Evaluation of blackcurrant ( Ribes nigrum ) germplasm structure by microsatellite-based fingerprinting for the diversification of the breeding material

Abstract

BACKGROUND:

Blackcurrants are an important berry crop whose further development depends mainly on the diversity of available plant material and its successful inclusion in the breeding.

OBJECTIVE:

The study aimed to evaluate selected SSR markers’ applicability for the analysis of germplasm consisting of genotypes developed through complicated multistage crosses among different Ribes species and estimate the genetic structure and level of genetic diversity of the blackcurrant collection.

METHODS:

The set of 110 blackcurrant accessions from the Latvian genetic resources collection was genotyped using 18 previously described SSR markers.

RESULTS:

The marker set provided all genotypes with unique fingerprints and proved the need for reference genotypes in international studies for data validation. The accessions clustered according to pedigree and did not group by country of origin or breeding programme.

CONCLUSIONS:

The tested SSR markers uncovered relationships between blackcurrant accessions of complicated interspecific composition and revealed an extensive mutual exchange of germplasm among breeding programmes, thus pointing to the need for new donors of valuable characteristics. The results also highlighted the necessity to identify each species’ proportion in the hybrid material to assess the impact of species-linked gene expression.

Keywords

microsatellites SSR germplasm genetic diversity

1 Introduction

The Ribes genus is distributed predominantly in the temperate regions of Europe, Asia, North America, South America, and North Africa. The most widely commercially used species is the blackcurrant (Ribes nigrum L.), which has also been the leading interest for breeding programs [1 –4]. R. nigrum is indigenous to central and northern Europe, Caucasus, Central Siberia and Himalayas [5]. Recent data shows that the cultivation of currants (blackcurrants and redcurrants) had reached 647 thousand tonnes on an area of 141 thousand hectares [6]. Europe accounts for 97.8 % of all currants production, with Russia, Poland, and Ukraine producing the most significant volume [6]. This crop is valuable for its broad processing uses. The berries are valuable for their phytochemical content; for example, anthocyanins in blackcurrant juice act as natural colourants in food and have been protective against chronic diseases [7]. Blackcurrant berries also contain other phytochemicals with antioxidant, antimicrobial and anti-inflammatory properties [8], resulting in high demand due to their nutritional value and possible pharmaceutical uses [9].

Blackcurrant breeding concentrates on increasing fruit quality, high productivity, suitability for mechanical harvest [10], and boosting resistance to diseases and pests [11]. One of the most devastating blackcurrant diseases is blackcurrant reversion disease caused by the blackcurrant E and R forms of reversion virus [12]. The introduction of new traits into the existing germplasm through interspecific hybridization has helped improve disease resistance and winter hardiness [13], which is an essential issue for crops of temperate regions. Breeding of blackcurrants is performed mainly in Europe (United Kingdom, Sweden, Norway, Finland, Ukraine, Poland and the Baltic states [10]), Russia [14] and New Zealand. Several botanical varieties of Ribes nigrum, e.g., R. nigrum L. var. sibiricum Pavl., R. nigrum L. var. europaeum Jancz., R. var. pauciflorum Turcz., as well as another species like R. bracteosum Dougl., R. dikusha Fisch., R. fontaneum Bochkarn., R. petiolare Douglas, R. procumbens Pall. and R. ussuriense Jancz. have been used in breeding programs to introduce valuable traits.

Blackcurrant breeding in Latvia was started in the 1960s at the Pure Horticultural Research Station (HRS) and continued at the National Botanical Garden (NBG) and Institute of Horticulture (former Latvia State institute of Fruit-Growing) (LatHort) [15, 16]. During the long-term breeding program, a wide range of black currant species and cultivars from Western Europe and the former Soviet Union and a wide range of interspecific blackcurrant hybrids were maintained at LatHort. Distant hybridization was widely used to improve the potential productivity, disease resistance and properties necessary for ease of mechanized harvesting in commercial plantations like shrub shape, the elasticity of branches, uniform berry ripening time, dry separation from the stalk, and skin thickness. Along with the species widely used in hybridization, R. dikusha and R. nigrum var. sibiricum, potential productivity donors were also used in breeding like R. bracteosum and R. petiolare. As a result, valuable breeding material was developed [15, 16]. Considering the facts mentioned above, Ribes plant material of Latvian germplasm collection should represent high genetic diversity.

The utilization of blackcurrant plant material in further breeding will benefit from germplasm characterization, genetic diversity evaluation, and plant material identification. Latvian blackcurrant cultivar identification has been based mainly on morphological and agronomic characteristics [17, 18]. Unfortunately, phenotypic traits are generally influenced by the environment and the growth stage of the plant. Therefore, a long and expensive evaluation during the entire vegetative growth period is required to obtain satisfactory data for genetic diversity and relatedness evaluation for several years. Hence, several molecular marker systems were developed and applied to Ribes, including: Amplified Fragment Length Polymorphism (AFLP) [2, 19], Inter Simple Sequence Repeats (ISSR) [19, 20], Random Amplified Polymorphic DNA (RAPD) [19 –21], Single Nucleotide Polymorphism (SNP) [2, 22] and Simple Sequence Repeats (SSR) [2 , 23] to overcome environmental influences and acquire more objective information on genetic diversity and the identity of different genotypes.

SSR markers have become the marker of choice for germplasm characterization and Marker Assisted Selection (MAS) of many plant species due to their co-dominant nature, high reproducibility, and abundance in many organisms [24]. However, in blackcurrants, a critical setback could be the phenolic compounds and tannin content in the leaves, which may inhibit polymerase chain reaction (PCR) [25]. A unique pair of primers flank each SSR locus, and individuals can be uniquely genotyped [26]. This property of SSRs has been used in the evaluation of Ribes genetic resources in Italy [4 , 28], Russia [29], Romania [30], Turkey [31], and the USA [32], and to assist in the creation of a Ribes core collection of Northern European germplasm [3]. One limitation of SSR markers is that the unique nucleotide sequences flanking the repeat regions must be determined. It is important to include common controls within a study to ensure repeatability [33] and take into consideration the SSR markers’ ability for spontaneous mutations. Due to sequence conservatism among species, it may be possible to transfer SSR markers developed in one species to other related species and interspecific hybrids [34], which must be empirically tested, and can vary from locus to locus.

Therefore, to clarify these issues, the aims of the present study were: (1) to evaluate the applicability of selected SSR molecular markers for the analysis of germplasm consisting of accessions developed through complicated multistage crosses among different Ribes species; (2) to use these SSRs to determine blackcurrant origin and identify each accession; and (3) to estimate blackcurrant collection genetic structure and level of genetic diversity

2 Material and methods

2.1 Plant material and isolation of genomic DNA

Young leaves of 110 blackcurrant accessions in the collection maintained at the Institute of Horticulture, Dobele, Latvia (LatHort) were collected between May and June, 2018. (Table 1). Total DNA was isolated using a Genomic DNA Purification Kit (ThermoScientific, Lithuania).

Table 1
The characterized Ribes accessions, their geographic origin, pedigree and groups based on population structure from Fig 3

Accession Name Country of origin^* Pedigree Group^**

3579 LVA R. nigrum×R. petiolare 3

3896 LVA Zagadka×R. petiolare 4

6455 LVA Keep 39×Katyusha 2

107G13v14 LVA Pilot A.Mamkin×Intercontinental 4

19G15r LVA 3579×Intercontinental 3

29 PET×dikusha LVA R. petiolare×R. dikusha 2

2A 47 LVA Keep 39×Vinogradnaja 4

2B–14 LVA Keep 39×Pamjatj Vavilova 4

6–26–113 LVA Ben Lomond×(3579 + 2255) 3

6–26–115 LVA Keep 39×IV a 3

675/10 LVA R. fontaneum×[R. procumbens 181/2 ×R. nigrum]×R. dikusha 2

97–A112 LVA unknown 3

AA–98 LVA R. nigrum var. europeum 4

Albos EST Boscoop Giant×20–24 4

Almiai LTA Minai Shmirev×Ojebyn 1

Almo EST Mulgi Must×Kantata 1

Bagira RUS Minai Shmirev/Brodtorp 3

Beloruskaya Sladkaya BLR (Baldwin×R nigrum var sibiricum)/(Karter’s Champion)×R. dikusha 2

Ben Alder GBR (Goliath×Ojebyn)×Ben Lomond 3

Ben More GBR (Goliath×Ojebyn)/? 4

Binar RUS Ojebyn×Narjadnaya 1

Blackdown GBR Baldwin×Brodtorp 3

BRI 8608–108–1 SWE Ri III–10 o.p. 3

BRI 8704–1 SWE P10/18/12×P 9/8/7 2

BRI 8709–42 SWE BRi 8707 o.p. 2

BRI 9316–1 SWE Ben Gairn×Minai Shmirjev 3

BRI 9508–1A SWE 79–204–2×Intercontinental 1

BRI 9508–2A SWE 79–204–2×Intercontinental 1

BRI 9508–2B LTU 79–204–2×Intercontinental 1

BRI 9508–3C SWE 79–204–2×Intercontinental 1

BRI 9538–1 SWE Veloi×Triton 1

BRI 9568–1A SWE Delikates×Pilot A.Mamkin 4

BRI8608–101 SWE Ri III–10 o.p. 4

BRI9504–4A SWE 65–59–5×Storklas 1

Ceres POL (R. dikusha×’Barchatnaya’)×self 4

Chereshneva UKR [(R. nigrum×R. petiolare)/(Junostj×Zoya)]/(Minai Shmiriev×Belorusskaya Sladkaya) 3

Chornaya Vual’ RUS (Belorusskaya Sladkaya×Sundebyn II) 3

×(Dikovinka)

Chornii Zhemchug RUS Minai Shmirev×Brodtorp 3

Chornij Kentavr RUS unknown 4

Detskosel’skaya RUS Vistavochnaya×(Stahanovka Alta + Chornaya Lisavenko) 3

Domino LTU 79–204–2×Intercontinental 1

E-170 LVA Ben Alder×Katyussha 1

E-217 LVA unknown 1

Elo EST Ojebyn×Kantata 1

Gagatai LTU Minai Shmiriev x Ojebyn 1

Golubichka RUS Izumnaya×Hyb.42–7 4

Guliver RUS Sejanets Golubki×No. 32–77 4

Ijunskaya Kondrashova RUS Sejanets Golubki×? 4

Intercontinental SWE Ri 74020–11/Titania 1

Iskushenie RUS (Belorusskaya Sladkaya/Sundebyn II) ×Chudesnica 3

Izjumnaya RUS Hyb.37–5×Sejanets Golubki 4

Jadrenaya RUS (Dikovinka×Brödtorp)×Lubimica Altaya 4

Jet GBR (R. bracteosum×R nigrum var. europaeum) ×Brodtorp 4

Joniniai LTU Minai Shmiriev×Nr.67–59–3 4

Karina LVA Lentjai×Intercontinental 3

Karri EST Mulgi Must×Kantata 1

Kazachka RUS (Junostj×Zoya)×Minai Shmirev 3

Keep 39×R. petiolare LVA Keep 39×R. petiolare×R. dikusha ×R. dikusha 4

KEEP39 LVA o.p. (R. nigrum×R. grossularia) 4

Kryviai LTU Minaj Shmirev×(Stachanovka Altaya×Sovchoznaya) 1

Kupalinka BLR Minai Shmirev o.p. 3

Lentyai RUS Brodtorp×Minai Shmirev 3

Mara Eglite LVA Black Naple’s×Katyusha 2

Meža upene vietējā LVA R. nigrum 1

Minai Shmirev RUS [(Baldwin×R nigrum var. sibiricum)× [(Baldwin×R nigrum var . sibiricum)]×Golubka 1

Monisto RUS (Brodtorp×?)×Samoplodnaya 3

Nara RUS Sejanets Golubki×(Brodtorp/Brodtorp) 4

Neapole×14 + 6+7145 LVA Black Naple’s pol. mix 2

NK 77 LVA Black Naple’s×Katyusha 2

No. 24–4 LVA (Ojebyn×Black Naple’s)×(Jet×Zagadka) 1

No. 14 LVA R. nigrum var. europaeum/×R. bracteosum 4

No. 24 LVA R. bracteosum×R. nigrum 4

No. 37 LVA Black Naple’s×Sejanets Golubki 4

No. 4 intersp LVA unknown 3

No. 5 intersp LVA unknown 2

No. 8709 SWE C2/15/40 o.p. 3

Ocharovanie RUS (Pobeda×Nochka)×Sunderbyn II×Ekzotika 2

Ojebyn SWE Clone of Ekheikki 1

Paulinka BLR [(Baldwin×Rnigrum var. sibiricum) ×Baldwin×R. sibiricum)]×Golubka 1

Pileniai LTU Minai Shmirev×Ojebyn 3

Pilot A.Mamkin BLR [(Baldwin×R. nigrum var sibiricum)/Karter’s Champion]×R.dikusha 3

Poezija RUS Minai Shmirev×Brodtorp 1

Polar SWE (Silvergieters Schwarze×Sunderbyn II)×Nikkala 1

R. dikuscha RUS R. dikusha 2

R. nigrum var europaeum RUS R. nigrum ssp europaeum 4

R. nigrum var sibiricum RUS R. nigrum var sibiricum 2

R. ussuriense 5071 RUS R. ussuriense 2

R. americanum 1297 LVA R. americanum×R. nigrum F₁ 4

Risarp SWE unknown 1

Ritmo SWE 79–204–2×Intercontinental 1

Selechenskaya-2 RUS Hyb 42–7×Hyb 1–116 4

Sevchanka RUS Sejanets Golubki×/(Brodtorp×Brodtorp) 4

Silvergieters Schwarze DEU Boskoop Giant×? 3

Sozvezdie RUS Minai Shmirev×Brodtorp 4

Stella II SWE Erkheikki×Boskoop Giant 1

Stor Klas SWE Sunderbyn II×(Consort×Kayanin Musta) 1

Svita Kievskaya UKR (Junost×Zoya)×Minai Shmirev 3

Titania SWE Altayskaya Desertnaya×(Consort×Kajanin Musta) 1

Triton SWE Altayskaya Desertnaya×(Consort×Kajanin Musta) 4

Ussuri RUS Usuriyskaya 507 o.p. 2

Vakariai LTU Stahanovka Altaya×Obilnaya 3

Varmaas EST Albos×Uus Must 3

Vernisazh UKR (Klussunovskaya×Triton) o.p. 3

Vertti FIN Ojebyn×Ojebyn 1

Viktor LTU 65–59–5×Storklas 4

Vologda RUS Kompaktnaya×Brodtorp 3

Wellington XXX GBR Boscoop Giant×Baldwin 4

Zagadka RUS Nina×Sopernik 4

Zaglyaden’e RUS [(Pobeda×Nochka)×Sunderbyn II]×Orlovskii Vals 3

Zelenaya Dimka RUS Minai Shmirev×Brodtorp 3

Accession Name	Country of origin^*	Pedigree	Group^**
3579	LVA	R. nigrum×R. petiolare	3
3896	LVA	Zagadka×R. petiolare	4
6455	LVA	Keep 39×Katyusha	2
107G13v14	LVA	Pilot A.Mamkin×Intercontinental	4
19G15r	LVA	3579×Intercontinental	3
29 PET×dikusha	LVA	R. petiolare×R. dikusha	2
2A 47	LVA	Keep 39×Vinogradnaja	4
2B–14	LVA	Keep 39×Pamjatj Vavilova	4
6–26–113	LVA	Ben Lomond×(3579 + 2255)	3
6–26–115	LVA	Keep 39×IV a	3
675/10	LVA	R. fontaneum×[R. procumbens 181/2 ×R. nigrum]×R. dikusha	2
97–A112	LVA	unknown	3
AA–98	LVA	R. nigrum var. europeum	4
Albos	EST	Boscoop Giant×20–24	4
Almiai	LTA	Minai Shmirev×Ojebyn	1
Almo	EST	Mulgi Must×Kantata	1
Bagira	RUS	Minai Shmirev/Brodtorp	3
Beloruskaya Sladkaya	BLR	(Baldwin×R nigrum var sibiricum)/(Karter’s Champion)×R. dikusha	2
Ben Alder	GBR	(Goliath×Ojebyn)×Ben Lomond	3
Ben More	GBR	(Goliath×Ojebyn)/?	4
Binar	RUS	Ojebyn×Narjadnaya	1
Blackdown	GBR	Baldwin×Brodtorp	3
BRI 8608–108–1	SWE	Ri III–10 o.p.	3
BRI 8704–1	SWE	P10/18/12×P 9/8/7	2
BRI 8709–42	SWE	BRi 8707 o.p.	2
BRI 9316–1	SWE	Ben Gairn×Minai Shmirjev	3
BRI 9508–1A	SWE	79–204–2×Intercontinental	1
BRI 9508–2A	SWE	79–204–2×Intercontinental	1
BRI 9508–2B	LTU	79–204–2×Intercontinental	1
BRI 9508–3C	SWE	79–204–2×Intercontinental	1
BRI 9538–1	SWE	Veloi×Triton	1
BRI 9568–1A	SWE	Delikates×Pilot A.Mamkin	4
BRI8608–101	SWE	Ri III–10 o.p.	4
BRI9504–4A	SWE	65–59–5×Storklas	1
Ceres	POL	(R. dikusha×’Barchatnaya’)×self	4
Chereshneva	UKR	[(R. nigrum×R. petiolare)/(Junostj×Zoya)]/(Minai Shmiriev×Belorusskaya Sladkaya)	3
Chornaya Vual’	RUS	(Belorusskaya Sladkaya×Sundebyn II)	3
×(Dikovinka)
Chornii Zhemchug	RUS	Minai Shmirev×Brodtorp	3
Chornij Kentavr	RUS	unknown	4
Detskosel’skaya	RUS	Vistavochnaya×(Stahanovka Alta + Chornaya Lisavenko)	3
Domino	LTU	79–204–2×Intercontinental	1
E-170	LVA	Ben Alder×Katyussha	1
E-217	LVA	unknown	1
Elo	EST	Ojebyn×Kantata	1
Gagatai	LTU	Minai Shmiriev x Ojebyn	1
Golubichka	RUS	Izumnaya×Hyb.42–7	4
Guliver	RUS	Sejanets Golubki×No. 32–77	4
Ijunskaya Kondrashova	RUS	Sejanets Golubki×?	4
Intercontinental	SWE	Ri 74020–11/Titania	1
Iskushenie	RUS	(Belorusskaya Sladkaya/Sundebyn II) ×Chudesnica	3
Izjumnaya	RUS	Hyb.37–5×Sejanets Golubki	4
Jadrenaya	RUS	(Dikovinka×Brödtorp)×Lubimica Altaya	4
Jet	GBR	(R. bracteosum×R nigrum var. europaeum) ×Brodtorp	4
Joniniai	LTU	Minai Shmiriev×Nr.67–59–3	4
Karina	LVA	Lentjai×Intercontinental	3
Karri	EST	Mulgi Must×Kantata	1
Kazachka	RUS	(Junostj×Zoya)×Minai Shmirev	3
Keep 39×R. petiolare	LVA	Keep 39×R. petiolare×R. dikusha ×R. dikusha	4
KEEP39	LVA	o.p. (R. nigrum×R. grossularia)	4
Kryviai	LTU	Minaj Shmirev×(Stachanovka Altaya×Sovchoznaya)	1
Kupalinka	BLR	Minai Shmirev o.p.	3
Lentyai	RUS	Brodtorp×Minai Shmirev	3
Mara Eglite	LVA	Black Naple’s×Katyusha	2
Meža upene vietējā	LVA	R. nigrum	1
Minai Shmirev	RUS	[(Baldwin×R nigrum var. sibiricum)× [(Baldwin×R nigrum var . sibiricum)]×Golubka	1
Monisto	RUS	(Brodtorp×?)×Samoplodnaya	3
Nara	RUS	Sejanets Golubki×(Brodtorp/Brodtorp)	4
Neapole×14 + 6+7145	LVA	Black Naple’s pol. mix	2
NK 77	LVA	Black Naple’s×Katyusha	2
No. 24–4	LVA	(Ojebyn×Black Naple’s)×(Jet×Zagadka)	1
No. 14	LVA	R. nigrum var. europaeum/×R. bracteosum	4
No. 24	LVA	R. bracteosum×R. nigrum	4
No. 37	LVA	Black Naple’s×Sejanets Golubki	4
No. 4 intersp	LVA	unknown	3
No. 5 intersp	LVA	unknown	2
No. 8709	SWE	C2/15/40 o.p.	3
Ocharovanie	RUS	(Pobeda×Nochka)×Sunderbyn II×Ekzotika	2
Ojebyn	SWE	Clone of Ekheikki	1
Paulinka	BLR	[(Baldwin×Rnigrum var. sibiricum) ×Baldwin×R. sibiricum)]×Golubka	1
Pileniai	LTU	Minai Shmirev×Ojebyn	3
Pilot A.Mamkin	BLR	[(Baldwin×R. nigrum var sibiricum)/Karter’s Champion]×R.dikusha	3
Poezija	RUS	Minai Shmirev×Brodtorp	1
Polar	SWE	(Silvergieters Schwarze×Sunderbyn II)×Nikkala	1
R. dikuscha	RUS	R. dikusha	2
R. nigrum var europaeum	RUS	R. nigrum ssp europaeum	4
R. nigrum var sibiricum	RUS	R. nigrum var sibiricum	2
R. ussuriense 5071	RUS	R. ussuriense	2
R. americanum 1297	LVA	R. americanum×R. nigrum F₁	4
Risarp	SWE	unknown	1
Ritmo	SWE	79–204–2×Intercontinental	1
Selechenskaya-2	RUS	Hyb 42–7×Hyb 1–116	4
Sevchanka	RUS	Sejanets Golubki×/(Brodtorp×Brodtorp)	4
Silvergieters Schwarze	DEU	Boskoop Giant×?	3
Sozvezdie	RUS	Minai Shmirev×Brodtorp	4
Stella II	SWE	Erkheikki×Boskoop Giant	1
Stor Klas	SWE	Sunderbyn II×(Consort×Kayanin Musta)	1
Svita Kievskaya	UKR	(Junost×Zoya)×Minai Shmirev	3
Titania	SWE	Altayskaya Desertnaya×(Consort×Kajanin Musta)	1
Triton	SWE	Altayskaya Desertnaya×(Consort×Kajanin Musta)	4
Ussuri	RUS	Usuriyskaya 507 o.p.	2
Vakariai	LTU	Stahanovka Altaya×Obilnaya	3
Varmaas	EST	Albos×Uus Must	3
Vernisazh	UKR	(Klussunovskaya×Triton) o.p.	3
Vertti	FIN	Ojebyn×Ojebyn	1
Viktor	LTU	65–59–5×Storklas	4
Vologda	RUS	Kompaktnaya×Brodtorp	3
Wellington XXX	GBR	Boscoop Giant×Baldwin	4
Zagadka	RUS	Nina×Sopernik	4
Zaglyaden’e	RUS	[(Pobeda×Nochka)×Sunderbyn II]×Orlovskii Vals	3
Zelenaya Dimka	RUS	Minai Shmirev×Brodtorp	3

^*BLR - Belarus, DEU - Germany, EST - Estonia, FIN - Finland, GBR - United Kingdom, LTU - Lithuania, LVA - Latvia, POL - Poland, RUS - Russia, SWE - Sweden, UKR –Ukraine. ^**The membership of the accession in the group was obtained by performing an analysis of the genetic structure of the tested collection using Structure software.

2.2 PCR and amplification fragment analysis

PCR analysis performed using two sets of previously described SSR markers: (i) eleven markers for evaluation of general diversity, RJL markers [23] and (ii) fourteen markers linked to the regions controlling particular traits important for breeding based on QTL analysis and to ensure distribution across the Ribes genome: g1-G11, g3-A17, g2-G12, g2-P03, g1-K04, g1-O17, g1-B02, g1-G06, g2-J08, g2-B20, g2-M19, e3-M04, g1-I02, e1-O01 [2]. PCR reactions performed in a 20μL reaction with 25 ng DNA, 2 mM each primer, 200 mM of each nucleotide, 1.5 mM MgCl₂ and 0.5 U Taq DNA polymerase (Sigma, USA) per reaction, in an Eppendorf epgradient thermal cycler (Eppendorf, Germany) according to the described protocol for each primer pair [2, 23]. PCR products were first checked on 1% agarose gels in 1x TAE buffer and visualized by staining with ethidium bromide to test for the presence of PCR products. The same PCR products were subsequently analyzed on an ABI PRISM® 3100 Genetic Analyzer (Applied Biosystems, USA) and genotyped using GeneMapper® Software v4.0 (Applied Biosystems, USA).

2.3 Data analysis

SSR marker characteristics (Na - number of alleles, Ne - number of effective alleles, I - Shannon’s information index, Ho - observed heterozygosity, He - expected heterozygosity) and statistical comparison of germplasm groups by Analysis of Molecular Variance (AMOVA) were calculated using GenAlEx 6.5. software [35]. For further Principal Coordinates Analysis (PCoA), SSR fragments were coded as present (1) or absent (0) in a binary matrix and analyzed by PAST 3.20 software [36]. The model-based clustering method of STRUCTURE 2.3.3 [37, 38] software was applied to identify the genetic structure of the 110 Ribes accessions and to define the most likely number of groups (K value). Ten independent runs of STRUCTURE were performed for each K value from 2 to 11. Each run included a burn-in period of 100,000 steps, followed by 100,000 Monte Carlo Markov Chain replicates, assuming an admixture model and correlated allele frequencies. No prior information was used for cluster definition. The most likely K was chosen to compare the average estimates of the data likelihood (ln[Pr(X|K)]), for each K value (38), as well as calculating the ad hoc statistics ΔK, based on the rate of change in the ln-probability of data between successive K values [39]. The proportion of membership (q) of each genotype in each group was estimated.

3 Results and discussion

3.1 Characterization of SSR markers in ribes germplasm

Nine of the eleven RLJ SSRs amplified in all tested accessions and were polymorphic in the blackcurrant germplasm: RJL-2, RJL-3, RJL-4, RJL-5, RJL-6, RJL-7, RJL-9, RJL-10 and RJL-11 (Table 2). In trait-linked SSR markers, successful amplification in all tested accessions and polymorphism were obtained for nine of the 14 SSRs, including g1-K04, g1-B02, g2-J08, g2-B20, e3-M04, g1-I02, g1-G11, g3-A17 and g2-G12. These SSRs were reported to be associated with full flower, first leaf and flower, bud break, pH, ascorbic acid content, titratable acidity and specific gravity [2]. In total, the 18 primer pairs provided unique fingerprints for each Ribes accession. The number of alleles varied from 5 (RJL-9) to 25 (e3-M04), averaging 11.4 per primer pair (Table 2). A slightly smaller number of alleles per primer pairs were previously reported (9.1 –10.4) (4, 23, 27), likely due to the presence of many interspecific hybrids with complicated multistage combinations of Ribes species in this study. The number of effective alleles ranged from 1.658 (RJL-10) to 9.207 (RJL-5). Observed heterozygosity was variable among SSRs, ranging from 0.192 (RJL-10) to 0.912 (g2-J08), with an average value of 0.590, which was also close to published data on Ribes. The fixation index was negative for six loci (RJL-6, RJL-9, g1-K04, g2-J08, g2-B20, g3-A17), indicating high heterozygosity in the studied blackcurrant collection and the possibilities for further use of this material in breeding without risk of inbreeding pressure.

Table 2
Characterization of eighteen SSR markers used to genotype the 110 accessions in the Latvian blackcurrant collection

SSR marker Na Ne I Allele range (bp) Ho He F

RJL-2 8 2.7 1.220 192–219 0.495 0.630 0.214

RJL-3 13 4.8 1.869 132–172 0.455 0.790 0.425

RJL-4 13 2.1 1.147 167–220 0.409 0.516 0.208

RJL-5 15 8.5 2.367 256–287 0.812 0.882 0.080

RJL-6 11 2.9 1.430 270–302 0.720 0.653 –0.101

RJL-7 15 7.9 2.319 193–229 0.864 0.871 0.008

RJL-9 3 2.0 0.807 203–207 0.555 0.500 –0.109

RJL-10 13 1.7 1.043 180–297 0.202 0.422 0.521

RJL-11 8 2.4 1.139 215–232 0.455 0.578 0.214

g1-K04 12 2.9 1.478 277–298 0.670 0.663 –0.010

g1-B02 6 2.6 1.131 175–193 0.358 0.608 0.412

g2-J08 9 4.2 1.635 151–172 0.907 0.760 –0.192

g2-B20 10 4.2 1.610 124–169 0.778 0.763 –0.019

e3-M04 21 9.9 2.617 254–335 0.358 0.900 0.602

g1-I02 8 2.7 1.267 183–212 0.509 0.625 0.186

g1-G11 12 2.8 1.345 214–244 0.509 0.645 0.211

g3-A17 15 4.3 1.813 118–177 0.664 0.766 0.134

g2-G12 14 6.6 2.092 140–192 0.882 0.848 –0.040

Average 11.4 4.18 1.574 - 0.589 0.690 0.152

SSR marker	Na	Ne	I	Allele range (bp)	Ho	He	F
RJL-2	8	2.7	1.220	192–219	0.495	0.630	0.214
RJL-3	13	4.8	1.869	132–172	0.455	0.790	0.425
RJL-4	13	2.1	1.147	167–220	0.409	0.516	0.208
RJL-5	15	8.5	2.367	256–287	0.812	0.882	0.080
RJL-6	11	2.9	1.430	270–302	0.720	0.653	–0.101
RJL-7	15	7.9	2.319	193–229	0.864	0.871	0.008
RJL-9	3	2.0	0.807	203–207	0.555	0.500	–0.109
RJL-10	13	1.7	1.043	180–297	0.202	0.422	0.521
RJL-11	8	2.4	1.139	215–232	0.455	0.578	0.214
g1-K04	12	2.9	1.478	277–298	0.670	0.663	–0.010
g1-B02	6	2.6	1.131	175–193	0.358	0.608	0.412
g2-J08	9	4.2	1.635	151–172	0.907	0.760	–0.192
g2-B20	10	4.2	1.610	124–169	0.778	0.763	–0.019
e3-M04	21	9.9	2.617	254–335	0.358	0.900	0.602
g1-I02	8	2.7	1.267	183–212	0.509	0.625	0.186
g1-G11	12	2.8	1.345	214–244	0.509	0.645	0.211
g3-A17	15	4.3	1.813	118–177	0.664	0.766	0.134
g2-G12	14	6.6	2.092	140–192	0.882	0.848	–0.040
Average	11.4	4.18	1.574	-	0.589	0.690	0.152

Na = number of alleles, Ne = number of effective alleles, I = Shannon’s information index, Ho = observed heterozygosity, He = expected heterozygosity, F = fixation index.

Allele size ranges were compared to previous reports for the same SSRs to check the consistency of the SSR pair results. The amplification fragments for the RJL loci were all within the parameters developed initially by R. Brennan and colleagues [23]. Similar ranges of amplification fragment lengths were also observed for other loci, e.g., g1-K04 [4 , 40]; g2-J08 [4, 29]; e3-M04 [4]. Results of the genotyping show that based on diversity characterization criteria, the collection is representative of the diversity in R. nigrum.

There is currently a shortage of large-scale Ribes genotyping data to make comprehensive comparisons of results. Existing research primarily covers a few dozen indigenous accessions [27 , 40]. The most extensive study of Ribes germplasm using SSR markers in the development of the Northern European Ribes core collection includes 846 Ribes accessions (including 400 blackcurrants) from eight national collections [3]. Although several Ribes germplasm collections have been analyzed worldwide, three cultivars and four SSRs used in this study were in common with that previously reported by Cavanna et al. [27] (Table 3). Comparison of genotyping data in ‘Ben More’, ‘Black Down’ and ‘Wellington’ identified the same alleles at g2-J08 in both studies, but slightly different allele sizes at g1-K04, and e3-M04. Such small differences in allele sizes or absence of an allele in one of the studies (like the absence of the 295 equivalent allele for ‘Wellington’ at g1-K04 in this study) could be attributed to different reagents, PCR conditions, genotyping platforms and errors in scoring. More considerable differences in lengths of marker RJL-10 amplification fragments, can be explained by marker’s specificity or error in primer sequences. These results prove the need for reference genotypes in international studies [33]. Discrepancies in genotyping data were also identified in the most prominent international Ribes germplasm characterization project to date [3], pointing to the need for reference accessions, especially in inter-collection analysis and comparison across collections.

Table 3

Comparison of allele sizes (in bp) of ‘Ben More’, ‘Blackdown’ and ‘Wellington’ between this study (B) and that of Cavanna et al. (27) (A) at the four common SSRs, g1-K04, g2-J08, e3-M04, and RLJ-10

Cultivar	Data source^*	SSR marker
		g1-K04	g2-J08	e3-M04	RJL-10
Ben More	A	289, 295	159, 163	332, 332	155, 155
	B	290,292	159, 163	314, 314	270, 270
Blackdown	A	289, 291	159, 163	332, 332	155, 157
	B	290, 292	159, 163	331, 331	201, 201
Wellington	A	289, 295	159, 163	325, 332	155, 157
	B	290, 290	159, 163	324, 331	201, 201

3.2 Geographic structure of ribes collection

Plant material of Ribes collections has been reported to cluster according to geographical origin [4 , 41]. The Latvian Ribes collection includes accessions from 11 countries: Belarus, Estonia, Finland, Lithuania, Latvia, Poland, Russia, Sweden, Ukraine, and United Kingdom (Table 1). Our collection contains a large proportion of accessions from Russia, followed by Latvia and Sweden (31, 20 and 21 accessions, respectively). The rest of the countries were represented by 9 (Lithuania), 5 (Estonia, United Kingdom), 4 (Belarus), and 3 (Ukraine) accessions and one each for Germany, Finland and Poland. Hybrids developed as part of the joint Latvian-Lithuanian-Swedish breeding program (hybrid names with the abbreviation BRI) were also included in the study, and their national origin was attributed according to the final evaluation or cultivar registration place. AMOVA with a country of origin as the population criteria stated only 2% difference between populations. Minor differences also confirmed the distribution of accessions discovered by PCoA, which did not show any grouping according to country of origin.

Although the studied germplasm did not show grouping by country of origin, a difference between the groups was observed in the diversity parameters (Table 4). A strong correlation between the average number of alleles and each group’s sample size was observed (Table 4) –the highest number of alleles was found for the accessions from Latvia, Russia and Sweden. A similar connection was also observed in the data published by O. Mezhnina, O. Urbanovich [40] –in a comparison of Belarusian and foreign cultivars. A contradicting trend was observed in the evaluation of wild populations of endemic Ribes species–there was no clear correlation between population size and the number of alleles per locus [28, 32]. However, it is essential to note that species with narrow, specific distributions tend to be less genetically diverse overall, highlighting the difference between wild and cultivated species. The highest observed heterozygosity was found for the Lithuanian population (0.713), which consisted of nine samples, whereas the second highest observed heterozygosity was observed for the Swedish population (0.625) (Table 4). High observed heterozygosity is a positive indicator for genetic diversity in the particular blackcurrant group and was entirely predictable due to the allogamy of blackcurrants [29] and extensive involvement of distant hybridization in breeding. In general, a similar trend was also observed among markers –the number of alleles correlated with the size of the population and larger populations (Latvian, Russian, Swedish) had a higher number of alleles per marker. Only in some cases (like RJL-4 and RJL-9) there were no differences in allele number between larger and smaller populations. These correlations were not stated for the observed heterozygosity. High heterozygosity was also found for small populations, which means higher genetic diversity inside groups (Table 4).

Table 4
Genetic parameters of the analyzed blackcurrant accessions according to country of origin and based on the eighteen SSR markers in this study

Country of origin N Na Ne I Ho He

Belarus 4 3.6 2.835 1.046 0.542 0.576

Germany 1 1.6 1.611 0.424 0.611 0.306

Estonia 5 3.5 2.804 1.019 0.597 0.563

Finland 1 1.4 1.444 0.347 0.500 0.250

United Kingdom 5 3.3 2.554 0.960 0.517 0.541

Lithuania 9 4.8 3.420 1.237 0.713 0.620

Latvia 28 8.3 3.984 1.552 0.578 0.691

Poland 1 1.6 1.611 0.424 0.611 0.306

Russia 30 8.4 3.753 1.470 0.559 0.670

Sweden 22 6.3 3.712 1.377 0.625 0.667

Ukraine 3 2.8 2.324 0.873 0.537 0.528

Country of origin	N	Na	Ne	I	Ho	He
Belarus	4	3.6	2.835	1.046	0.542	0.576
Germany	1	1.6	1.611	0.424	0.611	0.306
Estonia	5	3.5	2.804	1.019	0.597	0.563
Finland	1	1.4	1.444	0.347	0.500	0.250
United Kingdom	5	3.3	2.554	0.960	0.517	0.541
Lithuania	9	4.8	3.420	1.237	0.713	0.620
Latvia	28	8.3	3.984	1.552	0.578	0.691
Poland	1	1.6	1.611	0.424	0.611	0.306
Russia	30	8.4	3.753	1.470	0.559	0.670
Sweden	22	6.3	3.712	1.377	0.625	0.667
Ukraine	3	2.8	2.324	0.873	0.537	0.528

Na = number of alleles, Ne = number of effective alleles, I = Shannon’s information index, Ho = observed heterozygosity, He = expected heterozygosity.

The PCoA analysis with a country of origin as a population criterion showed close relatedness among the accession groups (Fig. 1). Exceptions were representatives from Poland, Finland and Germany, represented by a single accession, thus describing the unique properties of the sample itself, rather than the group (they can be used as outgroup samples). The Finnish cultivar ‘Vertti’ is blackcurrant with green berries, the only accession with this property among the studied plant material. Poland was represented by the cultivar ‘Ceres’ whose descendants showed unique genetic profiles also in other studies, as in the cultivar ‘Ores’ [4]. The German population was represented by ‘Silvergieters Schwarze’, representing typical blackcurrants. These exceptions have proven that material from breeding programs of different countries has a relatively similar genetic background, except accessions with specific traits.

Fig. 1

Distribution of blackcurrant accessions based on genotyping data of eighteen SSR markers selected according to the country of origin using the first two coordinates of Principal coordinate analysis (PCoA).

The lack of correlation between the groups of blackcurrant accessions with their country of origin could be explained by the wide distribution of the same plant material among breeding programmes supported by the pedigree data (Table 1). Pedigree data supports the widespread use of specific cultivars in breeding programs of different countries. For example, the cultivar ‘Ojebyn’ has been used in breeding programs of six countries (Estonia, Finland, Latvia, Lithuania, Russia, and United Kingdom), while ‘Baldwin’ appears in the pedigree of cultivars developed in three countries (Belarus, Russia, and United Kingdom). Furthermore, breeders from different countries collaborate on crossing and cultivar evaluation. In the Latvian-Lithuanian-Swedish breeding program, hybridization was done jointly, but the breeding material was evaluated in the different countries. This leads to a certain uniformity of plant material, which can lead to challenges in finding novel sources to address a changing climate, new pests or diseases, and consumer demand for quality. A phenotypic study with a similar Ribes germplasm also showed no association of the accession groups with the country of origin [18], showing negative trends of blackcurrant breeding, leading to a lack of genetically diverse germplasm.

3.3 Genetic structure of ribes collection

The model-based approach using Structure software [38] was used to analyze the blackcurrant collection’s genetic structure based on genotypic information. The most likely number of clusters was evaluated using the ΔK method, and the highest peak was stated for K = 4 (Fig. 2), indicating four groups with 15, 33, 30 and 32 accessions each, respectively. The proportions of membership (q) of each accession of Ribes germplasm are shown in Fig. 3.

Fig. 2

Population genetic structure of the estimated delta K value for ten-run replications of each from K2 to K11, based on genotyping data at eighteen SSR marker in 110 Ribes accessions.

Fig. 3

Structure of the Ribes germplasm revealed by STRUCTURE software. Bar plot of individual proportions for the genetic clusters inferred using K = 4 and the dataset of 110 accessions of blackcurrants and 18 SSR markers.

A high degree of admixture was observed in the Ribes plant material grouping, as the membership values over 80% were for 24 to 53% of the groups’ accessions. This is also supported by AMOVA (variability among groups was 9%) and PCoA results –a wide overlap of accession groups was observed (Fig. 4), which shows the shared genetic background of tested Ribes germplasm. Group No. 1 is characterized by primary interspecific hybrids, pre-breeding material and only two cultivars (’Mara Eglite’ and ‘Ocharovanije’). This group’s accessions have species like R. nigrum, R. nigrum var. sibiricum, R. dikusha, R. petiolare, R. fontaneum, R. procumbens and R. ussuriense (Table 1) in their pedigree and is represented mainly by the breeding programs from Latvia and Russia. Group No. 2 contained accessions whose pedigrees contain different Ribes species: R. nigrum var europaeum, R. bracteosum, R. petiolare, R. dikusha, R. grossularia, R. americanum. This group includes more advanced cultivars, which have been acquired by interspecific hybridization and contain breeding material from seven countries (Estonia, United Kingdom, Lithuania, Latvia, Poland, Russia, Sweden). Group No. 3 had the most uniform plant material in terms of species composition –only R. nigrum and R. nigrum var. sibiricum. It mainly includes ‘Ojebyn’ or ‘Intercontinental’ and their descendants. Accessions originating in Sweden were the most widely represented in this group. Group No. 4 includes accessions whose pedigree contains species like R. nigrum, R. nigrum var. sibiricum, R. dikusha and R. petiolare. The plant material in Group 4 was represented by nine countries of origin, dominated by accessions from Russia.

Fig. 4

Principal coordinate analysis plot of the first two principal coordinates categorized by genotype and based on the eighteen SSR marker genotyping data of 110 accessions. The enclosed groups of accessions refer to the groups identified by Structure software (Table 1).

Studies on Ribes germplasm often accentuate the relationship between Ribes species and the distribution of either the species or the cultivars derived from them. Grouping, according to species, is usually observed in studies on different Ribes species [27 , 43]. However, a similar tendency has also been observed in studies on a wide array of cultivars, when the genotypes are grouped according to their geographical origin and depending on the Ribes species the cultivar was derived from [4, 40]. It is important to note that a complete analysis of Ribes species based of the origin of specific accessions is challenging to perform, and it would take a separate study, as the breeding of different cultivars involves complex multistep interspecies crosses.

The connection between defined groups and accession pedigree was justified; for example, the cultivars ‘Ojebyn’, ‘Minai Shmirev’, ‘Brodtorp’ and ‘Boskoop Giant’ as parents are in accessions of Groups 2, 3 and 4. ‘Baldwin’ was the parent for the accessions in Groups 1 and 3, while ‘Intercontinental’- was in the pedigree of accessions in Groups 3 and 4. However, some parent plants were represented in only one group: Keep 39, and ‘Sejanets Golubki’ in Group 2, and ‘Kantata’ in Group 3. The grouping of accessions according to the parentage has also been observed in other studies on local germplasm [29]. Groups with greater genetic diversity could be used as raw material for breeding purposes. Cultivars that are represented as parent plants in several groups have so far been widely used in breeding, indicating their productivity as a parent to obtain new cultivars.

4 Conclusions

Tested SSR markers can be applied to reveal the relationships between blackcurrant accessions of complicated inter-specific composition and can be used to identify germplasm and evaluate its genetic diversity.

The blackcurrant germplasm analysis identified common goals and methods among breeding programs, with extensive mutual exchange of germplasm. The analysis did not identify genetically distant accessions, which could be used directly as a source of new, genetically different plant material. This points to the need for new donors of the required traits, potentially found in the neglected Ribes germplasm or development of hybrid material using new interspecific combinations.

Interspecific Ribes hybrids are well integrated into blackcurrant cultivars, making it challenging to identify the contribution of each species. The accession species composition would be essential to assess the impact of species-linked gene expression for some important traits like Ce and P genes for resistance to gall mite.

Footnotes

Acknowledgments

Data acquisition was supported by the Latvia State Research Program in Agrobiotechnology “Innovative technologies for the production of high-quality, reliable and healthy products from genetic, physiological and biochemical diverse plants and raw material of animals”, data analysis and manuscript preparation –in the frame of the ERDF project No. 1.1.1.1/18/A/026 “Studies on Ribes plants, Cecidophyopsis mites and Blackcurrant Reversion virus for sustainable resistance breeding and cultivation of Ribes”.

Funding

ERDF project No. 1.1.1.1/18/A/026 “Studies on Ribes plants, Cecidophyopsis mites and Blackcurrant Reversion virus for sustainable resistance breeding and cultivation of Ribes”.

Conflict of interest

The authors have no conflict of interest to report.

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, Gulen

, Ipek

. Genetic diversity among some currants (Ribes spp.) cultivars as assessed by AFLP markers. Pakistan Journal of Botany. 2010;42(2):1009–12.