Genetic architecture of anthocyanin pigment traits and purple spot (Stemphylium vesicarium) resistance in an F₁ pseudo‐testcross population of asparagus

Abstract

Stemphylium vesicarium (Wallr.) Simmons is a plant pathogenic fungus causing purple spot in both fern and spears of asparagus (Asparagus officinalis L.). Although the fern can be sprayed with fungicides to control the disease, pesticide applications during spear harvest are restricted. Infected spears can develop prominent pigmentation at lesion sites, reducing marketable yield. Breeding resistant asparagus cultivars with decreased lesion numbers and reduced purpling at the site of infection is considered the most economical and sustainable approach to combat this disease. The objectives of this study were to determine the genetic architectures of, and relationships among, anthocyanin pigment expression in spear scale leaves (ALS) and spear lesions (APS) and purple spot levels in spears (NPS) and fern (PSF). Traits were phenotyped over 2 years under natural conditions in an F₁ pseudo‐testcross population, and quantitative trait loci (QTL) were mapped. ALS, APS, NPS, and PSF were not correlated, suggesting independent regulation of the anthocyanin pathway in scale leaves and lesions and no relationship between pigment and disease. Segregation, 3 red:1 purple and 3 red:13 purple, was observed in scale leaves and lesions, respectively. Two stable QTL for each of ASL, APS, and NPS, one tentative QTL for ASL, four tentative QTL for APS, two tentative QTL for NPS, and three tentative QTL for PSF were identified. Candidate genes were found for four loci. This study advances the genetic understanding of anthocyanin pigmentation at a tissue‐specific level, and purple spot disease severity in spears and fern, supporting future breeding efforts.

Core Ideas

• One‐ and two‐gene models governed the inheritance of anthocyanin color in scale leaves and purple spot lesions.

• Anthocyanin levels in scale leaves and purple spot lesions were not linked to disease resistance in spear and fern.

• Six stable and 10 tentative quantitative trait loci (QTL) were identified for anthocyanin levels and purple spot resistance traits.

• Five candidate genes were mapped within the QTL regions.

1. INTRODUCTION

Asparagus officinalis L. is an herbaceous, dioecious perennial in the Asparagaceae family with a chromosome number of 2n = 2x = 20 and a haploid genome size of 1323 Mb (Bennett & Leitch, 2011). The cultivation of asparagus is challenged by various biotic and abiotic stresses that reduce growth and yield. Among these, purple spot, caused by the necrotrophic fungus Stemphylium vesicarium (Wallr.) Simmons, represents a major biotic stress that is a substantial threat to asparagus production worldwide (Han et al., 2019). This pathogen infects asparagus spears in the spring and produces lesions and anthocyanin at the infection sites. The infected spears have low visual appeal and are mostly unmarketable, thus reducing yield by up to 50% (Menzies et al., 1992). In the summer, the disease also manifests as purple spot lesions on the fern, damaging stems, branches, and cladophylls, which reduces the rate of photosynthesis, inhibits the flow of carbohydrates to the roots, and decreases spear yield in the subsequent year (Elena, 2007; Hausbeck et al., 1999).

In response to purple spot infection, the asparagus plant produces anthocyanins at the lesion sites. Anthocyanins can also accumulate in spear scale leaves and on the entire spear in certain cultivars. Six unique anthocyanin pigments have been identified: cyanidin, peonidin, malvidin, delphinidin, petunidin, and pelargonidin (Dong et al., 2019; Liang et al., 2022). Among these, cyanidin tri‐glycoside and peonidin‐3‐glucoside are the most abundant and provide purple and red color to spears, respectively. Their visible coloration is influenced by pH and co‐pigmentation (Khoo et al., 2017). Acidic conditions usually intensify the red color, neutral pH results in purple or violet color, and alkaline conditions shift the color toward blue, while co‐pigmentation with flavonoids or phenolic compounds enhances color intensity and stability (Boulton, 2001). In addition to their role in pigmentation, anthocyanins contribute to disease resistance via antioxidant activities (Sicilia et al., 2021), activation of defense‐related genes, synthesis of antimicrobial phytoalexins, and formation of physical barriers at infection sites to restrain pathogen invasion (Ibraheem et al., 2010; Khusnutdinov et al., 2021). Despite their role in plant defense response, anthocyanin production can sometimes increase plant susceptibility to diseases due to resource allocation trade‐offs (Figuero et al., 2021; Tanaka et al., 2014).

The inheritance, biosynthesis, and regulation of anthocyanin pigments in plants is a complex process influenced by several factors, including multiple genes, their interactions, and the environment (Gould et al., 2000; Lee & Collins, 2001). In asparagus, dominant alleles can enhance, or suppress anthocyanin production (Helper et al., 1957; Peirce, 1982; Sakaguchi et al., 2008). A quantitative effect, increasing pigment intensity by the cumulative action of alleles at two loci, has also been demonstrated (Janick & Topoleski, 1963), as well as modifier genes affecting color and intensity (Peirce, 1982).

Preliminary observations suggested cultivar‐specific differences among ‘Guelph Millennium’ (GM), ‘Guelph Eclipse’ (GE), and ‘Jersey Giant’ (JG) for disease severity and anthocyanin pigment production in response to S. vesicarium spear infection. GM showed less intense pigment development at lesion sites and fewer lesions than GE and JG (unpublished data). Although both cultivars produce anthocyanin pigments in their spear scale leaves and cladodes, GE and JG respond more strongly than GM to cool weather, increasing pigment production. Preliminary studies on cultivars GE and GM indicated a potential link between natural pigment intensities in scale leaves and pigmentation at lesion sites (unpublished data). However, these associations require further validation in segregating populations, as relying on comparisons among a limited number of genotypes can be biased by genetic background effects and sample size.

Previous efforts to breed asparagus cultivars resistant to purple spot in fern identified significant genotypic variation for disease traits, particularly within an F₁ segregating population (Moreno‐Pinel et al., 2021). Greenhouse screening of progeny from a plant resistant to purple spot in fern showed higher disease tolerance than cultivar JG, a standard for commercial production at the time (Falloon et al., 1987). Varying purple spot lesion numbers per spear were also observed among cultivars under controlled infections (Austin, 2023); however, no asparagus cultivar displayed complete resistance.

Although variation for anthocyanin pigment color, red or purple, and concentration in both scale leaves and purple spot lesions have been observed, the relationships between these factors have not been studied to determine if similar or independent pathways for pigment production exist. Additionally, associations between disease levels and anthocyanin traits have also not been assessed. To address these gaps, three hypotheses are proposed: (1) Pigment levels in scale leaves and lesions are correlated, with overlapping loci controlling tissue‐specific anthocyanin accumulation; (2) purple spot severity in spear and fern are not correlated; and (3) disease severity and pigment levels are not correlated, with distinct genetic loci controlling each trait. The objectives were to develop a segregating F₁ pseudo‐testcross population to assess purple spot severity in spear and fern, quantify anthocyanin pigments in scale leaves and lesions, and map quantitative trait loci (QTL) for these traits to understand tissue‐specific regulation of anthocyanin pigments and relationships with purple spot resistance. By dissecting the genetic architecture underlying tissue‐specific anthocyanin production and its relationship with disease resistance, this study aims to provide valuable insights for breeding asparagus cultivars with improved disease resistance and desirable color attributes.

2. MATERIALS AND METHODS

2.1. Plant material

Due to the dioecious nature of asparagus, where male and female plants occur in separate plants, selfing usually does not occur. To facilitate genetic mapping, an F₁ pseudo‐testcross population was developed by crossing two heterozygous parents: a female clone derived from cultivar Viking 2K and a supermale derived from cultivar JG. The female parent had light red pigmentation in the scale leaves, whereas the supermale had dark purple. The female also had fewer purple spot lesions in the spear and less intensity of pigmentation at the infection site than the male parent.

A pseudo‐testcross mapping strategy (Grattapaglia & Sederoff, 1994) is commonly used in outcrossing species like asparagus and involves crossing two heterozygous parents to produce an F₁ population. This strategy focuses on markers that are heterozygous in one parent and homozygous in the other, simulating a Mendelian testcross. Separate genetic maps are created for each parent, which can be integrated with markers heterozygous in both parents that segregate 1:2:1.

Core Ideas

• One‐ and two‐gene models governed the inheritance of anthocyanin color in scale leaves and purple spot lesions.

• Anthocyanin levels in scale leaves and purple spot lesions were not linked to disease resistance in spear and fern.

• Six stable and 10 tentative quantitative trait loci (QTL) were identified for anthocyanin levels and purple spot resistance traits.

• Five candidate genes were mapped within the QTL regions.

2.2. Plant establishment

Seeds of the F₁ pseudo‐testcross population, along with control cultivars GM and GE, were initially sown in 288‐cell plug trays using a potting mix (Sunshine L.C. 4, Sun Gro Horticulture) in the greenhouse during March 2018 and 2019. After 40 days, seedlings were transferred to 50‐cell plug trays filled with the same potting mix and grown in the greenhouse at 25/20°C (day/night) under natural irradiance with a 12 h photoperiod supplement with high‐pressure sodium lamps (∼80 µmol m² s⁻¹). Plants were fertilized weekly with 20N:3.50P:16.60K (1.25 g L⁻¹; Plant Products Limited). In June 2018 and 2019, 173 and 243 10‐week‐old seedlings, as well as control, were transplanted across two sites at the Simcoe Research Station in Simcoe, Ontario (Lat. 42°51′ N; Long. 80°16′ W, elevation 240.50 m), respectively. All seedlings, including controls, were spaced 0.30‐m in 20‐cm deep trenches, with rows spaced 1.25 m. Crowns were initially covered with 5 cm of soil, and trenches were gradually filled with soil over the summer. Guard rows were planted around the entire field to minimize the edge effect.

2.3. Experimental design

The 416 individuals from the F₁ pseudo‐testcross population and controls were phenotyped at two sites for two replicate years, and data were analyzed in an augmented randomized complete block design (Federer, 1956) structured in 28 blocks. Each block consisted of twenty genotypes, 18 of which were test entries (test genotypes), and the remaining two were control entries. Test genotypes were randomly assigned within each block in a row, while the control plants, either GM or GE, were alternately planted after every fifth and tenth genotype in a block. These seed‐propagated check cultivars were chosen for their extreme variation in anthocyanin pigment and purple spot traits in lieu of the parents of the cross, which would have required tissue culture micropropagation to achieve the required numbers for the experiment.

2.4. Phenotyping

Anthocyanin pigments in the scale leaves and at the sites of infection were assessed using two methods. First, a nominal scale was used for phenotyping the presence and absence of purple and red anthocyanin pigment in the scale leaves and sites of infection (Figure 1). Second, a 1–9 ordinal scale was employed to quantify anthocyanin pigment levels for the ASL (Figure 2) and APS (Figure 3) traits. The number of purple spot lesions on individual spears (NPS) was counted in response to natural purple spot infection. Data for all traits were collected on two spears per genotype (20 ± 5 cm in length), once weekly for 3 weeks in early May for two consecutive years, 2021 and 2022, from the same plants of the F₁ pseudo‐testcross population and controls. As asparagus is a perennial crop, the F₁ pseudo‐testcross population remained genetically stable across both years for evaluation.

FIGURE 1.

Visual rating used to evaluate anthocyanin pigment phenotype in the scale leaves (A and B) and purple spot lesions (C and D) in an asparagus F₁ pseudo‐testcross population as red (A and C) and purple (B and D).

FIGURE 2.

Variation of natural anthocyanin pigment in scale leaves in an asparagus F₁ pseudo‐testcross population where 1 and 9 indicate the phenotypic classes with the lowest and highest pigment levels, respectively.

FIGURE 3.

Variation of anthocyanin pigment levels in response to purple spot infection in an asparagus F₁ pseudo‐testcross population where 1 and 9 indicate the phenotypic classes with the highest and lowest pigment levels, respectively.

Plants were rated for anthocyanin pigment by three individuals, and the average of three ratings was computed to minimize the potential bias or error from a single rater. Spears of each genotype were also photographed in the field under natural light. The visually scored pigment data for all genotypes were validated using digital image review. Purple spot severity in fern (PSF) was evaluated in the last week of September and the first week of October in both 2021 and 2022 from natural infection after fungicide sprays ceased in late August. Disease severity in fern was scored using an ordinal scale (Figure S1). Phenotypic datasets collected using nominal, ordinal (ASL, APS, and PSF), and quantitative (NPS counts) were used for QTL analyses.

2.5. Extraction and quantification of anthocyanin

Total anthocyanin concentration was estimated following the method described by Sims and Gamon (2002). Five spears representing each phenotypic category (1–9 scale) for anthocyanin pigment in the scale leaves and purple spot lesions were collected from the field in early May 2021 and stored in a cooler during transport to the laboratory. Scale leaves were removed from the spears, and 1.0 × 0.5 cm sections of epidermal tissue at lesion sites containing four to five lesions of consistent size were dissected from each spear. Tissues were pooled for each phenotypic category of scale leaves and lesions, frozen with liquid nitrogen, and stored at −80°C until extraction. The freeze‐dried samples were ground into a fine powder using a mortar and pestle in the presence of liquid nitrogen. From the powdered samples, 100 mg was transferred to an Eppendorf tube containing 2 mL of acidified methanol (90:1:1 methanol:HCL:water, v/v/v) and mixed using a vortex. The homogenate was then centrifuged at 14,000 g for 10 min. From the supernatant, 1 mL was placed in a cuvette, and absorbance was measured at both 529 nm and 650 nm. Total anthocyanin was calculated using the following formula:

$$\begin{array}{ccc}& & \mathrm{Anthocyanin}\left(\frac{\mathrm{mg}}{100\mathrm{g}}\right)\hfill \\ & & =\frac{\left[\left(A529-0.288\times A650\right)\times \mathrm{D}.\mathrm{F}\times \mathrm{M}.\mathrm{W}\times V\times 1000\right]}{\left(\mathrm{\epsilon }\times P\times X\right)}\hfill \\ & & \times 100\hfill \end{array}$$ (1)

where (A529 − 0.288 × A650) is anthocyanin absorbance corrected for chlorophyll absorbance; D.F is the dilution factor (set as 1, the volume of samples remains constant); M.W is the molecular weight (449.2 for cyanidin‐3‐glucoside; the dominant anthocyanin in asparagus); V is the final volume (L) of anthocyanin containing supernatant; X is the weight (g) of the asparagus powder extracted; ɛ is the molar absorbance coefficient for anthocyanin (26,900), and P is the cuvette pathlength (1 cm).

In early May 2021, during the peak period of anthocyanin pigment expression, 10 asparagus spears (25 ± 5 cm) representing each phenotypic category (1–9) for scale leaves and lesions were collected from the field. Scale leaves and lesion tissue samples were handled and processed to produce powder, as described above. From the powder samples, 100 mg was added to an Eppendorf tube with 2 mL of 70% aqueous methanol. The mixture was incubated overnight at 4°C, then centrifuged at 14,000 g for 10 min. The samples were filtered through a 0.45 µm chromatography filter and then transferred to high‐performance liquid chromatography vials (National Scientific; model no. B7999‐1) with each vial containing a total volume of 500 µL. For analysis, 2 µL were analyzed with the Vanquish Flex Binary ultra‐high performance liquid chromatography system interfaced with a Thermo Scientific Q‐Exactive Orbitrap mass spectrometer utilizing a column C18 (Kinetex XB‐C18 100A) for chromatography separation, following the method outlined by Cox et al. (2021).

2.6. Genotyping

For DNA extraction, green fern tissues were collected from the 416 individuals of the F₁ pseudo‐testcross population and parents in 2021 in 15 mL Falcon Tubes (Thermo Fisher Scientific) and placed on dry ice. Samples were then frozen at −80°C and freeze‐dried using a Savant ModulyoD Thermoquest (Savant Instruments). Genomic DNA was extracted from 30 to 40 mg of dry fern per genotype using a NucleoSpin Plant II kit (Macherey‐Nagel) per the manufacturer's instructions. The quality of DNA was verified using a NanoDrop spectrophotometer (Thermo Fisher Scientific). DNA concentration was measured using a Qubit 2.0 fluorometer (Invitrogen), and samples (10 ng/µL) were sent to Plate‐forme D'analyses Génomiques at Université Laval (Laval) for genotyping‐by‐sequencing (GBS). The restriction enzymes MspI and PstI were used to generate the sequence library, following the methods outlined by Mascher et al. (2013). Sequencing was conducted on an Ion Proton sequencing machine (Life Technologies) by Université Laval, Québec, Canada. A total of 746 million reads, each ranging in length from 50 to 150 base pairs, were generated with a GC content of 49.91% and an average Q30 ratio of 89.36%, indicating the high quality of sequencing data.

The initial data preparation, genotyping, and filtration were executed using STACKS v2.62 (https://catchenlab.life.illinois.edu/stacks/) and stacks workflow v2.62 (https://github.com/enormandeau/stacks_workflow) following the methods described by Rochette and Catchen (2017). The demultiplexed reads were aligned to the reference genome using the Burrows–Wheeler Aligner (BWA v0.7.17‐r1188) with parameters ‐k 19 ‐c 500 ‐O 0,0 ‐E 2,2 ‐T 0 (Li & Durbin et al., 2008). These were further processed with SAM tools v1.8 with the flags ‐Sb ‐q 1 ‐F 4 ‐F 256 ‐F 2048, which converted data into the binary format while also filtering based on mapping quality and read types (Li & Durbin et al., 2008). To conclude the procedure, the population module from STACKS was run with parameters ‐p 1 ‐r 0.5 –ordered‐export –fasta‐loci –vcf to execute the last step of the STACKS pipeline, calculating population genetics statistics, exporting data in various formats, and conducting genotyping.

After genotyping, using STACKS steps, filtering of identified SNPs was performed using an in‐house Python script, 05_filter_vcf_fast.py, with parameters 3, 60, 0, and 1 so that all genotypes had a minimum coverage of 3, and all samples combined had at most 40% missing SNP data. This filtering process facilitated the generation of a high‐quality dataset suitable for downstream genetic analysis.

2.7. Linkage map construction, QTL analysis, and candidate gene identification

The filtered SNPs belonged to three distinct groups of marker segregation: (a) maternal testcross markers that were heterozygous in the female parent and homozygous in the male parent segregating as in the classical backcross (lm × ll) at a 1:1 ratio; (b) paternal testcross markers that were heterozygous in male parent and homozygous in the female parent (nn × np) segregating at a 1:1 ratio; (c) inter‐cross markers, which were heterozygous in both parents (hk × hk) and segregating in 1:2:1 ratio. For each parental map construction, only single‐dose markers were used. Markers segregating at distorted Mendelian ratios were removed. The single‐dose markers from the maternal and paternal parents were analyzed separately using JoinMap 5.11 (Van Ooijen, 2018), and the outcross‐pollinated family was selected as the population type. The linkage groups (LGs) were built using a regression mapping algorithm, with a minimum logarithm of odds (LOD) value at 4 for marker grouping and a maximum recombination frequency of 0.40. The distance between the markers was generated using the Kosambi map functions (Kosambi, 2016). LGs were drawn with MapChart (Voorrips, 2002). Heterozygous markers in both parents (hk × hk) were selected for integrated map construction after those with segregation distortion were eliminated.

For each genotype, means were estimated over the multiple sampling dates in each of the 2 years, then over the 2 years. To account for spatial heterogeneity within each block, individual yearly means and the combined 2‐year mean for each genotype were independently adjusted based on the average values of the replicated check treatments (GM and GE) among and within each block using a linear mixed model. The negative values from this adjustment were set to zero for correlation and QTL analysis, as negative means are not biologically feasible. An adjusted genotype mean was obtained using the formula:

$$\begin{array}{ccc}& & \mathrm{Adjusted}\mathrm{genotype}\mathrm{mean}=\mathrm{Genotype}\mathrm{mean}\hfill \\ & & -\left(\mathrm{mean}\mathrm{of}\mathrm{GM}\mathrm{and}\mathrm{GE}\mathrm{within}\mathrm{a}\mathrm{block}\right.\hfill \\ & & \left.-\mathrm{grand}\mathrm{mean}\mathrm{of}\mathrm{GM}\mathrm{and}\mathrm{GE}\mathrm{across}\mathrm{all}\mathrm{blocks}\right)\hfill \end{array}$$ (2)

QTL analysis was conducted using two methods based on the nature of the traits. For nominal data, such as the presence and absence of purple and red anthocyanin pigment in the scale leaves and lesions, QTL analysis was performed using R/qtl (Broman et al., 2003). For ordinal data (ASL, APS, PSF, and NPS), QTL were detected using composite interval mapping in WinQTL Cart 2.5 (Wang et al., 2012) with a walking speed of 1 cM. For determining the cofactors, a forward and backward regression method with a probability threshold of 0.1 and a window size of 10 cM was used. The significance of detected QTL was determined using an LOD threshold based on a 1000 permutation test for each dataset with a significance level of p ≤ 0.05 (Churchill & Doerge, 1994). A 95% confidence interval for each detected QTL was estimated using a 1‐LOD support interval (LSI) (Van Ooijen, 1992). Adjacent QTL on the same chromosome for the same trait were considered separate if their support intervals did not overlap (Haggard et al., 2015). The percentage of phenotypic variation (R ²) explained by each QTL in proportion to the total phenotypic variation was estimated. The QTL were named according to McCouch et al. (1997) and labeled as qVARx.y where VAR is a trait, x is chromosome number, and y is QTL number on a given chromosome.

The identified QTL were classified as stable or tentative. Those detected across multiple years of phenotypic data were considered stable, whereas QTL detected in only 1 year were classified as tentative. QTL explaining 15% or more of the phenotypic variation are considered major, whereas those explaining <15% are minor. The regions of colocalized QTL were searched using adjusted least square means to identify chromosomal regions containing putative pleiotropic genes controlling multiple traits. Finally, MapChart 2.3 (Voorrips, 2002) was used to visually represent the positions of identified QTL on each linkage map.

Flanking sequences (300–600 bp) of SNPs associated with each QTL from GBS analysis were aligned with the asparagus reference genome v1.1 (reference genome v1.1) using the Basic Local Alignment Search Tool. Candidate genes were identified within the LSI of QTL regions for the traits ASL, APS, NPS, and PSF based on gene function.

2.8. Statistical analysis

All statistical analyses were performed in R (R Core Team, 2022). Analysis of variance (ANOVA) and adjusted means were estimated using the package ‘augmentedRCBD’ (Aravind et al., 2021). A linear mixed model was employed for the ANOVA:

$$Y_{ijk}=\mathrm{\mu }+G_i+B_j+E_{ijk}$$ (3)

where Y_ijk is the measurement recorded in a plot, μ is the overall mean of the plot, G_i is the fixed effect of the ith genotype (which includes both test and check genotype), B_j is the random effect of the jth block, and E_ijk is the experimental error.

The normality of data was assessed with the Shapiro–Wilk test using the shapiro.test() function in the “stats” package. Bartlett's (Bartlett, 1937) tests for homogeneity of variance across years were estimated using the “car” package. Pearson correlation coefficients were estimated using the “psych” package (Revelle, 2023) for all traits. Grubbs’ outlier test (Grubbs, 1950) was conducted to detect outliers with a package “outlier.”

3. RESULTS

3.1. Inheritance of tissue‐specific anthocyanin pigment color, red or purple, in spear scale leaves and purple spot lesions

Pigment color segregated 3 red: 1 purple in scale leaves and 13 purple: 3 red in purple spot lesions in the F₁ pseudo‐testcross population (Table 1), suggesting one‐ and two‐gene models and unique genetic regulation of the two traits. However, these data are considered preliminary and require validation with additional crosses. No QTL for color, red and purple were identified, likely due to insufficient marker density on the male/female integrated genetic map (Tables S1–S5; Figures S2–S5).

TABLE 1.

Segregation of red and purple phenotypes for scale leaves and purple spot lesions in an asparagus F₁ pseudo‐testcross population.

		F1 Phenotype
Trait	Year	Observed red (#)	Observed purple (#)	Expected ratio	Chi‐square	p‐value
Scale leaves	2021	296	120	3:1	3.28	0.07
	2022	300	116	3:1	1.84	0.17
Purple spot	2021	73	343	13:3	0.52	0.39
	2022	75	341	13:3	0.14	0.70

3.2. Variation of anthocyanin composition in scale leaves and spear purple spot lesions

Cyanidin and peonidin anthocyanins, including cyanidin rhamnoside hexoside‐hexoside, cyanidin hexoside rhamnoside, peonidin rhamnoside hexoside‐hexoside, peonidin rhamnoside hexoside, and cyanidin glucoside, were identified using ultra‐high performance liquid chromatography coupled with mass spectrometry (LC/MS) in the segregating population (Table S1). Each pigment demonstrated unique physicochemical properties, including retention time, absorbance at UV‐520 nm, molecular weight (m/z), and a molecular formula.

The relative quantitative analysis of anthocyanin pigments in the red and purple scale leaves revealed significant concentration differences. Cyanidin (C) and peonidin (P) were notably more elevated in purple scale leaves compared to red scale leaves, with cyanidin being the most prominent (Table S2). Intriguingly, the C:P ratio differed between red and purple color classes, with a ratio of 26.81 observed in red scale leaves compared to 11.08 in purple scale leaves (Table 2).

TABLE 2.

Quantification of anthocyanin pigment types in asparagus scale leaves using liquid chromatography coupled with mass spectrometry (LC/MS), visually rated as purple or red in an F₁ pseudo‐testcross population.

Compounds	Relative anthocyanin concentration a
	Scale leaves		Purple spot
	Red	Purple	Red	Purple
Cya‐rham‐hexoside‐hexoside (C)	2.10E+08	1.90E+09	6.15E+08	1.63E+09
Cya‐hexoside‐rhamnoside (C)	1.37E+08	9.53E+08	6.02E+08	1.63E+09
Peo‐rham‐hex‐hex (P)	8.10E+06	1.64E+08	4.57E+07	1.24E+08
Peo‐rham‐hex (P)	5.06E+06	9.87E+07	5.50E+07	1.28E+08
Cya‐glucoside (C)	6.66E+05	5.66E+07	1.45E+07	4.99E+07
Cyanidin total	3.53E+08	2.90E+09	2.12E+09	2.55E+09
Peonidin total	1.31E+07	2.62E+08	1.23E+09	3.30E+09
C total/P total	26.79	11.07	12.24	13.14

^a Values represent the average relative anthocyanin concentration units as measured by LC/MS in scale leaves and purple spot lesions.

The comparative quantitative analysis of anthocyanin pigments in the red and purple spot lesions indicated that both C and P total concentrations were significantly elevated in purple lesions compared to red lesions, and C was the most dominant (Table S2). The C total:P total ratio was relatively consistent across both color types, 12.23 in red and 13.14 in purple lesions (Table 2).

3.3. Validation of visual anthocyanin ratings in scale leaves and purple spot lesions

Visual anthocyanin phenotypic ratings (1–9) based on pigment intensity, irrespective of red or purple color, in scale leaves and purple spot lesions were highly correlated with total pigment concentrations as determined by LC/MS (Table S2) or spectrophotometry (Table S3). For the scale leaves, the coefficient of determination (R ²) between the visual pigment ratings and the spectrophotometer measurements was 0.99, whereas that for LC/MS analysis was 0.88. For visual pigment ratings in spear lesions, the R ² values with spectrophotometer measurement and LC/MS analysis were 0.98 and 0.97, respectively. The high R ² values indicate that the visual assessments are reliable for determining total anthocyanin concentration in scale leaves and lesions.

3.4. Phenotypic assessment of the segregating F₁ pseudo‐testcross population

The ANOVA indicated significant differences (p < 0.05) for traits ASL, APS, NPS, and PSF among 416 individuals in the F₁ pseudo‐testcross population (Table S4). All traits showed normal to near‐normal distributions (Figure S2), suggesting they are most likely quantitative, involving multiple loci. Correlations between replicate years, 2021 and 2022, were high for ASL (0.78), moderate for NPS (0.50) and PSF (0.47), and low for APS (0.20). APS and ASL were poorly correlated within each of the years (0.21–0.33), as well as APS with NPS (0.22–0.29) (Table 3). Near zero correlations were observed for APS with PSF, ASL with NPS or PSF, and NPS with PSF.

TABLE 3.

Within‐year Pearson correlation coefficients among natural levels of anthocyanin in scale leaves (ASL) ^a , and spear purple spot lesions (APS) ^b , number of purple spot lesions in spears (NPS), and purple spot severity for fern (PSF) ^c in an asparagus F₁ pseudo‐testcross population evaluated in 2021 and 2022.

Phenotype	APS 2021	ASL 2021	NPS 2021
ASL 2021	0.21***
NPS 2021	0.29***	0.06
PSF 2021	−0.06	0.02	0.01

Phenotype	APS 2022	ASL 2022	NPS 2022
ASL 2022	0.33***
NPS 2022	0.22***	0.11*
PSF 2022	−0.02	0.05	−0.10*

^a Anthocyanin pigment phenotypic rating in spear (1 = low pigment level, 9 = high pigment level).

^b Anthocyanin pigment phenotypic rating for spear purple spot lesion (1 = low pigment level, 9 = high pigment level).

^c Purple spot severity for fern (0 = highly resistant genotype, 9 = highly susceptible genotype).

*p < 0.05,**p < 0.01,***p < 0.001.

3.5. Genetic map, QTL analysis, and candidate gene discovery

The genetic maps for the maternal and paternal parents resolved into 10 LGs (Table S5; Figure 4, Figures S3–S5). Initially, 5786 SNP markers were detected across 416 F₁ pseudo‐testcross genotypes. After filtration, 871 markers specific to maternal test crosses were identified; 288 showed segregation distortion and were excluded, leaving 583 for mapping. The female parent had a total genetic map covering 1543.93 cM, with individual chromosomes ranging from 106.11 to 203.65 cM. The average inter‐marker distance was 4.12 cM, and the number of SNPs per LG ranged from 13 to 88. For the paternal testcross, 846 markers were identified, and 67% were excluded due to segregation distortion, leaving 279 SNPs to construct the male genetic map. The male genetic map comprised a total distance of 826 cM, with individual chromosomes ranging from 18.44 to 134.16 cM. The average inter‐marker distance was 4.86 cM, and the number of SNPs per LG ranged from 2 to 77. For the integrated male and female maps, 189 of 339 markers were used, covering 974.11 cM. The lengths of the LGs varied between 53.23 cM and 147.46 cM, and the average inter‐marker distance was 6.70 cM.

FIGURE 4.

Quantitative trait loci (QTL) detected in the female parent of an asparagus F₁ pseudo‐testcross population for natural levels of anthocyanin pigment at scale leaves (ASL), anthocyanin pigment levels at spear purple spot lesions (APS), number of purple spots on spears (NPS), and purple spot severity in fern (PSF); black bar: detected only in 2021; red bar: detected only in 2022; green bar: detected based on the mean of data from 2 years. For QTL, the bar represents a 1‐LOD (where LOD is logarithm of odds) support interval, and the line represents a 2‐LOD support interval.

QTL were identified only with the female genetic map; no QTL were detected in the male or integrated maps due to insufficient resolution caused by low marker density and high segregation distortion (Table 4; Figure 4). For ASL, two stable QTL (qASL4.1, and qASL8.1), one in each of LG 4 and 8, were observed, which together accounted for 8.01% of the phenotypic variation. One tentative QTL (qASL1.1), also identified in LG 1, explained 7.27% of the phenotypic variance. Allelic effects for the three QTL ranged from 0.73 to 1.00, relative to the 1–9 rating scale; all three were positive. Two stable QTL for APS (qAPS4.1 and qAPS10.1) in LGs 4 and 10 explained 7.38% of phenotypic variance. Four tentative QTL (qAPS4.2, qAPS4.3, qAPS6.1, and qAPS8.1) were also identified, explaining 15.58% of the phenotypic variance. For APS, the allelic effects of the six QTL ranged from 0.47 to 0.76, relative to the 1 to 9 rating scale; four were positive, and two were negative. For NPS, two stable QTL (qNPS7.1 and qNPS8.1) in LGs 7 and 8 explained 10.73% of the observed phenotypic variance. Two tentative QTL (qNPS2.1 and qNPS4.1) were identified in LGs 2 and 4, contributing 14.27% of the phenotypic variance. The allelic effects of the four QTL ranged from 2.38 to 6.01, and all were positive. Three tentative QTL (qPSF 4.1, qPSF 7.1, and qPSF 8.1) were identified for PSF in LGs 4, 7, and 8, contributing to 9.98% of observed phenotypic variance. The allelic effects of the three QTL ranged from 0.51 to 0.76, relative to the 0–9 rating; two were positive, and one was negative. Notably, there was an overlap of one QTL for each of the PSF and APS, suggesting shared genetic determinants may be influencing the two traits.

TABLE 4.

Quantitative trait loci (QTL) for natural levels of anthocyanin pigment in spear scale leaves (ASL), anthocyanin pigment levels at spear purple spot lesions (APS), number of purple spot lesions in spears (NPS), and purple spot severity in fern (PSF) based on a 1–9 visual phenotypic scale detected in the female parent of an asparagus F₁ pseudo‐testcross population assessed across 2 years, 2021 and 2022.

QTL code	Year a	Chr.	Position (cM)	Peak LOD	Allele effect	R 2	LSI
qASL1.1	2021	1	33.41	3.15	1.01(+)	0.0727	32.40–34.90
qASL4.1	2021, 2021–2022	4	104.11	3.91	0.85(+)	0.0404	103.60–107.40
qASL8.1	2022, 2021–22	8	32.81	3.82	0.73(+)	0.0397	32.70–33.30
qAPS4.1	2021, 2022	4	3.01	2.91	0.72(+)	0.0390	0–10
qAPS4.2	2022	4	33.11	2.95	0.47(−)	0.0412	33.10–35
qAPS4.3	2021	4	135.41	3.29	0.76(+)	0.0332	134.30–142
qAPS6.1	2022	6	37.01	2.98	0.47(+)	0.0412	35.60–38
qAPS8.1	2021	8	142.51	3.96	0.73(+)	0.0402	139.7–143
qAPS10.1	2021, 2022	10	0.01	3.28	0.66(−)	0.0348	0–8
qNPS2.1	2022	2	61.41	3.86	6.01(+)	0.1127	59.30–63.90
qNPS4.1	2021	4	37.91	2.82	2.38(+)	0.030	45.80–48.70
qNPS7.1	2021, 2022	7	119.91	3.26	3.71 (+)	0.0662	118.80–122
qNPS8.1	2021, 2022	8	85.51	3.94	3.38 (+)	0.0411	84.50–86.30
qPSF4.1	2021‐22	4	137.01	3.11	0.76(+)	0.0332	133.60–143.70
qPSF7.1	2021	7	72.31	2.75	0.51(+)	0.0304	71.50–73.70
qPSF8.1	2022	8	34.71	3.25	0.59(−)	0.0362	34–34.90

^a Individual years; 2021–2022 = mean over 2 years when QTL detected.

Abbreviations: Chr., chromosome number; LOD, logarithm of odds; LSI, 1‐LOD support interval in cM; R ², coefficient of determination.

Candidate genes identified for QTL included crocetin glucosyltransferase chloroplast‐like (qAPS4.2) for APS, V‐type proton ATPase subunit e1‐like (qNPS4.1), and GDSL esterase/lipase EXL3‐like (qNPS7.1) for NPS, and homeobox‐leucine zipper HOX1‐like (qPSF 8.1), and ubiquitin‐conjugating E2 22‐like (qPSF 8.1) for PSF (Table 5; Table S6). No candidate genes were found for ASL.

TABLE 5.

Identification and characterization of asparagus candidate genes for anthocyanin pigment levels at spear purple spot lesions (APS), number of purple spot lesions in spear (NPS), and purple spot severity in fern (PSF) via NCBI Basic Local Alignment Search Tool (BLAST) search against the asparagus reference genome.

Trait	QTL	Candidate gene name	NCBI gene I.D.	Gene type	E‐value
APS	qAPS4.2	Crocetin glucosyltransferase, chloroplastic‐like	109,836,841	Protein coding	3E‐153
NPS	qNPS4.1	V‐type proton ATPase subunit e1‐like	109,846,756	Protein coding	8E‐39
NPS	qNPS7.1	GDSL esterase/lipase EXL3‐like	109,837,676	Protein coding	2E‐93
PSF	qPSF 8.1	Homeobox‐leucine zipper HOX1‐like	109,843,823	Protein coding	4E‐32
PSF	qPSF 8.1	Ubiquitin‐conjugating E2 22‐like	109,841,370	Protein coding	5E‐46

Abbreviation: QTL, quantitative trait loci.

4. DISCUSSION

Distinct inheritance patterns were observed for red:purple segregation in asparagus spear scale leaves and purple spot lesions, with ratios of 3:1 and 3:13, respectively. In addition, the two tissues exhibited different cyanidin:peonidin ratios for the two phenotypic classes. Low to near‐zero correlations were observed between ASL and APS, NPS, and PSF, and NPS and APS. Distinct stable and tentative QTL were identified for ASL, APS, NPS, and PSF, except one for each of PSF and APS were colocalized. The data suggested that independent genetic regulatory pathways are likely responsible for pigment produced in scale leaves and purple spot lesions, as well as resistance mechanisms for purple spot infection in spear and fern. Candidate genes were identified for APS, NPS, and PSF.

4.1. Anthocyanin regulation in scale leaves and purple spot lesions

The observed 3 red: 1 purple segregation in scale leaves and 3 red: 13 purple segregation in purple spot lesions suggested distinct genetic mechanisms: a single gene regulating pigmentation in the scale leaves and two epistatically interacting genes controlling pigmentation in purple spot lesions. Although additional crosses are required to validate the genetic models, these results strongly indicate tissue‐specific genetic regulation, which is plausible and not exceptional. Previous studies in carrot (Daucus carota L.) (Bannoud et al., 2021), grapes (Vitis vinifera L.) (Xie et al., 2015), maize (Zea mays L.) (Chatham & Juvik, 2021), and Arabidopsis (Arabidopsis thaliana (L.) Heynh.) (Falcone Ferreyra et al., 2012) have similarly documented differential regulation of anthocyanin biosynthetic genes across specific tissues. Additionally, tissue‐specific anthocyanin regulation in lesions and scale leaves of asparagus spears is further supported by C:P ratios, which were similar in red and purple lesions but varied between the color classes in scale leaves. Tissue‐specific variation in cellular pH, which affects pigment hue (Khoo et al., 2017), and co‐pigmentation with flavonoids, which can modify and intensify colors (Asen et al., 1972; Boulton, 2001), may explain anomalies with C:P ratios.

4.2. Purple spot resistance in spears versus fern

A low correlation between NPS and PSF suggests that purple spot resistance mechanisms are genetically distinct in fern and spear. These findings are consistent with those of Foster et al. (2019), who observed similar results in an analysis of asparagus hybrids, which parallel those of other species. In potato (Solanum tuberosum L.), the quantitative resistance of foliage to late blight, caused by Phytophthora infestans (Mont.) de Bary, was weakly correlated with tuber resistance, suggesting involvement of tissue‐specific gene or differential expression (Vale et al., 2001). Similarly, Kawuki et al. (2019) reported a consistently low correlation between disease severities of cassava (Manihot esculenta Crantz) brown streak disease on leaves and roots, further supporting the concept of tissue‐specific resistance mechanisms. Consequently, selection for resistance in one tissue will not simultaneously enhance levels in the other, and the breeding program would need to address asparagus spear and fern resistance separately.

4.3. Relationship between anthocyanin pigment levels and purple spot resistance in spears and fern

The low correlations observed between ASL and APS with NPS or PSF suggested anthocyanin plays no role in disease susceptibility or resistance in asparagus. These results add to the ongoing debate within the scientific literature about the role of anthocyanins in plant defense, which appears to be highly crop‐ and disease‐specific. For example, studies in wheat (Triticum aestivum L.) demonstrated that anthocyanins can enhance resistance to Fusarium head blight (Fusarium graminearum Schwabe.) (Gozzi et al., 2023), whereas research on apples (Malus domestica Borkh.) has shown that anthocyanins may have no effect or even increase susceptibility to certain pathogens (Hajnajari et al., 2012). Further analyses focusing on individual anthocyanin compounds, rather than total anthocyanin content, are warranted to understand if specific associations with purple spot resistance occur in asparagus, which can enhance breeding efforts.

4.4. QTL mapping for anthocyanin level and purple spot resistance in spears and fern

Multiple stable and tentative QTL were identified for APS and ASL, which did not overlap, and phenotypic correlations between traits were low (0.21–0.33), although significant, further supporting tissue‐specific regulation of anthocyanin production. Multiple QTL have been identified regulating pigment in carrot xylem and phloem (Bannoud et al., 2021), and 17 QTL controlled anthocyanin‐related traits in eggplant (Solanum melongena L.) (Toppino et al., 2020), indicating a complex genetic network. Multiple stable and tentative QTL were observed for NPS and PSF. Loci for the two traits did not overlap, suggesting independent resistance mechanisms in the two tissues, which was also supported by low phenotypic correlations between traits.

No major QTL, explaining 15% or greater of the phenotypic variance, were observed in this study, which could partly be explained by limited marker density. A moderate number of markers from the female parent, 67%, could be mapped to the reference genome. A similar percentage of markers were eliminated from the male map due to segregation distortion. Improved genomics tools to map increased numbers of markers to a reference genome and enhanced understanding of high segregation distortion will support precise QTL mapping in the future.

4.5. Candidate genes analysis for anthocyanin levels and purple spot resistance in spear and fern

Five candidate genes that may be involved in controlling disease resistance and anthocyanin accumulation in asparagus were identified within the confidence intervals of some QTL. The gene encoding crocetin glucosyltransferase chloroplast‐like protein was identified as a candidate for controlling APS due to its role in crocetin glycosylation, which stabilizes anthocyanins and enhances their solubility in the plant's cellular environment (Kapoor et al., 2022). Two genes were identified as candidates for controlling NPS: the V‐type proton ATPase subunit e1‐like protein, which regulates critical cellular processes such as homeostasis, hypersensitivity, stress response, and programmed cell death (Seidel, 2022; Z. Zhang et al., 2008), and the GDSL esterase/lipase EXL3‐like protein, which mediates cell wall fortification and defense signaling during pathogen attacks (Ji et al., 2023). Moreover, the genes for homeobox‐leucine zipper HOX1‐like protein and ubiquitin‐conjugating E2 22‐like protein (UBC22‐like) were associated with PSF. Homeobox‐leucine zipper HOX1‐like protein plays a vital role in disease resistance by activating defense‐related genes for synthesizing antimicrobial compounds, pathogenesis‐related proteins, and defense signal molecules, as reported in rice (Oryza sativa L.) and cotton (Gossypium hirsutum L.) (He et al., 2020; Salvador‐Guirao et al., 2018). The ubiquitin‐conjugating E2 22‐like protein facilitates post‐translational modification by attaching ubiquitin molecules to target proteins, thereby regulating their stability and localization (Wang & Wang, 2021). The ubiquitin‐conjugating E2 22‐like protein may also play a role in eliminating pathogen effectors, as evidenced by the studies on wheat and potatoes (S. Zhang et al., 2022; Zhou & Zeng, 2017). These candidate genes provide valuable targets for functional validation through gene overexpression or knockout studies. Incorporating important loci into the breeding program via marker‐assisted selection (MAS) could significantly improve resistance while maintaining desirable pigment traits.

5. CONCLUSIONS

This study provides important insights into the genetic basis of purple spot resistance and anthocyanin pigment variation in asparagus through genetic analysis. Tissue‐specific genetic regulation was observed for color, red versus purple, in spear scale leaves and purple spot lesions. QTL were identified for ASL, APS, NPS, and PSF. Complex and distinct inheritance patterns were observed for ASL and APS, indicating the involvement of different genetic pathways. NPS and PSF were not correlated, and QTL for the two traits did not colocalize, indicating that the selection for resistance in the spears does not increase or decrease resistance in the fern. The identification of candidate genes provides a foundation for future genetic and molecular studies, providing pathways for developing asparagus cultivars with improved resistance to purple spot and regulated anthocyanin content, potentially increasing the marketability of the crop.

AUTHOR CONTRIBUTIONS

Suman Parajuli: Data curation; formal analysis; investigation; methodology; software; visualization; writing—original draft. Mary Ruth McDonald: Methodology; resources; writing—review and editing. Laxman Adhikari: Formal analysis; methodology; software. David J. Wolyn: Conceptualization; funding acquisition; methodology; writing—review and editing.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

Supporting information

Supplementary Table S1: Anthocyanin pigments detected by LC/MS in asparagus scale leaves and purple spot lesions in an F₁ pseudo‐test cross population.

Supplementary Table S2: Quantification of anthocyanin pigment types in asparagus scale leaves and purple spot lesions using LC/MS, visually rated as purple or red in an F₁ pseudo‐testcross population.

Supplementary Table S3: Total anthocyanin pigment concentrations, as determined by spectrophotometry, for nine asparagus scale leaf pigment phenotypes based on visual ratings of an F₁ pseudo‐testcross population.

Supplementary Table S4: Analysis of variance of the natural levels of anthocyanin pigment at scale leaves (ASL), anthocyanin pigment levels at spear purple spot lesions (APS), number of purple spot lesions in spears (NPS), and purple spot severity in fern (PSF) for an asparagus F₁ pseudo‐testcross population across two years (2021 and 2022) and average over years.

Supplementary Table S5 : Summary of genetic maps constructed for an asparagus F₁ pseudo‐testcross population (n = 416).

Supplementary Table S6 : Quantitative trait loci (QTL) characterization for anthocyanin pigment levels at spear purple spot lesions (APS), number of purple spot lesions in spears (NPS) and purple spot severity in fern (PSF) for asparagus.

Supplementary Figure S1: Different levels of purple spot infection in an asparagus F₁ pseudo‐testcross population. 0: Highly resistant‐ fern displayed no signs of disease; 1: Resistant‐fern remained predominantly green with minimal cladophyll drop and no noticeable symptoms; 3: Moderately resistant‐fern retained green coloration, but with some cladophyll drop and few instances of purple leaf spot; 5: Moderately susceptible‐ fern showed a noticeable number of cladophylls dropped and purple leaf spot, yet without any stem desiccation; 7: Susceptible fern with significant cladophyll dropping and purple spot presence, accompanied by partial stem dryness and yellowing; 9: Highly susceptible fern with complete yellowing and extensive stem desiccation.

Supplementary Figure S2: Distribution of anthocyanin phenotypic classes (1 = low pigment level, 9 = high pigment level) in scale leaf (A, B, and C) and purple spot lesions (D, E, and F); numbers of purple spot lesions in spears (G, H, and I) and purple spot severity in fern J, K, and L) in an asparagus F₁ pseudo‐testcross population in 2021 (A, D, G, J), 2022 (B, E, H, K), and average of 2021–2022 data (C, F, I, L). The green and red vertical lines represent two control cultivars, Guelph Millenium, and Guelph Eclipse, respectively.

Supplementary Figure S3: Genetic linkage map of the female parent for an asparagus F₁ pseudo‐testcross population. The chromosome number is represented as the first number (e.g., 1.1, 2.1), following underscore are the position of markers in the reference genome. The scale bar indicates the distance in centimorgans (cM).

Supplementary Figure S4: Genetic linkage map of asparagus male parent. The chromosome number is represented as the first number (e.g., 1.1, 2.1), following underscore are the position of markers in the reference genome. The scale bar indicates the distance in centimorgans (cM).

Supplementary Figure S5: Integrated genetic linkage map of asparagus. The chromosome number is represented as the first number (e.g., 1.1, 2.1), following underscore are the position of markers in the reference genome. The scale bar indicates the distance in centimorgans (cM).

Parajuli, S. , McDonald, M. R. , Adhikari, L. , & Wolyn, D. J. (2025). Genetic architecture of anthocyanin pigment traits and purple spot (Stemphylium vesicarium) resistance in an F₁ pseudo‐testcross population of asparagus. The Plant Genome, 18, e70028. 10.1002/tpg2.70028

DATA AVAILABILITY STATEMENT

Phenotypic and genotypic data used in this study are available on Dryad at https://doi.org/10.5061/dryad.nzs7h452b. The raw sequencing data supporting this study have been deposited in the NCBI (SRA) under the BioProject accession number PRJNA1169105, available at https://www.ncbi.nlm.nih.gov/sra/PRJNA1169105.