Assessment of Genetic Diversity of Euphorbia hirta Linn in the Philippines using sequence-related amplified polymorphism (SRAP) markers

doi:10.21203/rs.3.rs-4851656/v1

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Assessment of Genetic Diversity of Euphorbia hirta Linn in the Philippines using sequence-related amplified polymorphism (SRAP) markers

https://doi.org/10.21203/rs.3.rs-4851656/v1

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Euphorbia hirta Linn. is a medicinal plant found in the Philippines and known for its application for dengue management. E. hirta collected from different geographical locations have demonstrated variations in anti-thrombocytopenic activity in vivo. Hence, it is necessary to determine the intraspecific diversity of E. hirta to provide insights on the observed bioactivity. In this study, thirty-one (31) E. hirta plant specimens were collected from various geographic locations in the Philippines. Species identity was confirmed through DNA barcoding using rbcL and matK primers. Identification of intraspecies genetic variations were made through Sequence-Related Amplified Polymorphism (SRAP) analysis. Three (3) SRAP primer pairs produced 23 distinct and reproducible bands with average percent polymorphism of 84.63. The average values of the evaluation indices Nei’s genetic diversity (H) and Shannon’s diversity index (I), and the Polymorphic Information Content (PIC) of the primers were 0.332 ± 0.017, 0.484 ± 0.024, and 0.425, respectively. A moderate genetic differentiation (F_st = 0.172; P value = 0.001) were also found in the E. hirta accessions. UPGMA clustering based on the presence or absence of these bands grouped the plant samples into three clusters. Geographical distance did not play a role in the clustering. Two gene loci were also identified to have a potential use as markers for species identification. The study has shown the utility of SRAP markers to generate DNA fingerprints and identify E. hirta genetic variants. This may be adapted as a standard method in the molecular characterization of medicinally important plant samples.

Euphorbia hirta

Sequence-related amplified polymorphism

genetic diversity

primer screening

DNA fingerprinting

Euphorbia hirta Linn., also known as snakeweed or locally termed as tawa-tawa/gatas-gatas, is a weed commonly found in wastelands and open grasslands of tropical and subtropical countries including the Philippines (Perera, Jayawardena, and Jayasinghe, 2018). It has been traditionally recognized to have various medicinal applications and have been validated to exhibit anti-inflammatory (Regassa et al., 2022), antibacterial (Tran et al., 2020), antioxidant (Cayona et al., 2022), antihelminthic, antitumor (Amtaghri et al., 2022), and antithrombocytopenic activities (Rahman et al., 2019). Studies have also revealed that it is generally safe to use (Ghosh et al., 2019) and in the Philippines, the leaves of E. hirta are used to make a decoction to alleviate dengue viral infection and associated symptoms. Interestingly, in a study by Heralde III and colleagues (2015), methanolic extracts of E. hirta collected from various geographical locations demonstrate varying platelet increasing activity in thrombocytopenic mouse model. Such observed variations in anti-thrombocytopenic activity of the E. hirta may be attributed to the influence of both genetic and environmental factors affecting the production of bioactive secondary metabolites. Thus, it is necessary to determine the intraspecies level of diversity to elucidate the potential of E. hirta for its medicinal applications.

Sequence-Related Amplified Polymorphism (SRAP) is one of the DNA- and PCR-based molecular systems that are used to assess plant diversity. It provides an invaluable tool for plant diversity analysis through its multilocal and dominant markers that can estimate the genetic variation in plants without the need for prior information on genomic sequence (Li, Gao, Yang, and Quiros, 2003). SRAP markers amplify coding regions of DNA with primers targeting open reading frames. These markers have proven to be robust and highly variable at lower taxonomic levels (Al-Ghamedi et al., 2023). Aside from these, SRAP analysis is cost-effective, reproducible with its single-step protocol, and requires minimal technical effort due to its binary scoring/reporting (0 or 1). SRAP have been successfully employed to show the intraspecific genetic diversity in various plant species such as Distylium chinense (Xiang et al., 2020), Stipa bungeana (Baiakhmetov et al., 2020), and many more. In the Philippines, SRAP was used to determine the intraspecies diversity in Allium sativum Linn. (Ilocos Pink) as supplemented by morphoanatomical and metabolite profiling (Relacion, Martin, Manalo, and Heralde III, 2023). With the observed variations in the bioactivity of E. hirta and the limited number of studies exploring the molecular diversity of E. hirta, this study aimed to provide a baseline information on the genetic variants of E. hirta found in the Philippines through DNA barcoding and SRAP analysis.

2.1. Collection of plant material

Thirty-nine (39) Euphorbia hirta plant samples were purposively collected based on accessibility of the location as well as its known availability in the Philippines. These locations include Cebu, Leyte, Bicol, South Cotabato, Cavite, La Union, Nueva Ecija, Metro Manila, Ilocos Sur, Pampanga, Iligan, Dipolog, Zamboanga del Sur and Eastern Samar. All plant samples were harvested at their full blooming stage. Collected plant samples were immediately stored in an ultra-low freezer until analyzed. Plant herbarium and voucher specimens with sample codes were submitted to Institute of Biology, University of the Philippines Diliman, Quezon City, Philippines for authentication (Supplemental Fig. 1).

2.2. Extraction of genomic DNA

Genomic DNA was extracted from young E. hirta leaves using and following the protocol of i-genomic Plant DNA Extraction Kit (iNtRON Biotechnology, South Korea). The quality and concentration of the DNA samples were assessed by agarose gel electrophoresis, and NanoDrop ND-1000 Spectrophotometer (NanoDrop Technologies, Wilmington, USA), respectively.

2.3 Species identification by DNA barcoding

Primers for rbcL and matK (Table 1) were used to confirm species identity of the collected samples. Amplification reactions were carried out in a 20 µl reaction mixture using a DOPPIO thermal cycler (VWR International, PA, USA). Each reaction contains 20 ng DNA template, 1X Platinum Green Hot Start PCR Master Mix (Invitrogen, California, USA), 0.2 µM of each primer, and nuclease-free water.

The PCR conditions for rbcL consist of 4 min of initial denaturation at 94°C followed by 35 cycles of 94°C for 30 s, 55°C for 30 s, 72°C for 1 min and then final extension at 72°C for 10 min. For matK, the PCR conditions consist of initial denaturation at 94°C for 1 min followed by 35 cycles of 94°C for 30 s, 52°C for 20 s, 72°C for 50 s and then final extension 72°C for 5 min (Lo and Shaw, 2018).

Table 1

Primer sequences used for DNA barcoding
Primer name	Sequence (5’-3’)	Direction	References
rbcLa-F	ATG TCA CCA CAA ACA GAG ACT AAA GC	Forward	Todd et al. (2020)
rbcLa-R	GTA AAA TCA AGT CCA CCR CG	Reverse	Li et al. (2015)
matK-xf	TAA TTT ACG ATC AAT TCA TTC	Forward	Zhang et al. (2018)
matK-MALP	ACA AGA AAG TCG AAG TAT	Reverse	Xie et al. (2020)

Amplification products were subjected to agarose gel electrophoresis at 100 V for 30 minutes, using 1.2% agarose gel and 0.5X TAE buffer. Estimation of the size of the amplicons used as the DNA marker was done with a VC 100bp plus DNA ladder (100–3,000 bp) (Vivantis, Malaysia). The PCR products were purified using a GF-1 Gel DNA Recovery Kit (Vivantis, Malaysia), and then submitted to Macrogen Inc. (South Korea) for sequencing using both the forward and reverse primers

The DNA sequences obtained were used as queries in the BLASTn search tool for molecular based species identification. Sequences were aligned together with reference and outgroup sequences obtained from GenBank. Aligned sequences were trimmed to obtain a consistent sequence length for all the samples. The phylogenetic analysis based on the rbcL and matK regions were performed using MEGA 7 using a Maximum Likelihood (ML) model. The best fit ML model was also determined using the software. Bootstrap support (BS) values for individual clusters were calculated by running 1000 bootstrap replicates of the data.

2.4. SRAP Fingerprinting

2.4.1. Selection of primer pair combinations

Twenty-five SRAP primer combinations from five forward and five reverse primers were initially screened (Table 2) (Relacion et al., 2023). Primer pairs that have banding patterns difficult to score or have failed to amplify consistently were excluded from the study. Primer pairs that produced consistent amplifications and clear polymorphic bands were used for the rest of the samples. PCR reactions were repeated at least thrice to confirm the reproducibility of the results.

Table 2

SRAP primers used in the study
Primer name	Primer sequence	Direction
ME1	5’- TGA GTC CAA ACC GGA TA − 3’	Forward
ME2	5’- TGA GTC CAA ACC GGA GC − 3’
ME3	5’- TGA GTC CAA ACC GGA AT − 3’
ME4	5’- TGA GTC CAA ACC GGA CC − 3’
ME5	5’- TGA GTC CAA ACC GGA AG − 3’
EM1	5’- GAC TGC GTA CGA ATT AAT − 3’	Reverse
EM2	5’- GAC TGC GTA CGA ATT GAC − 3’
EM3	5’- GAC TGC GTA CGA ATT TGA − 3’
EM4	5’- GAC TGC GTA CGA ATT AAC − 3’
EM5	5’- GAC TGC GTA CGA ATT GCA − 3’

2.4.2. DNA amplification by Polymerase Chain Reaction (PCR)

Amplification reactions were carried out in a 20 µL reaction mixture using a DOPPIO thermal cycler (VWR International, PA, USA). Each reaction contains approximately 20 ng DNA template, 1X Platinum Green Hot Start PCR Master Mix (Invitrogen, California, USA), 0.2 µM of each primer, and nuclease-free water. The PCR profile consists of a 5 min initial denaturation at 94°C, then five cycles of three steps: 1 min of denaturation at 94°C, 1 min of annealing at 35°C, 1 min of extension at 72°C, followed by 35 cycles with annealing temperature increased to 50°C, and a final extension step of 5 min at 72°C. The amplification fragments were resolved by agarose gel electrophoresis at 100 V for 30 minutes with 2% agarose gel and 0.5X TAE buffer.

2.4.3. SRAP Data analysis

Gel image analysis was performed using the PyElph software tool. Reproducible SRAP bands were scored as present (1) or absent (0). Smeared and weak bands were excluded. Fragments of the same molecular weight from the same primers were considered as the same locus. Allele frequencies and percent polymorphism were identified through POPGENE (v1.32) software. Assessment of the SRAP markers’ capacity to estimate genetic variability was determined through the computation of the polymorphic information content (PIC), multiplex ratio (EMR), and marker index (MI). The calculations of the PIC followed the formula indicated in the study by Botstein and colleagues (1980). EMR is the average number of DNA fragments amplified per genotype using a marker. The MI measures the primer’s ability to detect polymorphic loci among various genotypes and was calculated as a product of PIC, EMR and Fraction polymorphism (FP).

For genetic diversity assessment, GenAlEx 6.51 program was used to estimate various parameters such as Shannon's information index (I), Nei's gene diversity (H), unbiased expected heterozygosity (uH), Observed number of alleles (N_a) and Effective number of alleles (N_e). Analysis of molecular variance (AMOVA) was used to assess the degree of genetic variation among and within clusters groups, with the standard 999 times random permutations. An unweighted pair-group method with arithmetic mean (UPGMA) dendrogram was constructed to examine the genetic relationship among the populations based on the Simple Matching coefficient using NTSYSpc ver. 2.1. Mantel Test was also used to examine the correlation between the genetic variants and geographical distance.

3.1. Sample Collection

A total of 39 Euphorbia hirta samples were collected from different sites in the Philippines. Divided into the three island groups of the Philippines, twenty-four came from Luzon (61.5%), ten from Visayas (25.7%) and five from Mindanao (12.8%). The geographical distribution of these samples is represented in Fig. 1 and its global positioning system (GPS) coordinates is indicated in Supplemental table 1. Samples Eh16, Eh20 and Eh31 were excluded because of poor sample quality brought by wilting. The remaining 36 samples collected were used for the experimental procedures of the study.

3.2. Species Identification through rbcL and matK DNA analysis

DNA with good quality were isolated from 34 out of 36 samples used. Samples Eh18 and Eh22 had poor quality DNA and were excluded in the subsequent molecular analysis. The rbcL DNA region of E. hirta was successfully amplified in all 34 DNA samples. However, only 31 of the 34 amplicons generated good quality sequences based on their quality scores in the chromatogram and low number of ambiguous base calls (N’s) (Supplemental Fig. 2). The bidirectional sequence length of rbcL ranged from 457 to 571 nt.

BLASTn analysis of the rbcL sequences showed 100% identity match with Euphorbia hirta. The same species identity was obtained from the Barcode of Life Database (BOLD). The aligned length is 449 nt after trimming the ends to obtain a consistent length for phylogenetic analysis (Fig. 2a).

Molecular phylogenetic analysis of the 31 aligned sequences, reference E. hirta sequences and an outgroup sequence, Euphorbia hyssopifolia, was conducted by constructing a Maximum Likelihood (ML) tree based on the Jukes-Cantor model in MEGA7 software (Fig. 2b). All the 31 E. hirta sequences clustered with the reference sequences (GenBank accessions KF432064.1, GU441776.1, KX015732.1, JQ591416.1) in a single branch, with the tree rooted to the outgroup. This confirmed that the 31 samples collected were indeed Euphorbia hirta. The rbcL gene was also able to discriminate E. hirta from E. hyssopifolia through substitutions in 3 sites in the aligned sequence. These are nucleotide substitutions of T to C at position 88, C to T at position 430 and A to C at position 434.

The matK chloroplast gene that codes for the maturase K enzyme was also used to barcode the plant samples. The matK DNA region was successfully amplified and sequenced in 30 out of the 34 DNA samples. Samples Eh07, Eh11, Eh12 and Eh37 have noisy sequencing traces, and were excluded in the analysis. The bidirectional sequence length of matK ranged from 636 to 898 bp.

BLASTn analysis of the matK sequences showed 99.7%-100% identity match with Euphorbia hirta. The same species identity was obtained from the Barcode of Life Database, BOLD. Sequence alignment showed identical sequences in all the 30 samples (Supplemental Fig. 3). The aligned length is 594 nt after trimming the ends to obtain a consistent length for phylogenetic analysis (Fig. 3a).

Molecular phylogenetic analysis of the 30 sequences and an out-group was conducted by constructing a Maximum Likelihood (ML) tree based on the Tamura 3-parameter model in MEGA7 software (Fig. 3b). Similar to the rbcL gene, all the 30 E. hirta sequences clustered in a single branch with the reference sequences (GenBank accessions GQ434078.1, GU441795.1, HQ645733.1, MF159450.1), with the tree rooted to Euphorbia hyssopifolia. Both rbcL and matK barcode regions were able to confirm species identity of the E. hirta samples collected. In addition to this, both regions were able to discriminate E. hirta from the out-group E. hyssopifolia. For matK, substitutions in 12 sites in the aligned sequence. Single nucleotide substitutions observed were from T to C at positions 75, 144, 419 and 455, C to G at position 215, T to G at position 290, A to G at position 303, G to C at position 313, C to A at position 420 and 455, G to T at position 450, and G to A at position 460. Supplemental table 2 lists the sequences obtained and used in this study.

3.3. Sequence Related Amplified Polymorphism (SRAP) Analysis

Thirty-one E. hirta samples with confirmed species identity through rbcL and matK were used for the SRAP analysis. Twenty-five SRAP primer pairs were screened for their ability to produce clear, polymorphic, and reproducible banding patterns. Based on these criteria, primer combinations ME1-EM5 (SRAP-E), ME3-EM2 (SRAP-L), and ME4-EM1(SRAP-P) were selected. Six E. hirta samples were excluded from further analysis because of inconsistent banding patterns produced.

A total of twenty-three (23) DNA fragments that were clear and reproducible were generated by these three primer pairs, of which twenty (20) were polymorphic based on their allele frequencies determined through POPGENEv1.32 analysis (Supplemental Table 3). Bands with the same molecular weight were considered to be allelic, and originate from the same locus. Weak or ambiguous bands were excluded from the analysis. The molecular weight of these ranged from 90 to 1,600 bp. These DNA fragment loci were labeled E1 to E10, L1 to L4 and P1 to P9 based from which the bands were generated, and from longest to shortest fragment size. Four to ten polymorphic fragments were scored for each primer pair. Primer pair SRAP-E produced the highest number of amplification products with 10 DNA fragments (Fig. 4a), followed by SRAP-P with 9 DNA fragments (Fig. 4c). SRAP-L produced the lowest number with only four DNA fragments (Fig. 4b). Only loci E7 and L3 were consistently present in all the E. hirta samples analyzed.

Genetic variability parameters revealed the discriminatory capacity of the three SRAP marker pairs (Table 3). A total of 669 fragments were produced from three SRAP primer pairs, with a mean of 223 per marker pair. The SRAP-E produced 280 fragments, followed by SRAP-P with 225, and finally, SRAP-L which produced 164 fragments. The average PIC value of the three SRAP marker pairs was 0.425. The maximum PIC value was 0.439 while the minimum PIC value was 0.402. Aside from this, the fraction polymorphism (FP) differ across the SRAP markers having 0.9, 0.89, and 0.75 for SRAP-E, SRAP-P, and SRAP-L markers respectively. The average percent (%) polymorphism for all SRAP marker pairs were recorded as 84.63. Finally, the SRAP-E has the highest marker index of 3.903, followed by SRAP-P with 3.514 and SRAP-L with 1.206.

Table 3

Genetic variability among 25 *E. hirta* samples, as revealed by SRAP markers
Primer combination	Total number of fragments	Total number of bands	Number of Polymorphic loci	Fraction Polymorphism (FP)	% Polymorphism	PIC value	Marker Index
ME1-EM5 (SRAP-E)	280	10	9	0.9	90.00	0.434	3.903
ME3-EM2 (SRAP-L)	164	4	3	0.75	75.00	0.402	1.206
ME4-EM1 (SRAP-P)	225	9	8	0.89	88.89	0.439	3.514
Total	669	23				1.275
Average	223	8	7	0.85	84.63	0.425

3.4. Genetic Diversity by E. hirta

The genetic diversity estimates for the three E. hirta cluster groups are presented in Table 4. The Shannon's information index (I), Nei’s gene diversity index (H), and the number of alleles observed (N_a) are the evaluation indices used to characterize the E. hirta population which has a direct correlation with the genetic diversity of the marked E. hirta population. SRAP-P produced the highest evaluation indices among the tested SRAP primer pairs (N_a = 1.694 ± 0.118; I = 0.513 ± 0.041; h = 0.357 ± 0.030). The intra-cluster genetic diversity was highest in SRAP-P (h = 0.357 ± 0.030) followed by SRAP-L and SRAP-M (h = 0.347 ± 0.030 and 0.293 ± 0.030, respectively).

The assessment of genetic variation within and among E. hirta accessions was made through AMOVA (Table 5). Majority (83%) of the variation was due to variation within the SRAP clusters while the rest (17%) was due to variation among SRAP groups. The mean fixation index (F_st) among the three clusters have demonstrated moderate genetic differentiation (F_st = 0.172). Moreover, the difference within and among the groups were all statistically significant (P value = 0.001).

Table 4

Different genetic diversity estimates for three SRAP groups of *Euphorbia hirta* accessions.
Marker	N	N_a	N_e	I	H	uH
SRAP-E	10	1.639 ± 0.127	1.501 ± 0.059	0.438 ± 0.041	0.293 ± 0.030	0.326 ± 0.033
SRAP-L	4	1.694 ± 0.111	1.628 ± 0.060	0.500 ± 0.043	0.347 ± 0.030	0.463 ± 0.040
SRAP-P	9	1.694 ± 0.118	1.649 ± 0.059	0.513 ± 0.041	0.357 ± 0.030	0.401 ± 0.034
Mean		1.676 ± 0.068	1.593 ± 0.035	0.484 ± 0.024	0.332 ± 0.017	0.397 ± 0.021
Legend: N, Individual number of populations; Na, No. of different Alleles; Ne, No. of effective alleles; I, Shannon’s information index; h, Nei’s gene diversity; uh, Unbiased expected heterozygosity.

Table 5

Analysis of molecular variance (AMOVA) among and within the three SRAP groups of *Euphorbia hirta* accessions.
Source of variation	df	PMV (%)	SS	MS	Est. Var.	F_st	P value
Three groups
Among groups	2	17	33.814	16.907	1.403	0.172	0.001
Within groups	20	83	135.578	6.779	6.779
Total	22	100	169.391		8.182
Legend: df, degree of freedom; PMV, Percentages of molecular variance; SS, square deviation; MS, mean square deviation; Est. Var., exist variance; F_st, coefficient of genetic differentiation.

The presence or absence of these 23 SRAP markers were used to generate a UPGMA dendrogram. The genetic similarity coefficients among the 25 samples varied from 0.3043 to 0.9130. The lowest similarity coefficient was observed between Eh2 and Eh26. In contrast, the highest similarity coefficient was between Eh2 and Eh21, and between Eh14 and Eh17. The result grouped the 25 E. hirta samples into three distinct clusters at 0.65 coefficient cutoff. Cluster I consists of 15 samples, Cluster II with 6 samples, and Cluster III with 4 samples. The major group (Cluster I) consisted of samples from different Philippine geographical regions with a mix from the three major groups of islands Luzon, Visayas and Mindanao. The similarity matrix based on SRAP, however, did not have a significant relationship with the geographic separation of the samples (Mantel statistic: R = 0.0740, p = 0.1822).

Based on the generated tree, these clusters have characteristic banding patterns that were resolved by the SRAP-E, SRAP-L and SRAP-P primers (Fig. 5). Cluster I is characterized by the presence of bands E7, E9, L3, P6, and absence of P8 and P9. Cluster II have 7 loci that were consistently present. These were bands E7, E8, E9, L3, P6, P8 and P9. Band E4 is absent in Cluster II. The presence of bands P8 and P9 in Cluster II mainly separated it from Cluster I. For Cluster III, only bands E7, E8, L2 and L3 were consistently present. Multiple bands, E1, E2, E4, L1, P1, P3 and P7, were not observed in the samples included in Cluster III (Fig. 6).

The safety and efficacy of herbal medicines largely depend on their quality. Techniques for plant identification, analysis of purity and confirmation of the presence of chemical markers are being standardized to assure quality of plant medicinal products. The current standard in pharmaceutical companies include monitoring of chemical markers for its quality control (Nazim et al., 2018). However, the presence and levels of these markers are not always predictive of its bioactivity (Ruiz et al., 2016). For plant identification, DNA barcoding has been utilized well to discriminate substitutes and adulterants (Palhares et al., 2015). Identification of medicinal plants, however, often ends at the species level, and the influence of intraspecific genetic variation to observed bioactivities are overlooked. An important consideration is that aside from environmental factors, genetic factors may also influence phytochemical constituents.

The popular therapeutic properties of E. hirta ensues problems with authentication when collected from the field. This primarily involves misidentification due to nomenclatural confusion and morphological similarity to other species (De Villa, 2017) Correct identification of E. hirta in this study was therefore a crucial first step to ensure correct assessment of its genetic variants. The high amplification and sequencing success rate of rbcL and matK in E. hirta, as well as its ability to discriminate from the closely related E. hyssopifolia, qualifies these two genes as effective DNA barcode regions for its correct species identification. Compared to rbcL, the matK region has more variable sequences that increases the resolution among plant species (Lo and Shaw, 2018). The chloroplast gene matK has been successfully used to discriminate closely related species under the Chamaesyce clade of the Euphorbia genus (Wei et al., 2021). However, matK was unable to resolve the genetic differences among the 25 E. hirta samples analyzed. Suitability of barcode gene region for plants is based on the genetic variability at the species-level only (Lo and Shaw, 2018). It is therefore expected that the samples that were all identified as E. hirta would cluster in a single branch in the ML tree.

The inability of DNA barcodes to reveal substantial genetic variation in E. hirta was compensated by the use of SRAP markers. These markers provided a way to easily characterize genetic variation in E. hirta. The primary method of primer combination selection was to mark all samples with each primer and assess the primers based on produced polymorphic bands, percentage of polymorphism and PIC value. The three SRAP primer pairs produced an average of 84.63% polymorphism and is considered high as compared to 68.22% by using 17 combinations among Pyricularia oryzae (Longya et al., 2020) and 35.68% by using 4 combinations in Sideroxylon spinosum (Pakhrou et al., 2020). Among the three, SRAP-E produced the highest percent polymorphism of 90% and can be used as the primary pair of choice in characterizating E. hirta species using SRAP. Likewise, the three SRAP primer pairs were able to generate DNA fingerprints which led to the classification of E. hirta into three genetic variants. Two conserved genomic regions (E7 and L3) were also observed using the SRAP markers, and may be of potential use as a genetic marker for E. hirta.

Several molecular markers have been employed to reveal polymorphisms within species, but the choice of marker is usually dependent on the objective (Kress et al., 2015). SRAP markers were less commonly used than other DNA-based molecular markers but have been shown to be suitable for evaluating genetic diversity in medicinal plants (Relacion et al., 2023; Peng et al., 2015). These markers can also provide information pertaining to intraspecific differences in plants (Cardone et al., 2021). In this study, the aim was to use SRAP to obtain a DNA fingerprint that can reveal genetically different groups of E. hirta. SRAP has the advantage of being simple and fast to perform, and not requiring previous sequence information on E. hirta. Additionally, the use of AGE instead of PAGE to visualize polymorphic bands proved to be a more practical method as it is quicker and easier to perform, while still being able to reveal sufficient genetic variation in E. hirta. The high potential of arbitrary primers to detect polymorphisms at the species level was also shown in other Euphorbia species (Moustafa et al., 2016). However, this is the first time that the intraspecific genetic diversity in E. hirta has been studied. Evaluation indices have provided useful information on the genetic variability observed within and among the E. hirta accessions. AMOVA also revealed the significant moderate variation among and within clusters of E. hirta. The use of SRAP markers on E. hirta provided an effective approach to differentiate the samples used in the study and show their genetic relationships.

Intraspecific genetic variations have been shown to affect metabolite diversity in plants (De Santis et al., 2021; Havananda et al., 2019). There were also reports where genetic polymorphisms have been associated with observed phenotypic traits (Hirpara et al., 2016). This intraspecific variation was also true for E. hirta (Ahmed and Noureldeen, 2022). However, previous reports on E. hirta variants have already been reconsidered or refuted (Heralde III et al., 2015), and may not be used to evaluate the influence of genetic factors to observed bioactivities. The study, therefore, provides new insight on how we characterize plant natural products in order to have a more robust evaluation of bioactivities.

The separation of E. hirta samples into groups based on their SRAP profile was found to be unrelated to the geographic distance of collection sites. SRAP profiles were commonly observed to be related with geographic distance, but was not always the case (Huang et al., 2020; Amiriyan et al., 2019; Moonsap et al., 2019). The distribution of this dominant group of E. hirta across a wide region may be due to the seed dispersal mechanisms typical to weeds. Most of the species in the Chamaesyce clade of Euphorbia tend to have small, sticky seeds that can adhere to birds for long-distance dispersal (Horn et al., 2014). Likewise, evaluation indices have provided useful information on the genetic variability observed within and among the E. hirta accessions. AMOVA also revealed the significant moderate variation among and within clusters of E. hirta. The use of SRAP markers on E. hirta provided an effective approach to differentiate the samples used in the study and show their genetic relationships.

Overall, the study has shown the potential use of SRAP markers to identify genetic variants within E. hirta. This, however, has been limited by the sample size to make a firm generalization. Analysis of more E. hirta samples using the same SRAP primers may help validate the markers identified in this study. Future studies comparing the bioactivities within and among the clusters may also be performed to determine the extent of how these variations can influence the observed therapeutic properties.

The Euphorbia hirta found in the Philippines can be classified into three genetic variants based on the produced SRAP banding profiles. In addition, the three SRAP primers produced higher percent polymorphism in E. hirta as compared with other species. The study contributes to the dearth in information on SRAP application as molecular profiling tool in the country. The study also suggests its potential to be adapted as a quick and easy DNA fingerprinting method for the molecular characterization of not only E. hirta, but also of other plant species with known therapeutic uses.

AGE

agarose gel electrophoresis

BLASTn

Basic Local Alignment Search Tools–nucleotide

DNA

deoxyribonucleic acid

matK

maturase K

PAGE

polyacrylamide gel electrophoresis

PCR

polymerase chain reaction

rbcL

Ribulose 1,5–biphosphate carboxylase

SRAP

Sequence–related amplified polymorphism

TAE

Tris–acetate–ethylenediaminetetraacetic acid

UPGMA

unweighted pair–group method with arithmetic mean

Ethics approval and consent to participate.

The study is registered under the Research Grants Administration Office (RGAO) of the university (RGAO 2016 − 0510). The authors confirm that all methods were carried out by relevant guidelines and regulations of the university. The ethics review exemption was issued by the Research Ethics Board of the university (Supplemental Fig. 4). Similarly, the collection of the plants used in the study complies with local or national guidelines with no need for further affirmation.

Consent for publication.

Not applicable.

Competing interests.

The authors declare no competing interests.

Assessment of Genetic Diversity of Euphorbia hirta Linn in the Philippines using sequence-related amplified polymorphism (SRAP) markers

Patrick Gabriel G. Moreno¹, Patrick R. Relacion^1,, and Francisco M. Heralde III^1*

¹Department of Biochemistry and Molecular Biology, College of Medicine, University of the Philippines Manila, Pedro Gil St., Ermita Manila, Philippines 1000

*Corresponding author’s email address: [email protected]

Funding.

Not applicable.

Author Contribution

PGGM designed experiment, collected the samples, performed the experiments, analyzed the data, and wrote the manuscript; PRR analyzed the data and wrote the manuscript; FMH designed the experiment, analyzed the data, and wrote the manuscript. The authors read and approved the final manuscript.

Acknowledgement

Authors would like to thank Department of Biochemistry and Molecular Biology, College of Medicine, University of the Philippines – Manila, Philippines for providing research facilities.

Availability of data and material.

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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No competing interests reported.

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Assessment of Genetic Diversity of Euphorbia hirta Linn in the Philippines using sequence-related amplified polymorphism (SRAP) markers

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Abstract

Figures

1. Introduction

2. Materials and methods

2.1. Collection of plant material

2.2. Extraction of genomic DNA

2.3 Species identification by DNA barcoding

2.4. SRAP Fingerprinting

2.4.1. Selection of primer pair combinations

2.4.2. DNA amplification by Polymerase Chain Reaction (PCR)

2.4.3. SRAP Data analysis

3. Results

3.1. Sample Collection

3.2. Species Identification through rbcL and matK DNA analysis

3.3. Sequence Related Amplified Polymorphism (SRAP) Analysis

3.4. Genetic Diversity by E. hirta

Discussion

Conclusion

Abbreviations

Declarations

Author Contribution

Acknowledgement

Availability of data and material.

References

Additional Declarations

Supplementary Files

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