New Insights Into the History of Domesticated and Wild Apricots and Its Contribution to Plum Pox Virus Resistance

Molecular Ecology (2016) doi: 10.1111/mec.13772

New insights into the history of domesticated and wild apricots and its contribution to Plum pox virus resistance

1 STEPHANE DECROOCQ,*† AMANDINE CORNILLE,‡ DAVID TRICON,*† SEVDA BABAYEVA,§ AURELIE CHAGUE,*† JEAN-PHILIPPE EYQUARD,*† RAUL KARYCHEV,¶ SVETLANA DOLGIKH,¶ TATIANA KOSTRITSYNA,**2 SHUO LIU,††*† WEISHENG LIU,†† WENJUAN GENG,‡‡ KANG LIAO,‡‡ BAYRAM M. ASMA,§§ ZEYNAL AKPAROV,§ TATIANA GIRAUD¶¶ and VERONIQUE DECROOCQ*† *UMR 1332 BFP, Equipe de virologie, INRA, 71 Avenue Edouard Bourlaux, 33882 Villenave d’Ornon, France, †UMR 1332 BFP, CS20032, Universite de Bordeaux, 33882 Villenave d’Ornon, France, ‡Department of Ecology and Genetics, Evolutionary Biology Centre, Science for life Laboratory, Uppsala University, Uppsala, Sweden, §Genetic Resources Institute of ANAS, Azadlig ave. 155, AZ1106 Baku, Azerbaijan, ¶Kazakh Research Institute of Horticulture and Viticulture, 238-a Gagarin Avenue, 480060 Almaty, Kazakhstan, **Botanical Garden of National Academy of Sciences, Akhunbaeva street 1a, 720064 Bishkek, Kyrgyzstan, ††Liaoning Institute of Pomology, Tiedong Street, Xiongyue Town, Bayuquan District, Yingkou City, Liaoning 115009, China, ‡‡ College of Horticulture & Forestry Sciences, Xinjiang Agricultural University, 311 NongDaDong Road, 830052 Urumqi City, Xinjiang, China, §§Department of Horticulture, Inonu University, Malatya 44210, Turkey, ¶¶Ecologie Systematique Evolution, Univ. Paris-Sud, CNRS, AgroParisTech, Universite Paris-Saclay, Orsay, France

Abstract Studying domesticated species and their wild relatives allows understanding of the mechanisms of population divergence and adaptation, and identifying valuable genetic resources. Apricot is an important fruit in the Northern hemisphere, where it is threat- ened by the Plum pox virus (PPV), causing the sharka disease. The histories of apricot domestication and of its resistance to sharka are however still poorly understood. We used 18 microsatellite markers to genotype a collection of 230 wild trees from Central Asia and 142 cultivated apricots as representatives of the worldwide cultivated apricot germplasm; we also performed experimental PPV inoculation tests. The genetic markers revealed highest levels of diversity in Central Asian and Chinese wild and cultivated apricots, conﬁrming an origin in this region. In cultivated apricots, Chinese accessions were differentiated from more Western accessions, while cultivated apricots were differentiated from wild apricots. An approximate Bayesian approach indicated that apricots likely underwent two independent domestication events, with bottlenecks, from the same wild population. Central Asian native apricots exhibited genetic subdivision and high frequency of resistance to sharka. Altogether, our results con- tribute to the understanding of the domestication history of cultivated apricot and point to valuable genetic diversity in the extant genetic resources of wild apricots.

Keywords: fruit tree, pathogen, population structure, Prunus armeniaca, virus, wild progenitor Received 28 February 2016; revision received 14 July 2016; accepted 25 July 2016

Introduction Correspondence: Veronique Decroocq, Fax: +33 557122384; Domestication is an evolutionary process by which E-mail: [email protected] and Tatiana Giraud, Fax: humans produce, from wild species, populations with +33 169154697; E-mail: [email protected] modiﬁed traits, by selecting individuals most suited to 1Present address: Center for Adaptation to a Changing Envi- cultivation and consumption (Gerbault et al. 2014). ronment, ETH Zurich,€ 8092 Zurich,€ Switzerland 2Present address: International School of Medicine, 1 f, Street Domestication often involves a loss of genetic diversity Intergelpo, 720054 Bishkek, Kyrgyzstan in crops relative to their wild progenitors (Glemin &

Bataillon 2009; Miller & Gross 2011). Many traits cultivated apricots in the Irano-Caucasian region (i.e. desired by breeders, such as resistances to major crop Iran, Iraq, Syria, Azerbaijan, Georgia, Armenia, eastern pest/diseases, may thus be lacking in the cultivated Anatolia in Turkey) and in Europe, respectively. Previ- germplasm while present in wild relatives, for example ous studies aiming at evaluating genetic diversity in mildew resistance in grape germplasm (Riaz et al. 2013). apricot focused either on cultivated European apricots A comprehensive analysis of the genetic and pheno- and a few samples from botanical collections (Romero typic diversity in both crop- and wild-related species et al. 2003; Zhebentyayeva et al. 2003, 2008; Maghuly can help to understand domestication history and to et al. 2005; Pedryc et al. 2009), or on Chinese apricots identify valuable genetic resources in wild populations (He et al. 2007; Yuan et al. 2007; Zhang et al. 2014). The for further crop breeding. present study aimed at elucidating the domestication Prunus armeniaca L. (also called Armeniaca vulgaris) history of the cultivated apricot and characterizing the (Lingdi & Bartholomew 2003) corresponds to both the genetic diversity and population structure of the domesticated apricot, cultivated worldwide, and wild remaining wild P. armeniaca populations in their natural populations, now only growing in Central Asia. Mid- habitat in Central Asia using more comprehensive col- twentieth-century studies based on morphological fea- lections. Our aim was to gain fundamental knowledge tures suggested that the domesticated apricot originated on a key evolutionary process, domestication, as well as from Asia about 5000 years ago, possibly with two suc- on sources of diversity in wild apricots, in particular cessive domestication events, one in western Central regarding resistance to diseases. Asia (Fergana valley, at the border of Uzbekistan, Tajik- One of the most devastating diseases on apricots is istan and Kyrgyzstan) and one in China (Vavilov 1951). the sharka disease, caused by a potyvirus, the Plum The apricot would have then been transferred to the Pox Virus (PPV hereafter), to which all European culti- Irano-Caucasian area, where it would have undergone vars are susceptible (Dosba et al. 1991), and that affects further improvement. These domestication events might more generally all stone fruit species (i.e. Prunus sp.). have been associated with bottlenecks (Bourguiba et al. The disease was first identified about one century ago, 2012). Later on, apricot was brought to Europe during in Bulgaria, on European plums (P. domestica) and Alexander the Great’s incursions in Asia (356–323 BC) described officially in 1933 (Atanasoff 1933). Mean- or via the Silk Roads (Janik 2005; Ugurtan Yilmaz & while, the virus spread on other Prunus species, apri- Gurcan 2012). More recently, it spread with the Spa- cot included (Atanasoff 1935). Trade activity, including niards from Europe to North America and the rest of the exchange of grafted plants, facilitated the rapid the world. Key features distinguish domesticated apri- spread of PPV across Europe (Rimbaud et al. 2015), cots from wild populations: leaf and fruit size, cold har- and more recently in America and Asia (EPPO 2014). diness and, to some extent, reproductive system. Part of In Central Asia, sharka was first detected only the Mediterranean cultivars are indeed self-compatible 10 years ago (Spiegel et al. 2004), with no indication of while wild trees are strictly self-incompatible (Halasz earlier occurrence of sharka in this region. Yet, the et al. 2007). Wild populations of P. armeniaca once resistance to sharka discovered in a few North Ameri- occurred on vast areas in Fergana Valley, Almaty region can apricot cultivars has been suggested to result from down to Pakistan and Afghanistan (Kostina 1946), but an introgression from Asian apricots (Zhebentyayeva they are now found within a much more restricted area et al. 2008; Pedryc et al. 2009). There may therefore be in Central Asia, on the slopes of the Tien Shan ranges, further sources of resistance to sharka in Asia. Previ- likely leading to a reduction in valuable apricot genetic ous studies pointed to one major locus responsible for resources (Dzhangaliev et al. 2003). resistance, PPVres (Lambert et al. 2007; Marandel et al. Studies based on germplasm acquisition trips in Cen- 2009; Pilarova et al. 2010; Dondini et al. 2011; Vera tral Asia by the Nikitsky Botanical Garden in Yalta Ruiz et al. 2011). Markers linked to this locus in the (Crimea) in the late 1950s distinguished two main eco- North American apricot cultivars have been developed geographic groups within locally cultivated and wild (Soriano et al. 2012; Decroocq et al. 2014). However, P. armeniaca, mainly based on fruit size: (i) a group in selection based exclusively on the PPVres locus was Central Asia (including the western Chinese province of not sufficient to unambiguously select PPV-resistant Xinjiang, Pakistan, Afghanistan and Northern India) apricot cultivars (Decroocq et al. 2014; Rubio et al. and (ii) a ‘Dzhungar-Zailig’ group (corresponding 2014), suggesting that recombination can occur mostly to the Dzhungarsky and Zailisky national parks between the markers and the resistance locus or that located in the Tien Shan, between Kazakhstan, Kyrgyzs- this locus is not sufficient by itself to determine resis- tan and the northern part of the Chinese province of tance to sharka. In fact, a second locus involved in Xinjiang) (Kostina 1969). In addition, two other ecogeo- resistance has been recently identified, MetaPPV1b graphic groups were described that corresponded to (Mariette et al. 2016).

Here, we investigated genetic diversity and spatial from breeding programmes; ancient local, possibly feral, population structure in cultivated and wild apricots as varieties correspond to isolated trees, along roads or in a basis to then infer the history of apricot domestication abandoned human settlements (such as the Turk former and assess its genetic variability in Asia, including settlements in the former Armenia/Kurdistan area, in regarding apricot sharka resistance. For these goals, we Turkey and Azerbaijan), in areas where no forest with collected a comprehensive collection of wild and culti- apricots is present. This collection included cultivated vated apricot trees from Central Asia and Caucasus, apricots from: (i) the putative primary domestication with also representatives of the main western European centre (Kazakhstan, China, Kyrgyzstan and Uzbekistan) and North American cultivated phylogroups (Bour- (n = 75, CULT03 to 10 and CULT13), (ii) the secondary guiba et al. 2012). This collection was genotyped using putative domestication centre (Azerbaijan, eastern Ana- 18 molecular markers, 15 being putatively neutral tolia in Turkey) (n = 37, CULT01 and CULT11), (iii) at (Bourguiba et al. 2012) and four being linked in culti- least one representative of each cultivated Mediter- vated apricots to the identified loci conferring resistance ranean/North American phylogroup (Bourguiba et al. to sharka (Soriano et al. 2012; Decroocq et al. 2014; Mari- 2012), that is ‘Bakour’, ‘Bergeron’, ‘Canino’, ‘Currot’, ette et al. 2016). We also experimentally tested the actual ‘Goldrich’, ‘Luizet’, ‘Moniqui’, ‘Stark Early Orange’, resistance to sharka using inoculations on a subset sam- ‘Stella’ (CULT02, n = 9), and (iv) Central Asian acces- ple of wild apricots. The purpose was to trace back the sions from Pakistan, Afghanistan and Turkmenistan geographic origin of resistance to sharka, check its link- (CULT12, n = 21). age with the identified resistance loci in apricot wild Additionally, a total of 230 ‘wild’ accessions were col- populations and assess the resistance variability in wild lected across 15 Central Asian natural sites, in moun- populations. tainous forests of Kazakhstan, Kyrgyzstan, Uzbekistan More specifically, our questions were as follows: (i) and western China between 2011 and 2014 (Table 1, To what extent are wild and cultivated apricots geneti- WILD01 to WILD15). This corresponds to the range of cally differentiated? (ii) Is there any population struc- distribution of the Dzungar-Zailig ecogeographic group ture within wild and cultivated apricot populations, as described by Kostina (1946). Leaf material was respectively? (iii) What is the most likely scenario of retrieved from adult trees; when this was not possible domestication: a single event, two independent events due to degradation of the collected leaves, collected from different wild populations, or two successive seeds were germinated and leaves were sampled on the events from the same wild population? (iv) Have bottle- resulting seedlings (one single seedling per mother necks been associated with apricot domestication? (v) plant) (Table S1, Supporting information). The latitude What is the frequency of the resistance to the sharka and longitude coordinates of the plant material were disease in wild apricots, and does this inform on PPV recorded (Fig. S1, Supporting information). origin? DNA extraction and molecular genotyping Material and methods Genomic DNA was extracted using a modified previously published protocol (Doyle & Doyle 1987). Each Sample collection apricot leaf sample (8–16 cm2) was grinded in 5 mL of The apricot collection in total included 372 individuals buffer 1 (0.2 M Tris–HCl pH8, 0.07 M EDTA, 2 M NaCl, with 142 cultivated and 230 wild accessions. Wild acces- 0.02 M Sodium metabisulfite). A total of 500 lL of the sions as referred hereafter were considered as ‘wild’ first extract was completed with 450 lL of buffer 2 (2% when sampled in natural forest mountains, and culti- HATMAB, 1.4 M NaCl, 0.02 M EDTA pH8, 0.1 M vated accessions were considered as samples of recent Tris–HCl pH 8) and incubated for 30 min at 65 °C. varieties, landraces, and ancient local, possibly feral, After Chloroform: IAA (isoamylic alcohol) extraction varieties. Wild apricot trees in Central Asia are usually and isopropanol precipitation, supplemented with 10 M growing, away from the cultivation areas, in mountain- ammonium acetate, DNA was resuspended in 200 lLof ous forests at an altitude ranging from 1500 to 2000 m 0.19 TE buffer (Tris–HCl/EDTA). high, together with the wild apple (Malus sieversii) and Microsatellite markers were amplified using previ- walnut trees. ously published multiplex PCR protocols (Bourguiba The 142 cultivated accessions had different origins: et al. 2012; Decroocq et al. 2014). We initially used 23 cultivars come from orchards or breeding germplasm of microsatellite loci distributed across the eight chromo- the INRA and the ARS-USDA national repositories somes (Table S2, Supporting information) and one SSLP (Tables 1 and S1, Supporting information); landraces (simple sequence length polymorphism) marker (ZP002) were collected in private gardens and do not originate (Decroocq et al. 2014). See details in Supporting

Table 1 List of apricot, cultivated and wild groups sampled in this study

† Code* Type of material Habitat Origin Site of collection Ecogeographic group

Breeding varieties, local and ancient cultivars and landraces Cult01_AZE Landraces Cultivated Azerbaijan Azerbaijan_landraces Irano-caucasian Cult02_EUR Cultivars Cultivated EU, USA Occidental_cultivars (EU, USA) European ‡ Cult03_CHN Local cultivars Cultivated China Xiongyue_apricot_repository Chinese Cult04_KAZ Landraces and wild Cultivated Kazakhstan Almaty_Pomological_garden Dzhungar-Zailig Cult05_KAZ Landraces Semi-wild Kazakhstan Ak-Kain Dzhungar-Zailig ‡ Cult06_KAZ Landraces/local cultivars Cultivated Kazakhstan Chymkent_Dendro_Park Central Asian Cult07_KAZ Landraces Semi-wild Kazakhstan Sayram Dzhungar-Zailig Cult08_KAZ Landraces Semi-wild Kazakhstan Wine_yard_irrigation_canal Dzhungar-Zailig Cult09_KAZ Landraces and cultivars Cultivated Kazakhstan Almaty_market Dzhungar-Zailig Cult10_UZB Landraces Cultivated Uzbekistan Boukhara Central Asian Cult11_TUR Landraces Cultivated Turkey Eastern_Anatolian_landraces Irano-caucasian Cult12_PAK Local cultivars Cultivated Pakistan Pakistan_landraces Central Asian Cult13_KGZ Landraces Cultivated Kyrgyzstan Arslan_Bob Central Asian P. armeniaca natural populations Wild01_CHN Wild Montane forest China Ily_valley Dzhungar-Zailig Wild02_KAZ Wild Montane forest Kazakhstan Belbulak_Canyon Dzhungar-Zailig Wild03_KAZ Wild Montane forest Kazakhstan Esik_Lake Dzhungar-Zailig Wild04_KAZ Wild Montane forest Kazakhstan Medeu_valley Dzhungar-Zailig Wild05_KAZ Wild Montane forest Kazakhstan Turgen_Valley Dzhungar-Zailig Wild06_KAZ Wild Montane forest Kazakhstan Kaskelen_Canyon Dzhungar-Zailig Wild07_KAZ Wild Montane forest Kazakhstan Big_Almaty_Lake Dzhungar-Zailig Wild08_KAZ Wild Montane forest Kazakhstan Aksu_Zhabagyly_National_Park Dzhungar-Zailig Wild09_UZB Wild Montane forest Uzbekistan Chimgan_Beldersay Central Asian Wild10_KGZ Wild Montane forest Kyrgyzstan Issyk_Kul_Urukty_river Dzhungar-Zailig Wild11_KGZ Wild Montane forest Kyrgyzstan Issyk_Kul_Anan’Yevo_village Dzhungar-Zailig Wild12_KGZ Wild Montane forest Kyrgyzstan Issyk_Kul_Orto_Byrosun_river Dzhungar-Zailig Wild13_KGZ Wild Montane forest Kyrgyzstan Chuy_River_/_Boom_canyon Dzhungar-Zailig Wild14_KGZ Wild Montane forest Kyrgyzstan Ala_Archa_National_Park Dzhungar-Zailig Wild15_KGZ Wild Montane forest Kyrgyzstan Sary_Chelek_National_Park Central Asian

*Cult# refers to geographic groups of apricot landraces and cultivars, followed by country codes; Wild# refers to natural populations sampled in Kazakhstan (KAZ), China (CHN), Uzbekistan (UZB) and Kyrgyzstan (KGZ). † In semi-wild are included landraces or local, ancient selections. They can also correspond to feral wild apricot trees. ‡ The CULT03_CHN group is a repository of apricot accessions collected all over eastern and western China. Chinese provinces where apricots were collected are displayed in Table S1 (Supporting information). Similarly, CULT06_KAZ includes samples from Dzhun- gar-Zailig and old, local varieties from the Central Asian ecogeographic group (Tajikistan, Uzbekistan, etc.) which were collected in Soviet times. The ecogeographic groups correspond to the classiﬁcation of Kostina (1969).

information online. Alleles were scored with the Neighbor-Joining tree constructed using simple match- â GeneMapper software (Applied Biosystem). ing dissimilarity indices of Jaccard’s coefﬁcient method and bootstrap values over 2000 replicates as implemented in the DARWIN software package v6.0.010 (Perrier Genetic variation and differentiation & Jacquemoud-Collet 2006). Among-population FST and

The observed heterozygosity (H0), the unbiased Nei’s indices were estimated using ARLEQUIN v3.5 (Excof- expected heterozygosity (HE) and the inbreeding coeffi- fier & Lischer 2010). The significance of FST was cient FIS were calculated using SPAGEDI 1.3 (Hardy & assessed by random resampling of the genotypic data Vekemans 2002) and verified with GENETIX v4.05 (Belkhir through 1000 permutations. Jost’s D estimates among et al. 2004). Allelic richness (AR) and private allelic rich- populations (Jost 2008) were computed using GENALEX ness (APR) were computed with ADZE software to adjust (Peakall & Smouse 2012), and their significance was for sample size differences (Szpiech et al. 2008). established by bootstrapping over 1000 replicates. Mean We further explored the genetic differentiation and differences between Jost’s D values were tested using relationships among samples using an unweighted Student’s t-tests with JMP V.7.0 (SAS Institute).

Within the wild apricot sampling (n = 260 individu- Sharka resistance phenotyping als), we tested for an isolation-by-distance pattern using Fifty wild apricots were chosen at random in our sam- a Mantel’s test, as implemented in SPAGEDI (http:// ple for resistance phenotyping, using both visual ebe.ulb.ac.be/ebe/SPAGeDi.html) with 10 000 permuta- inspection of symptoms and ELISA measure of virus tions (Rousset 2008). load. Stems were collected from 2-year-old apricot seedlings and buds were grafted onto 6-month-old GF305 Population structure peach rootstocks. Five plants were grafted per sample, of which four were inoculated. The rootstocks were Representation of the genetic relationships among beforehand inoculated by chip-budding using bark individuals was explored with a factorial correspon- pieces from PPV-M20-infected peach tree showing typi- dence analysis (FCA) performed with GENETIX v4.05 cal symptoms of sharka. Once the scion started grow- (Belkhir et al. 2004). We also used the individual- ing, both the rootstock and the scion were pruned and based Bayesian clustering method implemented in the plants were placed in the cold chamber at 5 °C for STRUCTURE 2.3.3 (Pritchard et al. 2000) to investigate at least 3 months. Plants without sharka symptoms on = population subdivision. We ran STRUCTURE from K 2 the shoots growing from the chip-buds or rootstocks, = to K 10 using admixture and correlated allele fre- and with a negative ELISA reaction (enzyme-linked quencies assuming no prior information. Burn-in and immunosorbent assay) for both the inoculum (infected number of Markov chain Monte Carlo iterations were chip-bud as described above) and rootstock, were elimi- set to 10 000 and 100 000, respectively. Ten indepen- nated from the final scoring, as they represented failed dent runs were carried out for each K, and outputs inoculation treatments. were processed with CLUMPP V1.1.2 (Jakobsson & Responses of the grafted scions to PPV infection were Rosenberg 2007). STRUCTURE barplots were displayed scored for at least two vegetative cycles, starting from using DISTRUCT 1.1 (Rosenberg 2004). For all these anal- the first bud burst after the initial cold treatment. One yses, the markers linked to sharka resistance were vegetative cycle corresponds to a combination of D removed. We examined the distribution of K, plotted 3 months of dormancy in the cold chamber followed by with STRUCTURE harvester (http://taylor0.biol- 4 months of vegetative growth in the greenhouse. ogy.ucla.edu/structureHarvester/). Symptoms of sharka were visually evaluated on apricot leaves of the rootstocks, the scions and the inoculums if the chip-buds were still growing. ELISAs were per- Approximate bayesian computation formed to check the presence of the virus in leaves of We used ABCTOOLBOX (Wegmann et al. 2010) with fast- the scions tested for susceptibility to sharka. Two scor- simcoal 2.5 to compare domestication scenarios. See ings, 3 weeks apart, were performed per vegetative details in Supporting information online. cycle, including symptom observations and ELISA detection of the virus. After each 4-month growth period in the high-confinement greenhouse, plants were Frequency of resistance to sharka placed back in the cold chamber for 3 months to overgo Two loci have been identified as conferring resistance bud dormancy. Pruning was performed at the begin- to sharka so far, PPVres (Soriano et al. 2012) and ning of each growth period to induce vigorous new MetaPPV1b (Mariette et al. 2016), and markers linked to shoots used for symptom scoring. these loci in cultivated apricots have been identified. Viral accumulation was estimated for each individual We screened these markers in our sample to check plant from double antibody sandwich ELISAs. Optical whether they were also linked to resistance in wild densities (OD) were normalized using PPV-M20- apricots. PGS 1.21 and PGS 1.24 were used as markers, infected, ‘GF305’ indicator plants used as a positive being microsatellite loci flanking the PPVres resistance controls on each ELISA plate that was set at 100. Two locus, with alleles specific to resistance in cultivated serological assays were carried out per vegetative cycle, apricots (Soriano et al. 2012), although they are ~141 kb at 4-week interval, and the first test was performed distant from PPVres. We also used the SSLP marker 3 weeks after bud burst. The final viral accumulation ZP002, designed within the best candidate gene for the value (ACC) is the average of normalized measure- PPVres locus (Zuriaga et al. 2013; Decroocq et al. 2014). ments from all PPV-infected replicates of each apricot In addition, we developed a new marker, genotype, over two vegetative cycles. Analyses of the SSRLG1_11 m52, designed within the second locus phenotypic data were performed under R v2.15.0 involved in PPV resistance, MetaPPV1b (Mariette et al. (http://www.R-project.org). Both visual inspection and 2016). serological tests were used for phenotypic scoring and

– for assessing which plants were resistant, partially resis- (named W1 W5). Many wild trees showed footprints of tant or susceptible. Because PPV is a quarantine patho- admixture between the W1, W2 and W4 clusters, while gen and every infected plant has to be eradicated, little admixture was found among the other clusters regardless of symptom expression, we considered as (Fig. 1A, Table S3, Supporting information). We used valuable genitors for resistance breeding only the indi- STRUCTURE membership coefficients inferred at K=9to viduals with no viral particle detected by serological define the populations used in subsequent analyses. For tests (normalized OD ≤ negative control). analyses hereafter, genotypes were assigned to a given population if their membership coefficient for that population were ≥0.80 (Table S3, Supporting information; Results n = 196 individuals, excluding admixed genotypes). Within cultivated apricots, a west–east geographic Genetic variability and population differentiation differentiation was found across Eurasia. Q included among cultivated and wild apricots 1 essentially individuals from Europe, Turkey and Azer- After having filtered out markers that were linked one baijan (CULT02_EUR, CULT11_TUR and CUL- to each other or deviated from neutrality, and individu- T01_AZE), while cultivated apricots from China als that were likely clonemates or siblings (see Support- (CULT03_CHN) split into two clusters, Q2 and Q3, the ing information), 15 microsatellites markers and 372 later also including genotypes from southern Central apricots, including 230 wild and 142 cultivated trees, Asia (CULT12_PAK from Pakistan, Turkmenistan, were retained for analyses of genetic diversity and pop- Afghanistan). Q1 would thus correspond to the Irano- ulation structure (Tables S1 and S2, Supporting infor- Caucasian ecogeographic group previously defined mation). The apricot sample geographic distribution is (Kostina 1969). Q4 only included cultivated apricot trees depicted in Fig. S1 (Supporting information). The 372 from the Almaty Kazakh region that geographically apricot genotypes displayed from six to 22 alleles per overlaps with the Kostina’s Dzhungar-Zailig ecogeo- marker, and the allelic richness ranged from 2.48 to 3.55 graphic group. Some individuals appeared as hybrids (Table S2, Supporting information). The average between wild and cultivated apricots; they mainly observed and expected heterozygosities across markers belonged to CULT05_KAZ to CULT07_KAZ. They were = – – = were H0 0.72 (min max: 0.57 0.81) and HE 0.84 initially classified as ‘cultivated’ (Tables 1 and S1, Sup- (min–max: 0.66–0.92), respectively (Table S2, Supporting porting information) because they had been obviously information). planted by humans, in germplasm repositories or along The change rate in the log-likelihood between succes- roads. Furthermore, STRUCTURE assignment suggests that sive K values (DK) inferred with STRUCTURE revealed some recent Central Asian collections (i.e. CULT04_- three peaks at K=2, K = 5 and K = 9, respectively KAZ) and plantations of cultivars in fact correspond to < (Fig. S2A, B, Supporting information). For K 9, some wild genepools, being assigned to W2 with the wild clusters appeared admixed, while they appeared nonad- accessions from Kazakhstan. mixed and well-delimited at K=9 (e.g. the blue Q3 Regarding the wild genetic clusters, two main clus- cluster and the pink W4 cluster at K=9, Fig. 1A). Fur- ters, W3 and W5, clearly separated from the other wild ther increasing K above 9 did not reveal well-delimited clusters already from K=5; W3 is located in Kaza- = new cluster. This altogether suggested that K 9 corre- khstan (Wild03_KAZ, Esik Lake) and W5 in Kyrgyzstan sponded to the most relevant K value for our sampling. (Wild15_KGZ, Sary-Chelek national park). At K=9, the At K=9 (Fig. 1A), the cultivated apricots split into four remaining wild individuals formed three additional – distinct clusters (named Q1 Q4) and the wild apricots genetic clusters, although showing high levels of admix- formed five clusters, distinct from the cultivated ones ture. W1 and W2 mostly corresponded to Kazakh

Fig. 1 Population structure analysis of the cultivated and wild apricots inferred using the model-based program STRUCTURE from K=2toK=9. (A) Proportions of ancestry of cultivated and wild Prunus armeniaca accessions (n = 372) inferred with STRUCTURE for K=2, K=3, K=5, K=7 and K=9. Each individual is represented by a vertical bar, partitioned into coloured segments in proportion of the estimated membership in the different genetic clusters inferred with STRUCTURE. Above the figure are depicted the names of the cultivated and wild apricot sample locations as described in Table 1. The two stars (*) point to the two admixed North Ameri- can, PPV-resistant cultivars, ‘SEO’ and ‘Stella’. (B) Neighbor-Joining dendrogram based on DICE dissimilarity indices showing the relationships among the nonadmixed 196 apricot individuals (i.e. individuals assigned to one cluster at K=9 with a membership > – – coefficient 0.80). Genotypes were coloured according to their assignment to the different genetic clusters Q1 Q4 and W1 W5,as inferred by STRUCTURE. Branch length is proportional to the distance between nodes. (C) Microsatellite distance-based Neighbor-Joining (NJ) trees on apricot populations defined according to STRUCTURE inferences. The left- and right-rooted NJ trees were based on shared allele distance DSA (Chakraborty & Jin 1993) or Nei’s DA distance (Nei et al. 1983) and were computed as described in Vercken et al. (2010). The bootstrap values above 40% are shown.

Fig. 2 Spatial population genetic structure of Prunus armeniaca natural populations (n = 230) inferred by STRUCTURE. (A) Bayesian clustering results obtained with STRUCTURE at K=5. Above the ﬁgure are depicted the names of the wild apricot populations as described in Table 1. Each individual is represented by a vertical bar, divided into K segments represent- ing the amount of ancestry in its genotype corresponding to K clusters. (B) Graphical representation of the sampling area in Central Asia. (C) Visualization of the geographic distribution of the clusters for K=5.

apricot natural populations and W4 to wild germplasm Genetic variation and differentiation among the nine present in North Kyrgyzstan, around the Issyk-Kol apricot populations Lake. Altogether, these ﬁve wild clusters cover the range of distribution of the Dzhungar-Zailig ecogeo- We built a Neighbor-Joining tree of the nonadmixed graphic group (Kostina 1946). Figure 2A shows the dis- individuals (Table S3, Supporting information) based on tribution of the wild populations based on more dissimilarity scores (Fig. 1B). The dendrogram showed – detailed analyses (Supporting information). While W1 three major clades (labelled 1 3 in Fig. 1B). The Q1 and

(yellow) and W2 (orange) are spread across the Tien Q2 populations formed the ﬁrst clade, including Irano- Shan Mountains, the W4 (pink) formed a narrow spatial Caucasian, European and part of the Chinese cultivated cluster restricted to the eastern part of the distribution, apricot trees. The second clade included the wild popu- and the W3 (green) cluster corresponds to a single col- lations (number 2 in Fig. 1B, W1 to W4), plus a fraction lection site, Wild03_KAZ. The Wild15_KGZ natural of the Q4 population from the Almaty Kazakh region. population (W5, red) appears geographically isolated The wild cluster W5 (Kyrgyzstan) was part of the – and genetically highly differentiated from the other remaining Chinese and Central Asian cultivars (Q2 Q4) genetic clusters. No isolation-by-distance pattern was in the third clade. Further structure of the dendrogram found in wild apricots (r2 = 0.06, P = 0.35, Table S4, was also in agreement with the clustering inferred with

Supporting information). STRUCTURE, with the exception of Q2 and Q4, that each

split into two distinct clades. Dendrograms of popula- Pairwise FST and Jost’s D among the nine apricot tions (Fig. 1C) provided similar patterns of relationships populations were all signiﬁcant (Table 3, Fig. S3, Sup- – among groups, with Q1 and Q2 on one side and W1 W4 porting information) and in agreement with the struc- on the other side. ture found in previous analyses. They indicated a

The FCA (Fig. 3) revealed a similar pattern as strong differentiation between the Q1 population (Euro- inferred with STRUCTURE, with a clear differentiation pean and Irano-Caucasian cultivated apricots) and all between eastern and western cultivated apricots. other populations. The W5 population showed strong

Indeed, part of the Chinese cultivars (Q2 cluster) was differentiation from the other wild or cultivated popula- plotted on the top left (green triangles in Fig. 3), apart tions. Differentiation among the other wild populations – from the Irano-Caucasian and European/North Ameri- (W1 W4, corresponding to the Dzhungar-Zailig ecogeo- can apricots, which clustered together on the top right graphic group) was low. Jost’s D values further con- (grey triangles, equivalent to the Q1 cluster). In the firmed the strong differentiation between cultivated and – FCA, all Dzhungar-Zailig wild apricots (W1 W4) clus- wild populations (Table 3), with significantly lower tered together, except for the Sary-Chelek population mean Jost’s D among W populations (mean D = 0.35) = (W5 population, red points), that here again clearly sep- than between Q and W populations (mean D 0.45; arated from all other apricot populations. Student’s t-test, t = 15.07; P = 0.045). The mean D We computed population genetic statistics for the nine between Q populations was intermediate (mean genetic populations (Table 2). The inbreeding coefficients D = 0.040) and not significantly different from either W- > (FIS) were all low, indicating outcrossing and lack of fur- W or Q-W means (Student’s t-tests, P 0.05). ther strong population subdivision. High genetic diver- = Æ sity was found in the cultivated (HE 0.81 standard = = Æ = Testing domestication scenarios error SE 0.09) and wild (HE 0.80 SE 0.09) populations. Genetic diversity was similar across populations, We used an ABC approach for testing different domes- except for Q2 that showed higher values of allelic rich- tication scenarios. The populations simulated in our = Æ = ness (AR 8.22 SE 0.46) and private allelic richness models were defined based on STRUCTURE inferences at = Æ = = (APR 1.39 SE 0.27) than the other populations. K 9, excluding admixed accessions (CULT04 to

Among the wild populations, APR was higher in the W5 CULT07, Fig. 1). We also pooled some populations to = Æ = population (APR 0.39 SE 0.16) than in the other limit the number and complexity of scenarios. For the – populations. cultivated apricots, we pooled the Q2 Q4 populations

Fig. 3 Principal component analysis of the whole apricot data set based on 15 microsatellite markers. Triangles indicate cultivated apricot accessions such as depicted in Table 1, and circles wild apricots collected in natural populations. Axes 1, 2 and 3 explain 20.5%, 8.1% and 9.9% of the total variance, respectively. The right and left legends are depicting the names of the cultivated and wild apricot sample locations as described in

Table 1. (i) refers to the Q1 Irano-Cauca- sian and European cultivated apricots,

(ii) to the Chinese (Q2) cultivars and landraces; (iii) to the wild Central Asian apricot populations (corresponding – roughly to W1 W4) and (iv) to the Sary- Chelek (W5) natural population.

Table 2 Summary statistics of genetic variation among the nine Prunus armeniaca populations detected with STRUCTURE

Group Sample size H0 uHE FIS AR APR

Q1 48 0.652 (0.033) 0.716 (0.035) 0.077 5.15 (0.32) 0.38 (0.17) Q2 10 0.732 (0.043) 0.827 (0.030) 0.067 8.22 (0.46) 1.39 (0.27) Q3 16 0.683 (0.027) 0.771 (0.022) 0.083 5.86 (0.31) 0.33 (0.10) À Q4 13 0.754 (0.034) 0.788 (0.023) 0.001 5.95 (0.42) 0.41 (0.13) W1 29 0.703 (0.032) 0.722 (0.035) 0.003 5.38 (0.45) 0.10 (0.05) À W2 24 0.753 (0.046) 0.763 (0.030) 0.007 5.92 (0.43) 0.15 (0.07) À W3 21 0.719 (0.044) 0.713 (0.031) 0.031 5.03 (0.32) 0.15 (0.10) À W4 18 0.731 (0.032) 0.738 (0.033) 0.033 5.46 (0.39) 0.09 (0.04) W5 17 0.711 (0.042) 0.741 (0.037) 0.000 5.32 (0.38) 0.39 (0.16)

AR and APR, allelic richness and private allele richness averaged across loci, respectively, estimated by rarefaction using a sample size of four; H0, observed heterozygosity; uHE, unbiased expected heterozygosity which corresponds to gene diversity corrected for sam- < ple size; FIS, inbreeding coefﬁcient; SE, standard error. All values were signiﬁcant at P 0.001.

= Table 3 Pairwise FST (lower diagonal) and Jost’s D (upper diagonal) values among the nine apricot populations (n 196) inferred with STRUCTURE

Cluster Q1 Q2 Q3 Q4 W1 W2 W3 W4 W5

— Q1 0.4357 0.3819 0.5338 0.6506 0.5500 0.6935 0.6391 0.6604 — Q2 0.12537 0.4036 0.3288 0.3692 0.3158 0.4718 0.3318 0.3408 — Q3 0.12424 0.10050 0.3418 0.4313 0.4152 0.4995 0.4943 0.3677 — Q4 0.15797 0.07692 0.08903 0.3162 0.2733 0.3951 0.3207 0.3925 — W1 0.20910 0.10226 0.13376 0.09777 0.1899 0.2678 0.2058 0.5073 — W2 0.17185 0.07928 0.11873 0.07862 0.06228 0.3169 0.2189 0.4424 — W3 0.22235 0.13264 0.15363 0.12396 0.09990 0.10295 0.4255 0.4832 — W4 0.20526 0.08747 0.14610 0.09478 0.07016 0.06993 0.14412 0.4278

À The pairwise FST values (below the diagonal) were calculated with ARLEQUIN V3.5 as follows: FST/(1 FST). All pairwise FST and Jost’s D were signiﬁcant (P < 0.05, Number of permutations = 1000). together because of their weak genetic differentiation followed by a more recent domestication event of

(Table 3). Concerning the wild genepool, we simulated Q_WEST from Q_EAST; (ii) successive domestications of the Dzhungar-Zailig ecogeographic group as a single Q_EAST and Q_WEST from the same wild population (ei- population, pooling all Kazakh and Kirgiz populations ther W5 or W1–4, models 2 and 5, respectively), (iii) together (W1, W2, W3 and W4), because of their overlap- independent domestications of Q_WEST and Q_EAST ping geographic ranges, weak genetic differentiation from the two different wild populations (W5/W1–4 or and high levels of admixture. For all models of apricot W1–4/W5, respectively, models 3 and 6). In all scenarios, domestication, we therefore assumed four main popula- the Q_EAST and Q_WEST cultivated groups underwent tions: the cultivated European/Irano-Caucasian popula- bottlenecks, whose strength was estimated. tion (Q1_WEST), the cultivated Central and eastern Asian The comparisons of the six scenarios using an ABC group (Q2, Q3, Q4; called Q_EAST), the W5 wild apricot framework revealed that the model with the highest population and the Dzhungar-Zailig ecogeographic wild posterior probability (P) was the scenario assuming two + + + group (W1 W2 W3 W4). In our models, we successive domestications, of Q_EAST and Q_WEST, assumed Q_East as the most ancient cultivated group respectively, from the same Dzhungar-Zailig group in because of its higher level of genetic diversity. We Asia (W1–4), at different times, with rather weak bottle- assumed W5 as the most anciently derived population necks, although stronger western cultivated apricots (Q1 (i.e. outgroup) because of its strongest genetic differenti- population) (P = 0.91, Fig. 4, Table 4). Overall, the ation from other populations. In total, we simulated six Bayes factor (BF) for scenario 5 against the four others models of apricot domestication that were designed to was 10.75 (Table 4), which indicates strong support for distinguish between (i) a single domestication of Q_EAST this scenario. We checked that the power of the analy- from a wild population (either W5 or W1–4, models 1 ses was sufﬁcient to discriminate between the compet- and 4, respectively, Fig. S5, Supporting information), ing models. For scenario 5, against the ﬁve other

Fig. 4 Most probable scenario of domestication of Prunus armeniaca in Eurasia compared by approximate Bayesian computation (i.e. scenario 5: two consecutive independent domestications from the Dzhungar-Zailig ecogeographical group) provided with the model parameter estimates. Each parameter estimate is presented with the 95% conﬁdence interval in brackets. P: posterior probability of scenario 5; BF: Bayes factor of scenario 5 vs. the other ﬁve scenarios. Details of Bayes factors are summarized in Table 4. TX-y: divergence time between the population x and y, Nx: effective population size of population x; Q1 (or Q_WEST), Q2–4 (or Q_EAST), W1–4, W5 referred to populations detected with STRUCTURE (see details in Supporting information online), Bottleneck_x: the effective size of the population 9 one generation earlier in time relative to the effective size of the population x one generation later in time such = as NT Bottleneck * NT+1.

– Table 4 Bayes factor (BF) for the six historical models of domestication (i.e. sc1 sc6) assuming different wild groups (i.e. W1–4 or/ and W5) at the origin of the domestication, compared by approximate Bayesian computations

Wild group origin Scenarios sc1 sc2 sc3 sc4 sc5 sc6

– — A W5 sc1 Single domestication 4.0 0.67 0.22 0.01 0.64 sc2 – Independent consecutive domestications 0.25 — 0.17 0.05 0.00 0.16 – — W5 and W1–4 sc3 Independent domestications 1.50 6.0 0.32 0.02 0.97 – — W1–4 sc4 Single domestication 4.64 18.6 3.09 0.05 2.99 sc5 – Independent consecutive domestications 96.17 385.7 64.05 20.74 — 62.02 – — W5 and W1–4 sc6 Independent domestications 1.55 6.2 1.03 0.33 0.02

The models are described in Figs 4 and S5 (Supporting information). Bayes factors are represented for model A vs. model B. Wild group (W1–4 and/or W5) at the origin of domestications and scenario details are presented once in each row; bold values highlight BF of sc5 against other models. scenarios, the type I error rate was 0.3 and the mean thus provided support for two successive domestication type II error rate was 0.06. Parameter estimates for sce- events from the wild Dzhungar-Zailig group in Asia, at nario 5 are provided in Fig. 4. The cross-validation step different times, and with bottlenecks. used to check the accuracy of the marginal posterior distributions estimated using our approach revealed rel- Variation of the sharka resistance trait in the wild atively high prediction errors and independent of the Prunus armeniaca populations tolerance rate (Table S6, Supporting information). These parameter estimates should therefore be regarded with The analyses above revealed high genetic diversity in caution. However, the observed values marginally felt wild apricots that may therefore harbour valuable within the simulated data (P = 0.09), suggesting that genetic resources for breeding, and in particular for dis- the assumed model was capable of reproducing the ease resistance. For testing this hypothesis, we esti- observed summary statistics. Overall, ABC analyses mated the frequency of resistance in wild apricots. Fifty

© 2016 John Wiley & Sons Ltd 12 S. DECROOCQ ET AL. wild apricot trees from seven natural populations were chlorotic symptoms that were recorded both in the wild chosen at random for being evaluated for their response (UZ 11.5) and the cultivated PPV-susceptible apricots to PPV infection following a high-density inoculation (Manicot and Moniqui cultivars). Atypical symptoms (Fig. 5 and Table S8, Supporting information). Suscepti- were observed in the four replicates of the genotype bility to PPV was scored by recording symptoms and CH 128, with chickenpox-like symptoms (Fig. 5-A3). by semi-quantitative detection of viral accumulation in When considering the accumulation of the virus the grafted scions. The two types of disease scoring esti- across two vegetative cycles, we classiﬁed as ‘resistant’, mates were highly correlated (r2=0.89; P < 2.2e-16) individuals that showed mean optical density scores (Fig 5). We observed a high variability in the type of lower or equal to the negative control (Fig. 5B). Follow- symptoms among the wild apricot individuals when ing the results of the PPV-speciﬁc serological tests infected with PPV. The Fig. 5-A2 shows the typical (ELISA), the 50 wild apricot individuals displayed a

Fig. 5 Plum Pox Virus resistance phenotyping of wild apricot individuals. (A) Symptoms on PPV-resistant (1) or PPV-susceptible (2 and 3) wild apricot individuals (n = 50). (B) The graph shows the average of normalized optical density (OD) for four replicates of each wild apricot individual, each being tested four times by ELISA over two vegetative cycles. Accessions are ordered from the low- est to the highest viral accumulation value depicted as the mean OD value. PPV-infected ‘GF305’ peach indicator that was used as positive control in ELISAs was set at 100. The red line depicts the average optical density of the negative controls (uninfected apricot genotypes) over the two cycles. (C) Frequency of plants showing symptoms over the two vegetative cycles.

© 2016 John Wiley & Sons Ltd EVOLUTIONARY HISTORY OF APRICOTS 13 continuous phenotypic variation, ranging from high relevance of these groups and provides information on susceptibility to full resistance to PPV. In total, 12 of the their genetic structure, diversity and relationships. Our 50 tested individuals (24%) were found fully resistant to study further reveals the occurrence of a fourth genetic sharka (Fig. 5B, from KZ 125-1 to KZ 73B-1), showing group (Q2), in China. This fourth genetic group of Chi- that wild apricots may in fact harbour valuable genetic nese cultivars and landraces (Q2) was well separated resources for controlling diseases. from the wild apricot populations growing in North We then checked whether the markers previously Xinjiang (China), which grouped instead with the shown to be linked to resistance loci in cultivated apri- Kazakh wild populations. cots were also linked to resistance in wild apricots. This Within the wild germplasm sampled in Central Asia, would allow detecting resistance without phenotyping. we identiﬁed ﬁve populations. The W1 and W2 popula- The most susceptible genotype appeared to lack the tions were largely distributed along the Tien Shan – resistance-linked alleles for all three PPVres-associated Mountains, while W3 W5 were each restricted to a sin- markers (KZ 114-1, Fig. 5B and Table S8, Supporting gle sampling site, and W4 was mostly found in the information). However, many other susceptible acces- southern range of the Tien Shan Mountains (around the – sions displayed at least one or two resistance-linked Issyk-kol Lake, Kyrgyzstan). The W1 W4 wild popula- alleles at the PPVres or MetaPPV1b locus (see, e.g., KZ tions form a rather homogeneous group that corre- 127-1 in Table S8, Supporting information). Besides, the sponds to the Dzhungar-Zailig ecogeographic group,

KZ 8-2 or KZ 147-1 individuals, that displayed resis- together with the Q4 cultivated population. The W5 tance-associated allele at only one PPVres marker, were population, displaying the highest genetic divergence scored as resistant in phenotypic tests. In conclusion, no with the other wild apricot clusters, is located into the speciﬁc PPVres or MetaPPV1b haplotype could be asso- Sary-Chelek national park, close to the Fergana valley, ciated with PPV resistance or susceptibility in wild apri- several hundreds of kilometres away from the Tien cots (Table S8, Supporting information). These markers Shan Mountains. Our data indicate that W5 does not are therefore not useful for screening resistance in wild belong to the Dzhungar-Zailig ecogeographic group, populations. but instead to a genetically differentiated genepool that may correspond to the second ecogeographic group, that is the Central Asian group, that Kostina previously Discussion described (1969). Our study aimed at clarifying the identity of the ecogeographic groups previously described (Kostina 1969) and Apricot domestication history the relationships between the cultivated and wild com- partments, to elucidate the domestication history and to Approximate Bayesian computation allowed to distin- provide insights into the genetic diversity of wild apricots guish between different plausible scenarios of domesti- in comparison with common cultivars and ancient, local cation and indicated that the most likely history was varieties, in particular regarding the resistance to sharka. two independent and successive domestication events from the same wild genepool, the Dzhungar-Zailig ecogeographic group, at different times. This is in agree- Genetic differentiation between cultivated and wild ment with the origin and dissemination routes apricots previously proposed for cultivated apricots (Faust et al. Overall, we detected four populations of cultivated 1998). The domestication history has been studied in apricots and ﬁve populations of wild apricots. Cluster- only few other fruit trees (Gaut et al. 2015). A single ing analyses clearly differentiated cultivated from wild domestication event has been reported in apple trees apricot accessions, especially the western (European/ but with subsequent hybridization with another wild

Irano-Caucasian) cultivars (Q1) and Central Asian wild species than the original progenitor (Cornille et al. – forms (W1 W4). The Central Asian cultivated genepool 2012). In contrast, multiple domestication events have – (Q2 Q4) displayed a higher level of admixture, and been suggested in olive trees and grapes (Breton et al. partly with the wild compartment. 2009; Myles et al. 2011; Besnard et al. 2013; Diez et al. Based on morphological and location criteria, the 2015). In annual plants, several cases of multiple inde- existence of three ecogeographic groups (Irano-Cauca- pendent domestications have been documented, for sian, Central Asian and Dzunghar-Zailig) of apricot has instance in barley, common bean, sorghum and rice been previously suggested (Kostina 1969). Based on (Morrell & Clegg 2007; Bitocchi et al. 2012; Lin et al. their sampling sites, they correspond to our Q1, Q3 and 2012; Gaut et al. 2015; Poets et al. 2015).

Q4 genetic clusters of cultivated apricots, respectively. Our estimates of dates of domestication had large Our study thus conﬁrms, using genetic data, the conﬁdence intervals, but they included the dates

© 2016 John Wiley & Sons Ltd 14 S. DECROOCQ ET AL. provided by historical and archaeological evidence. Our number of microsatellites and then by genome rese- findings further indicated the occurrence of weak bot- quencing, for example in maize, peach and grape tlenecks during apricot domestication. ABC analyses (Aradhya et al. 2003; Grassi et al. 2003; Barnaud et al. indeed pointed to only slight decrease in population 2006, 2010; Aranzana et al. 2010; Myles et al. 2011; Huf- size in cultivated apricots. The inferred bottleneck was ford et al. 2013; Verde et al. 2013). a bit stronger in western cultivated apricots (Q1 population), as expected given modern improvement. These Are the wild apricots from the Dzhungar-Zailig results are in agreement with a previous study (Bour- natural populations at the origin of the resistance to guiba et al. 2012) that suggested a loss of diversity dur- sharka? ing domestication and/or during diffusion of apricots from the Irano-Caucasian area to the Mediterranean Our findings using microsatellite markers thus allowed basin. The ABC estimates showed high confidence inference on the domestication history of apricots and on intervals but pointed to weaker bottlenecks than previ- its centre of origin in central Asia. However, the origin ously inferred in cereals (Glemin & Bataillon 2009). Fur- and diversity of adaptive traits may follow a different thermore, we found that the current apricot cultivated evolutionary trajectory from neutral markers. Phenotyp- genepool retained high genetic diversity compared to ing of important agronomic traits, such as disease resis- wild apricots. Altogether, this is in agreement with tance, is therefore required for identifying valuable findings in other fruit trees, where domestication bottle- genetic resources. This may also provide fundamental necks were found limited. This has been explained by knowledge on the co-evolution history between trees the limited number of generations since domestication and their pathogens. We therefore also investigated the due to long juvenile phases, clonal propagation (which frequency of resistance in wild populations. restricts even more the number of sexual cycles separat- Based on markers linked to PPVres, the sharka resis- ing domesticated species from their wild progenitors) tance occurring in the North American germplasm has and ongoing crop–wild gene flow (Arroyo-Garcia et al. previously been suggested to have a Chinese origin 2006; Miller & Gross 2011; Cornille et al. 2012). (Zhebentyayeva et al. 2008). However, the discrepancy

The Chinese population (Q2) in particular displays a between our genotypic and phenotypic data invalidates very high level of genetic variation, characterized by a the strict association between allelic variation at the strikingly higher private allelic richness compared to PPVres locus and resistance to sharka. Indeed, no the eight other populations, both cultivated and wild. PPVres haplotype was systematically linked to resis- Private alleles were found at 10 different loci in the Chi- tance to PPV infection of the wild apricots. Such associ- nese germplasm, in agreement with previous studies ation breakage between phenotypic resistance and the (Zhebentyayeva et al. 2003; Pedryc et al. 2009). The PPVres resistance-associated alleles had already been occurrence of speciﬁc alleles within the Chinese germ- observed in several breeding progenies and cultivated plasm in comparison with the Central Asian germplasm germplasm (Decroocq et al. 2014; Rubio et al. 2014). This may be due to either the existence of a second centre of can be due to recombination events between markers domestication of apricot, in China, or to postdomestica- and resistance genes in natural apricot populations tion hybridization in China with closely related wild and/or to the presence of other factors or genes species sharing the same ecological niche as P. armeni- involved in the mechanism of resistance to sharka. A aca L. (i.e. P. sibirica, P. manshurica, P. ansu, P. mume). genomewide association study conducted on the apricot Gene ﬂow between common Chinese cultivated germ- cultivated germplasm recently showed the implication plasm and its wild relatives is considered to be still of at least another locus, MetaPPV1b (Mariette et al. occurring, while wild Siberian apricot resources are 2016). However, no clear linkage between phenotypic declining due to land management and deterioration of resistance and the MetaPPV1b genotype was found here their natural environment (Li et al. 2014; Wang et al. in wild apricots either. These linked markers therefore 2014). Further research on the Chinese cultivated and do not appear useful for investigating resistance fre- wild apricot(s), together with representatives of closely quencies in wild populations or the origin of sharka related species (P. siberica, P. mandshurica, P. mume and resistance, and only phenotyping resistance after experi- P. ansu), is required to infer the precise diversity and mental inoculations appeared reliable. population structure of apricot in China. Our study was Our results on phenotypes suggest that resistance to based on a dozen of microsatellite markers, but these sharka occurs at relatively high frequency in natural can give reliable information for deciphering crop cen- populations of the Dzhungar-Zailig ecogeographic tres of origin and dispersal history. Several previous group, with an estimated proportion of fully resistant studies indeed showed congruent results when infer- genotypes of 24%. This may sound surprising, as the ring domestication demographic histories with a limited wild populations in Central Asia were considered so far

© 2016 John Wiley & Sons Ltd EVOLUTIONARY HISTORY OF APRICOTS 15 to have evolved in the absence of PPV, thought to have domestication processes in fruit trees, that are still little originated in the Balkans (Atanasoff 1935). PPV would explored for these aspects (Gaut et al. 2015). have been more recently introduced in the Almaty region of the Tien Shan mountain ranges, less than two decades ago (Spiegel et al. 2004). According to this Acknowledgements hypothesis, apricot would have been domesticated in We acknowledge the FP7 European grants IRSES-246795 STONE the absence of PPV, before its transfer to its western and KBBE-613654 MARS, as well as funds from the French Inter- Irano-Caucasian and, later, European area of cultiva- professionnal Office for Fruits and Vegetables (FranceAgriMer). tion. This would explain the lack of resistance to PPV We also wish to acknowledge technical and financial help from the French Embassies in Kazakhstan (Astana, Almaty) and in the Irano-Caucasian and European cultivated germ- Uzbekistan (Tashkent). We thank Stephanie Mariette for invalu- plasm (Zhebentyayeva et al. 2008). However, this raises able help in sampling design and analyses, M. Lepert for help in questions about the origin of PPV resistance in natural genotyping, T. Mauduit and C. Chesseron for growing the plants populations and the forces driving apricot diversity and and Ed Stover, John Preece (ARS-USDA Davis), Jean-Marc Aud- variation in resistance to sharka, in the absence of its ergon (INRA, UGAFL) and Guillaume Roch (CEP Innovation) pathogen. We can formulate hypotheses, for example for providing samples from apricot germplasm collection. that the genetic factors controlling resistance to sharka Molecular analysis was performed at the Genomic and Sequenc- ing Facility of Bordeaux (grants from the Conseil Regional were linked to other adaptive trait(s), including resis- d’Aquitaine n°20030304002FA and 20040305003FA and from the tance to other pathogens or/and pests. In fact, the European Union, FEDER n°2003227 and from the Investisse- sources of PPV resistance currently used in the Euro- ments d’avenir, ANR-10-EQPX-16-01) and ADNid (Montpellier, pean breeding programmes were linked to resistance to France). high winter chilling (Badenes et al. 1996; Zhebentyayeva et al. 2008). Another hypothesis is that PPV, or an ancestral form, emerged much earlier than its first References description in 1917, not in the Balkans, but within the Aradhya MK, Dangl GS, Prins BH et al. (2003) Genetic struc- native area of stone fruit species in Asia. Under such a ture and differentiation in cultivated grape, Vitis vinifera L. scenario, apricot and PPV could have co-evolved for Genetical Research, 81, 179–192. long, in natural populations, thereby explaining the Aranzana M-J, Abbassi E-K, Howad W, Arus P (2010) Genetic existence of PPV resistance traits in the wild compart- variation, population structure and linkage disequilibrium in peach commercial varieties. BMC Genetics, 11, 69. ment. This discovery, in addition to being important for Arroyo-Garcia R, Ruiz-Garcia L, Bolling L et al. (2006) Multiple breeding-resistant cultivars, thus suggests that resis- origins of cultivated grapevine (Vitis vinifera L. ssp sativa) tance to PPV has a more complex evolutionary history based on chloroplast DNA polymorphisms. Molecular Ecol- than once thought when information was based only on ogy, 15, 3707–3714. breeding progenies, raising questions on the role of the Atanasoff D (1933) Plum pox. A new virus disease. Faculty of wild apricot genepool in the plant–pathogen interac- Agriculture and Forestry, University of Sofia Yearbook – – tions and its association with other adaptive traits. (1932 1933), Vol 11,49 69. Atanasoff D (1935) Mosaic of stone fruits. Phytopathology, 8, 259–284. Conclusion Badenes ML, Asins MJ, Carbonell EA, Glacer G (1996) Genetic diversity in apricot, Prunus armeniaca, aimed at In conclusion, our study showed that apricot natural improving resistance to plum pox virus. Plant Breeding, 115, populations in Central Asia, including China, have great 133–139. and original genetic diversity that can provide valuable Barnaud A, Lacombe T, Doligez A (2006) Linkage disequilib- germplasm for further breeding. In particular, studying rium in cultivated grapevine, Vitis vinifera L. 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Data accessibility Table S2 Descriptive genetic diversity estimates for the 15 microsatellite markers and the markers associated with the Files with microsatellite genotypes and input data for sharka resistance PPVres locus in the whole apricot data set. Structure are available on Data Dryad: DOI: 10.5061/ dryad.93633. Table S3 Percentage and counting of individuals assigned to each population deﬁned using STRUCTURE for 2 ≤ K ≤ 9 and 2 ≤ K ≤ 7 for the whole (n=372 including cultivated and wild trees) and the wild (n=230 including only trees from natural Supporting information populations) data sets, respectively, based on the 15 microsatellite marker data set. Additional supporting information may be found in the online ver- Table S4 Pairwise estimates of genetic (F /(1 À F ), lower sion of this article. ST ST diagonal) and geographic distances (in kilometres, upper diag- Fig. S1 Geographic origins of Prunus armeniaca accessions used onal) between wild populations previously deﬁned with STRUC- in this study (n = 372, including 230 wild and 142 cultivated TURE. trees). Table S5 Prior distributions used in approximate Bayesian Fig. S2 Estimated number of populations in Prunus armeniaca computations. from STRUCTURE analyses using the Ln(PD) and ΔK. Table S6 Prediction errors for each model parameter (i.e. sce-

Fig. S3 Matrix of pairwise FST in Prunus armeniaca among A) nario 5, two independent domestications from W1–4) for each all 28 cultivated groups and wild sites, B) the nine populations tolerance rate (0.01%, 0.1%, 1%). deﬁned with STRUCTURE. Table S7 Frequency among the nine apricot clusters of PPVres Fig. S4 Bayesian clustering results for the wild Prunus ameniaca alleles putatively linked to PPV resistance. sample (n=240) in Central Asia, obtained with STRUCTURE from Table S8 K=2toK=7. Genotypes at the PPVres and MetaPPV1b loci of wild apricot accessions tested for resistance to sharka. Fig. S5 The six scenarios of apricot domestication compared Appendix S1 using approximate Bayesian computation. Supplementary text describing the methods used for microsatellite marker analysis, ﬁltering, spatial population Table S1 Description of the Prunus armeniaca cultivated and structure and Approximate Bayesian Computation (ABC). wild accessions used in this study, with their geographic origin and, when applicable, provider.