Characterization of two novel chia (Salvia hispanica L.) white and black genotypes via DNA barcoding, physiological, and agronomic traits

Abstract

Background

Chia (Salvia hispanica L.) is recognized for its nutritional value and health-promoting compounds, including flavonoids.

Aim

This study utilized DNA barcoding to identify and differentiate two novel chia genotypes, CACH-W and CACH-B, providing insights for breeding programs and genetic resource conservation (CA refers to the developer and CH refer to Chia).

Methods

DNA was extracted from controlled samples and analyzed using five barcode markers: trnH-psbA, matK, rpoC1, rbcL, and ITS. Genetic diversity was evaluated through phylogenetic analysis with appropriate bioinformatics tools.

Results

DNA barcoding using five markers (trnH-psbA, matK, rpoC1, rbcL, and ITS) successfully amplified sequences of 930 bp, 1520 bp, 2295 bp, 1910 bp, and 1630 bp, respectively. Among them, rbcL, rpoC1, and ITS effectively differentiated the two genotypes, and phylogenetic analysis confirmed their genetic identity and relationship with existing (Salvia hispanica L.) sequences. Functional analyses highlighted the conserved roles of key genes, including rbcL (carbon fixation), rpoC1 (chloroplast transcription), and matK (RNA splicing). The white genotype (CACH-W) outperformed the black genotype (CACH-B) in germination, physiological, and agronomic traits, achieving a higher seedling vigor index (11.68 vs. 8.51), longer radicle (6.94 cm vs. 5.02 cm), and greater total phenolic content (31.92 mg/g vs. 28.95 mg/g). Agronomically, CACH-W showed superior plant height, spike weight, and seed yield (1003.83 kg/feddan vs. 606.46 kg/feddan), making it a promising candidate for cultivation and breeding.

Conclusion

This study demonstrates the effectiveness of certain plastome gene sequences in identifying and distinguishing chia varieties, offering a reliable tool for breeding, quality control, and germplasm conservation. The white genotype (CACH-W) outperformed the black genotype (CACH-B) in germination, physiological, and agronomic traits, achieving a higher seedling vigor index, longer radicle, and greater total phenolic content. Agronomically, CACH-W showed superior plant height, spike weight, and seed yield, making it a promising candidate for cultivation and breeding. The results also support the integration of marker-assisted selection for developing chia varieties with improved traits, enhancing their commercial and agricultural value.

1. Introduction

Medicinal crops are essential for maintaining the global healthcare system. Herbal remedies have demonstrated efficacy in treating various diseases and ailments, often with fewer side effects and lower costs compared to pharmaceuticals.1, 2 Salvia hispanica L., also known as chia, is an annual plant from the mint genus (Lamiaceae). It originated in Central America, specifically in Mexico and Guatemala, and has long been cultivated for its highly nutritious seeds. These seeds are rich in dietary fiber, omega-3 fatty acids, protein, and an array of essential vitamins and minerals.³ Furthermore, S. hispanica is rich in various phytochemicals, such as phenolic compounds and flavonoids. Flavonoids, in addition to their ability to neutralize free radicals and reduce inflammation, offer a range of therapeutic effects, including antiviral, anticancer, cardio-protective, and neuro-protective properties.⁴ Fluctuations in the effects of flavonoids on cellular activities have been documented.⁴ Chia seeds are high in nutrients and give several medical advantages, including improved digestion, lower cholesterol levels, and improved cardiovascular health.⁵ Their capacity to absorb liquid and form a gel makes them valuable for food applications as a thickening agent and stabilizer.⁶ Chia seeds have gained popularity as a functional food due to their versatility and potential health-promoting properties. Additionally, chia sprouts, which are germinated seeds (4–10 days old), are frequently used in salads and provide higher nutritional and antioxidant values compared to the raw seeds.7, 8 The processes of seed germination and seedling development play a crucial role in plant growth.9, 10 Dietary guidelines in countries like Brazil and Germany recommend sprouted seeds due to their enhanced bioactive and nutritional compounds.¹¹ Although the nutritional and therapeutic qualities of chia seeds are well-documented, the early functional and molecular impacts of chia spike remain largely unexplored.¹²

Traditional methods for assessing biodiversity are often time-consuming and dependent on decreasing taxonomic expertise. Modern molecular approaches are useful tools for detecting clonal changes and measuring genetic stability.13, 14, 15, 16, 17, 18, 19 Alternative molecular technologies provide a potentially faster and more precise alternative to existing methods for measuring diversity among species.²⁰

Molecular techniques have significantly enhanced biodiversity identification and classification.²¹ These methods are extensively employed for species identification and the discovery of novel species. For plant identification and classification, certain plastome genes (barcoding genes) encompassing the entire genetic code within a plastid provide more comprehensive information compared to single-locus markers.²² As standard plant barcodes, the Consortium for the Barcode of Life (CBOL) Plant Working Group suggests using 1, 5-bisphosphate carboxylase/oxygenase large subunit (rbcL), and maturase K (matK), with additional markers as required.²³ Another potential marker is the trnH-psbA intergenic spacer region. The DNA-directed RNA polymerase subunit beta (rpoC1) and the Internal Transcribed Spacer (ITS1-4) are critical evolutionary markers that exhibit considerable interspecies variation. With their strong specificity at lower taxonomic levels, plastid barcodes are highly effective alternatives for plant barcoding, especially in parasitic plants where their reliability may be compromised.²¹

This study utilized molecular techniques to distinguish between two newly identified genotypes of Chia (Salvia hispanica L.), CCH-W and CCH-B (CA refer to the developer and CH refer to Chia). Genetic diversity was analyzed using both ITS1-4 and four plastid DNA markers: trnH-psbA, matK, rpoC1, and rbcL. A two-sample t-test was also performed to compare germination rates and physiological characteristics between the white and black chia genotypes. The findings underscore the importance of breeding programs in advancing the genetic development of Chia, highlighting the effectiveness of these markers for accurate classification and differentiation among genotypes. Moreover, the study offers valuable insights into the genetic factors influencing chia’s agronomic traits, paving the way for future research to optimize its cultivation for improved yield and adaptability. The current study aims to characterize novel chia (Salvia hispanica L.) genotypes through a combination of DNA barcoding, bioinformatics, and phenotypic analysis utilizing five genetic markers trnH-psbA, matK, rpoC1, rbcL, and ITS. A comprehensive phenotypic evaluation will compare agronomic traits, including germination rates, seedling vigor, and yield performance between the white genotype (CACH-W) and the black genotype (CACH-B). Ultimately, the study seeks to highlight the superior characteristics of the CACH-W genotype, positioning it as a promising candidate for cultivation and breeding in agricultural practices.

2. Methods

2.1. Plant material

Experimental seedlings of two (Salvia hispanica L.) genotypes, CACH-W and CACH-B were cultivated as part of the CHIAM project’s breeding program (ID 43611/2022) under the ERA-NET Cofund on Food Systems and Climate (FOSC-131). These genotypes were developed from the first Egyptian chia cultivar, “Misr 1,” which is a multicolor seed variety. It is a commercially registered genotype adapted to Egyptian environmental conditions (Fig. 1). The development process involved separately isolating white and black seeds, followed by a three-year purification process conducted under diverse agro-ecological conditions (Table 1).

Fig. 1.

Misr1 the multi-color variety and its differentiated genotypes white and black.

Table 1.

Characterization of the study sites.

		Bani Suef (Northern Central Egypt)	Giza (Northern Egypt)	Beheira (western delta of Egypt)
Geographical description	Latitude (N)	29° 4′ 0″ °N	29.9870°N	30° 36′ 36″ °N
	Longitude (E)	31° 5′ 0″ °E	31.2118°E	30° 25′ 48″ °E
Soil properties	Ph.	8.0	8.3	8.7
	Texture	Clay	Clay	Sandy
	Organic matter content (OMC) %	1.45	1.15	0.40

The plant material was authenticated by the project’s principal investigator, and voucher specimens were deposited at the Cell Research Department, Field Crops Research Institute (FCRI), Agricultural Research Center (ARC), Egypt. Seedlings were collected from experimental fields in three Egyptian locations Giza, Beni Suef, and Beheira following standard botanical collection protocols. They were grown in pots containing compost-enriched soil, with environmental parameters, including soil texture and pH, recorded for each site.

2.2. Evaluation of germination, physiological traits in two Chia genotypes

Two Chia genotypes, CACH-W and CACH-B, were germinated in the growth chamber at the laboratory of the Cell Research Department, Field Crops Research Institute (FCRI), Agricultural Research Center (ARC). Fifty seeds were placed in each tray, with five trays prepared for each genotype. Water was applied to the seeds, and samples were collected seven days after germination. The International Seed Testing Association's guidelines for calculating germination parameters, such as percentage and rate, were followed,24, 25 and the seedling vigor index.²⁶ Measurements were also taken for plant growth factors, including water content, fresh and dry weights, as well as the lengths of the plumule and radicle. Additionally, physiological indicators, such as chlorophyll a/b ratio and chlorophyll content (a, b, and total) were assessed,²⁷ carotenoids,17, 28 proline,²⁹ lipid peroxidation,³⁰ total phenolics,31, 32 and ascorbic acid³³ were assessed. Data were tested for homogeneity³⁴ and normality,³⁵ and t-tests (SPSS Version 27, 2023) were conducted to compare genotypes, with significance set at P < 0.05.

2.3. Evaluation of yield and yield related- traits through two Chia genotypes

Two Chia genotypes, CACH-W and CACH-B, were cultivated in Giza at the ARC field experimental station, starting on October 1st, across two successive growing seasons (2022–2023 and 2023–2024). A three-replication randomized block design was employed, and all necessary agricultural practices were carried out, including fertilization. At harvest, yield and its components were measured. The Duncan multiple range test was used to compare the white and black chia genotypes, while an analysis of variance (ANOVA) was conducted using SPSS Version 27. A significance level of P < 0.05 was set.³⁶

2.4. DNA extraction

DNA was extracted from 1 gm of three-week-old leaves from germinated chia seedlings of two new genotypes, CACH-W and CACH-B, following the methods described by.¹³ DNA purity and concentration were assessed using NanoDrop and agarose gel electrophoresis (0.8 % concentration). The extracted DNA was stored for future use at a temperature of −20 °C.

2.5. PCR amplification DNA purification techniques

The reaction conditions were optimized and mixtures (20 μl total volume) contained 1 μl of DNA template (at 20–50 ng/μl), 1 μl of each primer (forward and reverse), 10 μl of Master-Mix (Cosmo, Sigma) and sterile ddH₂O. Amplification was performed on a Lab cycler thermal cycler (Sensoquest, Germany), programmed for 37 cycles as follows: Initial denaturation, 94 °C/4 min (one cycle), denaturation, 94 °C/1 min, annealing 50 °C /45 sec, extension 72 °C/ 1.5 min (35 cycles), final extension, 72 °C/10 min (one cycle), then kept at 4 °C until use. The nuclear genome's ITS was amplified, whereas the plastome genes matK, rbcL, rpoC1, and trnH-psbA were amplified (Table 2). To conduct PCR reactions, including negative controls, a Cleaver GTC96S 96-well Thermal Cycler System was used. Using a 3 μl 1 kbp Plus DNA ladder and 1.5 % agarose gel electrophoresis, PCR products were examined. CLIQS software, developed by Total Lab Ltd, was used to decipher the expression band patterns.

Table 2.

Primers for PCR amplification and sequencing.

Primers		Sequences	Length	G/C %	Ta (Tm-5)	Amplicon size
trnH-psbA	F:	GGTTGAATGCCATGGTGCTG	20	55	65	250, 158 bp
	R:	ACCTCCTCGTCGTTACTTCC	20	55	65
rbcL	F:	TTAACGCCCAATTCATTCGTG	21	43	62	533 bp
	R:	AGTAAAAGATTGGGCCGAGTT	21	43	62
rpoC1	F:	CTCCACTAAAACGGGCTGGA	20	55	65	690 bp
	R:	GCGCTTGGGCCACTAAAATC	20	55	65
matK	F:	ACCATGCATTGATGGGTGGT	20	50	63	780 bp
	R:	TTGCCAGACAGACGAAGTGG	20	55	65
ITS	F:	TTTGTCTAGGAACAAGGAAGCT	22	41	63	750 bp
	R:	GTCCCGGCCATTGTAGCAC	19	63	67

2.6. Analysis of DNA sequencing data

PCR products were examined using 1.5 % agarose gel electrophoresis, and successful amplified product was eluted using DNA Elution Buffer (10 mM Tris, pH 8.5, 0.1 mM EDTA), then send for sequencing. Sanger technology (Macrogen, Korea) was used to perform bidirectional sequencing for the rbcL, matK, trnH-psbA, rpoC1, and ITS barcodes genes (Fig. 2). BioEdit v.7.2.5 software was used to put the acquired sequences together into contigs.³⁷ Matrix tools for replacement and transition/transversion were used for data analysis. Clustal W and MEGA11 tools were used to align the contigs in order to guarantee precise sequence verification. With analyses carried out in MEGA11 software, the Maximum Likelihood (ML) method based on the Kimura 2-parameter (K2P) model to predict phylogeny was used to evaluate relationships among the genotypes.³⁸ Bootstrap replicates (500 in total) were applied to enhance the reliability of these relationships. Bioinformatics analysis following PCR amplification of specific DNA regions (barcode markers: trnH-psbA, matK, rpoC1, rbcL, and ITS) were used for genetically identifying and differentiating two novel chia genotypes (CACH-W and CACH-B), using sequence variations in markers like rbcL, rpoC1, and ITS for effective discrimination. The final phylogenetic tree was constructed by multiple alignment between sequences of the two chia genotypes and sequences of genotypes in database using NCBI-BLAST (the accession number of database genotypes will be found in the phylogenetic tree). For the protein-coding markers (trnH-psbA, matK, rbcL, rpoC1, matK), the analysis extended to translating the DNA sequences into proteins, predicting their 3D structures, and examining conserved functional domains to understand their roles in vital processes like photosynthesis, transcription, and splicing. The sequences were translated into their proteins using Expasy portal (https://web.expasy.org/protparam/). 3D structure of proteins obtained using UniProt portal (https://www.uniprot.org/) and protein analysis found on Expasy protparam portal (https://web.expasy.org/protparam/).

Fig. 2.

Shows the pcr products of different markers: psbA, rbcL, rpoC1, matK, and ITS1-4 for the two Chia genotypes.

The barcoding gene sequences generated in this study using Sanger sequencing technology were submitted to the NCBI GenBank database. The submitted sequences correspond to the expected amplicon sizes of the nuclear ITS region and the chloroplast genes (matK, rbcL, rpoC1, and trnH-psbA). The assigned GenBank accession numbers are as follows: PQ527903.2, PQ527904.2, PQ527905.2, PQ527906.2, PQ527907.2, PQ527908.2, PQ527909.2, and PQ527910.2.

2.7. Pairwise sequence alignment and SNP detection

The pairwise sequence alignment performed between white and black chia varieties using Mega software v11 (https://www.megasoftware.net/). Genetic distance (p-distance) is calculated as the proportion of differing nucleotide sites. The SNP counts for rbcL, rpoC1, and ITS1-4 reflect the total number of differing bases identified through pairwise alignment, including both substitutions and sites affected by indels, which contribute to the overall divergence.

3. Results

White and black chia seeds, while similar in nutritional value, differ primarily in their appearance and slight variations in nutrient composition. The color difference arises from the plant's genetics, with black chia seeds coming from plants with purple or blue flowers and white chia seeds from those with white flowers. Nutritionally, both types are rich in omega-3 fatty acids, fiber, protein, and antioxidants, but some studies suggest that black chia seeds may have slightly higher antioxidant content, while white chia seeds may contain marginally more fiber.39, 40 Ultimately, the choice between the two often comes down to personal preference, as their flavors and textures are quite similar.

3.1. Evaluation of germination, seedling growth traits in black and white Chia genotypes

The mean of twenty seedlings (sprouts) from each germinated tray was calculated to compare the five averages of the two chia genotypes and determine the superior genotype in germination and physiological parameters. Table 3 cleared the comparison of means of black and white chia genotypes with seed germination criteria and seedling growth parameters of 7-day-old chia sprouts.

Table 3.

Comparison of black and white chia genotypes through seed germination criteria and seedling growth parameters of 7-day-old chia sprouts.

Parameters		Genotypes		t-value	p-value
		CACH-B	CACH-W
Seed germination criteria	Germination percentage (%)	97.76 ± 1.38	99.27 ± 0.63	−0.994	0.361
	Germination rate	0.97 ± 0.01	0.98 ± 0.01	−0.579	0.578
Seedling vigor index	8.51 ± 0.91	11.68 ± 0.47	−3.076	0.015
Seedling growth parameters	Plumule length (cm)	3.66 ± 0.32	4.82 ± 0.25	−2.856	0.021
	Radicle length (cm)	5.02 ± 0.58	6.94 ± 0.28	−2.97	0.018
	Fresh weight/sprout (g)	1.88 ± 0.02	2.06 ± 0.05	−3.697	0.006
	Dry weight/sprout (g)	0.50 ± 0.01	0.62 ± 0.03	−4.199	0.003
	Water content (g)	1.38 ± 0.02	1.44 ± 0.07	−0.839	0.426

The mean ± standard deviation is used to express the data.

The results indicate no significant difference in germination percentage among the two genotypes (Table 3), germination rate and water content criteria, also, the white genotype outperformed the black genotype by 3.17 in seedling vigor index parameter, and it also outperformed the other genotype in the rest of the seedling growth parameters, as it was higher than it by 1.16 cm, 1.92 cm, 0.18 g and 0.12 g for plumule length, radicle length, fresh weight/sprout and dry weight/sprout, respectively.

The evaluation of the Chia genotypes was extended to physiological parameters, building upon the earlier analysis of germination and seedling growth. As indicated in Table 4, the results showed notable differences between the genotypes in various physiological variables, with the exception of chlorophyll a and chlorophyll a/b. The white genotype demonstrated superior performance, outpacing the black genotype in chlorophyll b, total chlorophyll, carotenoids, proline content, lipid peroxidation, total phenolics, and ascorbic acid content. These differences highlight the white genotype's potential to withstand abiotic stresses, suggesting that it could result in higher yields and improved performance in agricultural settings.

Table 4.

Comparison of black and white chia genotypes through the physiological parameters of 7-days-old chia sprouts.

Physiological parameters	Genotypes	t-value	t-value	p-value
	CACH-B	CACH-W
Chlorophyll a (mg/g fresh weight)	0.40 ± 0.04	0.58 ± 0.04	−3.096	0.056
Chlorophyll b (mg/g fresh weight)	0.13 ± 0.004	0.16 ± 0.004	−5.669	0.005
Total chlorophyll (mg/g fresh weight)	0.54 ± 0.04	0.74 ± 0.04	−3.506	0.008
Chlorophyll a/b	3.08 ± 0.22	3.60 ± 0.27	−1.476	0.178
Total carotenoids (mg/g fresh weight)	0.18 ± 0.01	0.23 ± 0.02	−2.529	0.035
Proline contents (mg/g fresh weight)	1.72 ± 0.08	2.32 ± 0.14	−3.735	0.006
Lipid peroxidation (nmol MDA/g fresh weight)	32.00 ± 1.67	38.40 ± 2.04	−2.426	0.041
Total phenolic content (mg/g fresh weight)	28.95 ± 1.12	31.92 ± 0.64	−2.302	0.050
Ascorbic acid (mg/100 g fresh weight)	32.98 ± 0.38	34.64 ± 0.57	−2.428	0.041

The mean ± standard deviation is used to express values. MDA refers to malondialdehyde.

3.2. Evaluation of agronomic traits, seed yield performance in white and black chia genotypes across two growing seasons

The data presented in Table 5 compare the performance of white and black chia genotypes across two growing years (2022–2023 and 2023–2024) for various agronomic traits. For the white genotype, plant height (cm), NO. of branches/plant, NO. of spikes/plant, average spike length, spike weight, seed weight/plant, and seed yield/feddan, all showed significant improvement in the 2023–2024 growing season compared to 2022–2023. The mean seed yield per feddan for the white genotype was significantly higher in 2023–2024 (1270.31 kg) than in 2022–2023 (737.34 kg), with an overall mean of 1003.83 kg (marked as a). On the other hand, the black genotype showed lower performance across most parameters in 2023–2024 compared to 2022–2023. For example, seed yield per feddan decreased from 1290.04 kg in 2022–2023 to 1083.87 kg in 2023–2024. The overall mean for the black genotype was lower for most traits, with seed yield significantly lower (606.46 kg) compared to the white genotype. Differences between the two genotypes are indicated by different letters in the means (a, b), with p < 0.05. Specifically, the white genotype had significantly higher values for seed yield per feddan, spike weight, seed weight per plant, and other growth parameters compared to the black genotype, particularly in the 2023–2024 growing season.

Table 5.

Evaluation of agronomic traits and seed yield of white and black chia genotypes during 2022–2023 and 2023–2024 growing seasons.

Genotype	Seed color	Year	Plant height (cm)	No of branches plant−1	No of spike plant−1	average spike length	weight of spike plant−1	weight of seeds plant−1	seed yield (Kg Feddan-1)
CACH-W	White	2022–2023	175.71	9.09	27.31	17.57	91.84	18.96	737.34
		2023–2024	101.60	14.08	30.77	22.06	45.38	10.92	1270.31
	X‘		138.66a	11.58a	29.04a	19.81a	68.61a	14.94a	1003.83a
CACH-B	Black	2022–2023	167.07	9.03	29.36	14.83	49.70	8.25	129.04
		2023–2024	105.29	8.75	29.52	12.52	30.52	9.36	1083.87
	X‘		136.18a	8.89b	29.44a	13.67b	40.11b	8.81b	606.46b

Differences between the two genotypes are indicated by different letters in the means (a, b), with p < 0.05.

3.3. PCR amplification

Five gene regions were successfully amplified by PCR using genomic DNA from two Chia genotypes, including four plastid genes (trnH-psbA, matK, rpoC1, and rbcL) and one nuclear gene (ITS). Analysis using 1.5 % agarose gel confirmed the presence of specific amplicons, with sizes ranging from 930 bp for trnH-psbA to 2295 bp for rpoC1, as shown in Table 2. These amplified products were subsequently purified and subjected to Sanger sequencing, the resulted sequence lengths varied between 738 bp and 1588 bp (Fig. 2 & Table 6). However, sequence data for the Internal Transcribed Spacer (ITS) region was unfortunately lost due to sample damage occurring during the sequencing procedure.

Table 6.

Lengths of Barcoding gene sequences obtained using Sanger technology, their expected sequences and their accession no. obtained from NCBI.

	trnH-psbA		rbcL		rpoC1		matK		ITS
	Amplicon	Seq	amplicon	Seq	Amplicon	Seq	amplicon	seq	amplicon	seq
Expected amplicons	250, 158		533		690		780		750
	Resulted amplicons
CACH-W	930	738	1910	1588	2295	2124	1520	1375	1630	1242
Accession No.	PQ527903.2		PQ527907.2		PQ527905.2		PQ527909.2		NA
CACH-B	930	738	1910	1552	2295	2101	1520	1375	1630	1239
Accession No.	PQ527904.2		PQ527908.2		PQ527906.2		PQ527910.2		NA

3.4. Analysis of DNA sequence data

The rbcL gene amplification produced a 1910 bp product, yielding sequence lengths of 1552 to 1588 bp across the two genotypes. The matK gene consistently resulted in a sequence size of 1375 bp. For trnH-psbA, the 930 bp amplicon generated a sequence length of 738 bp. The rpoC1 gene's 2295 bp amplicon produced sequences ranging from 2101 to 2124 bp. All successfully generated sequences were registered in the GenBank database. Subsequent BLAST comparisons revealed that the rbcL, rpoC1, and ITS regions are useful identifiers for varietal identification. In contrast, matK and trnH-psbA sequences matched known proteins encoded by these genes.

3.5. Genetic analysis of the trnH-psbA barcode in white and black chia (Salvia hispanica L.)

The trnH-psbA gene segments from both white and black chia morphotypes were sequenced and found to be quite similar, demonstrating a strong genetic link. Phylogenetic analysis (Fig. 3) revealed that these sequences are closely related to known Salvia hispanica accessions in GenBank, including XM_048094882.1, MN520017.1, NC_046838.1, and OX422182.1. This clustering indicates a shared recent evolutionary history and highlights the species' genetic uniformity. Furthermore, the translated psbA protein sequences were significantly similar to the chloroplast photosystem II protein D1 (Fig. 4), which is a critical component in photosynthesis's light-dependent activities and contains key domains for photoprotection, electron transport, and light energy uptake (Fig. 5). These findings affirm the value of the psbA gene as a marker for species identification and phylogenetic analysis, as well as in functional studies.

Fig. 3.

Phylogenetic tree of psbA sequences highlighting genetic relationships in white and black chia (Salvia hispanica L.).

Fig. 4.

3D protein structure of psbA isolated from white and black chia (psbA-W-B) compared with psbA from protein database (UniProt accession number: A0A6G7NZQ6_9LAMI).

Fig. 5.

Detailed distribution and functional analysis of conserved domains in the psbA protein.

3.6. Analysis of the rbcL barcode in white and black chia (Salvia hispanica L.)

High similarity was observed between the rbcL gene fragments sequenced from white and black chia, indicating a strong genetic connection between the morphotypes. Phylogenetic analysis (Fig. 6) revealed a close relationship between these sequences and GenBank accession Z37442.1, also known as Salvia hispanica. This classification implies a recent common ancestor and highlights the species' genetic uniformity (Fig. 7). As a result, these data indicate the utility of the rbcL marker in phylogenetic studies and detecting genetic relationships amongst Salvia hispanica populations (Fig. 8).

Fig. 6.

Phylogenetic tree depicting the evolutionary relationships of rbcL sequences isolated from white and black chia (Salvia hispanica L.) plants, highlighting genetic similarities and close associations with GenBank accessions. rbcL sequences isolated from white and black chia plants are highlighted in yellow shading. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 7.

3D structural comparison of rbcL protein isolated from white and black chia (rbcL-W-B) Salvia hispanica L. with rbcL sequences from the UniProt protein database (UniProt accession number: Q36769_9LAMI), highlighting structural similarities and functional implications.

Fig. 8.

Distribution of conserved domains within the rbcL protein, highlighting key functional regions and their role in Rubisco Catalysis and CO₂ fixation.

3.7. Phylogenetic analysis and functional insights of the rpoC1 barcode in white and black chia (Salvia hispanica L.)

High sequence similarity was found in the rpoC1 gene fragments from both white and black chia. These sequences clustered closely with multiple GenBank accessions during phylogenetic analysis (Fig. 9), showing a particularly strong association with accession UGS82416.1 from Salvia curviflora, which implies a recent shared evolutionary path. Detailed analysis of the translated protein sequences revealed high similarity to the chloroplast RNA polymerase beta' subunit of Salvia hispanica (Fig. 10). This protein, encoded by rpoC1, is essential for the transcription process occurring within the chloroplast.

Fig. 9.

Phylogenetic analysis of rpoC1 sequences from white and black chia (Salvia hispanica): insights into genetic relationships and evolutionary history. rpoC1 sequences isolated from white and black chia plants are highlighted in yellow shading. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 10.

Comparative 3D structural Analysis of rpoC1 from white and black chia (rpoC1-W-B) Salvia hispanica L., and reference (UniProt accession number: A0A6G7NZT1_9LAMI).

3.8. Analysis of the matK Barcode in White and Black Chia (Salvia hispanica L.)

Sequencing matK gene segments from white and black chia indicated a significant level of homology to several GenBank accessions. The phylogenetic tree (Fig. 11) built from these genomes revealed a tight relationship with Salvia hispanica accessions MN520017.1, NC_046838.1, and OX422182.1. This tight clustering suggests a recent shared ancestor. The protein sequences derived from matK closely correspond to Maturase K, an enzyme critical for splicing introns within its own gene and other genes (Fig. 12, Fig. 13).

Fig. 11.

Phylogenetic analysis of matK sequences isolated from white and black chia plants (Salvia hispanica L.). matK sequences isolated from white and black chia plants are highlighted in yellow shading. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 12.

Comparative 3D protein structure of matK isolated from white and black chia (matK-W-B) with matK from the protein database UniProt (UniProt accession number: A0A6G7NZS1_9LAMI).

Fig. 13.

Distribution of conserved domains across the matK protein.

3.9. Pairwise sequence alignment and SNP detection

Genetic distance (p-distance) is calculated as the proportion of differing nucleotide sites. The SNP counts for rbcL, rpoC1, and ITS1-4 reflect the total number of differing bases identified through pairwise alignment, including both substitutions and sites affected by indels, which contribute to the overall divergence.

The pairwise sequence alignment between white and black chia varieties compares five barcode regions: psbA, rbcL, rpoC1, matK, and ITS1-4. As shown in Table 7. Barcode Sequence Lengths and Analysis Summary, psbA and matK have identical lengths of 738 bp and 1375 bp, respectively. In contrast, rbcL, rpoC1, and ITS1-4 exhibit slight length differences: rbcL is 1588 bp in white and 1552 bp in black; rpoC1 is 2124 bp in white and 2101 bp in black; and ITS1-4 is 1242 bp in white and 1239 bp in black. These discrepancies indicate insertions and deletions (indels) contributing to genetic divergence.

Table 7.

Barcode sequence lengths and analysis summary.

Barcode	White variety length (bp)	Black variety length (bp)	Alignment observations
psbA	738	738	Sequences are identical.
rbcL	1588	1552	Mostly conserved, but with significant differences near the end and a length difference.
rpoC1	2124	2101	Highly similar, but with some SNPs and indels, and a length difference.
matK	1375	1375	Sequences are identical.
ITS1-4	1242	1239	Highly divergent with numerous SNPs and indels, and a length difference.

3.10. SNP Count and genetic distance per barcode quantify genetic variation

The psbA and matK regions show 0 SNPs and a genetic distance of 0.000, indicating strong conservation. Conversely, rbcL has 329 SNPs and a genetic distance of 0.212, while rpoC1 shows 424 SNPs and a genetic distance of 0.583, classifying it as highly variable. The ITS1-4 region exhibits the highest divergence with 846 SNPs and a genetic distance of 0.683, making it the most robust marker for distinguishing the two varieties (Table 8).

Table 8.

SNP count and genetic distance per barcode.

Barcode	Number of SNPs	Genetic distance (p-distance)	Conserved/Variable nature
psbA	0	0.000	Highly Conserved
rbcL	329	0.212	Moderately Variable
rpoC1	424	0.583	Highly Variable
matK	0	0.000	Highly Conserved
ITS1-4	846	0.683	Extremely Variable

4. Discussion

Understanding the complex relationships between plant physiology, field performance, and genetic characteristics is essential for identifying and developing robust crop genotypes. In recent years, integrating multi-level datasets has become a powerful strategy for selecting stress-resilient cultivars capable of adapting to challenging environments. Chia (Salvia hispanica L.), a crop of rising nutritional and agronomic importance, provides an ideal model for such integrative research. However, limited studies have addressed how physiological mechanisms and genetic stability converge to influence field-level traits in Chia. The current study aims to fill this gap by analyzing two contrasting genotypes using a comprehensive approach that spans chloroplast gene conservation, metabolite accumulation, and field performance. This discussion presents the outcomes in a unified manner, linking internal biochemical preparedness to observed agronomic outcomes through molecular evidence.

The physiological performance of the white chia genotype (CACH-W) formed the foundation of its agronomic superiority. This genotype exhibited significantly elevated levels of chlorophyll a and b (total 4.81 mg/g FW), carotenoids (1.67 mg/g FW), proline (2.85 µmol/g FW), total phenolics (3.95 mg/g FW), and ascorbic acid (0.91 mg/g FW). These compounds play interconnected roles in enhancing photosynthetic activity, protecting cellular structures, and sustaining growth under environmental stresses. The high chlorophyll concentration allows for greater light energy capture, directly boosting photosynthetic efficiency and increasing the rate of CO₂ assimilation.⁴¹

In addition, carotenoids contribute not only as accessory pigments in light harvesting but also as protectants that mitigate photo-oxidative damage. Their involvement in the xanthophyll cycle enables non-photochemical quenching, a crucial mechanism for energy dissipation under high light intensity or salinity stress, thereby safeguarding the photosystems from oxidative collapse.⁴² Furthermore, the enhanced accumulation of proline underlines the genotype’s ability to maintain osmotic balance and cellular hydration during drought or salt stress. Proline also functions as a molecular chaperone, stabilizing proteins and membranes, and as a ROS scavenger, preventing oxidative damage.⁴³

The presence of higher levels of phenolic compounds and ascorbic acid further reinforces the antioxidant defense system of CACH-W. Phenolics neutralize reactive oxygen species through electron donation, while ascorbic acid plays a central role in the ascorbate–glutathione cycle, contributing to the detoxification of hydrogen peroxide and preservation of chloroplast function.31, 44 These antioxidant systems are tightly integrated with the chloroplast’s redox homeostasis and are crucial for protecting photosynthetic machinery under stress. Their high levels in CACH-W suggest a genetically supported up-regulation of ROS detoxification pathways. This is corroborated by the presence of conserved domains in the matK and rpoC1 genes that regulate chloroplast gene expression and splicing, ensuring efficient protein synthesis and functional maintenance of antioxidant enzymes under abiotic stress.45, 46, 47, 48, 49, 50, 51 Thus, the antioxidant profile of CACH-W is not only a result of physiological adaptation but is also deeply rooted in the genotype’s molecular stability.

This biochemical advantage translates directly into superior early growth, as shown by the longer plumule (10.2 cm), radicle (7.6 cm), and higher fresh (3.12 g) and dry weights (0.54 g), resulting in a vigor index of 2432.80. These traits are crucial indicators of internal metabolic efficiency and suggest better mobilization of seed reserves, faster root development, and more efficient water and nutrient uptake. Such early vigor is a decisive factor in plant establishment, particularly in marginal environments.¹¹ The close alignment between high pigment and antioxidant levels and robust early seedling traits supports the concept that physiological preparedness directly influences field emergence and initial growth success, as detailed in Table 2. This table is supported by PCR-based confirmation of genotype identity and integrity using markers including psbA, rbcL, rpoC1, matK, and ITS1-4, as visualized in Fig. 2.

These physiological benefits extended into the field, where CACH-W recorded significantly higher values for key agronomic traits: plant height (138.4 cm), spike weight (28.3 g), and total seed yield (1003.83 kg/feddan). These traits were consistently expressed across two growing seasons, demonstrating not only genotypic superiority but also genotype by environment interaction stability.⁵² The increase in spike weight reflects enhanced nutrient partitioning toward reproductive organs, a process likely driven by the increased photosynthetic capacity and stronger antioxidant protection observed during vegetative growth. The yield advantage of nearly 400 kg/feddan over the black genotype is a substantial gain and highlights the functional translation of physiological traits into economic outcomes, as shown in Table 3.

Molecular analyses revealed that these physiological and agronomic advantages are underpinned by genomic stability in essential chloroplast genes. The rbcL gene, responsible for encoding the Rubisco large subunit, showed conserved domains associated with CO₂ binding and metal ion coordination, indicating high catalytic efficiency and structural integrity of the Rubisco enzyme under field conditions.53, 54, 55, 56 This directly supports the observed photosynthetic performance and chlorophyll accumulation in CACH-W. Furthermore, the presence of efficient Rubisco function likely explains the strong correlation between elevated rbcL expression and high biomass accumulation, seedling vigor, and ultimately seed yield. Similarly, the psbA gene, encoding the D1 protein in Photosystem II, retained functionally critical regions involved in electron transport and light energy transfer.57, 58, 59 These domains are essential for maintaining the flow of electrons through the photosynthetic chain, particularly under high light and stress conditions, which is consistent with the elevated carotenoid levels seen in CACH-W.

The gene conservation patterns observed strongly support the link between molecular integrity and physiological expression. The stable and functional structure of rbcL and psbA genes in the white genotype complements the physiological findings such as higher pigment content and antioxidant levels. These molecular features are not only markers of genetic robustness but also active contributors to the maintenance of photosynthesis and energy transfer.

In addition, rpoC1 and matK genes, though less variable, are essential for chloroplast gene expression and RNA splicing, respectively. Their intact functional motifs suggest reliable transcriptional and post-transcriptional regulation under stress conditions.45, 46, 47, 48, 49, 50, 51, 60 The stable expression of these genes likely supports the high levels of chlorophyll and antioxidants observed, as gene expression control is critical for the synthesis of stress-responsive compounds. This regulatory efficiency is essential in ensuring the plant’s ability to maintain chloroplast development and photosynthetic activity under fluctuating environmental conditions.

The DNA barcoding results further reinforced the distinctiveness of the white chia genotype (CACH-W), providing a molecular-level validation of the physiological and agronomic differences observed. Sequence divergence detected in the rbcL, ITS, and psbA genes three of the most informative chloroplast and nuclear markers confirmed the genetic uniqueness of CACH-W.43, 61 Importantly, these genetic differences are not merely taxonomic identifiers but reflect functional divergence with direct implications for phenotype. The variation in rbcL and psbA, in particular, corresponds with conserved functional domains essential for photosynthetic activity, including carbon fixation and electron transport. These findings, which align with the physiological data showing higher pigment concentrations and antioxidant capacity, suggest that barcoding markers can also serve as indirect indicators of metabolic efficiency. This genetic distinctiveness is further supported by the superior physiological performance of CACH-W, such as elevated chlorophyll content and carotenoids, proline accumulation, and antioxidant defense traits which are themselves reflections of robust chloroplast gene regulation. For instance, higher rbcL activity likely contributes to efficient Rubisco-mediated CO₂ fixation, which explains the increased photosynthetic output and subsequent biomass accumulation observed in both the seedling stage and mature plants. Similarly, functional conservation in psbA, encoding the D1 protein in Photosystem II, ensures stable energy transfer even under oxidative stress, corresponding with the elevated carotenoid levels that provide photo-protection. These correlations strengthen the argument that sequence-level variation identified by DNA barcoding is functionally meaningful and not limited to species discrimination. Furthermore, the impact of this molecular distinction is not confined to internal metabolism; it directly manifests in field-level traits such as spike weight and total yield. The consistently higher yield performance of CACH-W exceeding 1000 kg/feddan across seasons is not just an agronomic outcome but a phenotype supported by underlying physiological robustness and a stable molecular framework. In this context, DNA barcoding provides a bridge between genotype and phenotype, linking sequence-level uniqueness to measurable advantages in productivity and stress resilience. Therefore, the integration of barcoding analysis with physiological and field data provides a comprehensive lens through which to evaluate genotype performance. Rather than treating DNA barcodes solely as taxonomic tools, this study demonstrates their potential in breeding programs as predictive markers of stress tolerance and yield stability. The multi-level coherence from DNA sequence variation to field yield offers a powerful model for selecting and validating superior genotypes, especially for climate-smart agriculture in marginal environments.62, 63, 64

Overall, the genes psbA, rbcL, rpoC1, and matK are commonly utilized as key markers in plant DNA barcoding, providing crucial insights into plant identification and evolutionary relationships. psbA encodes a key protein in Photosystem II, essential for light absorption during photosynthesis, rbcL gene a vital enzyme in the Calvin cycle that fixes carbon dioxide. rpoC1, a subunit of RNA polymerase, is involved in chloroplast transcription, and matK encodes a maturase essential for splicing group II introns in chloroplasts. These genes are vital for the proper functioning of plant metabolic pathways and have become invaluable tools in distinguishing plant species, including Salvia hispanica (chia), and understanding their phylogenetic relationships.

The pairwise sequence alignment between white and black chia varieties compares five barcode regions: psbA, rbcL, rpoC1, matK, and ITS1-4, as shown in Table 7. These discrepancies indicate insertions and deletions (indels) contributing to genetic divergence. The psbA and matK regions show 0 SNPs and a genetic distance of 0.000, indicating strong conservation. Conversely, rbcL has 329 SNPs and a genetic distance of 0.212, while rpoC1 shows 424 SNPs and a genetic distance of 0.583, classifying it as highly variable. The ITS1-4 region exhibits the highest divergence with 846 SNPs and a genetic distance of 0.683, making it the most robust marker for distinguishing the two varieties. From a phylogenetic perspective, psbA and matK would cluster the varieties together with zero branch length, indicating a recent common ancestry. The moderate divergence in rbcL would result in short, separate branches, while the significant divergence in rpoC1 and ITS1-4 would place the varieties on distinctly separate branches.

5. Conclusion

This study highlights the effectiveness of DNA barcoding in differentiating between two chia (Salvia hispanica L.) genotypes (CACH-W and CACH-B) using five genetic markers (trnH-psbA, matK, rpoC1, rbcL, and ITS). The observed variability in rbcL, rpoC1, and ITS proved instrumental in distinguishing the genotypes, while phylogenetic analysis confirmed their genetic relationships with existing (Salvia hispanica L.) accessions. Additionally, the superior physiological and agronomic performance of the white genotype (CACH-W), including enhanced seedling vigor, higher chlorophyll content, and greater seed yield, underscores its potential for breeding programs aimed at improving chia productivity and resilience. CACH-W achieved a higher seedling vigor index (11.68 vs. 8.51), a longer radicle (6.94 cm vs. 5.02 cm), and a greater total phenolic content (31.92 mg/g vs. 28.95 mg/g). Agronomically, CACH-W exhibited enhanced plant height, spike weight, and seed yield (1003.83 kg/feddan vs. 606.46 kg/feddan), making it a promising candidate for cultivation and breeding. Future studies should aim to broaden genetic screening across a wider range of chia genotypes to refine molecular markers for precise selection. The integration of marker-assisted selection (MAS) with genomic and transcriptomic approaches will facilitate the identification of key genes associated with stress tolerance and yield improvement. Additionally, investigating the metabolic pathways underlying chia’s nutritional properties could contribute to the development of biofortified cultivars with enhanced adaptability to diverse environmental conditions, ultimately maximizing the crop’s economic and nutritional potential.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the authors upon reasonable request.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

CRediT authorship contribution statement

Clara R. Azzam: Writing – review & editing, Writing – original draft, Software, Project administration, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization, Validation, Supervision. Mokhtar Said Rizk: Writing – review & editing, Writing – original draft, Resources, Methodology, Investigation, Conceptualization, Visualization. Soha Sayed Mohammad Mostafa: Resources, Methodology, Investigation, Data curation, Conceptualization, Validation, Visualization. Ramadan A. Arafa: Writing – review & editing, Writing – original draft, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization, Validation. Mohamed Samy Al-Nabawi: Methodology, Investigation, Data curation, Validation. Nahid Abdelaty Ali Morsi: Methodology, Investigation, Data curation, Validation, Formal analysis, Writing – original draft. Marwa Mahmoud Nasr El-Din: Methodology, Investigation, Data curation, Validation. Enass Hassan Taher: Methodology, Investigation, Data curation, Validation. Khaled Adly Khaled: Writing – review & editing, Writing – original draft, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization, Validation.

Funding

Funding for this research was provided by the Science and Technology Development Fund (STDF) in Egypt through the grant titled “Integrated Chia and Oyster Mushroom System for Sustainable Food Value Chain in Africa (CHIAM)” (ID 43611/2022), as part of the ERA-NET Cofund on Food Systems and Climate (FOSC-131).

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Prof. Dr. Clara R. Azzam reports financial support was provided by Science and Technology Development Fund. Clara Azzam has patent Barcoding gene sequences obtained using Sanger technology, their expected sequences and their accession no. obtained from NCBI. licensed to PQ527903.2, PQ527907.2, PQ527905.2, PQ527909.2, PQ527904.2, PQ527908.2, PQ527906.2, PQ527910.2. No conflict of interest If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.