Received: 21 January 2024

Revised: 19 August 2024

Accepted: 1 October 2024

DOI: 10.1002/pld3.70016

RESEARCH ARTICLE

Leaf pigmentation in Cannabis sativa: Characterization of
anthocyanin biosynthesis in colorful Cannabis varieties
Kristina K. Gagalova 1,2
| Yifan Yan 3 | Shumin Wang 4 |
Simone D. Castellarin 3 | Inanc Birol 2,5 | David Edwards 6

Till Matzat 3 |
| Mathias Schuetz 4,7

1

Centre for Crop and Disease Management,
School of Molecular and Life Sciences, Curtin
University, Perth, WA, Australia

Abstract
Cannabis plants produce a spectrum of secondary metabolites, encompassing canna-

2

Canada’s Michael Smith Genome Sciences
Centre, BC Cancer, Vancouver, BC, Canada

binoids and more than 300 non-cannabinoid compounds. Among these, anthocyanins

3

have important functions in plants and also have well documented health benefits.

Wine Research Centre, University of British
Columbia, Vancouver, BC, Canada

Anthocyanins are largely responsible for the red/purple color phenotypes in plants.

4

Department of Botany, University of British
Columbia, Vancouver, BC, Canada
5
Department of Medical Genetics, University
of British Columbia, Vancouver, BC, Canada
6

School of Biological Sciences and Institute of
Agriculture, University of Western Australia,
Crawley, Western Australia, Australia
7

Department of Biology, Kwantlen Polytechnic
University, Surrey, BC, Canada
Correspondence
Mathias Schuetz, Department of Biology,
Kwantlen Polytechnic University, 12666
72 Ave, Surrey, BC V3W2M8, Canada.
Email: mathias.schuetz@kpu.ca

Although some well-known Cannabis varieties display a wide range of red/purple
pigmentation, the genetic underpinnings of anthocyanin biosynthesis have not been
well characterized in Cannabis. This study unveils the genetic diversity of anthocyanin biosynthesis genes found in Cannabis, and we characterize the diversity of anthocyanins and related phenolics found in four differently pigmented Cannabis varieties.
Our investigation revealed that the genes 4CL, CHS, F3H, F30 H, FLS, DFR, ANS, and
OMT exhibited the strongest correlation with anthocyanin accumulation in Cannabis
leaves. The results of this study enhance our understanding of the anthocyanin biosynthetic pathway and shed light on the molecular mechanisms governing Cannabis
leaf pigmentation.
KEYWORDS

Funding information
MITACS ACCELERATE grant (#IT21175) to
K.K.G., I.B.; Canada Foundation for
Innovation/Infrastructure Operating Fund and
British Columbia Knowledge Development
Fund (BCKDF) F15-03053 to S. C, Natural
Sciences and Engineering Research Council of
Canada (NSERC) College and Community
Innovation Program (CCIP) Innovation
Enhancement (IE) Grant (CCIP 555874-20) to
M.S.

1

|

2-ODD enzymes, anthocyanins, Cannabis, flavonols, leaf pigmentation

I N T RO DU CT I O N

plants develop glandular trichomes on their leaves and flowers, which
accumulate a diverse array of secondary metabolites. Cannabinoids

Cannabis sativa is among the earliest cultivated plants and has been

such as tetrahydrocannabinolic acid (THCA) and cannabidiolic acid

used for food and fiber production as well as for medicinal and recrea-

(CBDA) are the most well-known Cannabis-derived metabolites

tional use (McPartland et al., 2019; Rull, 2022; Small, 2015). Cannabis

(ElSohly & Gul, 2014; Turner et al., 1980). Due to its intoxicating

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any
medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
© 2024 The Author(s). Plant Direct published by American Society of Plant Biologists and the Society for Experimental Biology and John Wiley & Sons Ltd.
Plant Direct. 2024;8:e70016.
https://doi.org/10.1002/pld3.70016

wileyonlinelibrary.com/journal/pld3

1 of 17

GAGALOVA ET AL.

effects, the THCA/THC content in Cannabis is a key factor in its clas-

toward the synthesis of flavonoids. The branch point within the flavo-

sification, with higher levels resulting in stricter legal controls (e.g., as

noid biosynthesis pathway that channels metabolic intermediates

a drug type). In contrast to drug-type Cannabis, hemp-type Cannabis

toward flavonol and anthocyanin production occurs via the action of

is required to contain less than .3% per dry weight of THCA/THC but

flavonol synthase (FLS) and dihydroflavonol 4-reductase (DFR),

is permitted to contain higher levels of other non-intoxicating canna-

respectively (Martens et al., 2010). FLS and DFR compete for dihydro-

binoids such as CBDA/CBD.

flavonol, which is a key intermediate molecule for both flavonol and

In addition to cannabinoids, Cannabis plants produce a wide

anthocyanin formation. Flavonols and anthocyanins can be further

range of other non-cannabinoid molecules, including a diverse array

modified via methylation, acetylation, prenylation, or through conjuga-

of terpenoids and flavonoids (ElSohly & Slade, 2005). While cannabi-

tion to various sugar molecules (Castañeda-Ovando et al., 2009; Dias

noids like THC and CBD often take the spotlight, terpenoids and fla-

et al., 2021). For example, anthocyanidins are typically conjugated to

vonoids are crucial players in what is referred to as the “entourage

various sugar moieties to form anthocyanins, which are colorful pig-

effect” (Bautista et al., 2021; Ferber et al., 2020; Koltai &

ments that typically accumulate in plant vacuoles (Castañeda-Ovando

Namdar, 2020; Russo, 2011). This phenomenon highlights the syner-

et al., 2009; Passeri et al., 2016). The enzymes involved in attaching

gistic interactions between cannabinoids and these other metabolites,

sugars to flavonols and anthocyanidins are broadly categorized as uri-

collectively enhancing and modulating the activity of THC and CBD.

dine diphosphate-glucosyltransferases (UGT) (Louveau & Osbourn,

Cannabis accumulates a diverse array of terpenoids, which have

2019). Among the UGT family, UDP-glucose: flavonoid 3-O-

been well characterized in previous studies (reviewed in Booth &

glucosyltransferases (UGFT) (Zhao et al., 2012) are a distinct subgroup

Bohlmann, 2019; Sommano et al., 2020). However, the diversity of fla-

with a specialized function, specifically conjugating glucose to the

vonoids found in Cannabis remains relatively understudied until

3-position of flavonols.

recently (Bassolino et al., 2023; Cerrato et al., 2021, 2023; Izzo

Recent studies have begun characterizing flavonoids in C. sativa

et al., 2020). Flavonoids are a group of phenolic molecules that have

in terms of metabolites (Bassolino et al., 2023; Cerrato et al., 2021,

important functions in plants, including defense against pathogen

2023; Izzo et al., 2020), biosynthesis genes (Bassolino et al., 2020),

infection and countering the damage caused by UV radiation (Mierziak

and transcriptional regulation (Bassolino et al., 2020; Kundan

et al., 2014; Verdan et al., 2011). Different flavonoids are grouped into

et al., 2022). These studies are noteworthy considering the extensive

different subtypes based on their chemical structure, specifically the

range of physiological effects that flavonols and anthocyanins can

arrangement of their carbon atoms and the presence of certain func-

exert on plant physiology, as well as their direct impact on the aes-

tional groups. Anthocyanins and flavonols are two main flavonoid sub-

thetic qualities of Cannabis plants. Indeed, Cannabis exhibits a wide

types and are well known for their antioxidant and anti-inflammatory

spectrum of observable phenotypes, with perhaps one of the most

properties as part of the human diet (Khoo et al., 2017; Kumar &

prominent being the coloration of leaves and flowers (Aardema &

Pandey, 2013). The accumulation of anthocyanins is responsible for

DeSalle, 2021) (Figure 1). The diversity of colors was likely selected

the red, purple, and blue colors found in many plants, such as blue-

for by clandestine Cannabis breeders during the long period of Canna-

berries, rose flowers, and chard leaves. Although Cannabis plants have

bis prohibition. In this study, we provide a comprehensive inventory

diverse pigmentation patterns that are often reflected in the naming

of flavonoid biosynthesis genes in the Cannabis cs10 reference

schemes of some varieties (e.g., Purple Kush, Purple Haze, Pink Kush),

genome. We identified these genes using a knowledge-based identifi-

the diversity of anthocyanins found in Cannabis have not been studied

cation of pathway enzymes (KIPEs) approach that evaluates the func-

in detail until recently. Analysis of Cannabis leaves and reproductive

tionally significant aa residues and domains within the peptide

tissues identified cyanidin-3-rutinoside as the major anthocyanin in

sequences to accurately identify biosynthesis enzymes (Pucker

hemp-type Cannabis (Bassolino et al., 2023). Moreover, three LC–MS

et al., 2020). We document the biochemical phenotypes of four drug-

studies have identified flavonols and other phenolic compounds pre-

type Cannabis varieties and evaluate the phenylpropanoid/flavonoid

sent in the flowers and leaves of hemp-type Cannabis (Izzo

biosynthesis gene expression in the leaves of these varieties using

et al., 2020; Cerrato et al., 2021, 2023). These previous studies ana-

RNAseq. We extend our analysis to encompass the functional charac-

lyzed hemp-type Cannabis, likely due to the regulatory hurdles of

terization of three 2-oxoglutarate and oxygen-dependent dioxy-

working with drug-type Cannabis, which we examine in this study.

genases (2-ODD) genes (anthocyanidin synthase [ANS], FLS, and

The biosynthesis of flavonoids such as anthocyanins and flavonols commences via the general phenylpropanoid biosynthetic path-

flavanone 3-hydroxylase [F3H]), which are responsible for facilitating
key oxidation reactions in the flavonoid biosynthesis pathway.

way, orchestrated by the enzyme phenylalanine ammonia lyase (PAL)
(Vogt, 2010). This biosynthetic step involves the deamination of the
amino acid (aa) phenylalanine. Subsequent activity of cinnamate

2

M A T E R I A L S A N D M ET H O D S

|

4-hydroxylase (C4H) and 4-coumarate-CoA ligase (4CL) leads to the
formation of p-coumaroyl CoA, which is a precursor molecule for

2.1

|

Plant material

the biosynthesis of various phenolic compounds, including flavonoids,
lignin, and stilbenes (Vogt, 2010). Chalcone synthase (CHS) operates

Four different Cannabis varieties (CA19210, CK19206, Cali Kush, and

as a gatekeeper for flavonoid formation by directing p-coumaroyl CoA

Willow-alpha) were cultivated under uniform conditions by a licensed

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2 of 17

F I G U R E 1 Leaf pigmentation phenotypes in four different Cannabis varieties. Petiole and leaf pigmentation phenotypes are shown for
Willow-alpha (unpigmented phenotype), CA19210, CK19206, and Cali Kush (pigmented phenotypes). A magnified view of the petiole and
primary leaf veins is shown for each variety as well as the overall leaf morphology (inset). Scale bar = .5 cm.

Cannabis producer in British Columbia, Canada. The four plant varie-

to the flowering conditions. These apical flower buds were flash fro-

ties were selected by visually assessing their leaf pigmentation

zen in liquid nitrogen and subsequently used to determine the canna-

(Figure 1). Among them, the Cali Kush and CK19206 varieties exhibit

binoid content of the four Cannabis plant varieties.

pronounced leaf pigmentation with the presence of red/purple coloration. The CA19210 variety exhibited a moderate level of leaf pigmentation, while the Willow-alpha strain lacked any discernible red/purple
pigmentation. Plant clones were generated via cuttings and using
Stim-Root #1 rooting powder (Plant Products Co. Ltd., Leamington,

2.2 | Identification of genes involved in the general
phenylpropanoid, flavonoid, and anthocyanin
pathways

Canada), followed by planting into reconstituted Jiffy #7 peat pellets
(Jiffy Growing Solutions, Zwijndrecht, The Netherlands). Plants were

Genes responsible for enzymes within the flavonoid, anthocyanin, and

grown at 100% humidity under a plastic dome until roots became visi-

phenylpropanoid pathways were identified as follows. Initially, poten-

ble. The clones were individually potted into 3-gal plastic nursery pots

tial candidates were identified using the KIPEs pipeline v0.38 (Pucker

using Sunshine Mix #4 professional growing mix (Sun Gro Horticul-

et al., 2020), which was executed in its default mode using protein

ture, Agawam, USA). Plants were grown at temperatures between

sequences from the cs10 Cannabis genome reference (Grassa



22 and 24 C, and using NextLight Veg8 240 W full spectrum LED

et al., 2021). Subsequently, the chosen sequences were subjected to

lights (NextLight, Cincinnati, USA) using an 18 h/6 h cycle (hours of

validation as described below, via manual curation using assessments

light/hours of dark) during clone establishment and vegetative devel-

of alignments, phylogenetic trees, and the presence of conserved

opment. After 4 weeks of vegetative development, the plants were

binding or catalytic residues. Research into the annotation of

transferred to a neighboring grow room equipped with Next Light

flavonoid-related genes has been highly successful in Arabidopsis

Mega Pro 640 W full spectrum LED lights (Nextlight, Cincinnati, USA)

(Saito et al., 2013), making this system ideal for characterizing flavo-

using a 12 h/12 h cycle (hours of light/hours of dark) to facilitate

noid biosynthesis genes in other plants. All candidate proteins with a

reproductive development (e.g., flowering). Plants were watered as

sequence identity greater than 40% with their corresponding Arabi-

needed and fertilized using Miracle-Gro All Purpose (24-8-16) fertil-

dopsis homologs were retained. Additionally, proteins lacking more

izer during vegetative growth and Miracle-Gro Ultra Bloom

than 80% of their conserved residues according to KIPEs were dis-

(15-30-15) during flowering. Biological controls consisting of Ambly-

carded from the selection. Further validation was applied to the

seius californicus (Biobest, Westerlo, Belgium) were applied at regular

enzymes classified as 2-ODD, including FLS, ANS, and F3H that were

intervals to the plants to proactively mitigate spider mite pests. No

aligned with multiple sequence alignment (MSA) in Mafft v7.453a

visible signs of pests or disease were observed throughout the experi-

(Nakamura et al., 2018) using the argument -auto. Following the align-

ment. Leaf collection took place 3 weeks after transfer to the flower-

ment, each enzyme was individually examined for its catalytic and

ing conditions coinciding with the shift to a 12-h light/dark

binding sites.

photoperiod. At the time of leaf collection, Cannabis flowers were

The annotated enzymes’ functional residues (such as catalytic,

observed but not yet mature. For each of the four varieties, one fully

binding, or structural amminoacids) were identified according to

expanded fan leaf was collected from three individual plant clones

peer-reviewed studies or manual assertion based on sequence

and flash frozen in liquid nitrogen prior to further processing for RNA

similarity to entries in the UniProt database (www.uniprot.org) (The

and metabolite extraction. Moreover, the apical flower bud for each

UniProt Consortium et al., 2021) as follows. To annotate the

plant of the four varieties was harvested after 7 weeks post-transfer

functional residues, BLASTP (Camacho et al., 2009) was employed

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3 of 17

GAGALOVA ET AL.

GAGALOVA ET AL.

to align the protein sequences of the Cannabis predicted protein

2.4

|

Metabolite profiling

sequences with those of Arabidopsis. In doing so, residues at specified positions were compared to ascertain their correspondence

Ground leaf powder matching the samples from the transcriptome

between the two species, and the active residues of these annotated

profiling was used for metabolite analysis. Total phenolics were

enzymes were examined, specifically focusing on the catalytic and

extracted from ground-frozen leaf tissues using acidified methanol

binding sites.

(v/v, methanol:water:formic acid, 49.5:49.5:1). A total of 100 mg of

A sequence clustering approach was employed to categorize the

ground leaf tissue per ml of acidified methanol was incubated at room

UGT enzymes, utilizing Arabidopsis UGTs as a reference dataset,

temperature for 2 h with gentle shaking (100 RPM) on an orbital

sourced from the P450 database (http://www.P450.kvl.dk) (Paquette

shaker. Samples were centrifuged at room temperature for 10 min to

et al., 2009). The MSA was conducted using Clustal Omega v1.2.4

pellet the leaf material, and 1 mL of extraction buffer was aspirated

(Sievers & Higgins, 2014) with default parameters. Subsequently, a

and subsequently used for analysis using high-performance liquid

phylogenetic tree was constructed through a neighbor-joining cluster-

chromatography and mass spectrometry as described in Yan et al.

ing method using FastTree2 (Price et al., 2010), where the local sup-

(2020). Five microliters of each extract were injected into an Agilent

port values are used to score the reliability of the final tree. Cannabis

1100 Series LC coupled to an MSD Trap XCT Plus System (Agilent

candidate UGTs are assigned to the subclasses based on similarity

Technologies, Mississauga, Canada). Chromatographic separation was

with Arabidopsis UGTs.

performed using an Agilent ZORBAX SB-C18 Column (1.8 μm,

All the identified enzyme sequences were compared with the Ara-

4.6  50 mm)—(Agilent Technologies, Mississauga, Canada), with the

bidopsis reference genome TAIR10/Araport11 (Cheng et al., 2017)

temperature set to 67.0 C. The mobile phases consisted of aqueous

using BLASTP. The percent identity and percent positive scoring resi-

formic acid (98:2, v/v; Solvent A) and acetonitrile/formic acid (98:2,

dues (residues with similar biochemical properties) were then used to

v/v; Solvent B). The LC separation employed a binary solvent gradient

determine the degree of conservation between the two species.

at a flow rate of 1.20 mL/min. The gradient conditions were as follows: .20 min, 5.0% Solvent B; 6.00 min, 20.0% Solvent B; 9.00 min,
80.0% Solvent B; 10.00 min, 90.0% Solvent B; 10.10 min, 90.0% Sol-

2.3

|

Gene expression analysis

vent B; 11.00 min, 5.0% Solvent B, stopped at 11.50 min. Mass spectra were generated via electrospray ionization (ESI) in both positive

One fully expanded leaf was collected from three individual plant

and negative modes. Anthocyanins and flavonols were identified by

clones for each genotype and was used for RNA extraction and analy-

the following criteria: (i) comparing the retention time and elution

sis. Frozen leaf tissue was ground in liquid nitrogen using a mortar and

order of the identified peaks with authentic standards when available

pestle. RNA was isolated using PureLink Plant RNA reagent (Thermo

(i.e., cyanidin 3-O-glucoside, cyanidin 3-O-rutinoside, peonidin 3-O-

Fisher Scientific, Waltham, Massachusetts) according to the manufac-

glucoside, and peonidin 3-O-rutinoside); (ii) matching the mass spectra

turer’s instructions. RNA sequencing was performed by Genome Que-

of the identified peaks with the published data (Radwan et al., 2021;

bec using an Illumina NovaSeq 6000 PE (2  100 bp). A total of

Tulio et al., 2008; Wu et al., 2004). The identities of selected com-

25 million reads were generated per sample and screened for possible

pounds (i.e., cyanidin 3-O-glucoside, cyanidin 3-O-rutinoside, peonidin

contamination with BioBloomTools v2.3.3 (Chu et al., 2014). A series

3-O-glucoside, and peonidin 3-O-rutinoside) were further confirmed

of Bloom filters were built using a low negative rate (kmer_size = 25,

using LC Q-TOF (Agilent 1200 UHPLC/6530B coupled with accurate

desired_false_positve_rate = .001, number_of_hash_functions = 9)

Mass Q-TOF). Quantification of anthocyanins was based on a stan-

based on the genomes from viruses, archaea, protozoa, bacteria, fungi,

dard curve of cyanidin 3-O-glucoside (Cat. # 0915S) with malvidin

aphids (superfamily Aphidoidea), mites (subclass Acari), thrips (order

3,5-diglucoside (Cat. # 0930S) as an internal standard. The maximal

Thysanoptera), and Univec build #10, downloaded in September

absorption for anthocyanins is reported to be between 512 and

2020. The reads without a match to any Bloom filter were kept for

528 nm (Lee et al., 2005). The quantification results from LC-QTOF

quantification.

were corroborated using HPLC-UV/VIS by monitoring 512–528 nm

The cs10 genome reference (Grassa et al., 2021) was downloaded

wavelengths (Figure S1). Flavonol quantification was based on a stan-

from NCBI, accession ID GCF900626175, and used for alignment.

dard curve of quercetin 3-O-glucoside (Cat. #1099) with baicalein

The quantification was conducted through pseudoalignment with

(Cat. #1400S) as an internal standard. Cyanidin 3-O-rutinoside and

Kallisto v0.46 (Bray et al., 2016). The transcript abundances estimated

peonidin 3-O-rutinoside were verified using LC-QTOF (Agilent) analy-

by Kallisto were imported in R and analyzed with differential

sis against authentic standards (Cat #0914S and 0945, respectively).

expression analysis in DESeq2 v1.38.2 (Love et al., 2014). p-value

All standards were purchased from Extrasynthese (Genay, France).

statistical significance is adjusted with Benjamini–Hochberg for

The cannabinoid content of leaves and flowers was determined

multiple-testing correction at fasle discovery rate (FDR .1). Genes with

as follows. A total of 200 mg of ground frozen leaf and flower material

an absolute log2 fold change higher than 1.5 at p-value .05 statistical

was weighed into 15 mL centrifuge tubes and combined with 4 mL of

significance are considered differentially expressed. The RNAseq

extraction solvent (9:1 MeOH:chloroform). Samples were vortexed at

data generated in this study have been deposited in the NCBI’s

maximum for 2 min, followed by gently shaking (100 RPM) on an

Sequence Read Archive.

orbital shaker at room temperature for 15 min. The sample tubes were

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4 of 17

centrifuged (4000 RPM) using a tabletop centrifuge to pelletize the

by utilizing junctions detected in the first pass as “annotated” junc-

plant material. A total of 1 mL of extraction solvent was aspirated,

tions for the second pass. Reads from each sample are uniquely

diluted tenfold with fresh extraction solvent, and used for

mapped to the reference genome at an average rate of 87%.

ultra-high-performance liquid chromatography UV analysis. Chro-

The RNA analysis followed the best practices of the Genome

matographic separation was performed using a Vanquish Duo UHPLC

Analysis Toolkit (GATK) Variant Discovery v4.2.6.1 (DePristo

system with an Accucore Vanquish C18+ Column (1.5 μm,

et al., 2011). This included marking duplicate reads using GATK4’s

2.1  50 mm) from Thermo Fisher Scientific, Waltham, Massachu-

MarkDuplicates and separating reads with SplitNCigarReads. Variant



setts. Column temperature set to 50.0 C, and the mobile phases con-

calling was conducted using GATK HaplotypeCaller with a default min-

sisted of aqueous formic acid (.1% formic acid in deionized water, v/v;

imum Phred-scaled confidence threshold of 20 for diploid genomes.

Solvent A) and methanol/acetonitrile/formic acid (.1% formic acid:

The resulting variants were filtered with criteria: FisherStrand (FS)

75% methanol: 25% acetonitrile, v/v; Solvent B). LC separation

> 30.0, Quality by Depth (QD) < 2.0, and single nucleotide polymor-

employed a binary solvent gradient at a flow rate of .6 mL/min. The

phism (SNP) clusters within a 35 bp window size and cluster size of

gradient conditions were as follows: .00 min, 70% Solvent B; .30 min,

3. SNPs were further filtered for QUAL < 60 and retained if present in

70.0% Solvent B; 1.33 min, 79.0% Solvent B; 3.30 min, 95.0% Solvent

all three biological replicates of each strain, excluding indels and poly-

B; 3.50 min, 70% Solvent B; ending at 3.80 min. Cannabinoids were

morphic sites. The overall number of high-quality SNPs annotated

detected using a Vanquish Diode Array Detector (VF-D11-A-01;

averaged 220,000. The final SNP dataset was annotated with SnpEff

Thermo Fisher Scientific, Waltham, Massachusetts) and quantified via

v 5.2c (Cingolani et al., 2012) to predict functional effects using cs10

standard curves generated from authentic standards purchased from

database annotation.

Cerilliant Corporation (Round Rock, Texas), CBDA (Cat. #C-144),
CBGA (Cat. #C-142), and THCA (Cat. #T-093).

2.7 | Analysis of protein structures and enzymesubstrate docking of 2-ODDs enzyme family
2.5 | Correlation analysis of transcriptome and
metabolome

Cannabis

protein

3D

structures

were

predicted

for

ANS

(XP030501512), FLS (XP030502221, XP030492734), and F3H
Gene expression quantities and metabolite concentrations from the

(XP030486031, XP030497321) using the AlphaFold2 algorithm

Cannabis varieties were employed to calculate their non-parametric

through the ColabLab server notebook (Mirdita et al., 2022). The

correlation (Spearman correlation). The gene counts, normalized using

highest-ranked protein structure model, evaluated using the Local Dis-

the estimated size factor in DESeq2, were compared with the normal-

tance Difference Test (lDDT) score (Mariani et al., 2013), was selected

ized quantities of metabolites, which were adjusted by the corre-

for further analysis. The majority of residues showed a high-quality

sponding internal standard. The ρ (rho) scores for each individual gene

backbone prediction, with an IDDP score exceeding 70%. Structural

expression and metabolite concentration pair were derived from vec-

alignment with Arabidopsis protein homologs, AtLDOX/ANS (1GP4

tors containing values where each value corresponded to the quantity

(Wilmouth et al., 2002), AtF3H (F4J3A5), and AtFLS1 (B1GV57), was

and concentration from individual samples. This method captures the

used to infer protein homology, as protein structure is more con-

correlation by accounting for the contributions of samples, yielding a

served than aa sequence (Illergård et al., 2009). For this comparison,

ρ score that reflects the relationship based on these replicates.
Subsequently, the obtained correlation matrix was utilized for
clustering metabolic compounds and genes in R and heatmap.2. This

the structures were aligned using TM-align (Zhang, 2005), with
the shortest protein sequence serving as a reference for normalizing
the alignment score.

clustering was performed using Ward D2 hierarchical clustering

The substrates (2R,3S,4S)-leucocyanidin, (+)-dihydroquercetin,

coupled with the Euclidean distance metric, resulting in the grouping

(+)-dihydrokaempferol, and (S)-naringenin described in Table S7 were

of metabolites and genes based on their correlation patterns.

used in protein docking simulations with the predicted Cannabis proteins. CB-Dock2 (Liu et al., 2022) was used to detect the protein cavities and also calculate the binding affinity scores based on contact

2.6

|

Strain specific genotyping

residues. The template-based docking engine was used for ANS, specifically employing the 1GP4 protein structure, which CB-Dock2 auto-

RNAseq reads were employed for genotyping the four Cannabis varie-

matically selected to improve the prediction accuracy. For all other

ties, aiming to investigate their genetic variation. The analysis was

protein structures, the structure-based engine was used without any

performed using the rnavar pipeline (Ewels et al., 2020), commit

template. In addition, COACH-D (Wu et al., 2018) was used to iden-

#ccd9d82c, incorporating established genotyping tools. The reference

tify other ligands with high affinity binding scores, apart from the

genome, cs10, was indexed with the --runMode genomegenerate, and

tested substrates. The protein structures and representations of

genome annotations were provided via the --sjdbGTFfile parameter.

the protein-ligand complexes were generated respectively with

Reads from each sample were mapped using STAR v2.7.9a (Dobin

Open-Source PyMOL™ v2.3.0 and LigPlot+ v2.2.8 (Laskowski &

et al., 2013) in 2-pass mode, enhancing the accuracy of read mapping

Swindells, 2011).

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5 of 17

GAGALOVA ET AL.

GAGALOVA ET AL.

Missense variants identified from RNAseq were analyzed using

identified 13 genes involved in the general phenylpropanoid pathway

PremPS v1.0 (Chen et al., 2020). This web-based tool, accessed on

and 14 in the flavonoid pathway; the remaining 30 genes are specifi-

July 8, 2024, was employed to estimate the protein unfolding free

cally involved in the production of anthocyanins. The largest enzyme

energy and its effect on protein stability.

family of the latter is glycosyltransferases, which are responsible for
conjugating glycans to the anthocyanidins and represent the final step
of the anthocyanin biosynthesis (Table 1).

2.8

Computational infrastructure

|

The general phenylpropanoid pathway genes (PAL, C4H, and
4CL) found in Cannabis show a high level of sequence identity with

Data analysis was performed using the computational resources of

their Arabidopsis homologs, with the top hits ranging between 71%

the Genome Sciences Centre (GSC) in Vancouver, Canada, and the

and 87% aa identity. CHS was found to be a single gene copy with

Pawsey Setonix Supercomputer at the Pawsey Supercomputing

high protein sequence identity with Arabidopsis (87%). We identified

Research Centre (2023) in Perth, Australia. These facilities provided

several copies encoding for genes in the flavonoid biosynthesis path-

access to high-performance computing (HPC) cluster resources essen-

way. Flavanone 3-hydroxylase (F3H) was found in two copies and

tial for the comprehensive analysis of genomic data.

shows high aa conservation with 78% and 80% identity. Seven genes
encoding for flavonol 30 -hydroxylase (F30 H) were found with aa conservation ranging between 49% and 66%. Two copies of FLS were

3

|

RESULTS

found with aa conservation with 51% and 66% identity. Dihydroflavonol 4-reductase (DFR) and ANS enzymes have a high sequence iden-

3.1 | Pigmentation and anthocyanin assessment in
Cannabis varieties

tity with their Arabidopsis homologs, with 70% and 78% aa identity,
respectively. Other enzymes from the flavonoid and anthocyanin
pathways show lower homology with Arabidopsis homologs, ranging

The degree of red/purple leaf pigmentation can be visually assessed

from 52% to 70% aa identity.

during Cannabis growth and development. We utilized four Cannabis

Flavone synthase 1 and 2 (FNS1 and FNS2, respectively) perform

varieties, namely, Willow-alpha, CA19210, CK19210, and Cali Kush.

the same enzymatic reaction although being completely different

The Willow-alpha variety did not show any obvious red/purple pig-

enzymes (Martens & Mithöfer, 2005). We identified four gene copies

mentation, even in the petiole and primary leaf vein regions that are

of FNS2, but we did not identify any homologs to Arabidopsis FNS1.

often pigmented in other Cannabis varieties (Figure 1). In contrast, the

The anthocyanidin-producing enzymes, DFR and ANS, were found as

CA19210, CK19206, and Cali Kush varieties all have variably higher

single gene copies in the cs10 genome. We identified three genes

red/purple

of

encoding O-methyltransferase (OMT) that putatively facilitate the for-

anthocyanin-based leaf pigments can be quantified by analyzing leaf

mation of peonidin from cyanidin and 25 genes encoding flavonoid

extracts for anthocyanin diagnostic absorption spectra between

glycosyl transferases, with a high similarity to the Arabidopsis sub-

512 and 528 nm (Lee et al., 2005). Analysis of methanol leaf extracts

classes UGT72B, UGT75, UGT78D, UGT79B, and UGT80 (Figure S2).

leaf

pigmentation

(Figure

1).

The

abundance

identified the CA19210 variety as having the highest amounts of

We performed a comparison of the catalytic and substrate binding

anthocyanins, followed by CK19206 and Cali Kush (Figure S1).

sites to those found in their respective Arabidopsis homologs to

Willow-alpha was found to have the lowest accumulation of anthocy-

interrogate the functionality of the enzymes identified in the KIPEs

anins based on UV absorption.

homology search. All enzymes shared conserved functional aa residues with Arabidopsis homologs, except for FLS (XP030492734) and
ANS (XP030501512) (Table S1). FLS contains three functional residue

3.2 | Identification of phenylpropanoid, flavonoid,
and anthocyanin-producing enzymes in Cannabis

variants when compared with Arabidopsis: Glu329Ala, Tyr205Met,

Utilizing the annotated proteins derived from the cs10 Cannabis refer-

2008; Welford et al., 2005). In ANS, the residue at position 299, which

ence whole-genome prediction, the KIPEs homology search (Pucker

is crucial for binding the cofactor 2-ODD (Welford et al., 2005;

and His132Tyr, where the first two are involved in the enzymes’ catalytic activity and the latter binds to the 2-ODD cofactor (Chua et al.,

et al., 2020) successfully identified over 60 putative enzymes associ-

Wilmouth et al., 2002), is a hydrophobic chain aa, similar to its coun-

ated with the production of anthocyanins and their precursors

terpart in Arabidopsis (Ile299Val), indicating a similar substitution.

(Table 1). The KIPE search included enzymes involved in the general
phenylpropanoid biosynthesis as well as flavonoid biosynthesis. The
corresponding transcripts and Cannabis gene models were also

3.3

|

Flavonoid and anthocyanin gene expression

retrieved and are listed in Table 1. Similar to other plants, most of the
general phenylpropanoid pathway enzymes were identified as small

Among the Cannabis varieties, Willow-alpha exhibited the lowest

enzyme families in Cannabis. Multiple copies of PAL and 4CL genes

accumulation of anthocyanins in leaves, based on visual inspection

were found (Table 1), which is in line with observations in other plant

and LC-UV analysis of leaf extracts (Figure 1; Figure S1). Hence, this

species (Fraser & Chapple, 2011; Hamberger et al., 2007). Overall, we

variety served as the baseline for quantifying gene expression in

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6 of 17

T A B L E 1 Cannabis genes and associated proteins that are putatively involved in the production of phenylpropanoids (white), flavonoids
(gray), and anthocyanins (light blue) in Cannabis. Each entry, shown with the appropriate RefSeq ID, for locus, transcript, and protein sequence is
displayed with the corresponding Arabidopsis homolog ID. The homolog similarity is shown with % BLASTP identity and % positive scoring
residues (percent of amino acids that are either identical between the query and the subject sequence or have similar chemical properties).
Different isoforms are included for LOC115709845 (F30 H), LOC115712971 (OMT), LOC115724965 (UGT 79 superfamily), and LOC115720702
(UGT80). FNS2 enzyme is absent in the Arabidopsis thaliana genome but found in Cannabis sativa.

Locus ID

Transcript ID

Protein ID

Protein length (aa)

Arabidopsis homolog

Gene name

% identity

% positive
scoring

LOC115706668

XM030637350

XP030493210

707

AT3G53260

PAL2

82

92

LOC115709282

XM030634382

XP030490242

723

AT2G37040

PAL1

81

90

LOC115709383

XM030637471

XP030493331

709

AT3G53260

PAL2

82

90

LOC115709862

XM030638093

XP030493953

707

AT2G37040

PAL1

83

91

LOC115710186

XM030638528

XP030494388

711

AT3G53260

PAL2

83

91

LOC115710187

XM030638529

XP030494389

710

AT3G53260

PAL2

83

91

LOC115709609

XM030637745

XP030493605

530

AT2G30490

C4H

65

78

LOC115719463

XM030648524

XP030504384

505

AT2G30490

C4H

87

95

LOC115699364

XM030626724

XP030482584

550

AT3G21240

4CL2

71

84

LOC115717276

XM030646244

XP030502104

572

AT1G65060

4CL3

69

83

LOC115725019

XM030654419

XP030510279

553

AT1G51680

4CL1

71

83

LOC115724170

XM030653640

XP030509500

389

AT5G13930

CHS

87

93

LOC115716382

XM030645165

XP030501025

266

AT3G55120

CHI1

62

77

LOC115709313

XM030637390

XP030493250

514

AT5G07990

F30 H

66

81

LOC115709845

XM030638082

XP030493942

514

AT5G07990

F30 H

64

81

LOC115709845

XM030638083

XP030493943

514

AT5G07990

F30 H

64

81

0

LOC115709933

XM030638196

XP030494056

513

AT5G07990

F3 H

66

82

LOC115714670

XM030643420

XP030499280

519

AT1G58807

F30 H

52

64

0

LOC115715257

XM030644098

XP030499958

515

AT1G58807

F3 H

52

64

LOC115725467

XM030654999

XP030510859

492

AT3G26180

F30 H

49

60

LOC115702709

XM030630171

XP030486031

384

AT3G51240

F3H

80

89

LOC115712997

XM030641461

XP030497321

373

AT3G51240

F3H

78

89

LOC115708739

XM030636743

XP030492603

514

Na

FNS2

Na

Na

LOC115709046

XM030637075

XP030492935

512

Na

FNS2

Na

Na

LOC115709089

XM030637124

XP030492984

512

Na

FNS2

Na

Na

LOC115721328

XM030650599

XP030506459

544

Na

FNS2

Na

Na

LOC115708857

XM030636874

XP030492734

322

AT5G08640

FLS1

51

68

LOC115717395

XM030646361

XP030502221

337

AT5G08640

FLS1

63

77

LOC115710150

XM030638485

XP030494345

356

AT5G42800

DFR

70

84

LOC115716756

XM030645652

XP030501512

354

AT4G22880

LDOX/ANS

78

89

LOC115695175

XM030622265

XP030478125

467

AT5G54010

UGT79B6

45

67

LOC115695811

XM030622894

XP030478754

465

AT5G54060

UGT79B1

44

67

LOC115697078

XM030623988

XP030479848

460

AT4G27570

UGT superfamily

48

67

LOC115698903

XM030626102

XP030481962

462

AT5G54010

UGT79B6

45

67

LOC115716562

XM030645379

XP030501239

463

AT5G54010

UGT79B6

49

68

LOC115724965

XM030654351

XP030510211

470

AT5G53990

UGT superfamily

43

62

LOC115724965

XM030654352

XP030510212

470

AT5G53990

UGT superfamily

43

62

LOC115724966

XM030654353

XP030510213

466

AT2G36970

UGT superfamily

45

64

LOC115709176

XM030637224

XP030493084

640

AT1G43620

UGT80B1

82

90

LOC115712970

XM030641414

XP030497274

627

AT3G07020

UGT80B2

79

87

LOC115720702

XM030649869

XP030505729

606

AT3G07020

UGT80B2

74

85

(Continues)

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7 of 17

GAGALOVA ET AL.

TABLE 1

GAGALOVA ET AL.

(Continued)

Locus ID

Transcript ID

Protein ID

Protein length (aa)

Arabidopsis homolog

Gene name

% identity

% positive
scoring

LOC115720702

XM030649870

XP030505730

605

AT3G07020

UGT80B2

74

85

LOC115703173

XM030630692

XP030486552

488

AT4G01070

UGT72B1

44

62

LOC115705536

XM030632889

XP030488749

478

AT4G01070

UGT72B1

61

78

LOC115705626

XM030633020

XP030488880

478

AT4G01070

UGT72B1

61

78

LOC115705627

XM030633021

XP030488881

469

AT4G01070

UGT72B1

55

75

LOC115706084

XM030633600

XP030489460

484

AT4G01070

UGT72B1

50

66

LOC115718128

XM030647088

XP030502948

477

AT4G01070

UGT72B1

54

71

LOC115718147

XM030647108

XP030502968

476

AT4G01070

UGT72B1

48

64

LOC115720703

XM030649871

XP030505731

508

AT4G01070

UGT72B1

42

61

LOC115725407

XM030654924

XP030510784

479

AT4G01070

UGT72B1

47

65

LOC115716326

XM030645093

XP030500953

460

AT5G17050

UGT78D2

58

74

LOC115722389

XM030651591

XP030507451

503

AT1G05560

UGT75B2

42

60

LOC115722393

XM030651596

XP030507456

492

AT1G05560

UGT75B2

42

60

LOC115722394

XM030651597

XP030507457

490

AT1G05560

UGT75B2

45

62

LOC115722400

XM030651603

XP030507463

473

AT1G05560

UGT75B2

42

61

LOC115722403

XM030651605

XP030507465

459

AT1G05560

UGT75B2

42

62

LOC115712602

XM030640905

XP030496765

241

AT1G67980

OMT (CCOMT)

61

74

LOC115712603

XM030640907

XP030496767

240

AT1G67980

OMT (CCOMT)

60

44

LOC115712971

XM030641415

XP030497275

241

AT1G67980

OMT (CCOMT)

61

74

LOC115712971

XM030641416

XP030497276

241

AT1G67980

OMT (CCOMT)

61

61

comparison to the other three Cannabis varieties. An overview of the

differential gene expression in the pigmented Cannabis varieties com-

phenylpropanoid and flavonoid biosynthesis genes listed in Table 1, as

pared with Willow-alpha. Finally, at least one enzyme from UGT fami-

well as their corresponding substrates and products, is provided in

lies 72, 75, 78, and 79 (excluding UGT80) was putatively responsible

Figure 2a. The differential gene expression of these genes is shown as

for the production of flavonoid glycosides and showed differential

log2 fold-change in Figure 2b with adjusted p-value significance

expression (Figure 2b).

across the pair of genotypes; for example, Willow-alpha versus
CA19210; Willow-alpha versus CK19206; Willow-alpha versus Cali
Kush. The RNAseq read counts and the comprehensive analysis of differential gene expression can be found in Data S1.

3.4 | Flavonoid, anthocyanin, and cannabinoid
metabolite profiling

The genes/transcripts encoding for 4CL/LOC115717276 and
CHS/LOC115724170 show elevated gene expression for the varieties

To better understand the diversity of anthocyanins, flavonols, and fla-

that accumulated more anthocyanins compared with Willow-alpha

vones found in the Cannabis varieties used in this study, we per-

(Figure 2b). The genes encoding enzymes involved in flavonol (F3H,

formed metabolite analysis of leaf extracts. We identified and

F30 H, and FLS) and anthocyanin (DFR, ANS, and OMT) biosynthesis

quantified the abundance of six anthocyanins (Figure 3a,d), four flavo-

are significantly upregulated in the pigmentated Cannabis varieties

nols

(Figure 2b). Notably, both gene copies encoding for F3H and FLS,

encompassing five of their different glycosides (Tables S2 and S3) in

responsible for dihydrokaempferol/dihydroquercetin and kaempferol/

the Cannabis varieties here examined.

(Figure

3b,d),

and

two

major

flavones

(Figure

3c,d)

quercetin formation, respectively, are significantly upregulated. More-

The most abundant anthocyanin found in all Cannabis varieties in

over, two identified genes copy for F30 H, LOC115709933 and

this study was cyanidin 3-O-rutinoside (Figure 3a,d). Moreover, cyani-

LOC115709845, are upregulated in the pigmented varieties com-

din 3-O-rutinoside was much more abundant in Cannabis varieties

pared with Willow-alpha. On the other hand, the gene responsible for

showing a more pigmented leaf phenotype, such as CA19210,

FNS2, involved in the production of apigenin and luteolin from the

CK19206, and Cali Kush. Peonidin 3-O-rutinoside, an O-methylated

naringenin and eriodyctiol, respectively, does not exhibit a clear differ-

derivative of cyanidin 3-O-rutinoside, is the second most abundant

ential gene expression pattern among the evaluated varieties in this

anthocyanin found in CA19210, CK19206, and Cali Kush but was

study (Figure 2b). The only OMT/LOC115712971 identified that

nearly undetectable in Willow-alpha (Figure 3a,d). CA19210 is the

putatively catalyzes the production of peonidin showed increased

only Cannabis variety that accumulated cyanidin sophoroside, and this

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8 of 17

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Legend on next page.

FIGURE 2

9 of 17
GAGALOVA ET AL.

GAGALOVA ET AL.

F I G U R E 2 Flavonoid biosynthesis gene expression analysis. (a) Overview of phenylpropanoid and flavonoid (flavanone, flavone, flavonol, and
anthocyanin) biosynthesis pathways along with the main substrates and products for each metabolic step. (b) Differential gene expression
presented as log2 fold-change between the pigmented Cannabis varieties (Cali Kush—light gray; CA19210—medium gray; CK19206—black) and
Willow-alpha. Differential gene expression analysis for the six glycosyltransferases gene families (UGT80, 79, 78, 78, 75, and 72) identified in the
KIPEs homology search strategy is also presented. ±1.5 log2 fold change threshold is indicated in dashed red lines. Differential gene expression
results with statistical significance (p < .05 and absolute fold-change > 1.5) are indicated as circles. Non-statistically significant results are
indicated as triangles.

F I G U R E 3 Flavonoid metabolite analysis. Cumulative overview of (a) anthocyanin, (b) flavonol, and (c) flavone content in leaf samples from
Willow-alpha and three pigmented varieties, CA19210, CK19206, and Cali Kush. Average quantities are shown as normalized scores, resulting in
micrograms of metabolites for each gram of fresh leaf weight. The quantities for vitexin (*) are shown as the sum of vitexin 3-O-glucoside, vitexin
7-O-glucoside, and isovitexin-O-glucoside average values (c). This is due to the inability to distinguish between these specific compounds because
of their identical molecular masses. (d) Metabolite quantities, across three replicates; quantities are shown as individual normalized scores, with
median values represented by the bar in the boxplot and average values as empty diamond shapes.

variety had the highest total amount of anthocyanins (Figure 3a,d). In

Kush, whereas quercetin glucuronide was the most abundant flavonol

addition to anthocyanins, we detected several flavonol glycosides,

glycoside in CK19206 and Willow-alpha (Figure 3b,d). Rutin and quer-

including kaempferol glucuronide, quercetin glucoside, quercetin glu-

cetin glucoside were the most abundant flavonol glycosides in

curonide, and rutin (Figure 3b,d). Rutin and quercetin glucoside were

CA19210 and Cali Kush, whereas quercetin glucuronide was the most

the most abundant flavonol glycosides found in CA19210 and Cali

abundant in Willow-alpha and CK19206 (Figure 3b,d). Overall,

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10 of 17

Willow-alpha and CK19206 accumulated the lowest amount of flavo-

involved in the flavonoid biosynthesis pathway that are listed in

nols, while CA19210 accumulated the highest. Flavone glycosides

Table 1. The list of SNPs and their presence in each variety can be

such as apigenin, luteolin, and vitexin/isovitexin glycosides were also

found in Data S2. The most common genetic modifications identified

identified (Figure 3c and Tables S3 and S4). Notably, Willow-alpha

were low-impact variants, followed by SNPs affecting non-coding

and CK19206, which had the lowest amounts of anthocyanins

regions and upstream/downstream regions, and moderate-impact var-

+ flavonols, exhibited the highest average concentrations of flavones

iants resulting in aa sequence changes. A single high-impact event

(Figure 3c). Among these, apigenin-7-O-glucuronide and vitexin/isovi-

was detected in CA19210, where a premature stop codon was found

texin-glucosides were the most abundant flavones that we identified

in UGT72/LOC115706084.
The most prevalent type of variant was the synonymous variant

(Figure 3c).
The cannabinoid content in leaves and flowers was also documen-

(Data S2). This was followed by downstream gene variants and then

ted for the four Cannabis varieties used in this study. Leaf samples did

missense variants, the latter of which accounted for about one-third

not accumulate high levels of CBGA, CBDA, or THCA compared with

the number of synonymous variants. CK19206 exhibited the highest

mature flowers (Figure S3). Willow-alpha accumulated the highest

number of synonymous and missense variants, totaling 217 and

amount of THCA at .43 mg per 100 mg of leaf fresh weight (FW).

104, respectively. In contrast, Willow-alpha had the fewest synony-

CA19210 accumulated the lowest amount of THCA (.01 mg/100 mg)

mous SNPs, 189, and the least number of missense variants, 65.

but accumulated the highest levels of CBDA (.35mg/100mg) per leaf

Enzymes from large gene families shown in Figure S5, including PAL/-

FW (Figure S3). Willow-alpha flowers accumulated the highest

LOC115706668,

amounts of THCA at 3.8 mg/100 mg per FW (Figure S3). CA19210

LOC115720703, showed the highest variability in synonymous SNPs

accumulated the lowest amount of THCA and highest CBDA at

in at least one of the varieties. F30 H/LOC115715257 and UGT72/

.09 mg/100 g and 2.54 mg/100 g per flower FW respectively. Taken

LOC115715257 were among the genes with the highest number of

collectively, all the cultivars here used are defined as drug-type Canna-

missense variants.

UGT75/LOC115722394,

and

UGT72/

bis, with Willow-alpha able to produce a high THCA/low CBDA accumulation chemotype, Cali Kush and CK10206 producing a medium
THCA/medium CBDA accumulation chemotype, and CA19210 producing a low THCA/high CBDA accumulation chemotype.

3.7 | Structural and protein-substrate docking
analysis of Cannabis 2-ODD enzymes
To gain a more comprehensive understanding of the putative function

3.5 | Gene expression/metabolite correlation
analysis

of the 2-ODD enzymes identified in this study, we conducted protein
structural prediction of FLS, ANS, and F3H using AlphaFold. This
study aims to enhance our characterization of these enzymes and

We correlated gene expression and flavonoid metabolite abundance

contribute to a deeper insight into the enzyme family’s properties

across the four Cannabis varieties analyzed in this study in order to

and functions. Following structural prediction, the application of

identify the genes whose expression was most correlated with the

pairwise structure alignment (Table S5) revealed that ANS, produced

production or accumulation of specific metabolites. Figure S4

by a single copy gene within Cannabis, displays the most notable

presents the correlation scores alongside the corresponding genes

structural similarity score (98.2%) with its corresponding Arabidopsis

and

peonidin

homolog, AtLDOX/ANS (Table S5). FLS (XP030502221) and F3H

glucoside/rutinoside and cyanidin rutinoside exhibits a robust correla-

(XP030486031), which belong to multicopy gene families, demon-

tion (ρ > .7) with the gene expression of ANS/LOC115716756,

strate the highest structural similarity with their corresponding Arabi-

DFR/LOC115710150, F30 H/LOC115709933, CHS/LOC115724170,

dopsis homologs, with 97.6% and 94.5% structural similarity,

and 4CL/LOC115717276. Similarly, the production of cyanidin

respectively (Table S5).

clusters

of

metabolites.

The

accumulation

of

sophoroside demonstrates a strong positive correlation with the gene

Through the utilization of protein databank (PDB) templates

expression of UGT72B1/LOC115705626. On the other hand,

within the COACH-D protein ligand binding site prediction pipeline

the accumulation of Kaempferol glucuronide negatively correlates

(Wu et al., 2018), we identified the binding sites of the crucial co-

with genes involved in the anthocyanin and anthocyanidin biosynthe-

factors, 2-oxoglutarate (2-OG or α-ketoglutarate AKG) and non-heme

sis,

iron (Fe). CB-Dock2 (Liu et al., 2022) was employed to predict the

such

as

DFR/LOC115710150,

ANS/LOC115716756,

and

OMT/LOC115712971.

substrate binding sites and reveal the docking arrangements of ANS
(a), FLS (b), and F3H (c), with leucocyanidin, dihydroquercetin, and naringenin, respectively (Figure 4). The enzyme pocket is situated within

3.6 | Flavonoid biosynthesis genotype variation
analysis

the hydrophobic beta-sheet arrangement, referred to as the beta-jelly
roll (Wilmouth et al., 2002), and shown in yellow in Figure 4. Additionally, the active site is enclosed by alpha-helices, enveloping the

We utilized RNAseq reads to genotype the flavonoid biosynthesis

ligand’s placement as shown by the highlighted regions. ANS and FLS

genes in the four Cannabis cultivars. The analysis included all genes

exhibit a catalytic pocket with a more enclosed structure (Figure 4a,b),

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GAGALOVA ET AL.

GAGALOVA ET AL.

F I G U R E 4 Predicted structures for (a) ANS (XP030501512), (b) FLS (XP030492734) and (c) F3H (XP030486031), where beta-sheets are
shown in yellow, alpha-helices in red, and unstructured regions in green. The density cloud represents the predicted binding pocket where each
substrate is binding. The metabolites shown are (a) leucocyanidin, (b) dihydroquercetin, and (c) naringenin, which are the primary substrates for
the three enzymes.

T A B L E 2 Binding affinity scores for the Cannabis 2-ODD class enzymes and flavonoid pathway substrates. The lowest affinity score for each
enzyme, in the columns, is shown in bold.
Anthocyanidin synthase (ANS)
XP030501512

Flavonoid synthase (FLS)
XP030492734

Flavanone 3-hydroxylase (F3H)
XP030486031

Leucocyanidin

6.6

8.2

8.0

Dihydroquercetin

6.0

8.4

7.7

Dihydrokaempferol

5.8

7.9

7.7

Naringenin

5.7

8.1

8.1

whereas F3H reveals a more open conformation with an extended

variant and did not affect relevant binding sites as confirmed by pro-

N-terminal alpha-helix structure (Figure 4c).

tein docking experiments (Table S6). F3H/XM030630171 had the

The CBDock2 protein affinity analysis evaluates how flavonoid

highest number of annotated missense variants, including Ile370Asn,

ligands bind to the examined enzymes. Table 2 reveals the lowest

Leu342Ile, and Ser164Ala, found, respectively, in Willow-alpha/

binding affinity scores, indicative of the most stable interactions,

CK19206/Cali Kush, CK19206/Cali Kush, and all varieties (Willow-

which are attributed to the native substrates for each enzyme:

alpha/CA19210/CK19206/Cali Kush). All these variants involve sur-

leucocyanidin for ANS, dihydroquercetin for FLS, and naringenin for

face aas with non-significant destabilizing effects, similar to Arg53Gly

F3H. Remarkably, leucocyanidin and dihydroquercetin also exhibit the

in CA19210, which has a non-significant stabilizing effect on the pro-

second lowest binding affinity scores for ANS and FLS, respectively.

tein (Table S8). All the annotated aa changes in F3H/XM030630171

F3H demonstrates a notable affinity for leucocyanidin as well, repre-

are located on the surface of the protein andthus not predicted

senting its second highest affinity for the enzyme. The full list of

to interfere with predicted binding ligand sites (Table S8).

tested ligands is shown in Table S6, and the complete list of binding

FLS/XP030492734 did not show any aa changes in the studied

affinity scores and predicted interacting residues is shown in Table S7.

varieties.

Moreover, we report the aa residues predicted to interact with each
substrate for the reported enzymes and corresponding ligands
(Figures S6–S10).

4

|

DI SCU SSION

The protein structures resulting from the observed SNPs were
compared with their unaltered equivalent protein in C. sativa

This study investigated the genetic and chemical underpinnings of

reference genome, cs10, to determine if changes in the aa

diverse pigmentation patterns that are observed in drug-type

sequence could lead to significant structural alterations (Table S8).

C. sativa. We focused on four distinct Cannabis varieties displaying

ANS/XM030645652 had a Pro319Ser missense variant present in all

varying degrees of leaf pigmentation. Our analysis encompassed iden-

four varieties, which was not identified as a strongly destabilizing

tifying Cannabis genes involved in the phenylpropanoid and flavonoid

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12 of 17

biosynthetic pathways, followed by characterization of gene

dihydroquercetin and dihydrokaempferol toward subsequent flavonol

expression and metabolite analysis. We identified 60 general phe-

and anthocyanin biosynthesis (Figure 2a). Notably, the genes encoding

nylpropanoid and flavonoid biosynthesis genes using a KIPEs-enabled

flavonoid 30 ,50 -hydroxylase (F30 50 H) enzymes, which use dihydro-

genome-wide homology-based approach (Pucker et al., 2020). KIPEs

kaempferol for the downstream biosynthesis of delphinidin-derived

can identify proteins that share significant sequence similarity with

anthocyanins, were not identified in our study. This is further sup-

known functional proteins and thus increase the likelihood of accu-

ported by our metabolomic analysis, which also did not identify any

rately predicting the function of proteins in other genomes. A previ-

delphinidin-derived anthocyanins.

ous study identified 20 flavonoid biosynthesis-related genes in the

The final phase of anthocyanin and flavonol biosynthesis involves

cs10 Cannabis reference genome using BLAST and representative

the conjugation of glycosyl moieties to the aglycones (Yoshihara

sequences mined from Solanum species (Bassolino et al., 2020). We

et al., 2005). Our investigation revealed two UGT genes, specifically

identified all but 7 of these 20 sequences and expanded further on

UGT78D/LOC115716326 and UGT79B/LOC115724965 (Figure 2b),

this data set by identifying several additional gene models for previ-

that exhibit a strong correlation with the pigmentation accumulation

ously identified genes as well as new gene models for genes encoding

in colored varieties. The Arabidopsis homologs to these two genes

F30 H and FNS2 enzymes. Moreover, we used the Arabidopsis thaliana

have been implicated in controlling pigmentation in Arabidopsis

genome as our reference dataset because many of the phenylpropa-

(Jones et al., 2003; Knoch et al., 2018; Li et al., 2017). Our results sug-

noid/flavonoid biosynthesis genes identified in this study were first

gest that the two genes are good candidates for the formation of

characterized in Arabidopsis. Moreover, A. thaliana remains the best-

anthocyanins and flavonol-glycosides in Cannabis. However, the high

characterized model system for flavonoid biosynthesis (Saito

number of UGTs found in plants and the tens of thousands of poten-

et al., 2013).

tial substrates make the prediction of substrates of any particular

The results show that the significant upregulation of key phenyl-

UGT difficult (Osmani et al., 2009). Gene co-expression studies, like

propanoid/flavonoid biosynthetic genes is highly correlated with the

those performed in this work, can provide UGT enzymes that are can-

pigmentation phenotype in Cannabis plants. The high differential

didates for anthocyanin and flavonol accumulation, but future func-

expression of the 4CL/LOC115717276 and CHS/LOC115724170

tional studies would provide more insight into their substrate

genes in the pigmented Cannabis varieties suggests increased meta-

specificity.

bolic flux through the general phenylpropanoid biosynthetic pathway

We identified cyanidin 3-O-rutinoside and peonidin 3-O-

and toward flavonoid biosynthesis, respectively. This pattern of ele-

rutinoside as the most abundant anthocyanins in the four drug-type

vated differential gene expression in pigmented Cannabis varieties

Cannabis varieties. Our findings corroborate a previous report derived

continues for several other key flavonol and anthocyanin biosynthetic

from

genes identified in this study. The differential accumulation of a

et al., 2023). Taken collectively, these results demonstrate that cyani-

diverse range of anthocyanins and flavonols in the pigmented Canna-

din 3-O-rutinoside and peonidin 3-O-rutinoside are the dominant

bis varieties used here largely supports the gene expression findings.

anthocyanins found in both drug-type and hemp-type Cannabis. This

Taken together, these results support the hypothesis that differential

result was somewhat surprising considering the significant genome-

activation of anthocyanin biosynthetic pathway genes results in the

wide differentiation between the drug-type and hemp-type Cannabis

accumulation of anthocyanins and hence the pigmented phenotypes

as was previously reported after the genomic analysis of 81 drug-type

observed in C. sativa.

and 43 hemp-type Cannabis varieties (Sawler et al., 2015). Thus, the

six

different

hemp-type

Cannabis

varieties

(Bassolino

Flavonol glycosides like those found in our study (e.g., kaempferol

differences in cannabinoid accumulation, plant growth architecture,

glucuronide, quercetin glucoside, and rutin), are often colorless or

disease/pest resilience, and so forth observed in hemp-type and

have a pale yellow color (Castañeda-Ovando et al., 2009; Dias

drug-type Cannabis do not impact the diversity of anthocyanin accu-

et al., 2021). In contrast, anthocyanins such as cyanidin and peonidin

mulation in these different Cannabis types. However, the relative

3-O-rutinoside impart red/purple phenotypes (Castañeda-Ovando

abundance of the anthocyanins identified thus far (e.g., cyanidin 3-O-

et al., 2009; Dias et al., 2021). We observed the accumulation of

rutinoside, peonidin 3-O-rutinoside, or cyanidin sophoroside) in any

kaempferol and quercetin-derived flavonols along with cyanidin and

particular Cannabis variety can vary dramatically (Figure 3a; Bassolino

peonidin-derived anthocyanins in the pigmented Cannabis varieties.

et al., 2023).

These metabolites are derived from dihydrokaempferol or dihydro-

In addition to gene expression, other factors such as enzyme turn-

quercetin, which are intermediates leading to subsequent flavonol and

over, metabolon formation, catalytic activity, and substrate promiscu-

anthocyanin biosynthesis. The observation that the most abundant

ity are important factors regulating the metabolic flow through a

anthocyanins and flavonols found in this study were derived from

biosynthetic pathway toward specific endpoints. We therefore con-

dihydroquercetin (Figure 3a,b,d) is also supported by the high expres-

ducted a more comprehensive examination of the FLS, ANS, and F3H

sion of F30 H, which catalyzes the formation of dihydroquercetin using

genes, which all belong to the 2-ODD enzyme family, an evolution-

dihydrokaempferol as a substrate. However, the significant differential

arily related group of enzymes that oversee crucial reactions within

gene expression of two FLS genes (FLS/LOC115708857 and

flavonoid biosynthesis. Among these three, ANS emerges as the main

FLS/LOC115717395),

4-reductase

enzyme responsible for initiating anthocyanin production in plants

(DFR/LOC115710150), suggests that there is strong competition for

(Pelletier et al., 1997). Notably, the primary substrate of this enzyme,

as

well

as

dihydroflavonol

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13 of 17

GAGALOVA ET AL.

leucocyanidin, is produced by the upstream DFR enzyme, which competes with FLS for dihydroquercetin.

GAGALOVA ET AL.

In conclusion, our findings identify the Cannabis genes whose
expression is associated with Cannabis leaf pigmentation, while also

2-ODD enzymes are recognized for their multifunctional catalytic

identifying the diversity of anthocyanins, flavonols, and flavones

activity, which extends to the utilization of leucocyanidin by ANS,

found in four drug-type Cannabis varieties. Together, these data

naringenin by F3H, and dihydroquercetin/dihydrokaempferol by FLS

contribute to a deeper understanding of the underlying mechanisms

(Turnbull et al., 2004). The functional role of FLS has undergone

governing anthocyanin production in Cannabis and lay the foundation

exploration across various plant species (Chen et al., 2023; Xu

for future functional characterization of the biosynthesis genes

et al., 2012). Multiple copies of the FLS enzyme have been identified

identified in this study.

in several studies, including Arabidopsis (Owens et al., 2008), grapevine (Fujita et al., 2006), and canola (Schilbert et al., 2021). In Arabi-

AUTHOR CONTRIBU TIONS

dopsis, the gene family responsible for encoding FLS enzymes

Conceptualization: Kristina K. Gagalova, Mathias Schuetz, Till Matzat,

emerged from a recent gene duplication event, subsequently followed

and Shumin Wang. Methodology: Kristina K. Gagalova, Yifan Yan, and

by pseudogenization to eliminate redundant gene copies (Preuß

Shumin Wang. Formal analysis: Kristina K. Gagalova and Mathias

et al., 2009). Among these, FLS1 remains the sole functional enzyme-

Schuetz. Investigation: Kristina K. Gagalova and Mathias Schuetz.

encoding gene product, with the additional five gene copies yielding

Data curation: Kristina K. Gagalova and Mathias Schuetz. Writing—

non-functional outcomes (Owens et al., 2008; Wisman et al., 1998).

original draft preparation: Kristina K. Gagalova. Writing—review and

The analysis of FLS and ANS across multiple plant species by Wang

editing: Mathias Schuetz, Simone D. Castellarin, Till Matzat, David

et al. (2021) reveals an interesting observation that some enzymes

Edwards, and Inanc Birol. Data visualization: Kristina K. Gagalova. All

annotated as ANS cluster with FLS. This suggests functional redun-

authors have read and agreed to the published version of the

dancy or incomplete evolution of substrate selectivity among these

manuscript.

proteins. The presence of similar activities in this branch enriches the
functional diversity of the 2-ODD enzyme family. The enzymatic

ACKNOWLEDG MENTS

activity of FLS in Cannabis has been characterized by the study con-

We would like to thank Dr. Matthew Workentine for his support with

ducted by Zhu et al. (2022), which also includes a heterologous

data analysis and annotation during the early stages of this work.

assessment of FLS’s enzymatic activity in Escherichia coli. This study
indicates FLS2/XP030492734 as the enzyme demonstrating the high-

CONFLIC T OF INTER E ST STATEMENT

est catalytic activity toward substrates such as dihydrokaempferol

M.S., K.K.G., T.M., and S.W. were employed by Willow Analytics dur-

and dihydroquercetin. The FLS enzyme, XP030502221, which was

ing the data collection stage of this study. Willow Analytics was a for-

also identified in our study, did not show functional activity toward

profit analytical testing and Cannabis research lab located in Burnaby,

its primary substrates (Zhu et al., 2022). Furthermore, Zhu et al.

British Columbia.

(2022) present a functional analysis of FLS3/XP030501512, which
displays a minor degree of catalytic activity for the same two

PE ER RE VIEW

substrates. In this work, we present comprehensive annotations of

The peer review history for this article is available in the Supporting

enzymes contributing to the anthocyanin pathway, designating

Information for this article.

XP030501512 as ANS (Table 1), based on homology analysis, representative catalytic sites, and protein structure evaluation. Informed by

DATA AVAILABILITY STAT EMEN T

protein docking findings (Table 2), our attention was drawn to the

Data will be made available on request.

substrate exhibiting the most robust binding affinity—leucocyanidin—
which coincidentally serves as the primary substrate of the ANS

ORCID

enzyme. We therefore hypothesize that the ANS/LOC115716756

Kristina K. Gagalova

is the functional anthocyanin synthase in Cannabis based on

David Edwards

https://orcid.org/0000-0001-7599-6760

differential gene expression analysis (Figure 2b) and the protein struc-

Mathias Schuetz

https://orcid.org/0000-0002-2413-800X

https://orcid.org/0000-0002-5975-0805

ture and molecular docking studies (Figure 4; Table 2). The loss of
function phenotype of the Arabidopsis Leucoanthocyanidin Dioxygen-

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How to cite this article: Gagalova, K. K., Yan, Y., Wang, S.,
Matzat, T., Castellarin, S. D., Birol, I., Edwards, D., & Schuetz,
M. (2024). Leaf pigmentation in Cannabis sativa:
Characterization of anthocyanin biosynthesis in colorful
Cannabis varieties. Plant Direct, 8(11), e70016. https://doi.
org/10.1002/pld3.70016

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