The first molecular characterization of the Tunisian-Algerian endemic Trifolium julianiBatt. and Trifolium squarrosum L. from Dyr El Kef, North West Tunisia

The first molecular characterization of the Tunisian-Algerian endemic Trifolium julianiBatt. and Trifolium squarrosum L. from Dyr El Kef, North West Tunisia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The first molecular characterization of the Tunisian-Algerian endemic Trifolium juliani Batt. and Trifolium squarrosum L . from Dyr El Kef, North West Tunisia Karim Guenni, Nidhal Chtourou-Ghorbel, Salma Sai Kachout, Salah Ben Youssef, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8229370/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In Tunisia, clovers represent a valuable genetic resource due to their economic and ecological importance in forage and pastoral systems, particularly within meslin cropping systems. However, certain species, such as Trifolium squarrosum , are increasingly threatened with extinction owing to the lack of conservation and management strategies. This study proposes a clarification of the distinction between Trifolium squarrosum and Trifolium juliani . To substantiate this differentiation, molecular characterization was performed using two types of molecular markers: ISSR (Inter Simple Sequence Repeats) and SRAP (Sequence-Related Amplified Polymorphism). A total of 10 ISSR primers generated 70 polymorphic bands across the two Trifolium species, demonstrating a high polymorphism percentage (PPB = 80.46%), with notable variation in band patterns among primers. Conversely, 10 SRAP primer combinations yielded 46 polymorphic bands (PBP = 73.02%). While both marker systems effectively revealed molecular polymorphism, ISSR markers exhibited slightly higher efficiency. Analysis of molecular variance (AMOVA) indicated that genetic diversity primarily partitioned between the two species, reflecting low gene flow and high genetic differentiation. Principal component analysis (PCA) and hierarchical clustering which further supported that distinction, revealed clear genetic structure among the clover species. This structure was also corroborated by robust clustering and high assignment probabilities in the Bayesian inference analysis. This study underscores the efficacy of ISSR and SRAP markers in assessing genetic diversity and differentiating clover species, providing valuable insights into their genetic relationships. Plant Molecular Biology and Genetics Trifolium juliani Trifolium squarrosum Molecular polymorphism Genetic differentiation ISSR and SRAP markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Grasslands cover approximately 20 to 40% of the world’s agricultural land; they are crucial not only for food production, but also for climate change, mitigation and the provision of key ecosystem services. These services include water regulation, biodiversity preservation, and carbon sequestration within their root systems, which represent about 90% of total grass biomass (Gibson 2008 ). Forage grasses and legumes are key components of grasslands worldwide. In temperate regions, a relatively small number of species dominate, including Lolium perenne , Festuca spp., and Dactylis glomerata among grasses, and Trifolium spp., Medicago spp., and Lotus spp. among legumes (Ravagnani et al. 2012 ). The genus Trifolium L. (Clover) belongs to the Fabaceae (Leguminosae) family, within the subfamily Papilionaceae, and is one of the largest genera in the tribe Trifolieae (Ellison et al. 2006 ). Trifolium is grouped with closely related genera, including Trigonella , Medicago , and Melilotus . However, numerous revisions of the genus have been published, and several comprehensive reviews of its taxonomic history are available, such as those by Hossain ( 1961 ), Gillet (1970), and Zohary and Heller ( 1984 ) (Lamont et al. 2001 ). Clover is native to all humid, temperate regions worldwide, except for the Himalayas and Australasia. The three primary centers of diversity for the genus Trifolium are Turkey (Mediterranean center), Ethiopia (African center), and northern California, USA (American center) (Zohary and Heller 1984 ). Recent studies supported a Mediterranean origin for the genus during the Early Miocene, around 16–23 million years ago (Ellison et al. 2006 ), with the eastern Mediterranean showing the greatest species diversity, including many commercially significant forage species (Russi et al. 1992 ). Among the 299 Trifolium species recognized worldwide (POWO 2025 ), 217 of which are accepted by the ILDIS (International Legume Database and Information System ( https://www.ildis.org )), approximately 150 occur in the Mediterranean region. These represent seven of the eight sections of the genus, with most sections having the majority of species concentrated in this area (Zohary and Heller 1984 ). Several studies have shown the commercial values of about 30 cultivated Trifolium species (Herman 1953 ; Russell and Web 1976; Evans 1976 ; Speer and Allinson 1985 ; vanKeuren and Hoveland 1985 ), from which the most important cultivated species are: T. repens (White Clover), T. subterraneum , T. pratense (Red Clover), T. fragiferum , T. hybridum , T. resupinatum , T. incarnatum , T. alexandrinum , T. dubium , T. ambiguum . The majority of them are native to the Mediterranean, especially in Turkey (Zohary 1970 ; Zohary and Heller 1984 ). In North Africa, 33 species have been recorded in Tunisia and 41 species in Algeria (ILDIS 1999 ), 40 of which are native to Algeria. However, determining the geographical distribution of several clover species remains challenging due to confusion with their cultivated range. The genus Trifolium is economically important within the Fabaceae family, with at least 16 species widely cultivated as forage and green manure crops (Gillett and Taylor 2001 ). Their symbiotic relationship with Rhizobium leguminosarum enables nitrogen fixation through root nodulation, (Sprent 2001 ), enhancing soil fertility and improving pasture quality in both natural and managed grasslands. In Tunisia, plant genetic resources are of major economic and ecological importance. Research on spontaneous forage species, particularly Trifolium species, is driven by forage scarcity resources and the low nutritional quality of conventional animal feed, which limits the development of the livestock sector (Ben Salem and Smith 2008 ). Legumes are especially valued for their high protein content and environmental benefits. Studies on spontaneous Trifolium species in Tunisia, primarily focus on the variability observed between and within species at various levels. Since the 1990s, numerous exploration and collection missions have been conducted, particularly in northern regions, to enhance the value of spontaneous legume species with forage and pastoral potential. Several Trifolium species have been identified and are well-represented in Tunisia, especially in the northern areas (Zoghlami et al. 1995 ). These species constitute a highly diverse and rich genetic resource, encompassing numerous species whose prevalence varied by region (Zoghlami et al. 1995 ). Conservation, selection, and improvement efforts for Trifolium genetic resources continued into the 2000s. These initiatives enabled the agronomic enhancement and commercialization of species, such as the diploid species Trifolium subterraneum L. (Jaritz 1982 ), officially registered in the national catalog under the name of variety Faïja. Cultivars of T. subterraneum are also well integrated into ley-farming systems due to their adaptability to diverse Mediterranean climates and soils (Katznelson 1974 ; McGuire 1985 ; Ewing 1996 ). Although 33 clover species have been recorded in Tunisia (Le Floc’h et al. 2010 ), only a few have been widely exploited; nevertheless, the annual species T. alexandrinum (berseem) has shown promising performance in forage associations combining systems, particularly with triticale (Beji and Khemir 2012 ; Zoghlami-Khélil et al. 2015 ). Recent surveys led to the inclusion of Trifolium tunetanum on the IUCN Red List as Critically Endangered (CR). According to Pottier-Alapetite ( 1979 ), a Tunisian endemic clover, Trifolium squarrosum subsp. tunetanum , is reported in the southeastern Kef region and Trifolium juliani is a rare and endemic clover species native to Tunisia and Algeria (Pottier-Alapetite 1979 ). Conservation programs at National Institute for Agronomic Research in Tunisia (INRAT) and the National Gene Bank (BNG) have preserved seeds of both T. juliani and T. squarrosum ssp parnomitanum , enabling their use in forage trials that confirmed their potential. Due to morphological similarities and overlapping ecological niches, distinguishing T. juliani and T. squarrosum ssp tunetanum becoming T. tunetanum , a specie a part, is challenging. Indeed, several recent surveys have highlighted the close resemblance between these two sympatric taxa, and detailed botanical observations ultimately allowed the clear differentiation of the two taxa Trifolium juliani and Trifolium squarrosum subsp. panormitanum (Belaifa E and Ghrabi-Gammar Z, personal communication, 2022). The present work applies molecular characterization to examine the genetic diversity within and between the two taxa. Since to support the phylogeny of the two species, we focused on molecular markers. Unlike morphological traits, molecular markers are stable, environmentally independent, and reflect genome-wide variation (Clegg and Zurawski 1991 ; Gielly and Taberlet 1996 ). Our study emphasizes molecular polymorphism and interspecific differentiation using two types of markers: (a) arbitrarily amplified DNA markers (AADs), specifically ISSR markers (Inter Simple Sequence Repeats) (Zietkiewicz et al. 1994 ), and (b) targeted fingerprinting markers (TFMs), specifically SRAP markers (Sequence-Related Amplified Polymorphism) (Li and Quiros 2001 ). ISSR markers were used for the first time to study Trifolium genetic diversity in South American and Eurasian species (Rizza et al. 2007 ), with subsequent studies confirming their utility across the genus (Paplauskienė and Dabkevičienė 2008 ; Dabkevičienė et al. 2011 ; Dabkevičienė and Paplauskienė 2012 ; Aryanegad et al. 2013 ; Abate and Tesfaye 2017 ; Abate 2017 ; Mostapha Mohamed et al. 2024). SRAP markers have more recently gained traction for their reproducibility and ability to target coding regions (Yousefi et al. 2018 ; Youssef et al. 2019 ; Mostapha Mohamed et al. 2024). Understanding Trifolium ’s essential for germplasm management and conservation strategies. Both ISSR and SRAP markers have proven effective for detecting polymorphisms and identifying genotypes of high conservation value. These marker systems are increasingly valuable for exploring key genetic aspects in Trifolium species, including their evolutionary origins, centers of diversity, domestication processes, population structure, germplasm characterization, and the dentification of markers linked to agronomic traits. However, their application in assessing genetic diversity within Trifolium remains limited, mainly due to the genus’s high species richness. More recently, SRAP markers have demonstrated their effectiveness and versatility in analyzing genetic diversity within clover species (Yousefi et al. 2018 ; Youssef et al. 2019 ; Mostapha Mohamed et al. 2024). Understanding the genetic diversity of Trifolium is critical for germplasm management and the development of conservation strategies. Studies indicate that both ISSR and SRAP marker systems are well-suited for assessing DNA polymorphism in clover, revealing the existence of diverse genotypes with unique identities warranting conservation efforts. However, despite their potential, studies employing ISSR and SRAP markers to measure genetic diversity in Trifolium species remain limited, largely due to the extensive number of species within this genus. Materials and methods Plant material The molecular polymorphism analysis was performed on seven young seedlings from each of the two clover species, Trifolium juliani and Trifolium squarrosum ssp parnomitanum . Seeds were collected in 2021 from Dyr El Kef (36°12’53.323” N, 8°45’38.293” E) (North West of El Kef) (Fig. 1 ). Trifolium juliani and Trifolium squarrosum ssp parnomitanum , distinguished in particular by their calyxes during recent surveys (Fig. 2 ), are currently being propagated in concrete trays at INRAT. Genomic DNA isolation Fresh young leaves were sampled, frozen in liquid nitrogen, and ground to a fine powder. Genomic DNA was extracted and purified using the DNAeasy Plant Mini Kit (Qiagen Inc, USA). DNA concentration were measured with a NanoDrop™ 2000/2000c (Thermo Fisher Scientific, USA), and DNA quality was evaluated by electrophoresis on 0.8% agarose gel according to Sambrook et al. ( 1989 ). PCR-ISSR assays The detection of inter and intraspecific polymorphisms has been performed using 10 ISSR primers. These were designed based on di- or multi-nucleotide repeats complementary to microsatellites (Table 1 ). The di-nucleotide repeats were anchored at the 3’ end with a single degenerating nucleotide. DNA amplification was performed in 25 µL of final volume reaction mixture containing 10X PCR buffer, 1.5 mM of MgCl 2 (50mM), 200 µM of dNTPs, 10 ρmol of primer, 1.5 U of Taq DNA polymerase (Biomatik, USA), 10 ng of DNA, and double-distilled water. PCR amplifications were performed under the following conditions: one cycle of initial DNA denaturation at 94°C for 5 min, followed by 35 cycles each one including a denaturation step of 30 s at 94°C, a second step of 1 min 30 s for annealing at the primer-specific Tm and an extension step of 1 min at 72°C, followed by a final extension for 5 min at 72°C. Table 1 Characteristics of ISSR and SRAP primers used for genetic diversity in Trifolium species ISSR primer codes Sequence (5’-3’) Tm * Unanchored primers ISSR1 (AG) 10 48 ISSR2 (AGG) 6 48 ISSR3 (ACTG) 4 47 Anchored primers at the 3' end by a single degenerate nucleotide ISSR4 (AG) 10 C 48 ISSR5 (AG) 10 G 48 ISSR6 (AG) 10 T 48 ISSR7 (CT) 10 A 48 ISSR8 (CT) 10 T 50 ISSR9 (CT) 10 G 47 ISSR10 (TC) 10 A 48 SRAP primer codes Sequence (5’-3’) Forward primers me1 TGAGTCCAAA CCGG ATA me2 TGAGTCCAAA CCGG AGC me4 TGAGTCCAAA CCGG ACC me8 TGAGTCCAAA CCGG TGC me10 TGAGTCCAAA CCGG TTG Reverse primers em2 GACTGCGTACG AATT TGC em3 GACTGCGTACG AATT GAC em14 GACTGCGTACG AATT ACG * Tm: Melting temperature for primer, In bold: The core motifs ‘CCGG’ in the forward primer and ‘AATT’ in the reverse primer. Underlined: The selective 3' end sequences. PCR-SRAP assays Ten SRAP primer-pair combinations were randomly selected from a set of five forward and three reverse primers (Table 1 ) (Li and Quiros 2001 ; Zeng et al. 2012 ). PCR amplifications were performed in a 25 µL reaction volume containing 30 ng genomic DNA, 10X PCR buffer, 0.25 mM each primer (reverse and forward), 3 mM MgCl 2 , 1 mM dNTPs, 1.5 U of Taq DNA Polymerase (Biomatik, USA), and double-distilled water. The thermal cycling program consisted of an initial denaturation at 95°C for 5 min; 5 cycles of 94°C for 1 min, 35°C for 1 min, 72°C for 1 min, followed by 35 cycles of 94°C for 1 min, 47°C for 1 min 30 sec, 72°C for 1 min, and a final extension at 72°C for 10 min. All amplifications for both techniques were carried out in an Applied Biosystems-Veriti thermocycler (Thermo Fisher Scientific, USA) Both PCR products were separated on a 1.5% agarose gel stained with 0.5 pg mL − 1 ethidium bromide and electrophoresed in 0.5X TBE buffer (pH 8.0) at 90 V for 1 h. The bands were visualized under UV light using a Gel-Doc 2000 image analysis system (Bio-Rad, USA). Data analysis Amplified products were compiled into a binary data matrix based on the presence (1) or absence (0) of each selected band to generate the 0/1-matrix. The discriminatory power of the markers in estimating genetic variability was evaluated using several informative indices: number of polymorphic bands (NPB), percentage of polymorphic bands (PPB), expected heterozygosity (H), polymorphism information content (PIC), multiplex ratio (EMR), marker index (MI), discriminating power (D) and resolving power (Rp). These indices were calculated using the iMEC online tool (Amiryousefi et al. 2018 ). Additionally, genetic diversity was assessed with different parameters, such as the effective number of alleles (Ne), Nei’s gene diversity (H), Shannon’s information index (I), total genetic diversity (Ht), genetic diversity within population (Hs), genetic differentiation (Gst), and gene flow (Nm) using POPGENE version 1.31 (Yeh et al. 1999 ). Furthermore, an analysis of molecular variation (AMOVA) was performed in GenAlEx 6.5 software (Peakall and Smouse 2012 ) to partition variance components within and among Trifolium species based on SRAP and ISSR markers. A dendrogram was constructed using Ward’s method (Ward 1963 ), and a principal component analysis (PCA) was applied to visualize genetic relationships among Trifolium genotypes based on Euclidian distances, both implemented in PAST software (Hammer et al. 2001 ). Furthermore, the genetic structure of the population was analysed using bayesian clustering approach implemented in STRUCTURE version 2.3.4 (Pritchard et al. 2000 ; Evanno et al. 2005 ). The optimal of genetic clusters (K) was determined following the ΔK method proposed by Evanno et al. ( 2005 ), which identifies the K value with the highest ΔK as the most probable number of clusters. STRUCTURE was run under an admixture model with prior information on sampling locations. For each potential K value (ranging from 1 to 7), 10 independent runs were performed, each consisting of 100.000 burn-in steps followed by 100.000 iterations. The online tool Structure Selector (Li and Liu 2018 ) was used to summarize and evaluate clustering solutions. To align and average the results from replicate runs, the Clumpak program (Kopelman et al. 2015 ) was employed using the “Greedy” algorithm with 10.000 random input sequences and an additional 10.000 repetitions to compute pairwise similarity scores (H’). Finally, the cluster membership proportions were visualized using Distruct version 1.1 (Rosenberg 2004 ). Results ISSR polymorphism The use of 10 ISSR primers produced 87 bands in total, of which 70 were polymorphic (PPB = 80.46%) across the 14 individuals studied (Table 2 ), highlighting the efficiency of these primers in detecting molecular polymorphism and differentiating between the two clover species. The number of bands generated varied considerably, ranging from 18 bands with the ISSR3 (ACTG)₄ primer to only 4 bands with both ISSR5 (AG)₁₀G and ISSR8 (CT)₁₀T, indicating differences in the ability of primers to reveal polymorphism within the species. Although three anchored primers (ISSR5 (AG)₁₀G, ISSR8 (CT)₁₀T, and ISSR9 (CT)₁₀G) exhibited the highest percentage of polymorphism (100%), they produced very few bands, and therefore contributed to limited information. In contrast, the two unanchored primers, ISSR3 (ACTG)₄ and ISSR1 (AG)₁₀, generated the greatest number of bands and showed high polymorphism levels (83.33% and 80%, respectively), as well as strong resolving power (Rp = 11.571 for ISSR3 (ACTG)₄ and 6.714 for ISSR1 (AG)₁₀). These two primers were therefore the most informative for distinguishing the genotypes of the two clover species. Table 2 Summary of polymorphism parameters of ten ISSR primers applied to Trifolium juliani and Trifolium squarrosum ISSR primers Band size (pb) TNB * NPB PPB (%) H PIC EMR MI D Rp ISSR1 814–2010 10 8 80 0.497 0.371 5.357 1.987 0.715 6.714 ISSR2 750–1515 6 3 50 0.337 0.438 4.714 2.065 0.385 2.571 ISSR3 450–2837 18 15 83.33 0.500 0.370 8.929 3.301 0.755 11.571 ISSR4 519–2174 14 11 78.57 0.487 0.376 8.143 3.064 0.663 9.429 ISSR5 478–1065 4 4 100 0.490 0.375 2.286 0.856 0.678 2.857 ISSR6 418–1380 5 4 80 0.467 0.386 3.143 1.212 0.608 3.429 ISSR7 608–2554 9 7 77.78 0.494 0.373 4 1.491 0.804 4 ISSR8 574–2300 4 4 100 0.459 0.389 2.571 1.001 0.591 2.571 ISSR9 794–2552 6 6 100 0.500 0.370 2.929 1.083 0.765 3.286 ISSR10 266–1527 11 8 72.73 0.497 0.371 5.929 2.200 0.711 5.857 Total 87 70 48 18.259 6.675 52.286 Mean 8.70 7 80.46 0.473 0.382 4.800 1.826 0.667 5.229 * TNB: Total number of bands; NBP: Number of polymorphic bands; PPB (%): Percentage of polymorphism; H: expected heterozygosity; PIC: Polymorphism Information content; EMR: effective multiplex ratio; MI: marker index; D: discriminatory power; Rp: Resolving power The polymorphism information content (PIC) values ranged from 0.370 for ISSR3 (ACTG)₄ to 0.438 for ISSR2 (AGG)₆, with an average of 0.382, indicating moderate to high informativeness of the ISSR primers in detecting genetic polymorphism. Figure 3 shows representative ISSR amplification profiles illustrating polymorphic bands that differentiate the two clover species. SRAP polymorphism Ten SRAP primer combinations generated a total of 63 bands, 46 of which were polymorphic, corresponding to a polymorphism percentage (PBP = 73.02%) (Table 3 ). In spite of the effectiveness in detecting molecular polymorphism and distinguishing the two taxa SRAP markers showed a lower PPB compared to ISSR markers. Among the tested combinations, four primer pairs (me1-em2, me2-em3, me8-em2, and me2-em14) were the most informative (Fig. 4 ), each producing more than 8 bands, with polymorphism percentages exceeding 70% and resolving power (Rp) values above 6. Overall, SRAP markers showed moderate informativeness, with a mean PIC value and close to 0.5 (0.363) and an average polymorphism percentage (PPB) of 73.02%. Both SRAP and ISSR markers were effective in revealing molecular polymorphism between the two clover species although ISSR markers proved slightly more informative based on their higher performance indices. Table 3 Summary of polymorphism parameters of ten SRAP primer combinations applied to Trifolium juliani and Trifolium squarrosum SRAP primer combination Band size (bp) TNB * NPB PPB (%) H PIC EMR MI D Rp me1-em2 282–1549 11 8 72.73 0.493 0.340 6.143 2.089 0.690 6.286 me1-em3 242–1433 4 3 75 0.469 0.352 2.500 0.880 0.614 3 me1-em14 422–850 3 2 66.67 0.408 0.378 2.143 0.811 0.495 1.714 me2-em2 141–1011 5 3 60 0.420 0.374 3.500 1.307 0.513 3 me2-em3 269–1545 10 7 70 0.431 0.369 6.857 2.529 0.531 6 me2-em14 338–1372 8 7 87.50 0.492 0.341 4.500 1.533 0.686 6.714 me4-em2 199–1573 6 5 83.33 0.308 0.414 4.857 2.012 0.347 2 me4-em3 717–1983 3 2 66.67 0.472 0.351 1.857 0.651 0.623 1.714 me8-em2 263–2110 10 7 70 0.485 0.344 5.857 2.015 0.659 5.143 me10-em2 774–2097 3 2 66.67 0.444 0.363 2 0.726 0.561 2 Total 63 46 40.214 14.553 5.717 37.571 Mean 6.3 4.6 73.02 0.442 0.363 4.021 1.455 0.572 3.757 * TNB: Total number of bands; NBP: Number of polymorphic bands; PPB (%): Percentage of polymorphism; H: expected heterozygosity; PIC: Polymorphism Information content; EMR: effective multiplex ratio; MI: marker index; D: discriminatory power; Rp: Resolving power Analysis of molecular variance and diversity indices of species The analysis of molecular variance (AMOVA) revealed a pronounced hierarchical structure in the distribution of genetic variation. The majority of the total variance was attributed to differences between the two species, accounting for 82.89% for ISSR and 84.85% for SRAP. In contrast, variation within species represented a considerably smaller proportion of the total genetic diversity (17.11% for ISSR and 15.15% for SRAP) (Table 4 ). This pattern of partitioning suggests strong genetic divergence between species and limited variability within each species. The pronounced interspecific differentiation is further corroborated by low estimates of gene flow (Nm = 0.198 for ISSR and Nm = 0.116 for SRAP) and high genetic differentiation coefficients (Gst = 0.716 for ISSR and Gst = 0.812 for SRAP) (Table 5 ). Table 4 Analysis of molecular variance (AMOVA) for Trifolium juliani and Trifolium squarrosum based on ISSR and SRAP markers ISSR markers Source of variation d.f. * Sum of squares Mean squares Estimates variance Percentage of variation Among species 1 154.571 154.571 21.449 82.89% Within species 12 53.143 4.429 4.429 17.11% Total 13 207.714 25.878 100% PhiPT 0.829 ** p-Value < 0.001 SRAP markers Source d.f. Sum of squares Mean squares Estimates variance Percentage of variation Among species 1 120.571 120.571 16.796 84.85% Within species 12 36 3 3 15.15% Total 13 156.571 19.796 100% PhiPT 0.848 ** p-Value < 0.001 * d.f.: degrees of freedom; ** p-Value : significance after 1000 random permutations Table 5 Genetic indices, genetic differentiation, and gene flow between T. juliani and T. squarrosum based on ISSR and SRAP data ISSR markers Species PPB (%) * Na Ne H I Ht Hs Gst Nm T. juliani 9.20 1.092 1.068 0.037 0.054 T. squarrosum 39.08 1.391 1.255 0.146 0.215 Average 24.14 1.241 1.161 0.091 0.134 Total 80.46 1.805 1.594 0.321 0.465 0.321 0.091 0.716 0.198 SRAP markers Species PPB (%) Na Ne H I Ht Hs Gst Nm T. juliani 7.94 1.079 1.059 0.032 0.046 T. squarrosum 25.40 1.254 1.157 0.089 0.133 Average 16.67 1.166 1.108 0.060 0.089 Total 73.02 1.730 1.622 0.323 0.457 0.323 0.061 0.812 0.116 * PPB (%): percentage of polymorphic bands (%); Na: Number of observed alleles per locus; Ne: Effective number of alleles per locus; H: Nei’s genetic diversity; I: Shannon diversity index; Ht: total diversity; Hs: mean diversity within populations; Gst: inter-population differentiation index; Nm: Number of migrants (gene flow). Genetic structuration The results obtained from principal component analysis (PCA), hierarchical clustering using Ward’s method based on Euclidean distances, and Bayesian clustering consistently revealed a clear separation of the two clover species into two major clusters (K = 2, ΔK > 200, H’=0.9 for ISSR, SRAP and combined datasets), corresponding to groups I and II across the three data matrices (Fig. 5 ). In the dendrogram, these two main clusters exhibited the highest robustness, with bootstrap values of 100%. Similarly, Bayesian analysis assigned more than 90% of genotypes to their respective clusters, conforming strong genetic differentiation between the species. However, two genotypes (TJ-7 and TS-9) displayed minor admixture signals (> 10%) with the second cluster, suggesting the existence of a weak but detectable shared genetic background, possibly reflecting ancestral polymorphism or limited historical gene flow not fully captured by the dominant markers used. Discussion Molecular markers such as SSRs and SNPs are widely used in Fabaceae to assess genetic diversity and population structure, providing critical insights for breeding and conservation strategies (Burstin et al. 2015 ; Hong et al. 2021 ). Their efficiency has been demonstrated in several legume crops, including chickpea, pea, and groundnut, through applications in marker-assisted selection, QTL mapping, and genome-wide association studies (Varshney et al. 2019 ; Jurado et al. 2024 ; Istanbuli et al. 2024 ). Meta-QTL and RNA-seq integration further enhance the resolution of candidate gene discovery (Izquierdo et al. 2023 ), and a functional markers derived from these studies enable precise introgression of traits into elite cultivars. Genomic prediction models, such as those developed in Medicago truncatula , demonstrate the predictive power of genome-wide marker data (Gentzbittel et al. 2015 ). Moreover, recent advances integrate genome editing with marker-based trait targeting, offering a path toward accelerated trait fixation (Kumar et al. 2024 ). All together, molecular markers bridge genetic variation analysis and modern breeding tools, facilitating efficient improvement of Fabaceae crops across environments. Despite these advances, dominant markers remain highly relevant, particularly for species with limited genomic resources. Arbitrarily Amplified DNA (AAD) markers - such as ISSR, offer high discriminating power without requiring prior sequence information, whereas Targeted Fingerprinting Markers (TFMs), including SRAP preferentially amplify functional regions, improving both resolution and reproducibility (Li and Quiros 2001 ; Poczai et al. 2013 ). These complementary approaches continue to be widely applied in Fabaceae for diversity analysis, genetic structure assessment, and breeding purposes (Uzun et al. 2009 ; Alghamdi et al. 2012 ). Despite being an old technique since 1994 (Zietkiewicz et al. 1994 ), numerous studies continue to highlight the effectiveness of ISSR markers. These markers are highly efficient in detecting molecular polymorphism without requiring prior sequence information, making them robust and cost-effective tools for assessing genetic diversity in various Fabaceae species (Poczai et al. 2013 ; Alzate-Marin et al. 2018 ; Qiang et al. 2018 ; Nurhasanah et al. 2023; Diallo et al. 2024 ). In addition, ISSR markers have proven useful in identifying mutant lines in evaluating responses to salt stress, and in supporting their relevance in marker-assisted breeding programs. Overall, ISSR markers offer high discriminating power and valuable applications in breeding and the management of genetic resources within the Fabaceae family. While SRAP markers have proven to be powerful tools for detecting molecular polymorphism due to their ability to amplify open reading frames, they have been made highly suitable for targeting coding regions in plant genomes (Li and Quiros 2001 ; Uzun et al. 2009 ). In Fabaceae, SRAP markers revealed high levels of polymorphism and discriminated effectively among closely related accessions, as demonstrated in Vicia faba (Alghamdi et al. 2012 ). Their high reproducibility and informativeness make them ideal for assessing genetic structure, diversity, and evolutionary relationships (Li and Quiros 2001 ). Overall, SRAP markers offer a robust and gene-targeted molecular tool for genetic improvement and breeding programs in Fabaceae (Li and Quiros 2001 ; Alghamdi et al. 2012 ). In the local clover species, particularly Trifolium squarrosum and Trifolium juliani (an endemic species of Tunisia and Algeria), accurate genetic characterization is essential due to their sympatric distribution and significant potential for forage improvement. Differentiating these taxa is a prerequisite for effective conservation strategies and for exploiting inter- and intra-specific genetic variability in breeding programs. The present study assessed genetic diversity and population structure in these species using ISSR and SRAP markers to establish a robust framework for their sustainable use and genetic enhancement. Both marker systems were chosen for their proven efficiency in diversity studies and demonstrated high levels of polymorphism (> 73%) and substantial polymorphic information content (PIC = 0.382 for ISSR and 0.363 for SRAP), confirming their suitability for detecting molecular variation.. These results are consistent with previous reports on clover species (Abate and Tesfaye 2017 ; Abate 2017 ; Yousefi et al. 2018 ; Youssef et al. 2019 ; Mostafa Mohamed et al. 2024 ). Additionally, ISSR markers exhibited slightly higher values for genetic differentiation (H, PIC, EMR, MI, D, and Rp) than SRAP markers, corroborating the observations by Mostafa Mohamed et al. ( 2024 ). The variations in genetic similarity observed across different marker types may reflect differences in their mechanisms which are provided to detect polymorphisms. It may also show the extent of the sequencing genome coverage. Consequently, genetic similarity derived from combined datasets offers a more comprehensive representation of genetic relationships. Unlike ISSR markers, which are randomly distributed across the genome, SRAP markers specifically target open reading frame (ORF) sequences, corresponding to relatively conserved coding regions, thereby focusing on the functional genomic regions. In contrast, random markers such as ISSR capture a broader range of molecular polymorphism can be considerably informative when differentiating closely related species. This difference may explain why ISSR markers provided slightly higher genetic differentiation values than SRAP in the present study. The molecular analysis of variance (AMOVA) revealed a highly significant partitioning of genetic variation between the two species, confirming their clear differentiation. Intraspecific variance was comparatively low. Yet it highlights the presence of substantial genetic variability within each species. This structuring pattern was further supported by low estimates of gene flow and high genetic differentiation indices, reflecting the self-incompatibility system typical of clovers, favors outcrossing and limits interspecific hybridization (Casey et al. 2010 ). Multivariate and clustering analyses consistently corroborated these findings. PCA and Ward’s hierarchical clustering separated all accessions into two major groups corresponding to T. juliani and T. squarrosum, while Bayesian inference identified K = 2 as the most probable number of clusters (ΔK > 200, H’ = 0.9). Most genotypes were assigned to their respective clusters with high probability (> 90%) although two genotypes (TJ-7 and TS-9) exhibited minor admixture signals, suggesting possible shared ancestry or historical gene flow. These complementary analyses provide strong evidence of species-level differentiation, while also revealing subtle genetic connections among certain genotypes. Combining ISSR and SRAP data improved structural resolution by integrating signals from random and functional genomic regions, and by providing a holistic view of diversity. The concordance among these approaches further validates the robustness of our results and emphasizes the necessity of combining complementary marker systems in analyses of outcrossing species. Overall, the clear genetic separation, despite some rare signs of admixture, shows the importance of using combined approaches that consider both species distinctness and occasional interspecific gene flow, to ensure effective conservation and targeted breeding strategies. Conclusion This study provides the first molecular characterization of T. squarrosum ssp parnomitanum and T. juliani , revealing high genetic diversity and a clear species-level distinction using ISSR and SRAP markers. The results highlight the value of complementary markers for studying outcrossing species. These findings establish a foundation for effective conservation and targeted breeding strategies to enhance the genetic potential of clover crops. Future studies should integrate next-generation sequencing (NGS) and genome-wide association studies (GWAS) with traditional marker-based approaches to achieve high-resolution mapping of adaptive traits in clovers. Combining these genomic tools with interspecific hybridization and genomic selection will enhance the use of the genetic diversity identified in this study, enabling the development of resilient, high-performing forage cultivars tailored for sustainable agriculture. Declarations Acknowledgements The authors are grateful for the valuable contribution of les Amis de CAPTE (Collectif d’Acteurs Pour la Transition Environnementale) for its support to the Project Trefles at Dyr El Kef entitled “Ensemble pour la restauration des écosystèmes avec des agriculteurs locaux engagés à Dyr el Kef, Tunisie” with was funded by the CEPF (Critical Ecosystem Partnership Fund) between 2021 and 2024. The authors would like to express their sincere gratitude to Professor Zeineb Ghrabi-Gammarand her PhD student Emna Belaifa for their consistant contribution to the recognition of collected clover species based on their taxonomic skills. The authors would like to express their sincere gratitude to Miss Dorra Ben Nasr for helping improve the clarity and flow of this research paper. She is an experienced English teacher who collaborates with several international institutions, including Bourguiba School, Tunisian Private University, and Eight Hospitality Business School. Her support and expertise were greatly appreciated throughout the writing process. Author contributions KG supervised and conducted the molecular experiments, performed data analysis, prepared the figures, interpreted the results, and drafted the entire manuscript. AZ-K conceived the study design, was involved in the overall supervision of the project, and contributed to manuscript revision and editing. NC-G supervised the molecular experiments and revised the manuscript. SSK and SBY contributed in all prospections to collect and identify Trifolium species. EJ and HC participated in the sampling of clover specimens for the study as part of the project and also contributed to manuscript revision. All authors have read and approved the final version of the manuscript. Funding This research was partially supportet by the Trefles Project hosted at INRAT (at the Laboratory of Animal and Forage Production) (LR16INRAT01) and managed by CAPTE and also benefited from logistical support provided by the Laboratory of Molecular Genetics, Immunology and Biotechnology (LR99ES12) at the Faculty of Sciences of Tunis. Data availability All data supporting the findings are available within the manuscript. Conflict of interest/competing interests The authors declare that they have no known competing financial or non-financial interests related to the content of this article. References Abate T (2017) Genetic Diversity Study of Steudneri Clover ( Trifolium steudneri ) Accessions of Ethiopia Using Inter Simple Sequence Repeat (ISSR) Markers. Advances in Life Science and Technology54. ISSN 2224-7181 (Paper) ISSN 2225-062X (Online). Abate T, Tesfaye K (2017) Genetic Diversity in quarin Clover ( Trifolium quartinianum ) Accessions of Ethiopia Using Inter Simple Sequence Repeat (ISSR) Markers. African journal of biotechnology 16 (16): 869–878. https://doi.org/10.5897/AJB2015.14846 Alghamdi SS, Al-Faifi SA, Migdadi HM, Khan MA, El-Harty EH, Ammar MH (2012) Molecular diversity assessment using Sequence Related Amplified Polymorphism (SRAP) Markers in Vicia faba L. Int J Mol Sci 13(12): 16457–16471. https://doi.org/10.3390/ijms131216457 Alzate-Marin AL, Costa-Silva C, Sá Rivas PM, Bonifacio-Anacleto F, Santos LG, de Moraes Filho RM, Martinez CA (2018) Diagnostic fingerprints ISSR/SSR for tropical leguminous species Stylosanthes capitata and Stylosanthes macrocephala . Sci. Agric 77(3) : e20180252. http://dx.doi.org/10.1590/1678-992X-2018-0252 Amiryousefi A, Hyvönen J, Poczai P (2018) iMEC: Online Marker Efficiency Calculator. Applications in Plant Sciences 6(6): e1159. http://dx.doi.org/10.1002/aps3.1159 Aryanegad P, Farshadfar E, Safari H, Shirvani H (2013) Application of ISSR molecular markers in genetic diversity of three Trifolium species. J. Bio. & Env. Sci 3: 78–84. ISSN: 2220-6663 (Print) 2222-3045 (Online) Beji S, Khemir E (2012) Performance of two forage associations, triticale-berseem and triticale-common vetch, in a semi-arid environment in Tunisia. Fourrages 212: 337–342. Ben Salem H, Smith T (2008) Feeding strategies to increase small ruminant production in dry environments. Small Ruminant Research 77: 174–194. https://doi.org/10.1016/j.smallrumres.2008.03.008 Burstin J, Salloignon P, Chabert-Martinello M, Magnin-Robert J-B, Siol M, Jacquin F, Chauveau A, Pont C, Aubert G, Delaitre C, Truntzer C, Duc G (2015) Genetic diversity and trait genomic prediction in a pea diversity panel. BMC Genomics 16 : 105. https://doi.org/10.1186/s12864-015-1266-1 Casey NM, Milbourne D, Barth S, Febrer M, Jenkins G, Abberton MT, Jones C, Thorogood D (2010) The genetic location of the self-incompatibility locus in white clover ( Trifolium repens L.). Theor Appl Genet121(3): 567–576. https://doi.org/10.1007/s00122-010-1330-9 Clegg MT, Zurawski G (1991) Chloroplast DNA and the study of plant phylogeny. In: Soltis PS, Soltis DE, Doyle JJ (ed) Molecular systematics of plants. Chapman & Hall, New York, pp 1–13. Dabkevičienė G, Paplauskienė V, Vilčinskas E (2011) Assessment of genetic diversity in Trifolium spp. Using ISSR and RAPD markers. Journal of Food, Agriculture & Environment 9: 210–214. Dabkevičienė G, Paplauskienė V (2012) A study of genetic diversity in Trifolium hybridum varieties using morphological characters and ISSR markers. Žemdirbystė-Agriculture 99(3): 313–318. ISSN: 1392-3196. Diallo S, Badiane FA, Kabkia BA, Diédhiou I, Diouf M, Diouf D (2024) Genetic diversity and population structure of cowpea mutant collection using SSR and ISSR molecular markers. Sci Rep 14: 31833. http://dx.doi.org/10.1038/s41598-024-83087-y Ellison NW, Liston A, Steiner JJ, Williams WM, Taylor NL (2006) Molecular phylogenetics of the clover genus ( Trifolium —Leguminosae). Molecular Phylogenetics and Evolution 39: 688–705. http://dx.doi.org/10.1016/j.ympev.2006.01.004 Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14: 2611–2620. http://dx.doi.org/ 10.1111/j.1365-294X.2005.02553.x Evans AM (1976) Clovers. In: Simmonds NW (ed) Evolution of Crop Plants, Longman, London, pp 175–179. Ewing MA (1996) Successful pasture legumes in ley farming systems. In: Bennett SJ, Cocks PS (eds.) Genetic Resources of Mediterranean Pasture and Forage Legumes. Proceedings of international Workshop, Perth, Australia, 14-18 October1996. Gentzbittel L, Ben C, Mazurier M, Shin M-G, Triska M, Rickauer M, Nikolsky Y, Marjoram P, Nuzhdin S, Tatarinova T (2015) Whole-genome modeling accurately predicts quantitative traits in plants. Populations and Evolution. (arXiv). https://doi.org/10.48550/arXiv.1511.02514 Gibson DJ (2008) Grasses and grassland ecology. Oxford University Press, 2009 - 305 pages. http://dx.doi.org/10.1093/aob/mcp2019 Gielly L, Taberlet P (1996) A phylogeny of the European gentians inferred from chloroplast trnL (UAA) intron sequences. Bot. J. Linn. Soc 120(1): 57–75. https://doi.org/10.1111/j.1095-8339.1996.tb00480.x Gillett JM (1970) On the Taxonomy of the Genus Trifolium L. In: Report of the Trifolium research work conference, Clemson, California, USA, pp 26–46. Gillett JM, Taylor N (2001) The World of Clovers. Iowa State University Press, Ames, Iowa, USA. Hammer Ø, Harper DAT, Ryan PD (2001) PAST: Paleontological statistics software package for education and data analysis. Palaeontol. Electron 4(1): 9 pages. http://palaeo-electronica.org/2001_1/past/issue1_01.htm Herman FJ (1953) A botanical synopsis of the cultivated clovers (Trifolium) Agriculture Monograph No. 25. pp. 1–45. United States Department of Agriculture, Washington D.C, USA. Hong Y, Pandey MK, Lu Q, Liu H, Gangurde SS, Li S, Liu H, Li H, Liang X, Varshney RK, Chen X (2021) Genetic diversity and distinctness based on morphological and SSR markers in peanut. Agronomy Journal 113(6) : 4648–4660. https://doi.org/10.1002/agj2.20671 Hossain M (1961) A revision of Trifolium in the Nearer East. Notes from the Royal Botanic Garden Edinburgh23: 387–481. https://doi.org/10.24823/nrbge.1961.2591 ILDIS (1999) International Legume Database and Information Service. http://www.ildis.org. Accessed 20 May 2025 Istanbuli I, Nassar AE, Abd El-Maksoud MM, Tawkaz S, Alsamman AM, Hamwieh A (2024) Genome-wide association study reveals SNP markers controlling drought tolerance and related agronomic traits in chickpea across multiple environments. Front. Plant Sci, Sec. Plant Abiotic Stress 15:1260690. https://doi.org/10.3389/fpls.2024.1260690 Izquierdo P, Kelly JD, Beebe SE, Cichy K (2023) Combination of meta-analysis of QTL and GWAS to uncover the genetic architecture of seed yield and seed yield components in common bean. The Plant Genome 16(2): e20328. https://doi.org/10.1002/tpg2.20328 Jaritz G (1982) Amélioration des herbages et cultures fourragères dans le nord-ouest de la Tunisie : études particulières des prairies de trèfles, graminées avec Trifolium subterraneum L. Ed. GTZ. 345 pp. Jurado M, García-Fernández C, Campa A, Ferreira JJ (2024) Identification of consistent QTL and candidate genes associated with seed traits in common bean by combining GWAS and RNA-Seq. Theor Appl Genet 137(6): 143. https://doi.org/10.1007/s00122-024-04638-5 Katznelson J (1974) Biological Flora of Israel, 5: The subterranean clovers of Trifolium subsect. Calycomorphum Katzn. Trifolium subterraneum L. (sensu lato). Israel Journal of Botany 23: 69-108. Kopelman NM, Mayzel J, Jakobsson M, Rosenberg NA, Mayrose I (2015) Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resours 15: 1179–1191. https://doi.org/10.1111/1755-0998.12387 Kumar R, Das SP, Choudhury BU, Kumar A, Prakash NR, Verma R, Chakraborti M, Devi AG, Bhattacharjee B, Das R, Das B, Devi HL, Das B, Rawat S, Mishra VK (2024) Advances in genomic tools for plant breeding: harnessing DNA molecular markers, genomic selection, and genome editing. Biol Res 57(1): 80. https://doi.org/10.1186/s40659-024-00562-6 Lamont EJ, Zoghlami A, Hamilton RS, Bennett SJ (2001) Clovers ( Trifolium L.). In: Maxted, N., Bennett, S.J. (eds) Plant Genetic Resources of Legumes in the Mediterranean. Current Plant Science and Biotechnology in Agriculture, 1 st edn, Springer, Dordrecht, Netherlands, vol 39. pp 79–98. https://doi.org/10.1007/978-94-015-9823-1_4 Le Floc’h E, Boulos L, Véla E (2010) Catalogue synonymique commenté de la flore de Tunisie. Tunis: Banque nationale de gènes. Errata 2011. 504 pages. https://hal.science/hal-05015706/document. Accessed 20 May 2025 Li G, Quiros CF (2001) Sequence-related amplified polymorphism (SRAP), a new marker system based on a simple PCR reaction: its application to mapping and gene tagging in Brassica. Theor Appl Genet 103: 455–546. https://doi.org/10.1007/s001220100570 Li YL, Liu JX (2018) Structure Selector: a web based software to select and visualize the optimal number of clusters using multiple methods. Mol Ecol Resour 18: 176–177. https://doi.org/10.1111/1755-0998.12719 McGuire WS (1985) Subterranean clover. In : Taylor NL (ed) Clover science and technology, 25 th edn, American Society of Agronomy, Madison, USA, pp. 515–534. https://doi.org/10.2134/agronmonogr25.c23 Mostafa Mohamed H, Sayed Mohamed El‑Assal S, Gamal El‑Din AY, El‑Khishin DA (2024) Analysis of genetic diversity and population structure in some Egyptian Berseem ( Trifolium alexandrinum ) accessions based on ISSR, SCoT and SRAP markers. Genet Resour Crop Evol 71: 4885–4899. https://doi.org/10.1007/s10722-024-01940-5 Nurhasanah, Hindersah R, Suganda T, Concibido V, Sundari, Karuniawan A (2023) The First Report on the Application of ISSR Markers in Genetic Variance Detection among Butterfly Pea ( Clitoria ternatea L.) Accession in North Maluku Province, Indonesia. Horticulturae 9(9): 1059. https://doi.org/10.3390/horticulturae9091059 Paplauskienė V, Dabkevičienė G (2008) Genetic variability determination using ISSR–PCR markers in red clover varieties. Biologija 54: 56–59. https://doi.org/10.2478/v10054-008-0011-y Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research–an update. Bioinformatics 28: 2537–2539. http://dx.doi.org/ 10.1093/bioinformatics/bts460 Poczai P, Varga I, Laos M, Cseh A, Bell N, Valkonen JPT, Hyvönen J (2013) Advances in plant gene-targeted and functional markers : a review. Plant Methods 9:6. Pages : 31. http://www.plantmethods.com/content/9/1/6 Pottier-Alapetite G (1979) Flore de la Tunisie (Angiospermes-Dicotylédones). 2 vol. (1979 and 1981) Publications scientifiques tunisiennes, Ministère de l’Enseignement supérieur et de la Recherche Scientifique, Ministère de l’Agriculture, Tunis. https://bibdigital.rjb.csic.es/idurl/1/12768 POWO (2025) Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew. Published on the Internet ; https://powo.science.kew.org/ Retrieved 23 September 2025. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics. 155: 945–959. http://dx.doi.org/ 10.1093/genetics/155.2.945 Qiang Z, Wang Y, Li S, Wang M, Luo X, Li X, Feng X, Li C (2018) Efficiency of ISSR marker in assessing the genetic diversity of wild and cultivated Hedysarum polybotrys Hand. Mazz. Caryologia 71(2): 174–181. https://doi.org/10.1080/00087114.2018.1453322 Ravagnani A, Abberton MT, Skøt L (2012) Development of genomic resources in the species of Trifolium L. and its application in forage legume breeding. Agronomy 2: 116–131. https://doi.org/10.3390/agronomy2020116 Rizza M, Real D, Reyno R, Porro V, Burgueco J, Errico E, Quesenberry K (2007) Genetic diversity and DNA content of three South American and three Eurasiatic Trifolium species. Genetics and Molecular Biology 30(4): 1118–1124. https://doi.org/10.1590/S1415-47572007000600015 Rosenberg NA (2004) distruct: a program for the graphical display of population structure. Mol Ecol Notes 4: 137–138. https://doi.org/10.1046/j.1471-8286.2003.00566 Russell JS, Webb HR (1976) Climatic range of grasses and legumes used in pastures: Results of a survey conducted at the 11 th International Grassland Congress. Journal of the Australian Institute of Agricultural Science 42: 156–166. Russi L, Cocks PS, Roberts EH (1992) The fate of legume seeds eaten by sheep from a Mediterranean grassland. Jounal of Applied Ecology 29(3): 772–778. https://doi.org/10.2307/2404487 Sambrook J, Fritsch EF, Maniatis T (1989) Molecular cloning: A laboratory manual (Second edition), Volumes 1, 2 and 3. Cold Spring Harbor Laboratory Press. https://doi.org/10.1002/jobm.3620300824 Speer GS, Allinson DW (1985) Kura clover ( Trifolium ambiguum ): Legume for forage and soil conservation. Economic Botany 39(2): 165–175. https://doi.org/10.1007/BF02907841 Sprent J (2001) Nodulation in Legumes. Royal Botanic Gardens, Kew. PMCID: PMC4233837 Uzun A, Yesiloglu T, Aka-Kacar Y, Tuzcu O, Gulsen O (2009) Genetic diversity and relationships within Citrus and related genera based on sequence related amplified polymorphism markers (SRAPs). Scientia Horticulturae 121: 306–312. https://doi.org/10.1016/j.scienta.2009.02.018 vanKeuren RW, Hoveland CS (1985) Clover Management and Utilization. In: Taylor NL (ed) Clover science and technology, 25 th edn, American Society of Agronomy, Wisconsin, USA, pp. 326–354. Varshney RK, Pandey MK, Bohra A, Singh VK, Thudi M, Saxena RK (2019) Toward the sequence-based breeding in legumes in the post-genome sequencing era. Theor Appl Genet 132: 797–816. https://doi.org/10.1007/s00122-018-3252-x Ward JH Jr (1963) Hierarchical Grouping to Optimize an Objective Function. Journal of the American Statistical Association 58: 236–244. https://doi.org/10.1080/01621459.1963.10500845 Yeh FC, Yang RC, Boyle T (1999) POPGENE version 1.31. University of Albert and Center for International Research. Available at: http://www.ualberta.ca/~fyeh/popgene.html. Yousefi S, Saeidi H, Assadi M (2018) Genetic diversity analysis of red clover ( Trifolium pratense L.) in Iran using sequence related amplified polymorphism (SRAP) markers. J Agric Sci Technol 20(2) :373–386. https://jast.modares.ac.ir/article_16151_51d7224dc661635dad39ba553e288220.pdf Youssef SS, Ibrahim SA, Abdel Azim AM, Khashaba EH, El-Sharkawy AM (2019) Genetic variation among five egyptian clover cultivars using random amplified polymorphic DNA (RAPD) and sequence-related amplified polymorphism (SRAP) molecular markers. Egypt Acad J Biol Sci Physiol Mol Biol 11(2): 37–45. https://doi.org/10.21608/eajbsc.2019.31758 Zeng B, Wang G, Zuo F, Chen Z, Zhang X (2012) Genetic diversity analysis of cocksfoot ( Dactylis glomerata L.) accessions with sequence-related amplified polymorphism (SRAP) and inter-simple sequence repeat (ISSR) markers. African Journal of Biotechnology 11(67): 13075–13084. https://doi.org/10.5897/AJB11.3410 Zietkiewicz E, Rafalski A, Labuda D (1994) Genome fingerprinting by simple sequence repeat (SSR)-anchored polymerase chain reaction amplification. Genomics 20: 176–183. https://doi.org/10.1006/geno.1994.1151 Zoghlami A, Hassen H, Robertson LD, Reid B (1995) Observations sur la répartition et l’écologie des espèces de Trifolium et de Scorpiurus au nord de la Tunisie. Al Awamia 90: 115–120. https://www.inra.org.ma/sites/default/files/09011.pdf Zoghlami-Khélil A, Benyoussef S, Mezni M, Saïdi Missaoui H, Hanchi S, Elayed M, Gouhis F, Abdelguerfi A, Laouar M, Papastylianou P, Bilalis D, Cicek H, Ates S, Dost M (2015) Berseem clover ( Trifolium alexandrinum L.) in the Mediterranean Basin. Legume Perspectives 10: 27–28. https://www.legumesociety.org/wp-content/uploads/2019/12/legum_perspect_10.pdf Zohary M (1970) Chapter 46. Trifolium L., In: Davis PH (ed) Flora of Turkey and the East Aegean Islands, Edinburgh University Press, Edinburgh, Scotland, vol.3, pp 384–448. Zohary M, Heller D (1984) The genus Trifolium, The Israel Academy of Sciences and Humanities, Jerusalem. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8229370","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":552214783,"identity":"5adead2e-f4dc-4737-b699-1568a808fff2","order_by":0,"name":"Karim Guenni","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBACCSA+AOMc+GBDqpaDM9JAAsxAZgJ+LXDAzEOMFsn2sw8P3WCoTeyX7j142Cahro5BIv/oBsYfd3BqkeZJNzicw3A8ceaccwmHcxIOSzBIJLPdYEh4hlOLHEMaA1DLscQNN3IMDuf+OADTchi3Fv5nEC37QVosEuoIa5GWANtSk7hBAqiFIYGZsBbJGSBbDA4YzwDacrAn4bBkG89jsxsJabi1SJxPY/6cU1En2z8jx/jDj4Q6fn72xGc3Ptjg1gIBBkgK2EBEAgENQFBHWMkoGAWjYBSMXAAAgypVcii11BIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-6760-9123","institution":"Laboratory of Molecular Genetics, Immunology and Biotechnology (LR99ES12), Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia","correspondingAuthor":true,"prefix":"","firstName":"Karim","middleName":"","lastName":"Guenni","suffix":""},{"id":552214784,"identity":"30158486-e194-477c-a9fb-5737b0533e3d","order_by":1,"name":"Nidhal Chtourou-Ghorbel","email":"","orcid":"https://orcid.org/0000-0002-8289-1956","institution":"Laboratory of Molecular Genetics, Immunology and Biotechnology (LR99ES12), Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia","correspondingAuthor":false,"prefix":"","firstName":"Nidhal","middleName":"","lastName":"Chtourou-Ghorbel","suffix":""},{"id":552214785,"identity":"abb9f602-33fe-413b-9fd7-b305415ea883","order_by":2,"name":"Salma Sai Kachout","email":"","orcid":"https://orcid.org/0000-0002-8519-3432","institution":"Laboratory of Animal and Forage Production (LR16INRAT01), National Institute of Agronomic Research of Tunis, University of Carthage, Tunis, Tunisia.","correspondingAuthor":false,"prefix":"","firstName":"Salma","middleName":"Sai","lastName":"Kachout","suffix":""},{"id":552214786,"identity":"9b8b607c-fd10-490e-bb00-d771ee16d5f6","order_by":3,"name":"Salah Ben Youssef","email":"","orcid":"https://orcid.org/0000-0003-4213-048X","institution":"Laboratory of Animal and Forage Production (LR16INRAT01), National Institute of Agronomic Research of Tunis, University of Carthage, Tunis, Tunisia.","correspondingAuthor":false,"prefix":"","firstName":"Salah","middleName":"Ben","lastName":"Youssef","suffix":""},{"id":552214787,"identity":"90a6c120-98ec-4ca9-9f10-d751913223f8","order_by":4,"name":"Edouard Jean","email":"","orcid":"","institution":"CAPTE (Collectif d’Acteurs pour la Plantation et la Transition Environnementale), Marseille, France.","correspondingAuthor":false,"prefix":"","firstName":"Edouard","middleName":"","lastName":"Jean","suffix":""},{"id":552214788,"identity":"25ad8850-33c6-4a7f-8547-f6834fc439a5","order_by":5,"name":"Hazem Cherni","email":"","orcid":"","institution":"Association les amis de CAPTE, Bizerte, Tunisia","correspondingAuthor":false,"prefix":"","firstName":"Hazem","middleName":"","lastName":"Cherni","suffix":""},{"id":552214789,"identity":"be0c64fd-7721-4f6c-a2be-ed0fe548d832","order_by":6,"name":"Aziza Zoghlami-Khelil","email":"","orcid":"https://orcid.org/0000-0002-3194-7817","institution":"Laboratory of Animal and Forage Production (LR16INRAT01), National Institute of Agronomic Research of Tunis, University of Carthage, Tunis, Tunisia.","correspondingAuthor":false,"prefix":"","firstName":"Aziza","middleName":"","lastName":"Zoghlami-Khelil","suffix":""}],"badges":[],"createdAt":"2025-11-28 10:26:32","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8229370/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8229370/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97226358,"identity":"e00fa428-fe1e-40ad-8753-95867d248df8","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":92204,"visible":true,"origin":"","legend":"","description":"","filename":"1.Guennietal.2025Trifolium.docx","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/b356aa0826598ad1514f1045.docx"},{"id":97226361,"identity":"8ad3792a-a77e-4ed3-a03a-6c20559a4239","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs8229370.json","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/4b8e65e9fe1793ef1e812c71.json"},{"id":97226364,"identity":"aa51949c-bde9-4121-b9a0-926773432df1","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":200751,"visible":true,"origin":"","legend":"","description":"","filename":"rs82293700enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/15029cca985bd2177fb99670.xml"},{"id":97226365,"identity":"41200a0c-5f42-4515-8b3c-8e18dbbac61d","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":198391,"visible":true,"origin":"","legend":"","description":"","filename":"rs82293700structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/d6d928e2438b3ed6023540ae.xml"},{"id":97226366,"identity":"b36e74c5-efb7-49fc-a86f-7f1d0ecd248b","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":209497,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/ceb1fd143f9ccf3226996072.html"},{"id":97226360,"identity":"827e34db-ae17-48a6-963a-18bd6327f5ae","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":266325,"visible":true,"origin":"","legend":"\u003cp\u003eLocalisation of Dyr El Kef (Tunisia)\u003c/p\u003e","description":"","filename":"Fig1.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/dedd4d44e2e9a71274b220f9.jpg"},{"id":97226363,"identity":"138aec84-43de-4124-b4b8-bc01c4d3d6e2","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":630627,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTrifolium juliani\u003c/em\u003e (A) and \u003cem\u003eTrifolium squarrosum ssp. parnomitanum \u003c/em\u003e(B)\u003cem\u003e, \u003c/em\u003edistinguished in particular by their calyxes during recent surveyscollected in Dyr El Kef\u003c/p\u003e","description":"","filename":"Fig2.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/a800b4ff33b03acc0bd20ab9.jpg"},{"id":97250052,"identity":"80391f6f-3e3a-45cc-88e2-baa50e4fb564","added_by":"auto","created_at":"2025-12-02 13:13:49","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":601567,"visible":true,"origin":"","legend":"\u003cp\u003eAmplification profiles of representative ISSR markers\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. 3 footnotes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eL1\u003c/strong\u003e: 1kb DNA Ladder (BLUE, GeneON, UK, for ISSR-1, ISSR-4 and ISSR-8 / Biomatik, USA, for ISSR-3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eL2\u003c/strong\u003e: 100 pbDNA Ladder (Plus Blue, GeneON, UK, for ISSR-1, ISSR-4 and ISSR-8 / Biomatik, USA, for ISSR-3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNc:\u003c/strong\u003e Negative control\u003c/p\u003e\n\u003cp\u003eNumbers 1 to 7 represent \u003cem\u003eTrifolium juliani \u003c/em\u003esamples, and numbers 8 to 14 represent to \u003cem\u003eTrifolium\u003c/em\u003e \u003cem\u003esquarrosum\u003c/em\u003e samples. Polymorphic bands differentiating the two species are indicated on the gel images. Primer codes are listed in Table 1\u003c/p\u003e","description":"","filename":"Fig3.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/3f931c1aa8b4406cc851abb2.jpg"},{"id":97226357,"identity":"27434a42-df0c-4294-9db2-81d81bf07e98","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":746513,"visible":true,"origin":"","legend":"\u003cp\u003eAmplification profiles of representative SRAP markers\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. 4 footnotes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eL1\u003c/strong\u003e: 1kb DNA Ladder (Biomatik, USA)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eL2\u003c/strong\u003e: 100 pb DNA Ladder (Biomatik, USA)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNc:\u003c/strong\u003e Negative control\u003c/p\u003e\n\u003cp\u003eNumbers 1 to 7 represent \u003cem\u003eTrifolium juliani \u003c/em\u003esamples, and numbers 8 to 14 represent to \u003cem\u003eTrifolium\u003c/em\u003e \u003cem\u003esquarrosum\u003c/em\u003e samples. Polymorphic bands differentiating the two species are indicated on the gel images. Primer codes are provided in Table 1\u003c/p\u003e","description":"","filename":"Fig4.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/de904c0f408c3f8583df8396.jpg"},{"id":97226359,"identity":"18b5b636-b40f-45e6-986d-79e8d2bf7a6a","added_by":"auto","created_at":"2025-12-02 08:25:03","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1812628,"visible":true,"origin":"","legend":"\u003cp\u003eGenetic structure of two clover species, based on ISSR and SRAP molecular markers\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. 5 footnotes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTJ-1 to TJ-7 represent the seven individuals of \u003cem\u003eT. juliani\u003c/em\u003e, and TS-8 to TS-13 represent the seven individuals of \u003cem\u003eT. squarrosum\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eA, B and C: Principal component analysis based on ISSR, SRAP, and combined marker data, respectively.\u003c/p\u003e\n\u003cp\u003eD, E and F: Hierarchical clustering based on ISSR, SRAP, and combined marker data, respectively.\u003c/p\u003e\n\u003cp\u003eG, H and I: Bayesian analysis implemented in \u003cem\u003eSTRUCTURE\u003c/em\u003ebased on ISSR, SRAP and combined marker data, respectively\u003c/p\u003e","description":"","filename":"Fig5.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/409863d6cce74aeafb79ac58.jpg"},{"id":97252516,"identity":"c5c5e67d-cde1-408b-a1ce-44f396d4e2d4","added_by":"auto","created_at":"2025-12-02 13:22:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5161642,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8229370/v1/e22d2372-e45d-4470-82c9-d3511f8eed24.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe first molecular characterization of the Tunisian-Algerian endemic \u003cem\u003eTrifolium juliani\u003c/em\u003eBatt. and \u003cem\u003eTrifolium squarrosum \u003c/em\u003eL\u003cem\u003e.\u003c/em\u003e from Dyr El Kef, North West Tunisia\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGrasslands cover approximately 20 to 40% of the world\u0026rsquo;s agricultural land; they are crucial not only for food production, but also for climate change, mitigation and the provision of key ecosystem services. These services include water regulation, biodiversity preservation, and carbon sequestration within their root systems, which represent about 90% of total grass biomass (Gibson \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Forage grasses and legumes are key components of grasslands worldwide. In temperate regions, a relatively small number of species dominate, including \u003cem\u003eLolium perenne\u003c/em\u003e, \u003cem\u003eFestuca\u003c/em\u003e spp., and \u003cem\u003eDactylis glomerata\u003c/em\u003e among grasses, and \u003cem\u003eTrifolium\u003c/em\u003e spp., \u003cem\u003eMedicago\u003c/em\u003e spp., and \u003cem\u003eLotus\u003c/em\u003e spp. among legumes (Ravagnani et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe genus \u003cem\u003eTrifolium\u003c/em\u003e L. (Clover) belongs to the Fabaceae (Leguminosae) family, within the subfamily Papilionaceae, and is one of the largest genera in the tribe Trifolieae (Ellison et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). \u003cem\u003eTrifolium\u003c/em\u003e is grouped with closely related genera, including \u003cem\u003eTrigonella\u003c/em\u003e, \u003cem\u003eMedicago\u003c/em\u003e, and \u003cem\u003eMelilotus\u003c/em\u003e. However, numerous revisions of the genus have been published, and several comprehensive reviews of its taxonomic history are available, such as those by Hossain (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1961\u003c/span\u003e), Gillet (1970), and Zohary and Heller (\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e1984\u003c/span\u003e) (Lamont et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eClover is native to all humid, temperate regions worldwide, except for the Himalayas and Australasia. The three primary centers of diversity for the genus \u003cem\u003eTrifolium\u003c/em\u003e are Turkey (Mediterranean center), Ethiopia (African center), and northern California, USA (American center) (Zohary and Heller \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). Recent studies supported a Mediterranean origin for the genus during the Early Miocene, around 16\u0026ndash;23\u0026nbsp;million years ago (Ellison et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), with the eastern Mediterranean showing the greatest species diversity, including many commercially significant forage species (Russi et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1992\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong the 299 Trifolium species recognized worldwide (POWO \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), 217 of which are accepted by the ILDIS (International Legume Database and Information System (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ildis.org\u003c/span\u003e\u003cspan address=\"https://www.ildis.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)), approximately 150 occur in the Mediterranean region. These represent seven of the eight sections of the genus, with most sections having the majority of species concentrated in this area (Zohary and Heller \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). Several studies have shown the commercial values of about 30 cultivated Trifolium species (Herman \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1953\u003c/span\u003e; Russell and Web 1976; Evans \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Speer and Allinson \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; vanKeuren and Hoveland \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1985\u003c/span\u003e), from which the most important cultivated species are: \u003cem\u003eT. repens\u003c/em\u003e (White Clover), \u003cem\u003eT. subterraneum\u003c/em\u003e, \u003cem\u003eT. pratense\u003c/em\u003e (Red Clover), \u003cem\u003eT. fragiferum\u003c/em\u003e, \u003cem\u003eT. hybridum\u003c/em\u003e, \u003cem\u003eT. resupinatum\u003c/em\u003e, \u003cem\u003eT. incarnatum\u003c/em\u003e, \u003cem\u003eT. alexandrinum\u003c/em\u003e, \u003cem\u003eT. dubium\u003c/em\u003e, \u003cem\u003eT. ambiguum\u003c/em\u003e. The majority of them are native to the Mediterranean, especially in Turkey (Zohary \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Zohary and Heller \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). In North Africa, 33 species have been recorded in Tunisia and 41 species in Algeria (ILDIS \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), 40 of which are native to Algeria. However, determining the geographical distribution of several clover species remains challenging due to confusion with their cultivated range.\u003c/p\u003e\u003cp\u003eThe genus \u003cem\u003eTrifolium\u003c/em\u003e is economically important within the Fabaceae family, with at least 16 species widely cultivated as forage and green manure crops (Gillett and Taylor \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Their symbiotic relationship with \u003cem\u003eRhizobium leguminosarum\u003c/em\u003e enables nitrogen fixation through root nodulation, (Sprent \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), enhancing soil fertility and improving pasture quality in both natural and managed grasslands.\u003c/p\u003e\u003cp\u003eIn Tunisia, plant genetic resources are of major economic and ecological importance. Research on spontaneous forage species, particularly Trifolium species, is driven by forage scarcity resources and the low nutritional quality of conventional animal feed, which limits the development of the livestock sector (Ben Salem and Smith \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Legumes are especially valued for their high protein content and environmental benefits.\u003c/p\u003e\u003cp\u003eStudies on spontaneous \u003cem\u003eTrifolium\u003c/em\u003e species in Tunisia, primarily focus on the variability observed between and within species at various levels. Since the 1990s, numerous exploration and collection missions have been conducted, particularly in northern regions, to enhance the value of spontaneous legume species with forage and pastoral potential. Several \u003cem\u003eTrifolium\u003c/em\u003e species have been identified and are well-represented in Tunisia, especially in the northern areas (Zoghlami et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). These species constitute a highly diverse and rich genetic resource, encompassing numerous species whose prevalence varied by region (Zoghlami et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConservation, selection, and improvement efforts for \u003cem\u003eTrifolium\u003c/em\u003e genetic resources continued into the 2000s. These initiatives enabled the agronomic enhancement and commercialization of species, such as the diploid species \u003cem\u003eTrifolium subterraneum\u003c/em\u003e L. (Jaritz \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1982\u003c/span\u003e), officially registered in the national catalog under the name of variety Fa\u0026iuml;ja. Cultivars of \u003cem\u003eT. subterraneum\u003c/em\u003e are also well integrated into ley-farming systems due to their adaptability to diverse Mediterranean climates and soils (Katznelson \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1974\u003c/span\u003e; McGuire \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Ewing \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Although 33 clover species have been recorded in Tunisia (Le Floc\u0026rsquo;h et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), only a few have been widely exploited; nevertheless, the annual species \u003cem\u003eT. alexandrinum\u003c/em\u003e (berseem) has shown promising performance in forage associations combining systems, particularly with triticale (Beji and Khemir \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zoghlami-Kh\u0026eacute;lil et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRecent surveys led to the inclusion of \u003cem\u003eTrifolium tunetanum\u003c/em\u003e on the IUCN Red List as Critically Endangered (CR). According to Pottier-Alapetite (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1979\u003c/span\u003e), a Tunisian endemic clover, \u003cem\u003eTrifolium squarrosum\u003c/em\u003e subsp. \u003cem\u003etunetanum\u003c/em\u003e, is reported in the southeastern Kef region and \u003cem\u003eTrifolium juliani\u003c/em\u003e is a rare and endemic clover species native to Tunisia and Algeria (Pottier-Alapetite \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1979\u003c/span\u003e). Conservation programs at National Institute for Agronomic Research in Tunisia (INRAT) and the National Gene Bank (BNG) have preserved seeds of both \u003cem\u003eT. juliani\u003c/em\u003e and \u003cem\u003eT. squarrosum ssp parnomitanum\u003c/em\u003e, enabling their use in forage trials that confirmed their potential. Due to morphological similarities and overlapping ecological niches, distinguishing \u003cem\u003eT. juliani\u003c/em\u003e and \u003cem\u003eT. squarrosum ssp tunetanum\u003c/em\u003e becoming \u003cem\u003eT. tunetanum\u003c/em\u003e, a specie a part, is challenging. Indeed, several recent surveys have highlighted the close resemblance between these two sympatric taxa, and detailed botanical observations ultimately allowed the clear differentiation of the two taxa \u003cem\u003eTrifolium juliani\u003c/em\u003e and \u003cem\u003eTrifolium squarrosum subsp. panormitanum\u003c/em\u003e (Belaifa E and Ghrabi-Gammar Z, personal communication, 2022). The present work applies molecular characterization to examine the genetic diversity within and between the two taxa.\u003c/p\u003e\u003cp\u003eSince to support the phylogeny of the two species, we focused on molecular markers. Unlike morphological traits, molecular markers are stable, environmentally independent, and reflect genome-wide variation (Clegg and Zurawski \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Gielly and Taberlet \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Our study emphasizes molecular polymorphism and interspecific differentiation using two types of markers: (a) arbitrarily amplified DNA markers (AADs), specifically ISSR markers (Inter Simple Sequence Repeats) (Zietkiewicz et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), and (b) targeted fingerprinting markers (TFMs), specifically SRAP markers (Sequence-Related Amplified Polymorphism) (Li and Quiros \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eISSR markers were used for the first time to study Trifolium genetic diversity in South American and Eurasian species (Rizza et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), with subsequent studies confirming their utility across the genus (Paplauskienė and Dabkevičienė \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Dabkevičienė et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Dabkevičienė and Paplauskienė \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Aryanegad et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Abate and Tesfaye \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Abate \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Mostapha Mohamed et al. 2024).\u003c/p\u003e\u003cp\u003eSRAP markers have more recently gained traction for their reproducibility and ability to target coding regions (Yousefi et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Youssef et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mostapha Mohamed et al. 2024).\u003c/p\u003e\u003cp\u003eUnderstanding \u003cem\u003eTrifolium\u003c/em\u003e\u0026rsquo;s essential for germplasm management and conservation strategies. Both ISSR and SRAP markers have proven effective for detecting polymorphisms and identifying genotypes of high conservation value. These marker systems are increasingly valuable for exploring key genetic aspects in \u003cem\u003eTrifolium\u003c/em\u003e species, including their evolutionary origins, centers of diversity, domestication processes, population structure, germplasm characterization, and the dentification of markers linked to agronomic traits. However, their application in assessing genetic diversity within \u003cem\u003eTrifolium\u003c/em\u003e remains limited, mainly due to the genus\u0026rsquo;s high species richness.\u003c/p\u003e\u003cp\u003eMore recently, SRAP markers have demonstrated their effectiveness and versatility in analyzing genetic diversity within clover species (Yousefi et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Youssef et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mostapha Mohamed et al. 2024). Understanding the genetic diversity of \u003cem\u003eTrifolium\u003c/em\u003e is critical for germplasm management and the development of conservation strategies. Studies indicate that both ISSR and SRAP marker systems are well-suited for assessing DNA polymorphism in clover, revealing the existence of diverse genotypes with unique identities warranting conservation efforts. However, despite their potential, studies employing ISSR and SRAP markers to measure genetic diversity in Trifolium species remain limited, largely due to the extensive number of species within this genus.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePlant material\u003c/h2\u003e\u003cp\u003eThe molecular polymorphism analysis was performed on seven young seedlings from each of the two clover species, \u003cem\u003eTrifolium juliani\u003c/em\u003e and \u003cem\u003eTrifolium squarrosum ssp parnomitanum\u003c/em\u003e. Seeds were collected in 2021 from Dyr El Kef (36\u0026deg;12\u0026rsquo;53.323\u0026rdquo; N, 8\u0026deg;45\u0026rsquo;38.293\u0026rdquo; E) (North West of El Kef) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). \u003cem\u003eTrifolium juliani\u003c/em\u003e and \u003cem\u003eTrifolium squarrosum ssp parnomitanum\u003c/em\u003e, distinguished in particular by their calyxes during recent surveys (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), are currently being propagated in concrete trays at INRAT.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGenomic DNA isolation\u003c/h3\u003e\n\u003cp\u003eFresh young leaves were sampled, frozen in liquid nitrogen, and ground to a fine powder. Genomic DNA was extracted and purified using the DNAeasy Plant Mini Kit (Qiagen Inc, USA). DNA concentration were measured with a NanoDrop\u0026trade; 2000/2000c (Thermo Fisher Scientific, USA), and DNA quality was evaluated by electrophoresis on 0.8% agarose gel according to Sambrook et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1989\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003ePCR-ISSR assays\u003c/h3\u003e\n\u003cp\u003eThe detection of inter and intraspecific polymorphisms has been performed using 10 ISSR primers. These were designed based on di- or multi-nucleotide repeats complementary to microsatellites (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The di-nucleotide repeats were anchored at the 3\u0026rsquo; end with a single degenerating nucleotide. DNA amplification was performed in 25 \u0026micro;L of final volume reaction mixture containing 10X PCR buffer, 1.5 mM of MgCl\u003csub\u003e2\u003c/sub\u003e (50mM), 200 \u0026micro;M of dNTPs, 10 ρmol of primer, 1.5 U of Taq DNA polymerase (Biomatik, USA), 10 ng of DNA, and double-distilled water. PCR amplifications were performed under the following conditions: one cycle of initial DNA denaturation at 94\u0026deg;C for 5 min, followed by 35 cycles each one including a denaturation step of 30 s at 94\u0026deg;C, a second step of 1 min 30 s for annealing at the primer-specific Tm and an extension step of 1 min at 72\u0026deg;C, followed by a final extension for 5 min at 72\u0026deg;C.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of ISSR and SRAP primers used for genetic diversity in \u003cem\u003eTrifolium\u003c/em\u003e species\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eISSR primer codes\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSequence (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTm\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eUnanchored primers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(AG)\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(AGG)\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(ACTG)\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003eAnchored primers at the 3' end by a single degenerate nucleotide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(AG)\u003csub\u003e10\u003c/sub\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(AG)\u003csub\u003e10\u003c/sub\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(AG)\u003csub\u003e10\u003c/sub\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(CT)\u003csub\u003e10\u003c/sub\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(CT)\u003csub\u003e10\u003c/sub\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(CT)\u003csub\u003e10\u003c/sub\u003eG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eISSR10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(TC)\u003csub\u003e10\u003c/sub\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSRAP primer codes\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSequence (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eForward primers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eme1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTGAGTCCAAA\u003cb\u003eCCGG\u003c/b\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATA\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eme2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTGAGTCCAAA\u003cb\u003eCCGG\u003c/b\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAGC\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eme4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTGAGTCCAAA\u003cb\u003eCCGG\u003c/b\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eACC\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eme8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTGAGTCCAAA\u003cb\u003eCCGG\u003c/b\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTGC\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eme10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTGAGTCCAAA\u003cb\u003eCCGG\u003c/b\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTTG\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eReverse primers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eem2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGACTGCGTACG\u003cb\u003eAATT\u003c/b\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTGC\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eem3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGACTGCGTACG\u003cb\u003eAATT\u003c/b\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eGAC\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eem14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGACTGCGTACG\u003cb\u003eAATT\u003c/b\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eACG\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003eTm: Melting temperature for primer, In bold: The core motifs \u0026lsquo;CCGG\u0026rsquo; in the forward primer and \u0026lsquo;AATT\u0026rsquo; in the reverse primer. Underlined: The selective 3' end sequences.\u003c/p\u003e\n\u003ch3\u003ePCR-SRAP assays\u003c/h3\u003e\n\u003cp\u003eTen SRAP primer-pair combinations were randomly selected from a set of five forward and three reverse primers (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Li and Quiros \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Zeng et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). PCR amplifications were performed in a 25 \u0026micro;L reaction volume containing 30 ng genomic DNA, 10X PCR buffer, 0.25 mM each primer (reverse and forward), 3 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 1 mM dNTPs, 1.5 U of Taq DNA Polymerase (Biomatik, USA), and double-distilled water. The thermal cycling program consisted of an initial denaturation at 95\u0026deg;C for 5 min; 5 cycles of 94\u0026deg;C for 1 min, 35\u0026deg;C for 1 min, 72\u0026deg;C for 1 min, followed by 35 cycles of 94\u0026deg;C for 1 min, 47\u0026deg;C for 1 min 30 sec, 72\u0026deg;C for 1 min, and a final extension at 72\u0026deg;C for 10 min.\u003c/p\u003e\u003cp\u003eAll amplifications for both techniques were carried out in an \u003cem\u003eApplied Biosystems-Veriti\u003c/em\u003e thermocycler (Thermo Fisher Scientific, USA)\u003c/p\u003e\u003cp\u003eBoth PCR products were separated on a 1.5% agarose gel stained with 0.5 pg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e ethidium bromide and electrophoresed in 0.5X TBE buffer (pH 8.0) at 90 V for 1 h. The bands were visualized under UV light using a Gel-Doc 2000 image analysis system (Bio-Rad, USA).\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eAmplified products were compiled into a binary data matrix based on the presence (1) or absence (0) of each selected band to generate the 0/1-matrix. The discriminatory power of the markers in estimating genetic variability was evaluated using several informative indices: number of polymorphic bands (NPB), percentage of polymorphic bands (PPB), expected heterozygosity (H), polymorphism information content (PIC), multiplex ratio (EMR), marker index (MI), discriminating power (D) and resolving power (Rp). These indices were calculated using the iMEC online tool (Amiryousefi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Additionally, genetic diversity was assessed with different parameters, such as the effective number of alleles (Ne), Nei\u0026rsquo;s gene diversity (H), Shannon\u0026rsquo;s information index (I), total genetic diversity (Ht), genetic diversity within population (Hs), genetic differentiation (Gst), and gene flow (Nm) using POPGENE version 1.31 (Yeh et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Furthermore, an analysis of molecular variation (AMOVA) was performed in GenAlEx 6.5 software (Peakall and Smouse \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) to partition variance components within and among \u003cem\u003eTrifolium\u003c/em\u003e species based on SRAP and ISSR markers.\u003c/p\u003e\u003cp\u003eA dendrogram was constructed using Ward\u0026rsquo;s method (Ward \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1963\u003c/span\u003e), and a principal component analysis (PCA) was applied to visualize genetic relationships among \u003cem\u003eTrifolium\u003c/em\u003e genotypes based on Euclidian distances, both implemented in PAST software (Hammer et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurthermore, the genetic structure of the population was analysed using bayesian clustering approach implemented in \u003cem\u003eSTRUCTURE\u003c/em\u003e version 2.3.4 (Pritchard et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Evanno et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The optimal of genetic clusters (K) was determined following the ΔK method proposed by Evanno et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), which identifies the K value with the highest ΔK as the most probable number of clusters. STRUCTURE was run under an admixture model with prior information on sampling locations. For each potential K value (ranging from 1 to 7), 10 independent runs were performed, each consisting of 100.000 burn-in steps followed by 100.000 iterations. The online tool Structure Selector (Li and Liu \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) was used to summarize and evaluate clustering solutions. To align and average the results from replicate runs, the Clumpak program (Kopelman et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) was employed using the \u0026ldquo;Greedy\u0026rdquo; algorithm with 10.000 random input sequences and an additional 10.000 repetitions to compute pairwise similarity scores (H\u0026rsquo;). Finally, the cluster membership proportions were visualized using Distruct version 1.1 (Rosenberg \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eISSR polymorphism\u003c/h2\u003e\u003cp\u003eThe use of 10 ISSR primers produced 87 bands in total, of which 70 were polymorphic (PPB\u0026thinsp;=\u0026thinsp;80.46%) across the 14 individuals studied (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), highlighting the efficiency of these primers in detecting molecular polymorphism and differentiating between the two clover species. The number of bands generated varied considerably, ranging from 18 bands with the ISSR3 (ACTG)₄ primer to only 4 bands with both ISSR5 (AG)₁₀G and ISSR8 (CT)₁₀T, indicating differences in the ability of primers to reveal polymorphism within the species.\u003c/p\u003e\u003cp\u003eAlthough three anchored primers (ISSR5 (AG)₁₀G, ISSR8 (CT)₁₀T, and ISSR9 (CT)₁₀G) exhibited the highest percentage of polymorphism (100%), they produced very few bands, and therefore contributed to limited information. In contrast, the two unanchored primers, ISSR3 (ACTG)₄ and ISSR1 (AG)₁₀, generated the greatest number of bands and showed high polymorphism levels (83.33% and 80%, respectively), as well as strong resolving power (Rp\u0026thinsp;=\u0026thinsp;11.571 for ISSR3 (ACTG)₄ and 6.714 for ISSR1 (AG)₁₀). These two primers were therefore the most informative for distinguishing the genotypes of the two clover species.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of polymorphism parameters of ten ISSR primers applied to \u003cem\u003eTrifolium juliani\u003c/em\u003e and \u003cem\u003eTrifolium squarrosum\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR primers\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBand size (pb)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTNB\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNPB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePPB (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePIC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eEMR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRp\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e814\u0026ndash;2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.371\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.357\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.987\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.715\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e6.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e750\u0026ndash;1515\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2.571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e450\u0026ndash;2837\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8.929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e3.301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.755\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e11.571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e519\u0026ndash;2174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.487\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e3.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.663\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e9.429\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e478\u0026ndash;1065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.490\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2.857\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e418\u0026ndash;1380\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.212\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.608\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.429\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e608\u0026ndash;2554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e77.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.494\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.373\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.491\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.804\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e574\u0026ndash;2300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.459\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.389\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.591\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2.571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e794\u0026ndash;2552\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.765\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.286\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISSR10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e266\u0026ndash;1527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e72.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.371\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e5.857\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e18.259\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e6.675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e52.286\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.473\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.667\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e5.229\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003csup\u003e*\u003c/sup\u003eTNB: Total number of bands; NBP: Number of polymorphic bands; PPB (%): Percentage of polymorphism; H: expected heterozygosity; PIC: Polymorphism Information content; EMR: effective multiplex ratio; MI: marker index; D: discriminatory power; Rp: Resolving power\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe polymorphism information content (PIC) values ranged from 0.370 for ISSR3 (ACTG)₄ to 0.438 for ISSR2 (AGG)₆, with an average of 0.382, indicating moderate to high informativeness of the ISSR primers in detecting genetic polymorphism. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows representative ISSR amplification profiles illustrating polymorphic bands that differentiate the two clover species.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSRAP polymorphism\u003c/h3\u003e\n\u003cp\u003eTen SRAP primer combinations generated a total of 63 bands, 46 of which were polymorphic, corresponding to a polymorphism percentage (PBP\u0026thinsp;=\u0026thinsp;73.02%) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In spite of the effectiveness in detecting molecular polymorphism and distinguishing the two taxa SRAP markers showed a lower PPB compared to ISSR markers. Among the tested combinations, four primer pairs (me1-em2, me2-em3, me8-em2, and me2-em14) were the most informative (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e), each producing more than 8 bands, with polymorphism percentages exceeding 70% and resolving power (Rp) values above 6. Overall, SRAP markers showed moderate informativeness, with a mean PIC value and close to 0.5 (0.363) and an average polymorphism percentage (PPB) of 73.02%. Both SRAP and ISSR markers were effective in revealing molecular polymorphism between the two clover species although ISSR markers proved slightly more informative based on their higher performance indices.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of polymorphism parameters of ten SRAP primer combinations applied to \u003cem\u003eTrifolium juliani\u003c/em\u003e and \u003cem\u003eTrifolium squarrosum\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSRAP primer combination\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBand size (bp)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTNB\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNPB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePPB (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePIC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eEMR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRp\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme1-em2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e282\u0026ndash;1549\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e72.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.493\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.690\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e6.286\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme1-em3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e242\u0026ndash;1433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.469\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.352\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme1-em14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e422\u0026ndash;850\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.408\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme2-em2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e141\u0026ndash;1011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.420\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.513\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme2-em3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e269\u0026ndash;1545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.431\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6.857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.529\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme2-em14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e338\u0026ndash;1372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.492\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.533\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.686\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e6.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme4-em2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e199\u0026ndash;1573\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.308\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.414\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme4-em3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e717\u0026ndash;1983\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.351\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.651\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.623\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme8-em2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e263\u0026ndash;2110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.485\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e5.143\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eme10-em2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e774\u0026ndash;2097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.726\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.561\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e40.214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e14.553\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e5.717\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e37.571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e73.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.442\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.572\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.757\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003csup\u003e*\u003c/sup\u003eTNB: Total number of bands; NBP: Number of polymorphic bands; PPB (%): Percentage of polymorphism; H: expected heterozygosity; PIC: Polymorphism Information content; EMR: effective multiplex ratio; MI: marker index; D: discriminatory power; Rp: Resolving power\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of molecular variance and diversity indices of species\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe analysis of molecular variance (AMOVA) revealed a pronounced hierarchical structure in the distribution of genetic variation. The majority of the total variance was attributed to differences between the two species, accounting for 82.89% for ISSR and 84.85% for SRAP. In contrast, variation within species represented a considerably smaller proportion of the total genetic diversity (17.11% for ISSR and 15.15% for SRAP) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This pattern of partitioning suggests strong genetic divergence between species and limited variability within each species. The pronounced interspecific differentiation is further corroborated by low estimates of gene flow (Nm\u0026thinsp;=\u0026thinsp;0.198 for ISSR and Nm\u0026thinsp;=\u0026thinsp;0.116 for SRAP) and high genetic differentiation coefficients (Gst\u0026thinsp;=\u0026thinsp;0.716 for ISSR and Gst\u0026thinsp;=\u0026thinsp;0.812 for SRAP) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnalysis of molecular variance (AMOVA) for \u003cem\u003eTrifolium juliani\u003c/em\u003e and \u003cem\u003eTrifolium squarrosum\u003c/em\u003e based on ISSR and SRAP markers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eISSR markers\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource of variation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ed.f.\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSum of squares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean squares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEstimates variance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePercentage of variation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAmong species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e154.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e154.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21.449\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e82.89%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWithin species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.11%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e207.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhiPT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.829\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ep-Value\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eSRAP markers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ed.f.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSum of squares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean squares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEstimates variance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePercentage of variation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAmong species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e120.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.796\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e84.85%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWithin species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.15%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e156.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.796\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhiPT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.848\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ep-Value\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e*\u003c/sup\u003ed.f.: degrees of freedom; \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep-Value\u003c/em\u003e: significance after 1000 random permutations\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenetic indices, genetic differentiation, and gene flow between \u003cem\u003eT. juliani\u003c/em\u003e and \u003cem\u003eT. squarrosum\u003c/em\u003e based on ISSR and SRAP data\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\u003cp\u003eISSR markers\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePPB (%)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eNa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eHt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eHs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eGst\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eNm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eT. juliani\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e9.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eT. squarrosum\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e39.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e24.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e80.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.805\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.594\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.465\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.716\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\u003cp\u003eSRAP markers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPB (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eNa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eNe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eHt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eHs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eGst\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eNm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eT. juliani\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eT. squarrosum\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1.157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1.108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.730\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1.622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.323\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.457\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.323\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.812\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003ePPB (%): percentage of polymorphic bands (%); Na: Number of observed alleles per locus; Ne: Effective number of alleles per locus; H: Nei\u0026rsquo;s genetic diversity; I: Shannon diversity index; Ht: total diversity; Hs: mean diversity within populations; Gst: inter-population differentiation index; Nm: Number of migrants (gene flow).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eGenetic structuration\u003c/h2\u003e\u003cp\u003eThe results obtained from principal component analysis (PCA), hierarchical clustering using Ward\u0026rsquo;s method based on Euclidean distances, and Bayesian clustering consistently revealed a clear separation of the two clover species into two major clusters (K\u0026thinsp;=\u0026thinsp;2, ΔK\u0026thinsp;\u0026gt;\u0026thinsp;200, H\u0026rsquo;=0.9 for ISSR, SRAP and combined datasets), corresponding to groups I and II across the three data matrices (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In the dendrogram, these two main clusters exhibited the highest robustness, with bootstrap values of 100%. Similarly, Bayesian analysis assigned more than 90% of genotypes to their respective clusters, conforming strong genetic differentiation between the species. However, two genotypes (TJ-7 and TS-9) displayed minor admixture signals (\u0026gt;\u0026thinsp;10%) with the second cluster, suggesting the existence of a weak but detectable shared genetic background, possibly reflecting ancestral polymorphism or limited historical gene flow not fully captured by the dominant markers used.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMolecular markers such as SSRs and SNPs are widely used in Fabaceae to assess genetic diversity and population structure, providing critical insights for breeding and conservation strategies (Burstin et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hong et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Their efficiency has been demonstrated in several legume crops, including chickpea, pea, and groundnut, through applications in marker-assisted selection, QTL mapping, and genome-wide association studies (Varshney et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jurado et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Istanbuli et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Meta-QTL and RNA-seq integration further enhance the resolution of candidate gene discovery (Izquierdo et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and a functional markers derived from these studies enable precise introgression of traits into elite cultivars. Genomic prediction models, such as those developed in \u003cem\u003eMedicago truncatula\u003c/em\u003e, demonstrate the predictive power of genome-wide marker data (Gentzbittel et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Moreover, recent advances integrate genome editing with marker-based trait targeting, offering a path toward accelerated trait fixation (Kumar et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). All together, molecular markers bridge genetic variation analysis and modern breeding tools, facilitating efficient improvement of Fabaceae crops across environments. Despite these advances, dominant markers remain highly relevant, particularly for species with limited genomic resources. Arbitrarily Amplified DNA (AAD) markers - such as ISSR, offer high discriminating power without requiring prior sequence information, whereas Targeted Fingerprinting Markers (TFMs), including SRAP preferentially amplify functional regions, improving both resolution and reproducibility (Li and Quiros \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Poczai et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These complementary approaches continue to be widely applied in Fabaceae for diversity analysis, genetic structure assessment, and breeding purposes (Uzun et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Alghamdi et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite being an old technique since 1994 (Zietkiewicz et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), numerous studies continue to highlight the effectiveness of ISSR markers. These markers are highly efficient in detecting molecular polymorphism without requiring prior sequence information, making them robust and cost-effective tools for assessing genetic diversity in various Fabaceae species (Poczai et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Alzate-Marin et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Qiang et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Nurhasanah et al. 2023; Diallo et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In addition, ISSR markers have proven useful in identifying mutant lines in evaluating responses to salt stress, and in supporting their relevance in marker-assisted breeding programs. Overall, ISSR markers offer high discriminating power and valuable applications in breeding and the management of genetic resources within the Fabaceae family.\u003c/p\u003e\u003cp\u003eWhile SRAP markers have proven to be powerful tools for detecting molecular polymorphism due to their ability to amplify open reading frames, they have been made highly suitable for targeting coding regions in plant genomes (Li and Quiros \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Uzun et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In Fabaceae, SRAP markers revealed high levels of polymorphism and discriminated effectively among closely related accessions, as demonstrated in \u003cem\u003eVicia faba\u003c/em\u003e (Alghamdi et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Their high reproducibility and informativeness make them ideal for assessing genetic structure, diversity, and evolutionary relationships (Li and Quiros \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Overall, SRAP markers offer a robust and gene-targeted molecular tool for genetic improvement and breeding programs in Fabaceae (Li and Quiros \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Alghamdi et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the local clover species, particularly \u003cem\u003eTrifolium squarrosum\u003c/em\u003e and \u003cem\u003eTrifolium juliani\u003c/em\u003e (an endemic species of Tunisia and Algeria), accurate genetic characterization is essential due to their sympatric distribution and significant potential for forage improvement. Differentiating these taxa is a prerequisite for effective conservation strategies and for exploiting inter- and intra-specific genetic variability in breeding programs. The present study assessed genetic diversity and population structure in these species using ISSR and SRAP markers to establish a robust framework for their sustainable use and genetic enhancement.\u003c/p\u003e\u003cp\u003eBoth marker systems were chosen for their proven efficiency in diversity studies and demonstrated high levels of polymorphism (\u0026gt;\u0026thinsp;73%) and substantial polymorphic information content (PIC\u0026thinsp;=\u0026thinsp;0.382 for ISSR and 0.363 for SRAP), confirming their suitability for detecting molecular variation.. These results are consistent with previous reports on clover species (Abate and Tesfaye \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Abate \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yousefi et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Youssef et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mostafa Mohamed et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, ISSR markers exhibited slightly higher values for genetic differentiation (H, PIC, EMR, MI, D, and Rp) than SRAP markers, corroborating the observations by Mostafa Mohamed et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe variations in genetic similarity observed across different marker types may reflect differences in their mechanisms which are provided to detect polymorphisms. It may also show the extent of the sequencing genome coverage. Consequently, genetic similarity derived from combined datasets offers a more comprehensive representation of genetic relationships. Unlike ISSR markers, which are randomly distributed across the genome, SRAP markers specifically target open reading frame (ORF) sequences, corresponding to relatively conserved coding regions, thereby focusing on the functional genomic regions. In contrast, random markers such as ISSR capture a broader range of molecular polymorphism can be considerably informative when differentiating closely related species. This difference may explain why ISSR markers provided slightly higher genetic differentiation values than SRAP in the present study.\u003c/p\u003e\u003cp\u003eThe molecular analysis of variance (AMOVA) revealed a highly significant partitioning of genetic variation between the two species, confirming their clear differentiation. Intraspecific variance was comparatively low. Yet it highlights the presence of substantial genetic variability within each species. This structuring pattern was further supported by low estimates of gene flow and high genetic differentiation indices, reflecting the self-incompatibility system typical of clovers, favors outcrossing and limits interspecific hybridization (Casey et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMultivariate and clustering analyses consistently corroborated these findings. PCA and Ward\u0026rsquo;s hierarchical clustering separated all accessions into two major groups corresponding to T. juliani and T. squarrosum, while Bayesian inference identified K\u0026thinsp;=\u0026thinsp;2 as the most probable number of clusters (ΔK\u0026thinsp;\u0026gt;\u0026thinsp;200, H\u0026rsquo; = 0.9). Most genotypes were assigned to their respective clusters with high probability (\u0026gt;\u0026thinsp;90%) although two genotypes (TJ-7 and TS-9) exhibited minor admixture signals, suggesting possible shared ancestry or historical gene flow. These complementary analyses provide strong evidence of species-level differentiation, while also revealing subtle genetic connections among certain genotypes.\u003c/p\u003e\u003cp\u003eCombining ISSR and SRAP data improved structural resolution by integrating signals from random and functional genomic regions, and by providing a holistic view of diversity. The concordance among these approaches further validates the robustness of our results and emphasizes the necessity of combining complementary marker systems in analyses of outcrossing species.\u003c/p\u003e\u003cp\u003eOverall, the clear genetic separation, despite some rare signs of admixture, shows the importance of using combined approaches that consider both species distinctness and occasional interspecific gene flow, to ensure effective conservation and targeted breeding strategies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides the first molecular characterization of \u003cem\u003eT. squarrosum ssp parnomitanum\u003c/em\u003e and \u003cem\u003eT. juliani\u003c/em\u003e, revealing high genetic diversity and a clear species-level distinction using ISSR and SRAP markers. The results highlight the value of complementary markers for studying outcrossing species. These findings establish a foundation for effective conservation and targeted breeding strategies to enhance the genetic potential of clover crops.\u003c/p\u003e\u003cp\u003eFuture studies should integrate next-generation sequencing (NGS) and genome-wide association studies (GWAS) with traditional marker-based approaches to achieve high-resolution mapping of adaptive traits in clovers. Combining these genomic tools with interspecific hybridization and genomic selection will enhance the use of the genetic diversity identified in this study, enabling the development of resilient, high-performing forage cultivars tailored for sustainable agriculture.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors are grateful for the valuable contribution of les Amis de CAPTE (Collectif d\u0026rsquo;Acteurs Pour la Transition Environnementale) for its support to the Project Trefles at Dyr El Kef entitled \u003cem\u003e\u0026ldquo;Ensemble pour la restauration des \u0026eacute;cosyst\u0026egrave;mes avec des agriculteurs locaux engag\u0026eacute;s \u0026agrave; Dyr el Kef, Tunisie\u0026rdquo;\u003c/em\u003e with was funded by the CEPF (Critical Ecosystem Partnership Fund) between 2021 and 2024.\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Professor\u0026nbsp;Zeineb Ghrabi-Gammarand her PhD student Emna Belaifa\u0026nbsp;for their consistant contribution to the recognition of collected clover species based on their taxonomic skills.\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Miss Dorra Ben Nasr for helping improve the clarity and flow of this research paper. She is an experienced English teacher who collaborates with several international institutions, including Bourguiba School, Tunisian Private University, and Eight Hospitality Business School. Her support and expertise were greatly appreciated throughout the writing process.\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKG supervised and conducted the molecular experiments, performed data analysis, prepared the figures, interpreted the results, and drafted the entire manuscript. AZ-K conceived the study design, was involved in the overall supervision of the project, and contributed to manuscript revision and editing. NC-G supervised the molecular experiments and revised the manuscript.\u0026nbsp;SSK\u0026nbsp;and SBY contributed in all prospections to collect and identify Trifolium species. EJ and HC participated in the sampling of clover specimens for the study as part of the project and also contributed to manuscript revision. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003eFunding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was partially supportet by the Trefles Project hosted at INRAT (at the Laboratory of Animal and Forage Production) (LR16INRAT01) and managed by CAPTE and also benefited from logistical support provided by the Laboratory of Molecular Genetics, Immunology and Biotechnology (LR99ES12) at the Faculty of Sciences of Tunis.\u003c/p\u003e\n\u003cp\u003eData availability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll data supporting the findings are available within the manuscript.\u003c/p\u003e\n\u003cp\u003eConflict of interest/competing interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial or non-financial interests related to the content of this article.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003eAbate T (2017) Genetic Diversity Study of Steudneri Clover (\u003cem\u003eTrifolium steudneri\u003c/em\u003e) Accessions of Ethiopia Using Inter Simple Sequence Repeat (ISSR) Markers. Advances in Life Science and Technology54. ISSN 2224-7181 (Paper) ISSN 2225-062X (Online).\u003c/p\u003e\n\u003cp\u003eAbate T, Tesfaye K (2017) Genetic Diversity in quarin Clover (\u003cem\u003eTrifolium quartinianum\u003c/em\u003e) Accessions of Ethiopia Using Inter Simple Sequence Repeat (ISSR) Markers. African journal of biotechnology 16 (16): 869–878. https://doi.org/10.5897/AJB2015.14846\u003c/p\u003e\n\u003cp\u003eAlghamdi SS, Al-Faifi SA, Migdadi HM, Khan MA, El-Harty EH, Ammar MH (2012) Molecular diversity assessment using Sequence Related Amplified Polymorphism (SRAP) Markers in \u003cem\u003eVicia faba\u003c/em\u003e L. Int J Mol Sci 13(12): 16457–16471.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.3390/ijms131216457\u003c/p\u003e\n\u003cp\u003eAlzate-Marin AL, Costa-Silva C, Sá Rivas PM, Bonifacio-Anacleto F, Santos LG, de Moraes Filho RM, Martinez CA (2018) Diagnostic fingerprints ISSR/SSR for tropical leguminous species \u003cem\u003eStylosanthes capitata\u003c/em\u003e and \u003cem\u003eStylosanthes macrocephala\u003c/em\u003e. Sci. Agric 77(3) : e20180252. http://dx.doi.org/10.1590/1678-992X-2018-0252\u003c/p\u003e\n\u003cp\u003eAmiryousefi A, Hyvönen J, Poczai P (2018) iMEC: Online Marker Efficiency Calculator. Applications in Plant Sciences 6(6): e1159. http://dx.doi.org/10.1002/aps3.1159 \u003c/p\u003e\n\u003cp\u003eAryanegad P, Farshadfar E, Safari H, Shirvani H (2013) Application of ISSR molecular markers in genetic diversity of three Trifolium species. J. Bio. \u0026amp; Env. Sci 3: 78–84.\u003c/p\u003e\n\u003cp\u003eISSN: 2220-6663 (Print) 2222-3045 (Online)\u003c/p\u003e\n\u003cp\u003eBeji S, Khemir E (2012) Performance of two forage associations, triticale-berseem and triticale-common vetch, in a semi-arid environment in Tunisia. Fourrages 212: 337–342.\u003c/p\u003e\n\u003cp\u003eBen Salem H, Smith T (2008) Feeding strategies to increase small ruminant production in dry environments. Small Ruminant Research 77: 174–194.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1016/j.smallrumres.2008.03.008\u003c/p\u003e\n\u003cp\u003eBurstin J, Salloignon P, Chabert-Martinello M, Magnin-Robert J-B, Siol M, Jacquin F, Chauveau A, Pont C, Aubert G, Delaitre C, Truntzer C, Duc G (2015) Genetic diversity and trait genomic prediction in a pea diversity panel. BMC Genomics 16 : 105.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1186/s12864-015-1266-1\u003c/p\u003e\n\u003cp\u003eCasey NM, Milbourne D, Barth S, Febrer M, Jenkins G, Abberton MT, Jones C, Thorogood D (2010) The genetic location of the self-incompatibility locus in white clover (\u003cem\u003eTrifolium repens\u003c/em\u003e L.). Theor Appl Genet121(3): 567–576. https://doi.org/10.1007/s00122-010-1330-9\u003c/p\u003e\n\u003cp\u003eClegg MT, Zurawski G (1991) Chloroplast DNA and the study of plant phylogeny. In: Soltis PS, Soltis DE, Doyle JJ (ed) Molecular systematics of plants. Chapman \u0026amp; Hall, New York, pp 1–13.\u003c/p\u003e\n\u003cp\u003eDabkevičienė G, Paplauskienė V, Vilčinskas E (2011) Assessment of genetic diversity in Trifolium spp. Using ISSR and RAPD markers. Journal of Food, Agriculture \u0026amp; Environment 9: 210–214.\u003c/p\u003e\n\u003cp\u003eDabkevičienė G, Paplauskienė V (2012) A study of genetic diversity in \u003cem\u003eTrifolium hybridum\u003c/em\u003e varieties using morphological characters and ISSR markers. Žemdirbystė-Agriculture 99(3): 313–318. ISSN: 1392-3196.\u003c/p\u003e\n\u003cp\u003eDiallo S, Badiane FA, Kabkia BA, Diédhiou I, Diouf M, Diouf D (2024) Genetic diversity and population structure of cowpea mutant collection using SSR and ISSR molecular markers. Sci Rep 14: 31833. http://dx.doi.org/10.1038/s41598-024-83087-y\u003c/p\u003e\n\u003cp\u003eEllison NW, Liston A, Steiner JJ, Williams WM, Taylor NL (2006) Molecular phylogenetics of the clover genus (\u003cem\u003eTrifolium\u003c/em\u003e—Leguminosae). Molecular Phylogenetics and Evolution 39: 688–705. http://dx.doi.org/10.1016/j.ympev.2006.01.004\u003c/p\u003e\n\u003cp\u003eEvanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14: 2611–2620.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ehttp://dx.doi.org/\u003c/u\u003e10.1111/j.1365-294X.2005.02553.x\u003c/p\u003e\n\u003cp\u003eEvans AM (1976) Clovers. In: Simmonds NW (ed) Evolution of Crop Plants, Longman, London, pp 175–179.\u003c/p\u003e\n\u003cp\u003eEwing MA (1996) Successful pasture legumes in ley farming systems. In: Bennett SJ, Cocks PS (eds.) Genetic Resources of Mediterranean Pasture and Forage Legumes. Proceedings of international Workshop, Perth, Australia, 14-18 October1996. \u003c/p\u003e\n\u003cp\u003eGentzbittel L, Ben C, Mazurier M, Shin M-G, Triska M, Rickauer M, Nikolsky Y, Marjoram P, Nuzhdin S, Tatarinova T (2015) Whole-genome modeling accurately predicts quantitative traits in plants. Populations and Evolution. (arXiv). https://doi.org/10.48550/arXiv.1511.02514\u003c/p\u003e\n\u003cp\u003eGibson DJ (2008) Grasses and grassland ecology. Oxford University Press, 2009 - 305 pages. http://dx.doi.org/10.1093/aob/mcp2019\u003c/p\u003e\n\u003cp\u003eGielly L, Taberlet P (1996) A phylogeny of the European gentians inferred from chloroplast trnL (UAA) intron sequences. Bot. J. Linn. Soc 120(1): 57–75. \u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1111/j.1095-8339.1996.tb00480.x\u003c/p\u003e\n\u003cp\u003eGillett JM (1970) On the Taxonomy of the Genus \u003cem\u003eTrifolium \u003c/em\u003eL. In: Report of the \u003cem\u003eTrifolium \u003c/em\u003eresearch work conference, Clemson, California, USA, pp 26–46.\u003c/p\u003e\n\u003cp\u003eGillett JM, Taylor N (2001) The World of Clovers. Iowa State University Press, Ames, Iowa, USA.\u003c/p\u003e\n\u003cp\u003eHammer Ø, Harper DAT, Ryan PD (2001) PAST: Paleontological statistics software package for education and data analysis. Palaeontol. Electron 4(1): 9 pages. \u003c/p\u003e\n\u003cp\u003ehttp://palaeo-electronica.org/2001_1/past/issue1_01.htm\u003c/p\u003e\n\u003cp\u003eHerman FJ (1953) A botanical synopsis of the cultivated clovers (Trifolium) Agriculture Monograph No. 25. pp. 1–45. United States Department of Agriculture, Washington D.C, USA.\u003c/p\u003e\n\u003cp\u003eHong Y, Pandey MK, Lu Q, Liu H, Gangurde SS, Li S, Liu H, Li H, Liang X, Varshney RK, Chen X (2021) Genetic diversity and distinctness based on morphological and SSR markers in peanut. Agronomy Journal 113(6) : 4648–4660. https://doi.org/10.1002/agj2.20671\u003c/p\u003e\n\u003cp\u003eHossain M (1961) A revision of \u003cem\u003eTrifolium \u003c/em\u003ein the Nearer East. Notes from the Royal Botanic Garden Edinburgh23: 387–481. https://doi.org/10.24823/nrbge.1961.2591\u003c/p\u003e\n\u003cp\u003eILDIS (1999) International Legume Database and Information Service. http://www.ildis.org. Accessed 20 May 2025\u003c/p\u003e\n\u003cp\u003eIstanbuli I, Nassar AE, Abd El-Maksoud MM, Tawkaz S, Alsamman AM, Hamwieh A (2024) Genome-wide association study reveals SNP markers controlling drought tolerance and related agronomic traits in chickpea across multiple environments. Front. Plant Sci, Sec. Plant Abiotic Stress 15:1260690. https://doi.org/10.3389/fpls.2024.1260690\u003c/p\u003e\n\u003cp\u003eIzquierdo P, Kelly JD, Beebe SE, Cichy K (2023) Combination of meta-analysis of QTL and GWAS to uncover the genetic architecture of seed yield and seed yield components in common bean. The Plant Genome 16(2): e20328. https://doi.org/10.1002/tpg2.20328\u003c/p\u003e\n\u003cp\u003eJaritz G (1982) Amélioration des herbages et cultures fourragères dans le nord-ouest de la Tunisie : études particulières des prairies de trèfles, graminées avec \u003cem\u003eTrifolium subterraneum\u003c/em\u003e L. Ed. GTZ. 345 pp.\u003c/p\u003e\n\u003cp\u003eJurado M, García-Fernández C, Campa A, Ferreira JJ (2024) Identification of consistent QTL and candidate genes associated with seed traits in common bean by combining GWAS and RNA-Seq. Theor Appl Genet 137(6): 143. https://doi.org/10.1007/s00122-024-04638-5\u003c/p\u003e\n\u003cp\u003eKatznelson J (1974) Biological Flora of Israel, 5: The subterranean clovers of Trifolium subsect. Calycomorphum Katzn. \u003cem\u003eTrifolium subterraneum\u003c/em\u003e L. (sensu lato). Israel Journal of Botany 23: 69-108.\u003c/p\u003e\n\u003cp\u003eKopelman NM, Mayzel J, Jakobsson M, Rosenberg NA, Mayrose I (2015) Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resours 15: 1179–1191. https://doi.org/10.1111/1755-0998.12387\u003c/p\u003e\n\u003cp\u003eKumar R, Das SP, Choudhury BU, Kumar A, Prakash NR, Verma R, Chakraborti M, Devi AG, Bhattacharjee B, Das R, Das B, Devi HL, Das B, Rawat S, Mishra VK (2024) Advances in genomic tools for plant breeding: harnessing DNA molecular markers, genomic selection, and genome editing. Biol Res 57(1): 80. https://doi.org/10.1186/s40659-024-00562-6\u003c/p\u003e\n\u003cp\u003eLamont EJ, Zoghlami A, Hamilton RS, Bennett SJ (2001) Clovers (\u003cem\u003eTrifolium\u003c/em\u003e L.). In: Maxted, N., Bennett, S.J. (eds) Plant Genetic Resources of Legumes in the Mediterranean. Current Plant Science and Biotechnology in Agriculture, 1\u003csup\u003est\u003c/sup\u003e edn, Springer, Dordrecht, Netherlands, vol 39. pp 79–98. https://doi.org/10.1007/978-94-015-9823-1_4\u003c/p\u003e\n\u003cp\u003eLe Floc’h E, Boulos L, Véla E (2010) Catalogue synonymique commenté de la flore de Tunisie. Tunis: Banque nationale de gènes. Errata 2011. 504 pages. \u003c/p\u003e\n\u003cp\u003ehttps://hal.science/hal-05015706/document. Accessed 20 May 2025\u003c/p\u003e\n\u003cp\u003eLi G, Quiros CF (2001) Sequence-related amplified polymorphism (SRAP), a new marker system based on a simple PCR reaction: its application to mapping and gene tagging in Brassica. Theor Appl Genet 103: 455–546. https://doi.org/10.1007/s001220100570\u003c/p\u003e\n\u003cp\u003eLi YL, Liu JX (2018) Structure Selector: a web based software to select and visualize the optimal number of clusters using multiple methods. Mol Ecol Resour 18: 176–177. \u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1111/1755-0998.12719\u003c/p\u003e\n\u003cp\u003eMcGuire WS (1985) Subterranean clover. In : Taylor NL (ed) Clover science and technology, 25\u003csup\u003eth\u003c/sup\u003e edn, American Society of Agronomy, Madison, USA, pp. 515–534.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.2134/agronmonogr25.c23\u003c/p\u003e\n\u003cp\u003eMostafa Mohamed H, Sayed Mohamed El‑Assal S, Gamal El‑Din AY, El‑Khishin DA (2024) Analysis of genetic diversity and population structure in some Egyptian Berseem (\u003cem\u003eTrifolium alexandrinum\u003c/em\u003e) accessions based on ISSR, SCoT and SRAP markers. Genet Resour Crop Evol 71: 4885–4899. https://doi.org/10.1007/s10722-024-01940-5\u003c/p\u003e\n\u003cp\u003eNurhasanah, Hindersah R, Suganda T, Concibido V, Sundari, Karuniawan A (2023) The First Report on the Application of ISSR Markers in Genetic Variance Detection among Butterfly Pea (\u003cem\u003eClitoria ternatea\u003c/em\u003e L.) Accession in North Maluku Province, Indonesia. Horticulturae 9(9): 1059. https://doi.org/10.3390/horticulturae9091059\u003c/p\u003e\n\u003cp\u003ePaplauskienė V, Dabkevičienė G (2008) Genetic variability determination using ISSR–PCR markers in red clover varieties. Biologija 54: 56–59. \u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.2478/v10054-008-0011-y\u003c/p\u003e\n\u003cp\u003ePeakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research–an update. Bioinformatics 28: 2537–2539.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ehttp://dx.doi.org/\u003c/u\u003e10.1093/bioinformatics/bts460\u003c/p\u003e\n\u003cp\u003ePoczai P, Varga I, Laos M, Cseh A, Bell N, Valkonen JPT, Hyvönen J (2013) Advances in plant gene-targeted and functional markers : a review. Plant Methods 9:6. Pages : 31. http://www.plantmethods.com/content/9/1/6\u003c/p\u003e\n\u003cp\u003ePottier-Alapetite G (1979) Flore de la Tunisie (Angiospermes-Dicotylédones). 2 vol. (1979 and 1981) Publications scientifiques tunisiennes, Ministère de l’Enseignement supérieur et de la Recherche Scientifique, Ministère de l’Agriculture, Tunis.\u003c/p\u003e\n\u003cp\u003ehttps://bibdigital.rjb.csic.es/idurl/1/12768\u003c/p\u003e\n\u003cp\u003ePOWO (2025) Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew. Published on the Internet ; https://powo.science.kew.org/ Retrieved 23 September 2025.\u003c/p\u003e\n\u003cp\u003ePritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics. 155: 945–959. \u003cu\u003ehttp://dx.doi.org/\u003c/u\u003e10.1093/genetics/155.2.945\u003c/p\u003e\n\u003cp\u003eQiang Z, Wang Y, Li S, Wang M, Luo X, Li X, Feng X, Li C (2018) Efficiency of ISSR marker in assessing the genetic diversity of wild and cultivated \u003cem\u003eHedysarum polybotrys\u003c/em\u003e Hand. Mazz. Caryologia 71(2): 174–181. https://doi.org/10.1080/00087114.2018.1453322\u003c/p\u003e\n\u003cp\u003eRavagnani A, Abberton MT, Skøt L (2012) Development of genomic resources in the species of \u003cem\u003eTrifolium \u003c/em\u003eL. and its application in forage legume breeding. Agronomy 2: 116–131. https://doi.org/10.3390/agronomy2020116\u003c/p\u003e\n\u003cp\u003eRizza M, Real D, Reyno R, Porro V, Burgueco J, Errico E, Quesenberry K (2007) Genetic diversity and DNA content of three South American and three Eurasiatic \u003cem\u003eTrifolium\u003c/em\u003e species. Genetics and Molecular Biology 30(4): 1118–1124.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1590/S1415-47572007000600015\u003c/p\u003e\n\u003cp\u003eRosenberg NA (2004) distruct: a program for the graphical display of population structure. Mol Ecol Notes 4: 137–138. https://doi.org/10.1046/j.1471-8286.2003.00566\u003c/p\u003e\n\u003cp\u003eRussell JS, Webb HR (1976) Climatic range of grasses and legumes used in pastures: Results of a survey conducted at the 11\u003csup\u003eth\u003c/sup\u003e International Grassland Congress. Journal of the Australian Institute of Agricultural Science 42: 156–166.\u003c/p\u003e\n\u003cp\u003eRussi L, Cocks PS, Roberts EH (1992) The fate of legume seeds eaten by sheep from a Mediterranean grassland. Jounal of Applied Ecology 29(3): 772–778.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.2307/2404487\u003c/p\u003e\n\u003cp\u003eSambrook J, Fritsch EF, Maniatis T (1989) Molecular cloning: A laboratory manual (Second edition), Volumes 1, 2 and 3. Cold Spring Harbor Laboratory Press.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1002/jobm.3620300824\u003c/p\u003e\n\u003cp\u003eSpeer GS, Allinson DW (1985) Kura clover (\u003cem\u003eTrifolium ambiguum\u003c/em\u003e): Legume for forage and soil conservation. Economic Botany 39(2): 165–175. https://doi.org/10.1007/BF02907841\u003c/p\u003e\n\u003cp\u003eSprent J (2001) Nodulation in Legumes. Royal Botanic Gardens, Kew. PMCID: PMC4233837\u003c/p\u003e\n\u003cp\u003eUzun A, Yesiloglu T, Aka-Kacar Y, Tuzcu O, Gulsen O (2009) Genetic diversity and relationships within Citrus and related genera based on sequence related amplified polymorphism markers (SRAPs). Scientia Horticulturae 121: 306–312.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1016/j.scienta.2009.02.018\u003c/p\u003e\n\u003cp\u003evanKeuren RW, Hoveland CS (1985) Clover Management and Utilization. In: Taylor NL (ed) Clover science and technology, 25\u003csup\u003eth\u003c/sup\u003e edn, American Society of Agronomy, Wisconsin, USA, pp. 326–354. \u003c/p\u003e\n\u003cp\u003eVarshney RK, Pandey MK, Bohra A, Singh VK, Thudi M, Saxena RK (2019) Toward the sequence-based breeding in legumes in the post-genome sequencing era. Theor Appl Genet 132: 797–816. https://doi.org/10.1007/s00122-018-3252-x\u003c/p\u003e\n\u003cp\u003eWard JH Jr (1963) Hierarchical Grouping to Optimize an Objective Function. Journal of the American Statistical Association 58: 236–244.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1080/01621459.1963.10500845\u003c/p\u003e\n\u003cp\u003eYeh FC, Yang RC, Boyle T (1999) POPGENE version 1.31. University of Albert and Center for International Research. Available at: http://www.ualberta.ca/~fyeh/popgene.html.\u003c/p\u003e\n\u003cp\u003eYousefi S, Saeidi H, Assadi M (2018) Genetic diversity analysis of red clover (\u003cem\u003eTrifolium pratense\u003c/em\u003e L.) in Iran using sequence related amplified polymorphism (SRAP) markers. J Agric Sci Technol 20(2) :373–386.\u003c/p\u003e\n\u003cp\u003ehttps://jast.modares.ac.ir/article_16151_51d7224dc661635dad39ba553e288220.pdf\u003c/p\u003e\n\u003cp\u003eYoussef SS, Ibrahim SA, Abdel Azim AM, Khashaba EH, El-Sharkawy AM (2019) Genetic variation among five egyptian clover cultivars using random amplified polymorphic DNA (RAPD) and sequence-related amplified polymorphism (SRAP) molecular markers. Egypt Acad J Biol Sci Physiol Mol Biol 11(2): 37–45. https://doi.org/10.21608/eajbsc.2019.31758\u003c/p\u003e\n\u003cp\u003eZeng B, Wang G, Zuo F, Chen Z, Zhang X (2012) Genetic diversity analysis of cocksfoot (\u003cem\u003eDactylis glomerata \u003c/em\u003eL.) accessions with sequence-related amplified polymorphism (SRAP) and inter-simple sequence repeat (ISSR) markers. African Journal of Biotechnology 11(67): 13075–13084. https://doi.org/10.5897/AJB11.3410 \u003c/p\u003e\n\u003cp\u003eZietkiewicz E, Rafalski A, Labuda D (1994) Genome fingerprinting by simple sequence repeat (SSR)-anchored polymerase chain reaction amplification. Genomics 20: 176–183.\u003c/p\u003e\n\u003cp\u003ehttps://doi.org/10.1006/geno.1994.1151\u003c/p\u003e\n\u003cp\u003eZoghlami A, Hassen H, Robertson LD, Reid B (1995) Observations sur la répartition et l’écologie des espèces de Trifolium et de Scorpiurus au nord de la Tunisie. Al Awamia 90: 115–120. https://www.inra.org.ma/sites/default/files/09011.pdf\u003c/p\u003e\n\u003cp\u003eZoghlami-Khélil A, Benyoussef S, Mezni M, Saïdi Missaoui H, Hanchi S, Elayed M, Gouhis F, Abdelguerfi A, Laouar M, Papastylianou P, Bilalis D, Cicek H, Ates S, Dost M (2015) Berseem clover (\u003cem\u003eTrifolium alexandrinum\u003c/em\u003e L.) in the Mediterranean Basin. Legume Perspectives 10: 27–28.\u003c/p\u003e\n\u003cp\u003ehttps://www.legumesociety.org/wp-content/uploads/2019/12/legum_perspect_10.pdf\u003c/p\u003e\n\u003cp\u003eZohary M (1970) Chapter 46. Trifolium L., In: Davis PH (ed) Flora of Turkey and the East Aegean Islands, Edinburgh University Press, Edinburgh, Scotland, vol.3, pp 384–448.\u003c/p\u003e\n\u003cp\u003eZohary M, Heller D (1984) \u003cem\u003eThe genus \u003c/em\u003eTrifolium, The Israel Academy of Sciences and Humanities, Jerusalem.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Tunis El Manar University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Trifolium juliani, Trifolium squarrosum, Molecular polymorphism, Genetic differentiation, ISSR and SRAP markers","lastPublishedDoi":"10.21203/rs.3.rs-8229370/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8229370/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn Tunisia, clovers represent a valuable genetic resource due to their economic and ecological importance in forage and pastoral systems, particularly within meslin cropping systems. However, certain species, such as \u003cem\u003eTrifolium squarrosum\u003c/em\u003e, are increasingly threatened with extinction owing to the lack of conservation and management strategies. This study proposes a clarification of the distinction between \u003cem\u003eTrifolium squarrosum\u003c/em\u003e and \u003cem\u003eTrifolium juliani\u003c/em\u003e. To substantiate this differentiation, molecular characterization was performed using two types of molecular markers: ISSR (Inter Simple Sequence Repeats) and SRAP (Sequence-Related Amplified Polymorphism). A total of 10 ISSR primers generated 70 polymorphic bands across the two \u003cem\u003eTrifolium\u003c/em\u003e species, demonstrating a high polymorphism percentage (PPB\u0026thinsp;=\u0026thinsp;80.46%), with notable variation in band patterns among primers. Conversely, 10 SRAP primer combinations yielded 46 polymorphic bands (PBP\u0026thinsp;=\u0026thinsp;73.02%). While both marker systems effectively revealed molecular polymorphism, ISSR markers exhibited slightly higher efficiency. Analysis of molecular variance (AMOVA) indicated that genetic diversity primarily partitioned between the two species, reflecting low gene flow and high genetic differentiation. Principal component analysis (PCA) and hierarchical clustering which further supported that distinction, revealed clear genetic structure among the clover species. This structure was also corroborated by robust clustering and high assignment probabilities in the Bayesian inference analysis. This study underscores the efficacy of ISSR and SRAP markers in assessing genetic diversity and differentiating clover species, providing valuable insights into their genetic relationships.\u003c/p\u003e","manuscriptTitle":"The first molecular characterization of the Tunisian-Algerian endemic Trifolium julianiBatt. and Trifolium squarrosum L. from Dyr El Kef, North West Tunisia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 08:24:54","doi":"10.21203/rs.3.rs-8229370/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2c0ba9e8-2e76-498d-8003-2eaa39a1ef3e","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58767413,"name":"Plant Molecular Biology and Genetics"}],"tags":[],"updatedAt":"2025-12-02T08:24:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-02 08:24:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8229370","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8229370","identity":"rs-8229370","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}