Molecular Biology Reports https://doi.org/10.1007/s11033-018-4546-4

ORIGINAL ARTICLE

Genetic diversity between two Egyptian varieties and QTL analysis for some agro-morphological traits

Bahaa E. S. Abdel‑Fatah1 · Bahy Raghib Bakheit2

Received: 27 June 2018 / Accepted: 30 November 2018 © Springer Nature B.V. 2018

Abstract Genetic diversity between two ecotypes of Egyptian clover varieties, namely Fahl (mono-cut) and Helaly (multi-cut) have been assessed based on forage yield and yield components as well as molecular marker systems. The two parental genotypes were crossed to produce seeds of F­ 1 and ­F2 progenies. Analyses of variance indicated significant differences between four populations (P­ 1 (Fahl), ­P2 (Helaly), ­F1 and ­F2) for fresh forage yield, number of florets/inflorescence, number of seeds/inflo- rescence and 1000 seed weight. The mean of ­F1 hybrid indicated over-dominance of the higher performance. The phenotypic and genotypic coefficients of variation were high for fresh forage yield, intermediate for 1000-seed weight and low for number of florets/inflorescence and number of seeds/inflorescence. Four molecular marker systems with 80 primers, 30 RAPD, 10 ISSR, 10 SRAP and 30 SSR were used for studying the genetic diversity between the two parents, out of which 64 primers (26 RAPD, 7 ISSR, 7 SRAP and 24 SSR) were polymorphic between the parents. The four molecular marker systems gen- erated unique DNA bands for each parent. Twenty-one primers which produced higher unique bands in both parents were surveyed on bulked DNA from the extremes of four agro-morphological traits within and between the two ecotypes in F­ 2 generations. Twenty-one primers produced bands distinguish between the bulked extremes for at least one trait within each ecotype or between the two ecotypes. All polymorphic primers were subjected to QTL analysis, out of them 23 only were mapped on three linkage groups with four agro-morphological traits and showed 24 putative QTLs.

Keywords RAPD · ISSR · SRAP · Single marker · BSA

Introduction multi-cut variety and about 5 months for mono-cut variety where it is planted for soiling, hay and/or silage as well as Egyptian clover (Trifolium alexandrinum L.) is a well an open pasture [1]. adapted forage crop to Semi-arid conditions which is grown Among the biological features which limit the choice of in India, Pakistan, Turkey, and Mediterranean region. This the breeding method in berseem case the inability to make crop occupies the top in annual acreage in Egypt (about clonal lines, presence of self-incompatibility, small perfect one million hectares) and lasts for about 7 months for the flowers that make controlled out-crossing difficult, and insect pollination which renders distal isolation difficult to accomplish and poor seed set [2]. Evidently, Egyptian clover Electronic supplementary material The online version of this received little breeding efforts with few studies directed to article (https​://doi.org/10.1007/s1103​3-018-4546-4) contains measuring heterosis and inbreeding depression of morpho- supplementary material, which is available to authorized users. logical and seed characteristics [3]. * Bahaa E. S. Abdel‑Fatah However, recent molecular markers, have been used in [email protected] evaluating genetic diversity among clover genotypes includ- Bahy Raghib Bakheit ing random amplified polymorphic DNA (RAPD) [4, 5], [email protected] inter-simple sequence repeats (ISSR) [5, 6], sequence related amplified polymorphism (SRAP) [7, 8] and simple sequence 1 Department of Genetics, Faculty of Agriculture, Assiut repeats (SSRs or microsatellites) [9]. These studies gave University, Assiut 71526, Egypt important information in understanding species relationships 2 Department of Agronomy, Faculty of Agriculture, Assiut University, Assiut 71526, Egypt

Vol.:(0123456789)1 3 Molecular Biology Reports which may further help in developing and designing breed- Egypt. In the 2014/2015 season, the two parental popula- ing strategies. tions were crossed to produce seeds of F­ 1 hybrid using ran- Bulked segregant analysis (BSA) provides a simple dom bi-parental crosses. In 2015/2016 season the ­F1 and approach for rapidly identifying molecular markers tightly the two parents of the cross were sown to obtain additional linked to the causal gene implicit a particular ecotype [10]. ­F1 seed and produce F­ 2 seeds by selfing theF ­ 1 . In Starting with construction of a segregating population, two 2016/2017 season two experiments were conducted, in the bulked DNA samples are generated from progenies with first one, seeds of the two parents and their ­F1 hybrid and ­F2 contrasting phenotypes and genotyped with molecular mark- progenies were sown in rows 1 m-long with 15 cm spacing ers polymorphic between the parental lines [11]. BSA tech- (10 plants/row) using randomized complete block design nologies have been used in many crops for important genes with four replications. F­ 1 entry was represented by one row/ mapping [12]. replication, but the parents and F­ 2 generations were repre- Forage yield, yield component, quality and some forms sented by four rows/replication. The fresh forage yield was of abiotic and biotic stress resistance are controlled by determined as the average of three cuts from parent Helaly, polygenes and the regions within genomes that contain ­F1 hybrid and ­F2 generation, but one-cut for Fahl variety. genes associated with a particular quantitative trait are The second experiment was used to record the number of known as quantitative trait loci (QTLs) [13]. QTL mapping florets/inflorescence, number of seeds/inflorescence and is an important approach that received growing interest in 1000 seed weight. The experimental design and number of breeding. Although quantitative traits are difficult to rows/replication was described above. The fresh forage yield manipulate by conventional breeding methods, yet they can of the individual plants was recorded. The data of all traits be dissected into individual QTL using molecular markers, were analyzed on mean basis according to Steel and Torrie which allow plant breeders to locate and follow the numer- [21]. Least significant difference was used for comparisons ous interacting genes that affect a polygenic trait [14]. Sev- among populations average. The amount of heterosis and eral QTL, e.g. yield, yield components, and morphological inbreeding depression percentage was determined as follows traits have been reported for forage crops. In white clover F − MP Trifolium repens F heterosis % from mid parents (MP) = 1 × 100 ( L.), QTLs for seed yield and other seed 1 MP  yield components have been developed [15–17]. QTL maps of red clover (Trifolium pratense L.) have also been devel- F − BP oped [18, 19], and more recently a consensus QTL map of From best parent (BP) = 1 × 100 BP clover species has become available [20].  To the best of our knowledge, this is the one of the early − report on QTL analysis in Egyptian clover, which represents F2 F1 Inbreeding depression of F2 = × 100 an important first step towards marker-assisted selection and F1  may help to implement new breeding programs for complex traits. The expected mean squares for all traits were performed as outlined by Miller et al. [22]. The genotypic (σ2g) and The objectives in the present study were (a) study the 2 genetic diversity between two different ecotypes of Egyp- the phenotypic (σ p) variance were calculated according tian clover, (b) detect molecular markers associated with to Al-Jibouri et al. [23]. Phenotypic (PCV) and genotypic ecotype, and (c) identify QTLs associated with some agro- (GCV) coefficient of variability were calculated according morphological traits, which are critical traits for selection to Burton [24]. in breeding programs. Molecular markers Materials and methods DNA extraction Plant materials and field experiments Total DNA was isolated from young leaves (bulked from five Seeds of two Egyptian clover (T. alexandrinum L.) culti- different plants per parent) by following the CTAB protocol [25] with minor modification of the extraction buffer (2% vars, namely the mono-cut Fahl (P­ 1) and the multi-cut Helaly CTAB, 100 mM Tris–HCl pH 8.0, 20 mM EDTA, 1.4 M ­(P2) were obtained from Forage Crops Section, Field Crops Research Institute, Agriculture Research Center, Egypt. NaCl and 0.06% β-mercaptoethanol added just before use). The study was carried out during the three winter growing The quality and quantity of the purified DNA was measured seasons of 2014/2015, 2015//2016 and 2016//2017 at El- using spectrophotometer at 260–280 nm and checked on 1% Ghoraieb Farm, Faculty of Agriculture, Assiut University, agarose gel.

1 3 Molecular Biology Reports

Bulk segregant analysis (BSA) Chicago, USA). Given that ANOVA displays significant difference among marker genotype classes, a putative QTL In order to perform BSA for identifying of markers closely could be considered to be located at or near such marker. linked to cut-ecotype and DNA isolated from P­ 1, P­ 2, and two Composite‑interval mapping (CIM) extreme groups of ­F2 plants (15 plants high and 15 plants low for four traits, fresh forage yield, number of florets/ inflorescence, number of seeds/inflorescence and 1000-seed The linkage analysis for 24 codominant markers (SSRs) weight within and between the two ecotypes) [10]. and 40 dominant markers (26 RAPD, 7 ISSR and 7 SRAP) was performed using Mapmaker 3.0/exp [26]. A minimum RAPD, ISSR, SRAP and SSR analyses 3.0 LOD score (log of odds ratio) was set as thresholds for linkage group (LG) determination. Recombination fractions Thirty ten-mer random oligonucleotide for RAPD, ten inter- were converted into map distances in centimorgans (cM) simple sequence repeat (ISSR) primers, ten sequence related using the Kosambi mapping function [26, 27]. QTL analy- amplified polymorphism (SRAP) primer combinations and sis using CIM method was then performed for fresh forage simple sequence repeat (SSR) microsatellite markers for yield/plant cut, number of florets/inflorescence, number of thirty loci (Supplementary, Table 1), obtained from Meta- seed/inflorescence and 1000 seed weight traits using Win- bion International AG Company (Germany), were tested in QTL cartographer 2.5 [28]. The presence of a putative QTL this investigation to amplify the template DNA. was declared when the LOD score was larger than 2.5. QTL Amplification reactions were carried out in 25 µL vol- position, genetic effects and the proportion of phenotypic 2 umes, containing 11.7 µL dH­ 2O, 3.0 µL reaction buffer variation explained by the QTL (R­ ) were then calculated (10×), 3.0 µL dNTP’s mix (2.5 mM each dNTP; Promega), for each putative QTL [28]. 2.0 µL primer (2.5 µM) for each RAPD and ISSR markers and 1.0 µL forward primer, 1.0 µL reverse primer for SRAP and SSR markers each, 4.0 µL MgCl­ 2 (25 mM), 0.3 µL Taq Results and discussion DNA polymerase (5 U/µL; Promega) and 1 µL template DNA (50 ng/µL). Amplification conditions were carried out Field experimental analysis in a Lab Cycler (Model SensoQuest, GmbH, Germany) with the following specification: The description of qualitative traits are presented in Table 1. For RAPD and ISSR: Initial denaturation for 5 min at The mono-cut Fahl variety has branches restricted to the 94 °C, 40 cycles of 1 min at 92 °C, 1 min at (33 °C for apical part of the main stem, whereas Helaly variety and the RAPD and 44 °C for ISSR) and 2 min at 72 °C, and final ­F1 hybrid (multi-cut) have had basal branches which profuse extension step for 10 min at 72 °C. indicating complete dominance of multi-cut over mono-cut For SRAP: 5 min at 94 °C followed by 10 cycles: 1 min type. These results are in line with previous reports [3, 29]. at 94 °C, 1 min at 35 °C and 2 min at 72 °C then 35 cycles The analysis of variance for fresh forage yield, number with 1 min at 94 °C, 1 min at 50 °C and 2 min at 72 °C then of florets/inflorescence, number of seeds/inflorescence and finally extension for 10 min at 72 °C. 1000 seed weight indicated significant differences among For SSR markers: 5 min denaturation at 94 °C, then 45 the four populations which reflected the genetic variability cycles comprising 94 °C for 60 s, annealing of primer for that could be assessed (Table 2). The results of Table 3 60 s at 58–60 °C, extension for 60 s at 72 °C followed by indicated that the parents differed significantly in fresh final extension for 10 min at 72 °C. forage yield/cut, number of florets/inflorescence, number The PCR products were separated in an Ultra-Pure aga- of seeds/inflorescence and 1000 seed weight. The mean of rose gel with different concentrations, 1.4% (RAPD), 2% ­F1 hybrid exceeded that of the highest parent indicating (ISSR) and 2.5% (SRAP and SSR), at 80 V for 3–3.5 h. Gels were stained with ethidium bromide (EB) (0.5 µg/mL) and Table 1 Qualitative characters for the various populations of Egyp- DNA fragments were visualized using GelDoc-It®2 Imager. tian clover QTL detection Populations Character Type of cuts Branching habit Single‑marker ANOVA Fahl ­(P1) Monocut Apical and spare Helaly ­(P ) Multicut Basal and profuse In order to detect any associations between molecular mark- 2 F hybrid (P­ × P ) Multicut Basal and profuse ers and the phenotypic variation of the studied traits, single- 1 1 2 F generation Multicut Basal and profuse marker ANOVA was performed using SPSS 21.0 (SPSS Inc., 2

1 3 Molecular Biology Reports

Table 2 Analysis of variance Source of variations D.F. Mean squares of forage and seed yield and their components for the four Fresh forage yield/ Number of florets/ Number of seeds/ 1000 seed populations plant/cut (g) inflorescence inflorescence weight (g)

Replications 3 376.2 116.17 143.1 0.602 Populations 3 2473.0** 291.7** 126.3** 1.040* Error 9 202.39 41.1 17.2 0.202

* and ** Significant at 0.05 and 0.01 levels of probability, respectively

Table 3 Means of forage and Populations Character seed yield and their components of the four populations Fresh forage yield/ Number of florets/ Number of seed/ 1000 seed plant cut (g) inflorescence inflorescence weight (g)

Fahl ­(P1) 150.2 61.3 56.8 3.9

Helaly ­(P2) 115.3 71.2 50.1 3.2

F1 hybrid (P­ 1 × P2) 173.5 81.6 63.2 4.4

F2 generation 160.0 76.3 60.1 4.1 LSD 5% 22.7 10.2 6.6 0.7

Table 4 Heterosis and Heterosis % Character inbreeding depression percentage for various Fresh forage yield/ Number of florets/ Number of seed/ 1000 seed characters in Egyptian clover plant cut (g) inflorescence inflorescence weight (g)

From mid-parents 30.7 23.2 18.2 23.9 From best parent 15.0 14.6 11.3 12.8 Inbreeding depression % − 7.9 − 6.3 − 4.9 − 6.8

that over dominance was operating. Heterosis percentage Table 5 Phenotypic (σ2p), genotypic (σ2g) variances, phenotypic relative to mid and better parent (Table 4) were 30.7 and (PCV), genotypic (GCV) coefficient of variations and heritability % 15% for fresh forage yield, 23.2 and 14.6% for number of for studied characters in four populations of Egyptian clover florets/inflorescence, 18.2% for 1000 seed weight, respec- Estimate Fresh forage Number of Number of 1000 seed tively relative to mid and higher parent. The inbreeding yield/plant florets/inflo- seed/inflores- weight (g) cut (g) rescence cence depression were − 7.9, − 6.3, − 4.9 and − 6.8 for fresh forage yield/plant cut, number of florets/inflorescence, σ2p 618.3 72.9 31.6 0.26 number of seed/inflorescence and 1000 seed weight, σ2g 567.7 62.7 27.3 0.21 respectively (Table 4) revealing that selfing of Egyptian PCV 16.6 11.8 9.8 13.1 clover expressed is very detrimental to trait performance. GCV 15.9 10.9 9.1 11.8 The genotypic variance relative to the environmental H 91.8 86.0 86.4 80.8 variance (σ2p − σ2g) were high for the four studies traits (Table 5). The percentage of environmental variation from the phenotypic variance ranged from 8.2% for fresh for- Polymorphism between Fahl (mono‑cut) and Helaly age yield to 19.2% for 1000 seed weight. The phenotypic (multi‑cut) parents and genotypic coefficients of variation were descending from fresh forage yield to 1000-seed weight to number Molecular polymorphism between the parental ecotypes, of florets/inflorescence to number of seeds/inflorescence. Fahl (mono-cut) and Helaly (multi-cuts) was assessed The broad sense heritability estimates were 91.8, 86.0, using four molecular marker systems with 80 primers. 86.4 and 80.8% for fresh forage yield, number of florets/ Out of 80 primers or primer pairs, 64 (80%) (26 RAPD, inflorescence, number of seed/inflorescence and 1000 seed 7 ISSR, 7 SRAP and 26 SSR) were polymorphic between weight, respectively (Table 5). These results are in line the parental ecotypes and were used for further analysis with those reported by Bakheit [30].

1 3 Molecular Biology Reports

(Supplementary Table 2–5). In our study, the monomor- and 1000 seed weight). Of these primers, five primers (one phic primers or primer pairs were excluded from analysis. RAPD, one ISSR, one SRAP and two SSR) were able to A total of 235 bands were generated by the RAPD prim- produce DNA fragments that discriminated between the ers, and out of these, 65 (27.78%) were polymorphic with bulked ecotypes. In this regard, three fragments, 847 bp an average of 2.5 polymorphic bands per primer. The per- (UBC03), 195 bp (SSR-3) and 250 bp (SSR-10) were centage of polymorphism ranged from 9.09% (OPB02) to specific for mono-cut ecotype which appeared only in 64.29% (UBC09). Out of 65 polymorphic bands, 39 were both high and low DNA bulk of mono-cut ecotype (Fahl) unique for mono-cut ecotype (Fahl) while 26 were unique (Fig. 1a–c). In addition, two fragments i.e., 356 bp (HB15) for multi-cuts ecotype (Helaly). The maximum number of and 328 bp (SRAP-3) were presented only in both high and unique bands was produced by UBC09 (eight) followed by low DNA bulk of multi-cut ecotype (Helaly) (Fig. 1d, e). UBC03 (six), OPA13 (five), OPA01 (five) and OPA07 (four) These bands could be used as specific markers for each (Supplementary Table 2). ecotype. These specific bands were putatively associated A total of 69 bands were produced by ISSR primers with ecotype cut and subsequently screened against the screened in this study, with an average of 9.86 bands per 30 ­F2 individual of both ecotypes. In general, the mono- primer. Out of the amplified bands, 17 (64.64%) were poly- cut specific bands were presented only in allF ­ 2 mono-cut morphic. The number of polymorphic bands ranged from ecotype, and similarly, the multi-cut specific bands were one (produced by HB09 and HB11) to 4 (generated by found only in 93.75% of ­F2 multi-cuts ecotype with no ISSR-814 and ISSR-844), with an average of 3.52 bands appearance in all ­F2 mono-cut ecotype. These findings per primer. Of 17 polymorphic bands, 9 bands were specific confirmed that the unique bands for each ecotype could for mono-cut ecotype and 8 bands were specific for multi-cut be considered as specific markers for them. ecotype (Supplementary Table 3). For the agro-morphological traits, several unique bands A total of 68 SRAP amplicons were produced by SRAP were generated by the different molecular markers used primer combinations, out of which, 25 (36.76%) were poly- in this study, which were specific for high or low bulks morphic. The number of polymorphic bands ranged from 1 of F­ 2 individuals along with F­ 1 and one of the ecotype (SRAP-1 and SRAP-8) to 10 (SRAP-5) with an average of parents. As shown in the Supplementary Tables 6–9 and 3.57 bands per primer combination. Out of 25 polymorphic Supplementary Figs. 1–4, the 21 primers or primer pairs bands, 14 were specific for mono-cut ecotype and 11 bands produced DNA fragments that discriminated between the were specific for multi-cut ecotype (Supplementary Table 4). bulked extremes. SSR primer pairs amplified a total of 133 alleles, out of Such bands were which transmitted into ­F2 generations them 33 (24.81%) showed polymorphism with an average of from the two parents contributed to the improvement and 1.38 polymorphic alleles per primer. The number of alleles upgrading of these traits. Thus, the results suggested that per locus ranged from 3 (SSR-2, SSR-10, SSR-11, SSR-12 the selection of plants that contained alleles raising value and SSR-25) to 11 (SSR-6) with an average of 7 alleles per of these traits could be used in the breeding programs to primer pairs. Out of the 33 polymorphic alleles, 20 were improve such traits, while the exclusion of plants that specific for mono-cut ecotype and 13 were specific for multi- include alleles which decreasing value of these traits from cuts ecotype (Supplementary Table 5). breeding programs provides the effort and time necessary The four molecular marker systems used in this study to improve such traits. were found to be quite effective in determining the genetic The present study agreed with the results obtained by variations among Egyptian clover ecotypes. The results Zayed [31], Abd El-Naby et al. [32] and Zayed et al. [33] are in agreement with several researchers [4–6, 8, 9] who who found both ecotypes varied as indicated by different reported that DNA markers can be applied in clover to esti- molecular markers and observed unique bands for each mate the genetic diversity and variety identification. ecotype. Genetic diversity and relationship between the two Identification of molecular markers associated Egyptian clover ecotypes have been studied using ISSR with ecotypes and agro‑morphological traits markers [6], the results revealed that the Fahl mono-cut ecotype had 29 present bands, 3 absent bands in total of 32 Twenty-one primers of the four markers (5 RAPD, 5 ISSR, bands; among those, there was 2 unique bands. The multi- 5 SRAP and 6 SSR) that produced clear distinguishing pat- cut ecotype had given different pattern of bands, Gem- terns between the parental ecotypes were used to discrimi- miza1 (21 present and 11 absent), Giza6 (21 present and nate between bulked DNA from high and low extremes 11 absent) and Serw1; (23 present and 9 absent). Three within each ecotype in four traits (fresh forage yield, num- unique bands appeared in the two ecotypes. ber of florets/inflorescence, number of seeds/inflorescence

1 3 Molecular Biology Reports

Fig. 1 a–e Unique bands for the mono-cut (Fahl, P1) and multi-cut (Helaly, P2) ecotypes generated by molecular markers using bulked seg- regant analysis. Traits abbreviations are as in Table 7. 1: mono-cut F2, 2: multi-cut F2, H: high performance, L: low performance

Single‑marker analysis (SMA) analyzed with the four traits studied, only, 12 RAPD, 5 ISSR, 3 SRAP and 7 SSR markers showed significant Single-marker ANOVA (Table 6) revealed that out of 26 associations with all studied traits. These results indicate RAPD, 7 ISSR, 7 SRAP and 24 SSR polymorphic markers

1 3 Molecular Biology Reports

Table 6 Single-marker ANOVA for markers showing significant In general, SSR-10 and SSR-11 markers were associated association with the phenotypic variation of fresh forage yield/plant only with fresh forage yield/plant/cut trait, OPZ04 marker cut, number of florets/inflorescence, number of seed/inflorescence and 1000 seed weight was associated only with number of florets/inflorescence, OPA14 marker was found to be associated with three of the Primers Fresh forage Number of Number of 1000 seed four traits studied and the remaining markers were found yield/plant florets/inflo- seed/inflores- weight rescence cence to be associated with all traits studied. Moreover, pheno- R2 (%) R2 (%) R2 (%) R2 (%) typically, these traits were significantly associated with each other (Supplementary Table 10). These results suggested UBC03 84.8 65.79 65 68.62 that same gene (s) could be involved in the inheritance of OPI09 62.98 52.94 53.89 63.16 these traits (pleiotropic genes) or close linkage between the OPB05 72.97 57.82 58.77 65.82 genes or QTLs that control these traits. This signifies the UBC09 71.81 73.16 71.73 70.77 plural selection efficiency by selecting marker(s), closely OPD11 83.06 63.14 63.64 68.09 associated with these traits [34, 35]. Therefore, these mark- OPA13 12.71 20 20.14 19.17 ers could be considered as useful markers for yield improve- OPZ05 67.69 70.73 70.91 70.48 ment programs. Moreover, additional markers tests are also OPS19 53.27 47.57 49.52 59.31 required to identify candidate genes in the QTLs regions OPA11 41.97 55.98 53.67 49.93 controlling these traits. OPA01 13.31 12.93 13.26 13.62 OPA14 10.52 10.3 10.63 – Linkage analysis and simple‑interval mapping (SIM) OPZ04 – 7.88 – – HB 85.53 69.93 67.53 69.4 The Chi square (χ2) test for segregation ratios of co-dom- HB15 71.81 73.16 71.73 70.77 inant and dominant markers declared that, 25 markers (15 844 47.66 44.99 47.38 55 RAPD, 5 ISSR, 3 SRAP and 2SSR) showed the expected HB13 42.14 41.44 44.9 50.94 3:1 for dominant and 1:2:1 for co-dominant markers seg- 814 79.56 71.39 69.58 70.62 regation ratio in the F­ 2 population. The linkage analysis SRAP-2 72.97 57.82 58.77 65.82 using Mapmaker showed that, of 64 markers, 27 (42.19%) SRAP-7 67.91 55.43 56.28 64.43 were significantly correlated with agronomic traits. 23 of 64 SRAP-5 76.74 72.02 70.72 70.79 markers, mapped on three linkage groups, and the remaining SSR-24 12.56 13.18 11.26 11.88 markers were not assigned to any linkage group and des- SSR-7 13.09 16.7 16.77 15.44 ignated as unmapped markers. The number of markers on SSR-2 14.57 13.05 11.41 12.7 individual linkage groups (LG) were 3 (LG-1) with a total SSR-5 11.71 14.88 16.81 13.97 length of 78.8 cM (Fig. 2a), 5 (LG-2) with a total length SSR-6 14.52 13.8 14.12 15.61 of 79.1 cM (Fig. 2b) and 15 (LG-3) with a total length of SSR-11 9.67 – – – 121.1 cM (Fig. 2c). The total map with a length of 279 cM SSR-10 10.05 – – – in our study was shorter than the 444.2 cM, 535.7 cM of the red clover map reported by Doris et al. [36] and Isobe et al. [18], respectively and 1,144 cM of white clover map that putative QTLs for the studied traits could be located reported by Barrett et al. [15]. The large difference in locus at or near these markers. number may be one reason for the different map lengths, The percentage of phenotypic variation explained as was also reported for other species, such as perennial by the putative QTLs (R­ 2) associated with fresh forage ryegrass [37, 38]. Other factors, such as the heterogeneity yield/plant/cut ranged from 10.05% for SSR-10 marker of the parents, i.e. the particular parental genotype, may also to 85.53% for ISSR-HB marker. The ­R2 values of puta- play an important role. tive QTLs associated with number of florets/inflorescence QTL analysis using CIM method performed for the 23 ranged from 7.88% for OPZ04 (RAPD) to 73.16 for each markers assigned to LG-1, LG-2 and LG-3 with fresh for- markers UBC09 and ISSR-HB15. The ­R2 values of the age yield/plant cut, number of florets/inflorescence, num- marker UBC09 and ISSR-HB15 associated with number ber of seed/inflorescence and 1000 seed weight showed of seed/inflorescence (71.73%) was higher in magnitude that 24 putative QTLs with a LOD score higher than 3 were than other markers analyzed. Meanwhile, the lowest R­ 2 declared. value (10.63%) for such trait was found with OPA14. As Eight QTLs were detected for fresh forage yield/plant for 1000-seed weight, the lowest R­ 2 (12.7%) was observed cut, one QTL, QTLFfY1-1was located on LG-1 between with SSR-2 while the highest ­R2 (70.79%) was found with OPA07 and OPA14 markers at a map position of 9.09 cM SRAP-5 marker (Table 6). with a maximum LOD score of 8.36. The additive gene

1 3 Molecular Biology Reports

Fig. 2 Three Linkage groups, (a) LG-1, (b) LG-2 and (c) LG-3 showing the position in cM of 12 RAPD, 5 ISSR, 3 SRAP and 3 SSR markers created by Mapmaker

effect of this QTL (a = − 20.78) was higher in magnitude The remaining four QTL, QTLFfY1-3 (at 51.01 cM, than the dominant gene effect (d = 14.44), indicating the LOD = 19.94), QTLFfY2-3 (at 67.57 cM, LOD = 26.11), importance role of the additive gene action. Moreover, the QTLFfY3-3 (at 91.42 cM, LOD = 25.13) and QTLFfY4-(at negative value of the additive gene effect indicates thatP ­ 2 107.6 cM, LOD = 14.05) were located on LG-3 (Table 7; contributes the increasing allele, while ­P1 contributes the Fig. 3c). These QTLs explained 86.08%, 86.07% and 85.34% decreasing allele. The CIM results showed a high propor- of the phenotypic variance respectively. The positive values tion of phenotypic variation explained by the putative QTL of additive effect for QTLFfY1-3, QTLFfY2-3, QTLFfY3-3 ­(R2 = 85.0%) (Table 7; Fig. 3a). and QTLFfY4-3 indicating that the alleles increasing fresh Three QTL, QTLFfY1-2, QTLFfY2-2 and QTLFfY3-2, forage yield in these loci came from mono-cut parent ‘Fahl’, were located on LG-2 with a LOD score of 13.34, 15.45 while the negative values of dominant effect for QTLFfY3-3 and 22.29, respectively. QTLFfY1-2 was flanked by SSR-7 and QTLFfY4-3 indicating that the heterozygotes had lower and HB13 markers (at 27.01 cM), QTLFfY2-2 near OPZ05 fresh forage yield/plant cut as compared to ‘Fahl’. marker (at 57.3 cM) and QTLFfY3-2 between OPZ05 Six QTLs were detected for number of florets/inflores- and OPA11 (at 78.3 cM) (Table 7; Fig. 3b). These QTLs cence, three of them, QTLNF1-2, QTLNF2-2 and QTLNF3-2 explained 82.86%, 71.52% and 90.95% of the phenotypic were located on LG-2 with a LOD score of 6.98, 16.32 and variance respectively (Table 7). The additive gene effects 14.77, respectively. QTLNF1-2 was located between SSR-7 of three QTL on LG-2 were negative, indicate that the and HB13 markers (at 34.5 cM), QTLNF2-2 was located alleles increasing fresh forage yield in ­F2 plants, came near OPZ05 marker (at 57.3 cM) and QTLNF3-2 was located from multi-cut parent ‘Helaly’. between OPZ05 and OPA11 markers (at 78.3 cM) (Table 7;

1 3 Molecular Biology Reports

Table 7 QTLs identified in the ‘Fahl’ × ‘Helaly’ clover population Trait LG QTL Interval markers QTL position Max LOD value Additive effect Dominance R2 (%) Favora- (cM) effect ble alleles

Fresh forage 1 QTLFfY1-1 OPA07-OPA14 9.09 8.36 − 20.78 14.44 85.0 P2 yield/plant cut 2 QTLFfY1-2 SSR7-HB13 27.01 13.34 − 19.74 − 16.75 82.86 P2

2 QTLFfY2-2 OPA13-OPZ05 57.30 15.45 − 20.65 − 5.98 71.52 P2

2 QTLFfY3-2 OPZ05-OPA11 78.30 22.29 − 21.84 9.71 90.95 P2

3 QTLFfY1-3 UBC03-UBC09 51.01 19.94 19.57 13.12 86.08 P1

3 QTLFfY2-3 UBC09-HB 67.57 26.11 19.06 12.55 86.07 P1

3 QTLFfY3-3 ISSR-814- 91.42 25.13 20.09 − 12.49 85.34 P1 OPA01

3 QTLFfY4-3 ISSR-844- 107.60 14.05 20.41 − 14.09 84.5 P1 SSR-24

Number of 2 QTLNF1-2 SSR7-HB13 34.50 6.98 − 5.61 − 6.61 40.8 P2 florets/inflo- 2 QTLNF2-2 OPA13-OPZ05 57.30 16.32 − 7.09 − 2.89 72.38 P2 rescence 2 QTLNF3-2 OPZ05-OPA11 78.30 14.77 − 7.67 0.39 80.15 P2

3 QTLNF1-3 UBC03-UBC09 59.35 17.51 4.83 8.85 77.32 P1

3 QTLNF2-3 UBC09-HB 67.57 17.98 6.48 1.58 77.54 P1

3 QTLNF3-3 HB-HB15 84.56 19.22 6.81 − 2.18 77.14 P1

Number of seed/ 2 QTLNS1-2 SSR7-HB13 34.50 7.77 − 5.95 − 6.98 44.2 P2 inflorescence 2 QTLNS2-2 OPA13-OPZ05 57.30 16.97 − 7.98 − 1.49 77.35 P2

2 QTLNS3-2 OPZ05-OPA11 78.30 14.18 − 8.07 0.40 76.9 P2

3 QTLNS1-3 UBC03-UBC09 59.35 16.64 5.01 8.01 73.5 P1

3 QTLNS2-3 UBC09-HB 67.57 16.90 6.53 1.17 76.41 P1

3 QTLNS3-3 HB-HB15 84.56 18.97 7.13 − 1.71 77.33 P1

1000 seed 2 QTLTSW1-2 SSR7-HB13 34.50 9.30 − 0.51 − 0.63 50.21 P2 weight 2 QTLTSW2-2 OPA13-OPZ05 57.30 18.66 − 0.67 − 0.03 82.49 P2

2 QTLTSW3-2 OPZ05-OPA11 78.30 16.10 − 0.71 0.13 82.21 P2

3 QTLTSW1-3 UBC03-UBC09 59.35 16.05 0.44 0.50 69.77 P1

3 QTLTSW2-3 HB-HB15 84.56 21.01 0.63 − 0.03 82.06 P1

Fig. 3d). These QTLs explained 40.8%, 72.38% and 80.15% LG-2, with LOD scores of 7.77, 16.97 and 14.18, respec- of the phenotypic variance, respectively (Table 7). Both tively. These QTLs explained 44.2%, 77.35% and 76.9, of QTLs, QTLNF1-2 and QTLNF2-2 showed negative addi- the phenotypic variance respectively, with negative additive tive and dominant effects, indicating that in these chro- effects (Table 7; Fig. 3f). The others three QTLs, QTLNS1-3, mosomal regions, the recessive allele which increases the QTLNS2-3 and QTLNS3-3 were located on LG-3 in the same number of florets/inflorescence in ­F2 plants, came from regions of QTLs for number of florets/inflorescence on this multi-cut parent ‘Helaly’ and that number of florets/inflo- linkage group with different LOD scores (Table 7; Fig. 3g). rescence of heterozygotes was lower than mono-cut parent The CIM results showed a high proportion of phenotypic ‘Fahl’. The other three QTLs for this trait were located on variation explained by the putative QTLs (R­ 2 = 73.5%, LG-3. QTLNF1-3 was located between UBC03 and UBC09 76.41% and 77.33%). Two QTLs, QTLNS1-3, QTLNS2-3 markers (at 59.35 cM, LOD = 17.51), QTLNF2-3 was found had a positive additive and dominance gene actions, while to be located near HB marker (at 67.57 cM, LOD = 17.98) QTLNS3-3 had a positive additive effect and negative domi- and QTLNF3-3 was flanked by HB and HB15 markers (at nant effect (Table 7). 84.56 cM, LOD = 19.22) (Table 7; Fig. 3e). These QTLs Five QTLs were detected for 1000 seed weight, three showed positive additive effects and explained 77.32%, QTL were located on LG-2 in the same positions of QTLs 77.54% and 77.14% of the phenotypic variance (Table 7). for number of florets/inflorescence and number of seed/ Six QTLs were detected for number of seed/inflores- inflorescence traits on this linkage group with differ- cence, three QTL, QTLNS1-2, QTLNS2-2 and QTLNS3-2 ent LOD scores, 9.3, 18.66 and 16.1 for QTLTSW1-2, were located on LG-2. These QTLs were found in the same QTLTSW2-2 and QTLTSW3-2, respectively. These QTLs position of QTLs for number of florets/inflorescence on had negative additive effects and explained 50.21%,

1 3 Molecular Biology Reports

Fig. 3 Composite interval mapping (CIM) graphs showing LOD scores and map positions of putative QTL for fresh forage yield/plant cut (a–c), number of florets/inflorescenced, ( e), number of seed/inflorescence f,( g) and 1000 seed weight (h, i) on LG-1, LG-2 and LG-3

82.49% and 82.21% of the phenotypic variance, respec- QTLTSW1-3 was flanked by UBC03 and UBC09 markers tively (Table 7; Fig. 3h). The remaining two QTLs, (at 59.35 cM, LOD = 16.05), and QTLTSW2-3 was flanked QTLTSW1-3 and QTLTSW2-3 were located on LG-3. by HB and HB15 markers (at 84.56 cM, LOD = 21.01),

1 3 Molecular Biology Reports which explained 69.77% and 82.06% of the phenotypic 4. Taški-Ajduković K, Nagl N, Milić D, Katić S, Zorić M (2014) variance, respectively. Both QTLs showed positive addi- Genetic variation and relationship of populations and their progenies based on RAPD markers. Cent Eur J Biol tive effects, and could increase the 1000 seed weight 9(8):768–776 (Table 7; Fig. 3i). 5. Touil L, Aike B, Suomin W, Ali F (2016) Genetic Diversity of According to Collard et al. [39], QTLs accounting for Tunisian and Chinese Alfalfa (Medicago sativa L.) revealed by more than 10% of phenotypic variation ­(R2) are major QTLs. RAPD and ISSR markers. Am J Plant Sci 7:967–979 6. Zayed E, Sayed M, Omar A (2015) Genetic variations between In our study, all the reported putative QTLs were major for two ecotypes of Egyptian clover by inter-simple sequence repeat the four traits (Table 7). These results are corresponding (ISSR) techniques. Afr J Biotechnol 14(23):1947–1953 with several researchers who studied QTL for different traits 7. Jin-xing M, Tie-mei W, Xin-shi L (2013) Genetic diversity of wild Medicago sativa in clover varieties [36, 40, 41]. A total of 38 QTLs were by sequence-related amplified polymorphism markers in Xingjiang region China. Pak J Bot 45(6):2043–2050 detected for eight seed yield components, five of eight traits, 8. Rhouma HB, Ksenija TA, Nadia Z, Dorra S, Dragan M, Neila TF seed number/plant, seed yield/head, seed number/head, head (2017) Assessment of the genetic variation in alfalfa genotypes number/plant and percent seed set were highly correlated using SRAP markers for breeding purposes. Chil J Agric Res with seed yield per plant, and QTLs for several of these 77(4):332–339 9. Verma P, Chandra A, Roy AK, Malaviya DR, Kaushal P, Pandey traits were often detected in the same chromosome region D, Bhatia S (2015) Development, characterization and cross-spe- [36]. Barrett et al. [42] discovered 23 QTL involved in seed cies transferability of genomic SSR markers in berseem (Trifolium production. Most of them were dominant in nature and suit- alexandrinum L.), an important multi-cut annual forage legume. able for marker assisted selection (MAS) to improve seed Mol Breed 35(23):1–14 10. Michelmore RW, Paran I, Kesseli RV (1991) Identification of production. They also indicated genomic regions involved markers linked to disease-resistance genes by bulked segregant in seed production. Cogan et al. [43] identified 10 QTLs analysis: a rapid method to detect markers in specific genomic related to seed production of white clover. Two QTLs, one regions by using segregating populations. Proc Natl Acad Sci on LG3 and other on LG8 were shown to have strong influ- USA 88(21):9828–9832 11. Quarrie SA, Lazic-Jancic V, Kovacevic D, Steed A, Pekic S (1999) ences on seed yield. Bulk segregant analysis with molecular markers and its use for This study revealed that some QTLs for different traits improving drought resistance in maize. J Exp Bot 50:1299–1306 were mapped in the same region on map. Correlation 12. Whipple CJ, Kebrom TH, Weber AL, Yang F, Hall D, Meeley R between these traits (Supplementary Table 10) and co- et al (2011) Grassy tillers1 promotes apical dominance in maize and responds to shade signals in the grasses. Proc Natl Acad Sci location could indicate a common genetic control. Similar USA 108:E506–E512. https​://doi.org/10.1073/pnas.11028​19108​ results were reported earlier in clover [36, 41] indicating 13. Mohan M, Nair S, Bhagwat G, Krishna T, Yano M, Bhatia CR, that pleiotropism and/or tight linkage of different polygenes Sasaki T (1997) Genome mapping, molecular markers and or QTLs could be the possible reasons for the congruence marker-assisted selection in crop plants. Mol Breed 3:87–103. https​://doi.org/10.1023/A:10096​51919​792 of several QTLs. 14. Newbury HJ (2003) Plant molecular breeding. Blackwell, Oxford 15. Barrett B, Griffiths A, Schreiber M, Ellison N, Mercer C, Bou- Acknowledgements The authors would like to deeply appreciate the ton J, Ong B, Forster J, Sawbridge T, Spangenberg G, Bryan G, support provided by the Faculty of Agriculture, Assiut University, Woodfield D (2004) A microsatellite map of white clover. Theor Egypt. Appl Genet 109(3):596–608 16. Zhang Y, Sledge M, Bouton J (2007) Genome mapping of white Compliance with ethical standards clover (Trifolium repens L.) and comparative analysis within the using cross-species SSR markers. Theor Appl Genet Conflict of interest 114(8):1367–1378 The authors declare that they have no conflict of 17. Wang J, Drayton MC, George J, Cogan NOI, Baillie RC, Hand interest. ML, Kearney G, Trigg P, Erb S, Wilkinson T, Bannan N, Forster JW, Smith KF (2010) QTL analysis of salt stress tolerance in white clover (Trifolium repens L.). Theor Appl Genet 120:607–619 18. Isobe S, Klimenko I, Ivashuta S, Gau M, Kozlov NN (2003) First References RFLP linkage map of red clover (Trifolium pretense L.) based on cDNA probes and its transferability to other red clover germ- plasm. Theor Appl Genet 108:105–112 1. Bakheit BR, Hashad MM, Ahmed TA (2008) Assessment of 19. Sato S, Isobe S, Asamizu E, Ohmido N, Kataoka R, Nakamura genetic relationship between a new multifoliate strain and seven Y, Kaneko T, Sakurai N, Okumura K, Klimenko I, Sasamoto S, Egyptian commercial cultivars of berseem clover as revealed by Wada T, Watanabe A, Kohara M, Fujishiro T, Tabata S (2005) protein and RAPD markers. Forage Res 34(1):1–8 Comprehensive structural analysis of the genome of red clover 2. Abd El-Monem AMA (2016) Improvement of the mono-cut Egyp- (Trifolium pratense L.). DNA Res 12:301–364 tian clover (Trifolium alexandrium L.) by recurrent selection and 20. Isobe S, Kolliker R, Hisano H, Sasamoto S, Wada T, Klimenko I, synthetic varieties. Ph.D. thesis, Faculty of Agriculture, Assiut Okumura K, Tabata S (2009) Construction of a consensus link- University age map for red clover (Trifolium pratense L.). BMC Plant Biol 3. Mahdy EE, Bakheit BR (1985) The inheritance of forage yield in 9(1):57 Egyptian clover (Trifolium alexandrinum L.). Alex. Sci. Exchange 21. Steel RG, Torrie JM (1997) Principles and procedures of Statis- 6(2):114–140 tics, 3rd edn. McGraw-Hill, New York

1 3 Molecular Biology Reports

22. Miller PA, Williams JC, Robinson HF, Comstock RE (1958) for grain yield in the field at two water regimes. Plant Mol Biol Estimates of genotypic and environmental variances and covari- 48:697–712 ances in upland cotton and their implications in selection. Agron 35. Hittalmani S, Huang N, Courtois B, Venuprasad R, Shashidhar J 50:126–131. https​://doi.org/10.2134/agron​j1958​.00021​96200​ HE, Zhuang JY, Zheng KL, Liu GF, Wang GC, Sidhu JS, Sri- 50000​30004​x vantaneeyakul S, Singh VP, Bagali PG, Prasanna HC, McLaren 23. Al-Jibouri HA, Miller PA, Robinson HF (1958) Genotype and G, Khush GS (2003) Identification of QTL for growth and grain environmental variances and co-variance in upland cotton cross of yield-related traits in rice across nine locations of Asia. Theor interspecific origin. Agron J 50:633–637. https://doi.org/10.2134/​ Appl Genet 107:679–690 agron​j1958​.00021​96200​50001​00020​x 36. Doris H, Beat B, Bruno S, Franco W, Roland K (2006) QTL analy- 24. Burton GW (1952) Quantitative inheritance in grasses. In: Pro- sis of seed yield components in red clover (Trifolium pratense L.). ceedings of the sixth international grassland congress, Pennsyl- Theor Appl Genet 112:536–545. https​://doi.org/10.1007/s0012​ vania State College, USA, 17, 23 August 1952, pp. 277–283 2-005-0158-1 25. Murray HG, Thompson WF (1980) Rapid isolation of high molec- 37. Armstead IP, Turner LB, King IP, Cairns AJ, Humphreys MO ular weight DNA. Nucleic Acids Res 8(19):4321–4325 (2002) Comparison and integration of genetic maps generated 26. Lander ES, Green P, Abrahamson J, Barlow A, Daly MJ, Lincoln from ­F2 and ­BC1-type mapping populations in perennial ryegrass. SE, Newburg L (1987) Mapmaker: an interactive computer pack- Plant Breed 121:501–507 age for constructing primary genetic linkage maps of experimental 38. Jones ES, Mahoney NL, Hayward MD, Armstead IP, Jones JG, and natural populations. Genomics 1:174–181 Humphreys MO, King IP, Kishida T, Yamada T, Balfourier F, 27. Lincoln S, Daly M, Lander E (1992) Constructing genetic maps Charmet G, Forster JW (2002) An enhanced molecular marker with Mapmakere/EXP 3.0. Whitehead Institute Technical Report, based genetic map of perennial ryegrass (Lolium perenne) reveals 3rd edn comparative relationships with other Poaceae genomes. Genome 28. Wang S, Basten CJ, Zeng ZB (2006) Windows QTL Cartographer 45:282–295 2.5. Department of Statistics, North Carolina State University, 39. Collard BCY, Jahufer MZZ, Brouwer JB, Pang ECK (2005) An Raleigh, NC. http://statg​en.ncsu.edu/qtlca​rt/WQTLC​art.htm introduction to markers, quantitative trait loci (QTL) mapping 29. Abd El-Naby ZM, Wafaa WMS, El-Nahrawy MA (2014) Genetic and marker-assisted selection for crop improvement: the basic analysis and maternal effects in berseem clover. Life Sci J concepts. Euphytica 142(1–2):169–196 11(5):407–418 40. Joseph GR, Gary RB, Charles BE (2007) Genetic mapping forage 30. Bakheit BR (1989) Effect of recurrent selection and performance yield, plant height, and regrowth at multiple harvests in tetra- of seed synthetics in berseem clover, Trifolium alexandrinum L. ploid alfalfa (Medicago sativa L.). Crop Sci 47:11–18. https://doi.​ Forage Res 15:1–7 org/10.2135/crops​ci200​6.07.0447 31. Zayed EM (2013) Applications of biotechnology on Egyptian clo- 41. Luz del Carmen LE, Thierry H, Bernadette J (2012) Multi-popu- ver [(Berseem) (Trifolium alexandrinum L.)]. Int J Agric Sci Res lation QTL detection for aerial morphogenetic traits in the model 3:99–120 legume Medicago truncatula. Theor Appl Genet 124:739–754. 32. Abd El-Naby ZM, Zayed EM, Abo-Feteih SSM (2012) Biochemi- https​://doi.org/10.1007/s0012​2-011-1743-0 cal and molecular differences between Egyptian clover hybrids. 42. Barrett B, Baird IJ, Woodfield DR (2005) A QTL analysis of white Egypt J Biotechnol 41:104–118 clover seed production. Crop Sci 45:1844–1850 33. Zayed EM, Soliman MI, Ramadan GA, Tarrad MM (2010) Molec- 43. Cogan NOI, Abberton MT, Smith KF, Kearney G, Marshall AH, ular characterization of two cultivars of Egyptian clover (Trifolium Williams A, Michaelson-Yeates TPT, Bowen C, Jones ES, Vec- alexandrinum L.). Range Manage Agrofor 31(2):140–143 chies AC, Forster JW (2006) Individual and multi-environment 34. Tuberosa R, Sanguineti MC, Landi P, Giuliani MM, Salvi S, Conti combined analyses identify QTLs for morphogenetic and repro- S (2002) Identification of QTLs for root characteristics in maize ductive development traits in white clover (Trifolium repens L.). grown in hydroponics and analysis of their overlap with QTLs Theor Appl Genet 112:1401–1415

1 3