Nord-Ouest, du nord du Caucase et de l’ouest de la Sibérie.
Mots clés: logiciel VAT, marqueurs moléculaires, rouille brune du blé, virulence
Wheat leaf rust, caused by Puccinia triticina Eriks., isan important disease which affects production in manyagroclimatic regions of the Russian Federation. The majorgrain production in Russia (about 75% of the grain-growing area) is concentrated in the North Caucasian,Central Black Earth, Central, Volga, Ural and Volga-Vyatka regions (Fig. 1). During the last 20 years, severeepidemics in the North Caucasian region were reportedfrom 2 to 3 times within a decade and resulted in yieldlosses of 30–35%. In the Central and Volga regions, epi-demics were registered from 5 to 7 times in a decadewith estimated losses of 20–30%. In the Central BlackEarth region, epiphytotics have occurred in up to 4 yearsout of 10, causing crop losses of 15–20%. In the Volgo-Vyatka and Ural regions, severe disease development wasobserved every two years, and crop losses were estimatedat 15–20% (Sanin et al., 2004).
Annual virulence surveys of P. triticina in differentregions of Russia and the former USSR were con-ducted by the All Russian Institute of Plant Protection(St. Petersburg) since 1980. Differentiation among theCaucasian, European, and West Siberian populations wasestablished on the basis of virulence analysis on the localdifferential set of two ‘Thatcher’ lines (Lr1 and Lr2a)and seven cultivars. The West Asian population differsfrom the European one, while typical ‘European’ and‘Asian’ phenotypes were observed in the Volga region(Mikhailova, 1996; Mikhailova & Gultyaeva, 1997). The‘Thatcher’ near-isogenic lines as differentials and the
Fig. 1. Map of Russian agroecological regions. NW – Northwestern, NC – North Caucasian, CBE – Central Black Earth, C – Central, LV -Low Volga, U – Ural, WS – West Siberian, MV – Middle Volga, VV – Volgo-Vyatka.
North-American nomenclature for encoding virulencephenotypes (Long & Kolmer, 1989) have been used since2002 to characterize P. triticina races in Russia. Resultsobtained with the 16 ‘Thatcher’ differentials supported thefindings of Mikhailova (1996) concerning the structure ofRussian leaf rust population (Gultyaeva, 2007).
Variation in virulence of P. triticina might depend onselection pressure of resistance genes deployed in wheatcultivars. In contrast, molecular markers are generallyassumed to be neutral to host selection. Therefore, theymay provide more accurate tools for analysing geneticvariation of plant pathogens with gene-for-gene relation-ships within a host–pathogen system.
Analyses of genetic variability using molecular markersbegan in the mid 1990s and have provided new insight intothe population biology of P. triticina. The first studies onwheat leaf rust used random amplified polymorphic DNA(RAPD) markers (Kolmer et al., 1995) and amplifiedfragment length polymorphism (AFLP) markers (Kolmer,2001), which revealed distinct groups of P. triticina geno-types in Canada. Development of simple sequence repeat(SSR) DNA markers for P. triticina has greatly facilitatedand improved analysis of the population structure of thepathogen (Duan et al., 2003; Szabo & Kolmer, 2007).The neutral molecular markers (RAPD, AFLP, SSR) pro-vide stable instruments for differentiation among groupsof isolates of P. triticina (Ordoñez & Kolmer, 2009).Virulence and molecular markers were utilized to studywheat leaf rust in Western Europe (Park et al., 2000),North America and South America (Ordoñez et al., 2010),Central Asia and Caucasus (Kolmer & Ordoñez, 2007),
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Diversity of Puccinia triticina in Russia 215
Ethiopia (Mebrate et al., 2006) and Italy (Mantovani et al.,2010). Although wheat leaf rust has been characterizedwith molecular markers in many regions all over theworld, the current study is the first analysis of P. triticinain Russia using molecular markers (RAPDs).
The major objective of this study was to examine vir-ulence and molecular variability in isolate collectionsof P. triticina from the main wheat growing areas ofRussia. Virulence and molecular diversity within andamong regional populations of P. triticina in Russia wereanalysed on the basis of the leaf rust survey of 2007.
Materials and methods
P. triticina isolates
The annual 2007 survey of wheat leaf rust was con-ducted in the period of extensive spread of the fungusin the summer. Samples were taken from widely culti-vated commercial cultivars on regional plant protectionstations located in different agroclimatic zones (Fig. 1)and from susceptible cultivars grown in plant breedingnurseries. All samples consisted of several leaves withuredia. The leaves were air-dried and stored at 4 ◦C untilmultiplication and analysis. Multiplication of single ure-diniospore isolates for virulence tests and DNA extractionwas performed by the method of detached leaf seg-ments preserved in water–benzimidazol solution (40 mgL−1) (Mikhailova & Gultyaeva, 1997; Lind & Gultyaeva,2007). Individual pustules that developed on the leaf seg-ments were transferred by a sterile needle onto new leafsegments of the susceptible cultivar ‘Leningradka’. Theyare regarded to be single uredia progenies. The leaf seg-ments were incubated at 100% relative humidity and17–22 ◦C in darkness for 18 h, followed by 20 ◦C at18 h of light. Using the same procedure, progenies of pus-tules and single spores were multiplied on leaf segmentsand subsequently on isolated seedling plants to get neces-sary amount of spores for inoculation of wheat tester linesand DNA extraction for virulence and molecular markeranalyses, respectively.
Determination of virulence phenotypes
Infection types were assessed after 7 days of incubationusing a 0–4 scale (McIntosh et al., 1995). Isolates withinfection types 0–2 were assumed to be avirulent, whereasisolates with infection types 3–4 were considered to bevirulent.
Virulence of leaf rust isolates was determined on 24‘Thatcher’ near-isogenic lines, which were divided into
six ordered subsets of four differentials. The subsetsconsisted of lines with resistance genes Lr1, Lr2a, Lr2cand Lr3a; Lr9, Lr16, Lr24 and Lr26; Lr3ka, Lr11, Lr17and Lr30; LrB, Lr10, Lr14a and Lr18; Lr2b, Lr3bg, Lr14band Lr15; and Lr19, Lr20, Lr21 and Lr28. ‘Thatcher’ wasincluded as a susceptible control. Each isolate was given asix-letter race designation, adapted from the nomenclaturedeveloped by Long & Kolmer (1989). Each letter corre-sponds to a specific combination of low or high reactionon the four differentials from the corresponding set.
Determination of molecular genotypes
DNA was extracted according to Justesen et al. (2002)from 10 to 20 mg of fresh urediniospores of each isolate.Spores were ground by shaking with 20 mg of glass beads(G9268, Sigma) in a FastPrep24 shaker (MP Biomedicals,USA) for 50 s. PCR reactions were performed in aC1000TM Thermal Cycler (BioRad) programmed at 94 ◦Sfor 3 min; followed by 40 cycles of 30 s at 92 ◦S, 1 min at36 ◦S and 1 min at 72 ◦S. This was followed by 10 minat 72 ◦S for RAPD and 94 ◦S for 3 min; followed by30 cycles of 35 s at 92 ◦S, 70 s at 53 ◦S, and 30 s at72 ◦S, with a final 10 min at 72 ◦S for UP-PCR. Eachreaction comprised 2 µL 10× Tag polymerase reactionbuffer (Mg free), 1.2 µL of 25 mM MgCl2, for RAPD or1.6 µL for UP-PCR, 1.6 µL of a 2.5 mM stock of each ofdATP, dCTP, dGTP and dTTP, 0.2 µL of Taq polymerase(Dialat; 5 units µL−1), 2.0 µL of template DNA, 1 µL ofprimer (10 pM for RAPD and 20 pM for UP-PCR), and 12µL of sterile double-distilled water for RAPD or 11.6 forUP-PCR. Amplification products were separated by elec-trophoresis in 1.5% agarose gels prepared in 1× TBEbuffer and containing 0.5 µg mL−1 of ethidium bromide,for 2 to 3 h at 70V.
Twenty RAPD primers (402, 450, 489, 517, 521,531, 538, 556, 180.01, 270.01, 270.09, 280.02, 270.09,280.02, 360.04, 370.02, 370.09, 480.04, OPQ9 andOPR) previously used by Kolmer et al. (1995) andPark et al. (2000) were also utilized in the currentstudy. Arbitrary decamer primers were obtained fromthe Eurogen company (Moscow, http://www.evrogen.ru).Selection of polymorphic primers was performed with16 and 19 isolates from the North Western and LowVolga regions, respectively. In addition, five universalprimers (L45, 3–2, 15–19, AS15inv and AS4) relatedto the UP-PCR technique (Bulat et al., 1998) werealso included in molecular analysis. This technique useslonger primers, relatively higher annealing temperatures,and faster ramping in order to produce more repro-ducible band patterns. Only one UP-PCR primer AS4
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(TGTGGGCGCTCGACAC) and six RAPD primers(450 (CGGAGAGCCC), 490 (AGTCGACCTT), 538(TGACCTCTCC), 280.02 (CGACGCGTGC), 270.09(GCTCTCACCG) and 480.04 (CGCCACGAGC)) werechosen due to their polymorphism and ability to produceconsistent banding patterns with major band differencesbetween the isolates.
Data analysis
Descriptive analysis of populations with virulence andmolecular data included calculation of the followingparameters: virulence frequency on each differential line,phenotype/genotype frequencies, average virulence com-plexity (number of virulent reactions per isolate), simplerichness (SR, number of phenotypes/genotypes per iso-late), and evenness (E, Sheldon index). Pathogenicitydata for each isolate were converted to ‘1’ (virulent) or‘0’ (avirulent), and major reproducible RAPD and UP-PCR bands were scored as ‘1’ (present) or ‘0’ (absent).Dissimilarity between virulence patterns of isolates wasmeasured with the simple mismatch coefficient (m), whilefor the molecular data pairwise comparison of isolateswas made using the simple mismatch (m) and Jaccard (j)dissimilarities according to Kosman & Leonard (2005).
Diversity within and between regional collections ofisolates was assessed with three types of indices: geno-typic (Shannon normalized diversity and Rogers’ dis-tance, based on phenotype/genotype frequencies), gene(Nei’s diversity and distance, based on virulence/allelefrequencies), and genetic (Kosman’s diversity [KWm andKWj] and distance [KBm and KBj] with regard to thesimple mismatch (m) and Jaccard (j) dissimilarity, whichtake into account both the phenotype/genotype struc-ture of populations and measure of resemblance betweendifferent phenotypes/genotypes). Detailed description ofthe mentioned diversity and distance measures can befound in Kosman & Leonard (2007). All diversity anddistance parameters and their statistics based on boot-strapping across isolates (200 random samples of isolatesdrawn with replacement from the original collections)were calculated with the VAT software (Kosman et al.,2008).
The Mantel test (Mantel, 1967) was employed to mea-sure the degree of relationship (correlation) between anytwo relevant distance matrices. The genotypic, gene andgenetic distances between the wheat leaf rust popula-tions for each type of data, as well as genetic distances(KBm) obtained with the virulence and molecular mark-ers, were compared. The corresponding calculations wereperformed with the MXCOMP program of NTSYSpcpackage, version 2.1 (Exeter Software, Setauket, NY).
The UPGMA dendrograms for the wheat leaf rust pop-ulations with regard to the Rogers, Nei, and Kosman dis-tances between them were derived using the SAHN pro-gram of NTSYSpc package, version 2.1 (Exeter Software,Setauket, NY). For each dendrogram, the cophenetic cor-relation was calculated (COPH and MXCOMP programsof NTSYSpc) to test goodness of fit for clustering withdendrograms (assessment of matching the dendrogramstructure with the original distance matrix upon which theclustering was based).
Results
Populations of wheat leaf rust from seven agroecologicalregions of Russia (Fig. 1) were analysed for virulence andmolecular variability. In total, 417 single-uredinial iso-lates were tested. The number of isolates in the regionalcollections varied from 19 in the Low Volga area to 138 inthe Northwestern region (Table 1). Further reported differ-ences among diversities within or distances between pop-ulations were statistically significant (the bootstrap-basedstandard errors of all diversity and distance estimates didnot exceed 0.001).
Virulence study
There were 79 virulence phenotypes of P. triticina distin-guished on the set of 24 near-isogenic wheat differentiallines. The number of different virulence phenotypes inthe regional populations varied from four in the Volgacollection to 35 in the Northwestern region (Table 1).Fourteen phenotypes were detected in two or more regions(Table 2), while only one (THTTTJ) appeared in all sevenregions. THTTTJ was predominant everywhere exceptthe Central Black Earth region, with frequency rangingfrom 25% to 63%. The second most common phenotype(TGTTTJ) was found in six regions and was less fre-quent (2–35%) than THTTTJ, but was predominant in theCentral Black Earth region (Table 2). The average viru-lence complexity of isolates was high in all populations(Table 1). Phenotype richness of the North Caucasianpopulation was the highest (SR = 0.349), and the cor-responding phenotypes were the most evenly distributed(E = 0.803). The minimum richness and evenness wereestablished in the Low Volga (SR = 0.211) and Central(E = 0.635) regions, respectively.
The P. triticina isolates varied for virulence on genesLr1, Lr2a, Lr2b, Lr2s, Lr3, Lr3bg, Lr3ka, Lr14a, Lr14b,Lr15, Lr16, Lr17, Lr18, Lr19, Lr20, Lr21, Lr24, Lr26,Lr28 and LrB (Table 3). All isolates were virulent onlines with Lr10, Lr11 and Lr30. No virulence on Lr9 wasdetected. A few isolates were virulent on Lr24, Lr19 and
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Diversity of Puccinia triticina in Russia 217
Table 1. Descriptive parameters of Russian regional populations of P. triticina in 2007 obtained withvirulence phenotyping.
Populationsb
Parameter NW NC CBE C LV U WS
Number of isolates 138 43 40 48 19 84 44Number of pathotypes 35 15 11 14 4 24 14Number of pathotypes with at least
a Frequency of the predominant phenotype (%).b Region abbreviations: NW – Northwestern, NC – North Caucasian, CBE – Central Black Earth, C – Central,LV - Low Volga, U – Ural, WS – West Siberian.
Lr28, while the virulence frequency was usually very highon all other differentials. Relatively strong regional vari-ation in virulence frequency was observed on Lr1, Lr2a,Lr26, Lr15 and Lr20, whereas little variability in virulencewas found on all other differentials. The most variablevirulence reaction was detected on Lr26 with minimum(30%) in the Central Black Earth region and maximum(100%) in the Central region.
Rank order of diversity estimates within the regionalcollections of isolates was generally inconsistent for thegene (Nei), genotypic (Shannon normalized) and genetic(Kosman) diversity measures (data not shown). Therefore,Kosman’s diversity index (KWm) was used for compar-ison of the regions (Fig. 2). Virulence diversity withinthe Northwestern and North Caucasian regions was sig-nificantly higher (KWm = 0.122 and 0.110, respectively)
Table 2. Frequency of common virulence phenotypes of P. triticinain seven agroecological regions of Russia (%).
NW – Northwestern, NC – North Caucasian, CBE – Central Black Earth,C – Central, LV – Low Volga, U – Ural, WS – West Siberian.
than that within the Central, Central Black Earth, WestSiberian, Ural, and Low Volga regions (KWm = 0.069,0.066, 0.083, 0.074 and 0.035, respectively).
Comparison of different types of distances betweenthe regional collections of leaf rust with the Manteltest (Mantel, 1967) revealed low levels of relationshipsbetween them (correlations of the genetic KBm distancewith the genotypic and gene distances were 0.773 and0.461, respectively). This may explain the structural dif-ferences in the UPGMA dendrograms built with the cor-responding distance matrices (data not shown). Due to this
Table 3. Virulence frequency (%) within the Russian regionalpopulations of P. triticina in 2007.
NW – Northwestern, NC – North Caucasian, CBE – Central Black Earth,C – Central, LV – Low Volga, U – Ural, WS – West Siberian.
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Fig. 2. Virulence (a) and molecular (b) diversity within P. triticina populations from seven agroecological regions of Russia according to theKosman’s (KWm) diversity index. Region abbreviations: NW – Northwestern, NC – North Caucasian, CBE – Central Black Earth, C – Central,LV - Low Volga, U – Ural, WS – West Siberian.
discrepancy, analysis of the relationship between the pop-ulations was performed with KBm distance. Differencesbetween all populations were small (KBm values variedfrom 0.027 to 0.073), but statistically significant.
Confidence in results obtained for the regional collec-tion from Low Volga was low because a relatively smallnumber of isolates obtained from a single variety wastested in this region. Therefore, the Low Volga collectionwas not included in analysis of relationship among theregional populations of wheat leaf rust by UPGMA den-drograms for virulence and molecular data. The UPGMAdendrogram with regard to the genetic distance KBm(Fig. 3a) conveys nearly ‘actual’ relationships between thepopulations, because its degree of fit to the correspondingKBm distance matrix was very good (cophenetic corre-lation = 0.901). Thus, the North Caucasian and Centralcollections of P. triticina were the most distant from allthe other regional populations according to the virulencedata (Fig. 3a). The most similar were collections fromWestern Siberia and Ural, which together with the CentralBlack Earth region formed a group of closely related pop-ulations. The Northwestern population was closer to thisgroup than to the isolates from the Central and NorthCaucasian regions (Fig. 3a).
Molecular study
Six RAPD and one UP-PCR polymorphic primers wereselected to perform molecular markers analysis of P. trit-icina isolates. Five RAPD primers (450, 538, 280.02,
270.09 and 480.09) distinguished two polymorphic frag-ments each; another one (490) detected three fragments;and UP-PCR primer AS4 generated one polymorphiclocus. Altogether, 14 polymorphic binary loci with two‘alleles’ (0 and 1) were utilized to obtain profiles ofisolates with molecular markers.
There were 71 molecular genotypes distinguishedamong 417 P. triticina isolates. The number of differ-ent genotypes in the regional populations varied from11 to 37 in the North Caucasian and Northwestern col-lections, respectively (Table 4). About 50% of all thegenotypes found in each population (except the LowVolga region) were represented by two or more isolates.Frequencies of predominant genotypes varied from 10%to 53% in the Low Volga and North Caucasian popula-tions, respectively (Table 4). The genotype richness in theLow Volga region was the highest (SR = 0.842; Table 4),and the corresponding genotypes were the most evenlydistributed (E = 0.983). The minimum richness andevenness were established in the Ural (SR = 0.250) andNorth Caucasian (E = 0.694) populations, respectively(Table 4).
Only one molecular genotype was detected in all thecollections, with frequencies ranging from 5% in theCentral Black Earth and Volga regions to 54% in the NorthCaucasian region. Common leaf rust genotypes were iden-tified in different regions (Table 5) – the Northwestern andNorth Caucasian regions shared 11 genotypes (maximumvalue), while only two genotypes (minimum) were sharedby the Low Volga and West Siberian regions.
Fig. 3. UPGMA dendrograms of the Russian regional populations of P. triticina based on virulence (a) and molecular (b) markers data withregard to the Kosman’s (KBm) genetic distance. Region abbreviations: NW – Northwestern, NC – North Caucasian, CBE – Central Black Earth,C – Central, U – Ural, WS – West Siberian.
Table 4. Descriptive parameters of Russian regional populations ofP. triticina in 2007 obtained with molecular markers.
Parameter Populationsb
NW NC CBE C LV U WS
Number of isolates 138 43 40 48 19 84 44Number of genotypes 37 11 13 14 16 21 12Number of genotypes
a Frequency of the predominant genotype (%).b Region abbreviations: NW – Northwestern, NC – North Caucasian,CBE – Central Black Earth, C – Central, LV – Low Volga, U – Ural, WS –West Siberian.
Qualitatively different estimates of molecular diversitywithin the populations were obtained with the gene (Nei),genotypic (Shannon normalized) and genetic (Kosman)
Table 5. Number of common molecular genotypes of P. triticina inRussian regional populations.
Region abbreviations: NW – Northwestern, NC – North Caucasian, CBE –Central Black Earth, C – Central, LV – Low Volga, U – Ural, WS – WestSiberian.
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diversity measures (data not shown). Since KWm and KWjindices ranked the populations identically (KWj data notshown) and their values were strongly correlated, we fur-ther refer only to the KWm genetic diversity measure(Fig. 2). Molecular diversity within the Low Volga pop-ulation of P. triticina was considerably higher (KWm =0.308) than that within all other regions, while the low-est molecular diversity was within the North Caucasiancollection (KWm = 0.080).
Comparison of different types of distances betweenthe regional collections of P. triticina with the Manteltest (Mantel, 1967) established rather good correspon-dence between them. The genetic distances KBm and KBjwere very strongly correlated (0.998), while the correla-tions of the genetic KBm distance with the genotypic andgene distances were 0.926 and 0.830, respectively. Thismay explain the qualitative identity of topology of theUPGMA dendrograms based on the corresponding dis-tance matrices (data not shown). Thus, only the UPGMAdendrogram with regard to the genetic distance KBm ispresented in Fig. 3b to describe relationships between theregional leaf rust populations derived from the molecu-lar marker data. This dendrogram conveys nearly ‘actual’relationships between the populations because its degreeof fit to the corresponding KBm distance matrix was verygood (cophenetic correlation = 0.917). The differencesbetween all populations measured with the KBm distancewere statistically significant. The most similar were col-lections from North Caucasus and Western Siberia, whichtogether with the Northwestern one formed a group ofclosely related populations of P. triticina. Another groupconsisted of the Central, Ural, and Central Black Earthpopulations (Fig. 3b).
No association was found between the virulence dataand the molecular data. A negative correlation (−0.213;Mantel test) was ascertained between the KBm distancesamong populations for virulence and molecular markers.Relationships between the leaf rust regional collections,as expressed by the corresponding UPGMA dendrograms(Fig. 3), were also inconsistent.
Discussion
Virulence analysis of the Russian leaf rust populationsrevealed low differentiating ability when using the inter-national set of differentials. Isolates from all populationswere virulent on about 19 differentials on average. Theextremely high frequencies of virulence to most resistancegenes tested (Lr2b, Lr2c, Lr3a, Lr3bg, Lr3ka, Lr10, Lr11,Lr14a, Lr14b, Lr16, Lr17, Lr18, Lr21, Lr30 and LrB)could be explained by the wide distribution of these genesin Russian commercial wheat varieties for a long time,
which makes the differential lines inefficient for virulenceanalysis of Russian P. triticina populations. According toMcIntosh et al. (1995), about 26 genes had been identifiedin wheat germplasm from 1946 to 1980 and most of themwere utilized by Russian wheat breeders. Zhemchuzhinaet al. (1992) found 11 Lr-genes (Lr1, Lr2b, Lr2c, Lr3a,Lr10, Lr14a, Lr16, Lr17, Lr20, Lr23, Lr26) in 47 of60 wheat varieties released in the North Caucuses before1990. Some of the most successful winter wheat vari-eties with ineffective genes have been widely utilized inmodern breeding in Russia. These include ‘Mironovskaya808’, ‘Tarasovskaya 29’, ‘Bezostaya 1’ and ‘Skorospelka3’ (Lr3a); ‘Zernogradka 6’, ‘Zernogradka 31’ and‘Krasnodarskaya 70’ (Lr2b, Lr17); ‘Labinka’ and‘Odesskaya krasnokolosaya’ (Lr14a); ‘Obriy’, ‘Zirka’and ‘Olviya’ (Lr17 Lr23); and ‘Albatros odesskiy’ (Lr30)(Zhemchuzhina et al., 1992). A limited number of molec-ular markers are known for identification of Lr genes,thus the estimation of actual distribution of Lr genes inRussian varieties is unknown. Distribution of the inef-fective Lr10 and Lr26 genes in modern Russian varieties(above 30% and 15% of varieties, respectively) was estab-lished by Gultyaeva et al. (2009). High frequencies ofvirulence to some Lr genes also may be the ‘hitchhiking’phenomenon, when unnecessary virulence is present. Forinstance, the presence of Lr21 was not found in Russianvarieties with molecular markers (Gultyaeva et al., 2009),but virulence to Lr21 was high in 2007 and in previousyears (Lind & Gultyaeva, 2007). Finally, it is possiblethat erroneous virulence assessments occurred, due to thelimited reliability of the detached leaf method for sev-eral Lr genes (Felsenstein et al., 1998). However, weakeffectiveness of most seedling Lr genes in Russian regionsin 2006–2008 was also reported by Zhemchuzhina &Kurkova (2010).
Only five differentials (Lr1, Lr2a, Lr15, Lr20 andLr26) provided variable patterns of virulence frequency(30–100%) across the regional populations. Virulence toLr26 was the most variable among the regional popula-tions in 2007. Long-term analysis of Russian populationsrevealed fluctuations in virulence (Lind & Gultyaeva,2007) that might be caused by broad range of cultivationof varieties with Lr26 gene and their uneven proportionin the regions in different years. The increase in the fre-quency of virulence to Lr1 during the last decade is likelydue to the massive cultivation of wheat varieties with Lr1gene (e.g. ‘Moskovskaya 35’, ‘Deya’, ‘TAU’) (Gultyaevaet al., 2009). Cultivars with Lr9 and Lr19 were introducedinto Russia in the late 1980s and early 1990s, respec-tively. Lr9 is still effective, while Lr19 is effective in theCentral, North Caucasus and Northwestern regions wherecultivars with this gene are not grown. In the Volga region,
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Diversity of Puccinia triticina in Russia 221
resistance to Lr19 was defeated since the end of the 1990s(Sibikeev & Krupnov, 2007). In the current virulence sur-vey, we did not detect virulence to Lr19 in the Low Volgaregion probably because a relatively small number of iso-lates obtained from a single variety was tested in thisregion. Virulence to Lr24 was detected for the first timein Russia (the Central and Central Black Earth regions) inthe present survey.
Very high levels of virulence on Lr16, Lr18 and Lr21were established in Russia, compared with some otherregions of the world. Thus, virulence frequencies on thesegenes vary from very low in Canada and USA (McCallum& Seto-Goh, 2008; Kolmer et al., 2009) to much higherin Europe and Middle East (Manisterski et al., 2000;Mesterházy et al., 2000; McVey et al., 2004; Lind &Gultyaeva, 2007; Manninger, 2009; Hanzalová et al.,2010). There could be some differences in how the infec-tion types are interpreted in different regions. However,it seems that the Russian population of wheat leaf rust israther similar to the European populations, which are fun-damentally more virulent for Lr16, Lr18 and Lr21 genesthan the populations in North America.
The virulence pattern of wheat leaf rust in the NorthCaucasian region was the most distinct because of thelarge range of winter wheat cultivars grown there, theabundance of wild relatives of wheat, and the ability ofthe pathogen to survive during winter periods. Collectionsfrom Ural and West Siberia regions were closely related,which may be due to the genetically similar wheatcultivars with a uniform set of resistance genes grownin these regions. These populations of P. triticina differfrom the Central and North Western regions, where pos-sible migration of the rust spores from the neighbouringEuropean countries may affect the pathogen populationcomposition.
Genetic distances, based on virulence data, betweenthe regional collections of P. triticina in Russia werevery small (though statistically significant) despite theconsiderable geographic distances between the regions(many hundreds or even thousands of kilometres). Theserelationships among the populations may be explainedby the wheat cultivars that have similar compositionsof resistance genes, by the variable wind direction inthe European and West Siberian parts of Russia, andby the absence of geographical barriers (except the UralMountains). Relative uniformity of the Russian popula-tion of P. triticina is in contrast to the general structureof wheat leaf rust populations in the USA. Although geo-graphical distances among the Russian regions and amongseven areas of the USA are comparable, populations ofP. triticina in USA were much more distant from eachother (values of KBm varied from 0.06 to 0.390 in USA
[Table 5 in Kolmer et al., 2003] relative to 0.027–0.073 inRussia). Virulence diversities within the regions were alsomuch higher in the USA compared with Russia (see Fig. 2here and Table 4 in Kolmer et al., 2003).
The relationships among the regional collections ofP. triticina based on molecular marker data differed fromthat established with virulence data. The six popula-tions were separated into two distinct clusters, whichcould be characterized by specific molecular genotypes.One cluster included the Ural, Central Black Earth, andCentral regions (four specific RAPD genotypes, 9% oftotal 417 isolates tested), and the other one consisted ofNorthwestern, North Caucasian and West Siberian regions(three specific RAPD genotypes, 5% of total number ofisolates).
Estimates of diversity within the groups of P. tritic-ina isolates were inconsistent between virulence data andmolecular markers. The high virulence diversity withinthe Northwestern and North Caucasian populations wasprobably due to the sample collection, which was mainlyfrom breeding stations with a variable spectrum of resis-tance genes in the host plants. This would support theparadigm that the main driving force of virulence evolu-tion of wheat leaf rust in Russia is selection pressure fromresistance genes in the host plants. Existence of commonmolecular genotypes in geographically distant regionsmight result from long-distance migration of P. triticinaurediniospores in Russia. However, the molecular mark-ers used in this study did not allow for comprehensiveanalyses of the genetic variation.
No reliable region-specific combinations of virulenceand avirulence were detected in the Russian populations,unlike the results obtained in wheat leaf rust surveys inCanada and Europe (Kolmer et al., 1995; Park et al.,2000). In Europe, nearly all detected virulence phenotypescould be separated into two groups on the basis of viru-lence or avirulence to the genes Lr3a, Lr3bg, Lr3ka andLr30 (Park et al., 2000). However, this division was notso apparent using molecular marker (RAPD) data, indi-cating that phenotypes within the two groups may notbe as closely related as the virulence data would sug-gest. All Russian isolates were virulent on Lr30, andonly a few were avirulent on Lr3a, Lr3bg and Lr3ka.The latter isolates were sporadically detected in NorthCaucasian, Ural and West Siberian regions and just likethe European P. triticina populations, their moleculargenotypes were not identical. Moreover, the isolates avir-ulent on Lr3a, Lr3bg and Lr3ka shared three common,widely distributed molecular genotypes with many othervirulence phenotypes. This situation was contrary to thatreported in Canada, where two major geographically sep-arated groups of P. triticina had certain virulence and
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E. Gultyaeva et al. 222
molecular (RAPD and SSR) genotypes (Kolmer et al.,1995). One group consisted of virulence phenotypes thatwere either virulent or avirulent on both Lr2a and Lr2c,whereas phenotypes from the other group were aviru-lent on Lr2a and virulent on Lr2c (Kolmer et al., 1995).The majority of the Russian isolates were virulent onboth Lr2a and Lr2c, but 13% of the isolates from theNorthwestern and North Caucasian regions were avirulenton Lr2a and virulent on Lr2c. Molecular genotypes werenot unique for isolates from these groups, while some iso-lates from the different groups had identical molecularpatterns.
Methodological issues of data analysis in plant pathol-ogy require attention, because inferences from diversityanalysis of populations can be driven by techniques ofdiversity and distance assessments and not only by thedata. Commonly used measures of diversity within orbetween populations consider either phenotype (geno-type) frequencies (e.g. Shannon normalized diversityindex or Rogers’ distance) or virulence (allele) frequen-cies (e.g. Nei diversity or Nei gene distance). Kosman’sdiversity (KWm) and distance (KBm) measures are moresuitable for populations with an asexual or mixed modeof reproduction, because they take into account notonly the phenotype (genotype) frequencies but also thegenetic similarity between virulence or banding patternsof isolates (Kosman, 1996; Kosman & Leonard, 2007).Qualitative differences in diversity and distance assess-ments with the gene, genotypic and genetic measures,including discrepancy in topology of the correspondingUPGMA dendrograms, were reported here. Such disparitymay lead to false interpretations of relationship betweenpopulations. Therefore, a uniform diversity analysis is anessential condition for valid comparison of outcomes andinferences obtained in different studies.
Acknowledgements
The studies were conducted with financial support fromthe Russian Foundation for Basic Researches (GrantNo. 07-04-01455a). Collaboration between Russian andIsraeli researchers was initiated thanks to the travelgrant from Israeli Academy of Sciences and Humanities.We thank Prof. A. Dinoor (Hebrew University ofJerusalem) and anonymous reviewers for critical readingof the manuscript and helpful comments and suggestions.
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