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Article

The GRF9-6Ab Allele Compensates for the Pleiotropic Deficits of the Ddw1 Dwarfing Gene in Triticale

by
Pavel Yu. Kroupin
1,*,
Timofey D. Mokhov
1,
Vladimir V. Panchenko
2,
Yana S. Meglitskaya
1,
Ludmila A. Bespalova
2,
Anastasiya G. Chernook
1,
Mikhail S. Bazhenov
1,
Victor Ya. Kovtunenko
2,
Aleksandra Yu. Kroupina
1,
Gennady I. Karlov
1 and
Mikhail G. Divashuk
1
1
All-Russia Research Institute of Agricultural Biotechnology, 127434 Moscow, Russia
2
P.P. Lukyanenko National Grain Center, Department of Breeding and Seed Production of Wheat and Triticale, Central Estate of KNIISH, 350012 Krasnodar, Russia
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(12), 2701; https://doi.org/10.3390/agronomy15122701
Submission received: 7 November 2025 / Revised: 19 November 2025 / Accepted: 21 November 2025 / Published: 24 November 2025
(This article belongs to the Section Crop Breeding and Genetics)
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Abstract

The Ddw1 dwarfing gene is pivotal for reducing plant height and improving lodging resistance in triticale, but its pleiotropic effects on yield components and heading date pose significant challenges for breeders. This study identifies the Growth-Regulating Factor 9-6A (GRF9-6A) gene that compensates for these drawbacks. Field trials across locations (Moscow, Krasnodar) and years (2018, 2019) confirmed the effect of Ddw1, reducing plant height by 26.1–30.1 cm (31.8–32.5%) and thousand-kernel weight (TKW) by 6.0–6.3 g (11.8–15.7%) while increasing the harvest index by up to 4.8 percentage points in three out of four environments, with its effect nullified under the heat stress of Krasnodar 2019. In a Ddw1 background, the GRF9-6Ab allele distinguished by a 12 bp deletion in its promoter compensated for yield losses by increasing grain weight per main spike by up to 0.34 g (19.2%) via boosts in grain number per spike (up to 11.6%) and TKW (up to 11.5%). This combination also elevated the harvest index by up to 4.0 pp and, critically, provided a key agronomic advantage by accelerating heading by 6.3–6.5 days (10.0–10.2%), thereby mitigating the Ddw1-associated developmental delay. Our results demonstrate that pyramiding Ddw1 with the GRF9-6Ab allele the development of semi-dwarf, high-yielding, and early-maturing triticale cultivars for food and forage. This breeding strategy, facilitated by a newly developed diagnostic marker for GRF9-6Ab, is particularly advantageous for cultivation in environments similar to the Central Non-Chernozem region.

1. Introduction

Triticale (×Triticosecale Wittmack) is a high-yielding forage crop with significant potential for feed production. Its high ecological plasticity, stable productivity across a wide range of soil and climatic conditions, and resistance to a number of diseases make it a valuable source of grain and green mass for animal husbandry [1,2]. The high protein content, balanced amino acid profile, and suitability for inclusion in the diets of various farm animals underpin the growing interest in triticale as a forage crop [3]. However, its widespread adoption in feed production is hindered by several limitations, including susceptibility to lodging due to excessive plant height, as well as inconsistent grain quality and plumpness [4].
A reliable solution to the lodging problem is the utilization of dwarfing genes. The dominant, gibberellin-sensitive dwarfing gene Ddw1, which originated from rye and was first described by V.D. Kobylyanskii [5], has been successfully deployed in triticale breeding. Subsequent research has demonstrated that the introgression of this gene into hexaploid triticale leads to a stable reduction in plant height of 20–40% across diverse environments [6,7]. However, the introduction of Ddw1 is associated with several negative pleiotropic effects, including reduced thousand-kernel weight, decreased spike productivity, and increased susceptibility to Fusarium head blight, which can ultimately negate the benefits of improved lodging resistance [8,9,10]. Consequently, the search for genetic factors capable of compensating for the negative effects of the Ddw1 gene represents a relevant objective in modern breeding.
Promising candidates for such fine-tuning are genes from the Growth-regulating factors (GRF) family—plant-specific transcription factors that play a key role in regulating growth, development, and stress responses [11]. In particular, GRF homologs in wheat and rice are associated with increased grain size and yield [12,13]. Previous studies have shown that the allelic state of the TaGRF3-2A and TaGRF-2D genes in wheat is associated with grain weight and size [14,15], and their homologs TaGRF3-2A and ScGRF3-2R exhibit a compensatory effect against the negative action of the Ddw1 gene in triticale [9,16].
Nevertheless, the functional role of another homolog, GRF9-6A, its allelic diversity, and its influence on agronomically valuable traits in triticale, particularly in combination with the Ddw1 gene, remain largely unstudied. Investigating this gene is of particular interest since its rice homolog, OsGRF4, is a key regulator of grain size and yield [12].
The aim of this study was to identify novel allelic variants of the GRF9-6A gene and to comprehensively evaluate their effects on key traits for feed production—plant height, lodging resistance, grain mass, and earliness—in a collection of recombinant inbred lines of triticale. Special attention was paid to the analysis of the combined effects of GRF9-6A alleles with the Ddw1 dwarfing gene to determine their practical value for marker-assisted selection of high-yielding forage cultivars.

2. Materials and Methods

2.1. Plant Material

The phenotypic effects of the Ddw1 and GRF9-6A genes were studied using a population of recombinant inbred lines (RILs) of triticale at the F4:5(2018) and F5:6(2019) generations. The parental forms were triticale cultivars carrying contrasting allele combinations of the studied genes. The tall spring triticale cultivar ‘Dublet’ (Danko Hodowla Roslin Sp. z o.o., Choryń, Poland) with a genotype homozygous for the ddw1 allele was used as the paternal parent. The semi-dwarf winter triticale cultivar ‘Hongor’ (P.P. Lukyanenko National Grain Centre, Krasnodar, Russia) with a genotype homozygous for the Ddw1 allele was used as the maternal parent. A detailed description of the plant material development is provided in our previous publications [9,16].

2.2. Field Experiments and Phenotyping

Field experiments were conducted in Moscow (Field Experimental Station of the Russian State Agrarian University—Moscow Timiryazev Agricultural Academy, Central Non-Chernozem region) and Krasnodar (P.P. Lukyanenko National Grain Centre) in 2018 and 2019 according to established methodologies, detailed in our previous publications [9,16,17]. The weather conditions during the field experiments in Moscow and Krasnodar are presented in Table S1.
Plant developmental stages were visually assessed, with the transition to heading and flowering phases recorded when 80% of plants in a row reached the respective stage. The following agronomic traits were measured after harvest: plant height (PH, cm), grain weight per main spike (GWS, g), number of grains per main spike (NGS), thousand-kernel weight (TKW, g), and days to heading (DTH, days). Seed counting was performed using the SeedCounter application [18].

2.3. DNA Extraction, PCR and Sequencing

Genomic DNA was extracted from leaves of young plants using the CTAB-based protocol [19]. The sequences of GRF9-6A (TraesCS6A02G269600) and its homoeologues genes (TraesCS6B02G296900 and TraesCS6D02G245300) were extracted from the reference bread wheat genome RefSeq1.0 using the genome browser [20]. The PCR primers for amplifying the gene into fragments (Table 1, Figure 1) were designed using Primer-BLAST online tool (www.ncbi.nlm.nih.gov/tools/primer-blast/; accessed on 22 November 2022) [21]. The specificity of the primers was checked using alignment of the three homoeologues’ genes in GeneDoc 2.7 [22].
PCR was performed in 25 µL reaction volumes, containing 70 mM Tris–HCl buffer (pH 9.3), 16.6 mM (NH4)2SO4, 2.5 mM MgCl2, 0.2 mM of dNTPs, 0.3 µM forward and reverse primers (Sintol Ltd., Moscow, Russia), 0.04 U/µL LR (long reading) Plus polymerase (Sileks Ltd., Moscow, Russia), 0.02 U/µL Taq polymerase (Sileks Ltd.), and 4 ng/µL DNA template. PCR conditions were as follows: (1) 95 °C for 10 min, (2) 45 cycles of 95 °C for 30 s, 60 °C for 30 s, 72 °C for 4 min; and (3) final extension step of 72 °C for 10 min. The quality of PCR products was assessed using electrophoresis in 1.5% agarose gels in TBE (90mM Tris, pH 8.3, 90 mM boric acid, 0.1 mM EDTA) buffer using GeneRuler 100 bp Plus DNA Ladder (Thermo Fisher Scientific, Waltham, MA, USA) as a molecular weight marker, and stained with ethidium bromide for subsequent visualization in Gel Doc XR+ (Bio-Rad Laboratories, Inc., Hercules, CA, USA).
The PCR products obtained from GRF9-6A gene of triticale ‘Dublet’ were mixed and submitted for NGS sequencing on Illumina MiSeq system. Sequencing was performed at “Genomed, Ltd.” (Moscow, Russia). DNA libraries were prepared using Swift 2S™ Turbo DNA Library Kits. The quality of the sequencing reads was assessed using FastQC (v0.12) software [25]. Mapping of reads on wheat chromosome 6A fragment obtained from RefSeq1.0 bread wheat genome (‘Chinese Spring’) was done using SNAP (v1.0) software [26]. Variant calling was done using freebayes (v1.3.9) [27], and the confident variants were introduced to the reference sequence using bcftools (v1.10.2) [28] to produce sequence of triticale ‘Dublet’. The variants introduced in sequence were checked by visualization of reads alignment to reference in IGV 2.8.2 [29]. The sequences of GRF9-6A were annotated using Augustus gene prediction online tool [30]. Alignment of ‘Chinese Spring’ and ‘Dublet’ chromosome 6A fragments, predicted gene and protein-coding sequences was performed in Mega 11.0.13 [31] using MUSCLE [32] algorithm, translation of protein-coding sequences to amino acids was done in GeneDoc 2.7.

2.4. Evolutionary Analysis

GRF9-6A sequences were obtained from the assembled genomes of bread wheat, spelt [33], durum wheat [34], wild emmer wheat [35], Urartu wheat [36] and einkorn wheat [37]. The sequences were found in the genomes using the BLAST 2.17.0+ command line tool [38]. The obtained sequences were aligned in MEGA 11.0.13 using MUSCLE algorithm. The alignment was trimmed to make uniform edges, and sequences were compared to each other to find unique haplotypes using Python 3.11 code (https://github.com/MikhailBazhenov/FASTA-dedup/; accessed on 5 November 2025). The unique sequences were subjected to evolutionary analysis conducted in MEGA 11.0.13 software using the maximum-likelihood method and Hasegawa–Kishino–Yano model [39]. All sites, including gaps, were used. The bootstrap support values were calculated using 1000 replicates. The trees were drawn to scale, with branch lengths measured by numbers of substitutions per site. To establish a tree root, the most similar sequence to GRF9-6A from Lo7 rye genome was used for evolutionary analysis as an outgroup.
Protein domains were identified using a Conserved Domains Database search at the NCBI website using default search parameters (www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi; accessed on 5 November 2025) [40]. The functional significance of amino acid substitutions was predicted using the SIFT online tool (https://sift.bii.a-star.edu.sg/; accessed on 5 November 2025) [41].
The analysis of the promoter sequence for the presence of transcription factor binding sites was done using the PlantCARE online service (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/; accessed on 5 November 2025) [42].

2.5. Visualization

Visualization of gene structure and cis-elements in promoter sequences was done using Python code. The code was created with the assistance of the Qwen3-MAX LLM (https://chat.qwen.ai/; accessed on 1 November 2025) [43]. The code was reviewed, the bugs were fixed and minor changes were made to obtain the final functional version, which is available at: https://github.com/MikhailBazhenov/cis-elements-figure/ (accessed on 3 November 2025), https://github.com/MikhailBazhenov/gene_visualisation/ (accessed on 3 November 2025).
Other figures of alignments were created in GeneDoc 2.7. The evolution tree was created in MEGA 11.0.13. The final versions of the vector images were created using Inkscape 1.3.2 software.

2.6. Genotyping

For detection of the 12-nucleotide in-del in gene promoter differentiating T. aestivum and T. durum (and triticale ‘Dublet’) alleles we designed a pair of primers GRF9-12del-F/R giving PCR products of either 203 or 191 base pairs (see Table 1). The PCR was performed in 20 mL reaction volumes, containing 70 mM Tris–HCl buffer (pH 8.6), 16.6 mM (NH4)2SO4, 1.2 mM MgCl2, 0.2 mM of each dNTP, 0.3 mM forward and reverse primers (Sintol Ltd., Moscow, Russia), 0.02 U/mL Taq polymerase (Sileks Ltd., Moscow, Russia), 4 ng/mL DNA template. The PCR conditions were as follows: (1) 95 °C for 5 min, (2) 35 cycles of 95 °C for 30 s, 58 °C for 30 s, 72 °C for 1 min; and (3) final extension step of 72 °C for 10 min. The PCR products were separated by electrophoresis in 2% agarose gel with TBE buffer along with M100 size standard (Sintol Ltd., Moscow, Russia), stained with ethidium bromide and documented under UV light.
A combination of indirect molecular marking methods is used to determine Ddw1 gene allelic state in modern studies. The primary approach is the analysis of the tightly linked microsatellite marker REMS1218 [44]. Its amplification is carried out using specific primers (F: 5′-CGCACAAACAAAAACACGAC-3′, R: 5′-CAAACAAACCCATTGACACG-3′) under standard PCR conditions: initial denaturation at 94 °C for 5 min, 35 cycles (94 °C—30 s, 60 °C—30 s, 72 °C—1 min), and a final elongation at 72 °C for 5 min. The resulting PCR products are subjected to fragment analysis on genetic analyzers such as the Applied Biosystems™ 3130 or Nanophor05, which allows for precise determination of allele sizes and establishment of the genotype. To enhance the reliability and accuracy of detection, particularly for identifying the specific dwarfing allele, an additional method is used, the CAPS marker (Cleaved Amplified Polymorphic Sequences). The PCR products generated by the REMS1218 marker were digested with the restriction enzyme MnlI (recognition site: 5’-C↓CTC-3’). The resulting restriction fragments were separated by electrophoresis in a 2% agarose gel. This CAPS assay allows for the clear discrimination of homozygous Ddw1 and ddw1 genotypes, as well as heterozygotes, based on their distinct banding patterns [45]. The combined use of the REMS1218 marker and CAPS analysis forms a robust system for the unambiguous identification of allelic variants of the Ddw1 gene.

2.7. Statistical Analysis

The analysis of variance (ANOVA) for assessing the effects of the genes and their interaction on agronomic traits was performed using the general linear model (GLM) procedure. The statistical model included the main fixed effects of genotype at the Ddw1 locus, genotype at the GRF9-6A locus, year, location, and all possible interactions between these factors. For the analysis of the duration of the vegetative period (time to heading), data from Krasnodar in 2019 were excluded due to missing values.
Following a significant F-test in the ANOVA, post hoc pairwise comparisons of least-squares means were conducted using Fisher’s Least Significant Difference (LSD) test at a significance level of p < 0.05.
The relative effect of the Ddw1 allele was calculated for each relevant trait as a percentage, using the formula: ((Ddw1 − ddw1)/ddw1) × 100, where Ddw1 and ddw1 represent the mean values of the trait for the respective homozygous genotype groups. Similarly, the relative effect of the GRF9-6Ab allele was calculated relative to the GRF9-6Aa allele as: ((GRF9-6Ab − GRF9-6Aa)/GRF9-6Aa) × 100. To quantify the proportion of phenotypic variation explained by each factor and their interactions, partial eta-squared (η2) values were calculated for significant effects in the ANOVA models using the formula: η2 = SS_effect/(SS_effect + SS_error), where SS_effect is the sum of squares for the factor of interest and SS_error is the sum of squares of the residual variance.
All statistical analyses were performed using the Statistica 12.5 software package (StatSoft, Inc., Tulsa, OK, USA).

3. Results

3.1. Sequencing of GRF9-6A in Triticale ‘Dublet’

To characterize the GRF9-6A locus in triticale, we sequenced the corresponding gene (TraesCS6A02G269600, following the nomenclature of Huang et al. [13]) in the cultivar ‘Dublet’ and conducted a comparative analysis with the reference genome of bread wheat ‘Chinese Spring’.
The analysis of the coding sequence revealed no polymorphisms at the known microRNA binding site for miR396 [46] in ‘Dublet’ compared to ‘Chinese Spring’ (Figure 2a). This indicates a high degree of conservation in this critical post-transcriptional regulatory region. Alignment of the deduced GRF9 protein sequence identified four amino-acid substitutions between ‘Dublet’ and the ‘Chinese Spring’ reference (Figure 2b). Importantly, none of these substitutions were located within the highly conserved QLQ and WRC domains, which are essential for protein–protein interactions and DNA binding, respectively. This suggests that the core molecular function of the GRF9 transcription factor protein is likely preserved (Table 2).
We next investigated the promoter region of the GRF9-6A gene. The alignment of sequences identified 14 variations between ‘Dublet’ and ‘Chinese Spring’, including 12 single-nucleotide variations, 1 di-nucleotide substitution and 12-nucleotide indel (Table 3). These variations resulted in alterations to the composition of predicted cis-regulatory elements located approximately 800 bp upstream of the transcription start site (Figure 3) as revealed by analysis using the PlantCARE database. Specifically, one CTCC motif, associated with light responsiveness, was lost in ‘Dublet’. Concurrently, four new motifs were gained, that are involved in stress responsiveness, including oxidative stress (that could be part of drought or heat stress), responsiveness to hormones salicylic acid, jasmonic acid and auxins (Figure 3).
To elucidate the evolutionary history of the GRF9-6A allele in ‘Dublet’, a phylogenetic analysis was performed using the Maximum Likelihood method (Figure 4). The analysis included sequences from wild emmer (Triticum dicoccoides ‘Zavitan’), bread wheat (T. aestivum ‘Chinese Spring’), durum wheat (T. durum ‘Cappelli’), T. urartu, and T. monococcum, with the most similar gene from rye (Secale cereale Lo7) used as an outgroup. The resulting phylogenetic tree demonstrated that the GRF9-6A sequence from triticale ‘Dublet’ clusters most closely with the sequence from durum wheat ‘Cappelli’, suggesting the durum wheat origin of this allele in ‘Dublet’.

3.2. Genotyping of the RIL Population for Ddw1 and GRF9-6A Loci

The recombinant inbred line (RIL) population, derived from a cross between triticale cultivars ‘Dublet’ and ‘Hongor’, was genotyped for the allelic state of two key genes: the dwarfing gene Ddw1 and the GRF9-6A gene. For the GRF9-6A gene, a new PCR marker GRF9-12del was developed and applied in this study. The marker targets a 12 bp indel polymorphism in the promoter region. Analysis confirmed that the parental line ‘Hongor’ possesses the allele without the 12 bp deletion, while ‘Dublet’ carries the allele with the deletion. According to the established nomenclature, the ‘Hongor’ allele was designated as GRF9-6Aa, and the ‘Dublet’ allele as GRF9-6Ab. For the purpose of this study on stable RILs, only homozygous genotypes were considered for the final phenotypic analysis. The results of the genotyping for the homozygous RILs across all field experiments are summarized in Table 4. The distribution of the four main genotypic classes (ddw1/GRF9-6Aa, ddw1/GRF9-6Ab, Ddw1/GRF9-6Aa, Ddw1/GRF9-6Ab) was well-represented in each environment (Moscow and Krasnodar) over two years, with the valid N for each class detailed below.

3.3. Phenotypic Effects of the Ddw1 and GRF9-6A Genes and Their Interaction

3.3.1. Effects of the Ddw1 Gene

Multifactor analysis revealed a significant influence of the Ddw1 allele on plant height (p < 0.001, Table S2). In Moscow in 2018, plants homozygous for the Ddw1 allele were 26.1 cm (32.3%) shorter compared to ddw1 homozygotes, and in 2019, the reduction was 27.5 cm (32.5%, Table 5). In Krasnodar in 2018, the height reduction effect due to Ddw1 was 30.1 cm (31.8%), whereas in 2019, the Ddw1 allele was associated with a statistically non-significant height increase of 1.7 cm (1.8%, Table S3).
ANOVA indicated a significant effect of the Ddw1 allele on grain weight per main spike and thousand-kernel weight (TKW, p < 0.001, Table S2). In Moscow in 2018, the difference in grain weight per main spike was 0.31 g (16.1%), and in 2019, it was 0.33 g (13.0%, Table 5). A similar trend towards reduction was observed in Krasnodar in 2018 (0.35 g, 15.2%); however, in 2019, the difference was minimal and statistically insignificant (Table S3). The reduction in grain weight per main spike was attributed to a significant decrease in TKW. In Moscow in 2018, the difference in TKW was 6.0 g (14.9%), and in 2019, it was 6.1 g (11.8%, Table 5). In Krasnodar, the reduction was 6.3 g (15.7%) in 2018, whereas in 2019, the decrease was minimal and statistically insignificant (Table S3).
Under Moscow conditions in both study years, Ddw1 homozygotes exhibited a higher harvest index compared to ddw1 homozygotes: the difference was 2.3 percentage points (pp) in 2018 and 4.8 pp in 2019. In Krasnodar, the harvest index was 0.9 pp higher in Ddw1 plants in 2018 but 3.0 pp lower in 2019 (Table S3).

3.3.2. Effects of the GRF9-6A Gene

Analysis of variance revealed a significant influence of GRF9-6A on the length of the main spike (p < 0.001, Table S4). Statistically significant effects were observed in Moscow in 2019 and in Krasnodar in 2018: homozygotes for the GRF9-6Ab allele had spikes that were longer than those of GRF9-6Aa homozygotes by 0.3 cm (3.7%) and 0.7 cm (6.5%), respectively (Table S5).

3.3.3. Interaction Between Ddw1 and GRF9-6A Genes

Multifactor analysis revealed a statistically significant interaction between the genes on grain weight per main spike (p < 0.05, Table S6). Under Moscow conditions, in semi-dwarf Ddw1 carrier plants during both years of the field experiment, carriers of the GRF9-6Ab allele exhibited a higher grain weight compared to carriers of the GRF9-6Aa allele, by 0.28 g (19.2%) in 2018 and by 0.34 g (16.9%) in 2019 (Figure 5). This effect of GRF9-6Ab in semi-dwarf plants with the Ddw1 allele was the result of both an increase in the number of grains per spike by 3.0 (6.8%) in 2018 and by 5.2 (11.6%) in 2019, and an increase in TKW by 3.7 g (11.5%) in 2018 and by 2.9 g (6.6%) in 2019 (Table 6 and Table S7). In Krasnodar, the positive influence of GRF9-6Ab on the grain weight of the main spike in semi-dwarf Ddw1 carrier plants was observed only in 2018 and amounted to an increase of 0.35 g (19.7%), which was determined by the positive influence of GRF9-6Ab on the number of grains per spike (+8.5 grains, 16.0%, Table S8, Figure 5).
Analysis of variance showed a significant interaction between the genes on the harvest index (p < 0.05, Table S6). Under Moscow conditions, an increase in the index was noted under the influence of the GRF9-6Ab allele compared to GRF9-6Aa in semi-dwarf Ddw1 carrier plants by 4.0 pp in 2018 and by 2.8 pp in 2019 (Table S7). In Krasnodar, this effect was observed only in 2018 and amounted to 2.8 pp (Table S8).
ANOVA revealed a significant interaction for the duration of the vegetative period in Moscow (p < 0.01, Table S6), manifested as a reduction in the period to heading under the influence of the GRF9-6Ab allele in Ddw1 carriers by 6.3 days (10.0%) in 2018 and by 6.5 days (10.2%) in 2019 (Table 6).

4. Discussion

This study provides a multifaceted characterization of the GRF9-6A gene in triticale, elucidating its evolutionary origin, molecular features, and, crucially, its significant role as a modulator of agronomically valuable traits, particularly through its interaction with the dominant dwarfing gene Ddw1.
Our sequencing and phylogenetic analysis unequivocally demonstrate that the GRF9-6Ab allele in the triticale cultivar ‘Dublet’ is identical to that of the durum wheat (Triticum durum) ‘Senator Cappelli’ [34], clustering robustly with it to the exclusion of the bread wheat (T. aestivum) ‘Chinese Spring’ reference. This confirms the durum wheat pedigree of the A-genome in this triticale line. The coding sequence analysis revealed a high degree of conservation, with no polymorphisms at the microRNA binding site for miR396, a key post-transcriptional regulator of GRF genes [46,47]. Furthermore, the four identified amino acid substitutions were located outside the critical QLQ and WRC domains, which are essential for protein–protein interactions and DNA binding, respectively [11]. This structural conservation suggests that the core molecular function of the GRF9-6A transcription factor is preserved in triticale.
While the coding region was largely conserved, analysis of the promoter sequence revealed substantial polymorphism. The 14 variations identified between ‘Dublet’ and ‘Chinese Spring’ altered the repertoire of predicted cis-regulatory elements. The loss of a light-responsive CTCC motif and the gain of motifs associated with stress responses (oxidative stress) and hormone signaling (auxin, jasmonic acid, and salicylic acid) suggest potential differences in the regulatory landscape of the GRF9-6A gene [42]. These promoter alterations provide a molecular hypothesis for the observed G × E interactions, positing that the GRF9-6Ab allele may be more responsive to certain environmental or endogenous signals, thereby fine-tuning plant development and stress adaptation.
Consistent with previous reports, the Ddw1 gene exerted a strong, pleiotropic influence, significantly reducing plant height and increasing harvest index but at the cost of grain weight per spike and thousand-kernel weight [6,7]. However, the expression of these traits was highly dependent on the environment. The absence of a significant Ddw1 effect on height in Krasnodar in 2019 is a salient example of G × E interaction. We hypothesize that the intense heat stress experienced that year acted as a primary growth limiter, effectively masking the additional reduction imposed by the dwarfing gene, a phenomenon aligning with the concept that the efficacy of dwarfing genes can be nullified under severe drought or heat stress [48]. This observation aligns with the concept that the temperature response during stem elongation can be a dominant factor influencing final plant height [49]. While our data provide a strong phenotypic premise, the exact molecular mechanism remains to be fully elucidated. Based on the work identifying ScGA2ox12 as the candidate gene for Ddw1 [50], a key enzyme in the gibberellin (GA) inactivation pathway [51], we can hypothesize that the heat stress may have suppressed its expression or activity. The potential for abiotic stress to modulate the GA pathway is well-documented [52], and the stability of dwarfing gene effects can be highly dependent on genetic background and environment [17,53]. However, this specific hypothesis requires direct validation. Our results therefore underscore the necessity for future investigations that directly measure the expression dynamics of ScGA2ox12 and the endogenous levels of GAs in the stems of plants carrying Ddw1 under controlled stress conditions, building on methodologies used to profile GA-related gene expression (e.g., [50,54]). Such targeted molecular studies will be crucial to confirm whether the stability of this valuable dwarfing gene is compromised by specific abiotic stressors, which is a critical consideration for breeding resilient cultivars.
Independent analysis positioned GRF9-6A as a regulator of spike architecture and developmental timing. The GRF9-6Ab allele was associated with increased spike length and, notably, a consistent acceleration of heading date. This identifies GRF9-6A as a novel genetic factor controlling earliness in triticale, a trait of paramount importance for escaping terminal stresses.
The most significant finding of this work is the statistically significant and compensatory interaction between Ddw1 and GRF9-6A (Figure 6). The positive influence of the GRF9-6Ab allele on productivity was predominantly evident in the semi-dwarf genetic background. In Ddw1 carrier plants, the GRF9-6Ab allele significantly increased grain weight per spike by boosting both grain number and TKW, directly counteracting the negative pleiotropic effects of the dwarfing gene. This compensatory effect on yield components is an emerging functional theme for GRF genes in triticale, having been previously reported for TaGRF3-2A and the rye-derived ScGRF3-2R [9,16].
However, our multi-environment trials revealed that this compensation is highly dependent on growing conditions. The effect of GRF9-6Ab was most consistent and pronounced under favorable environments (Moscow, Central Non-Chernozem region), while its efficacy diminished under abiotic stress (Krasnodar 2019). This environmental modulation can be attributed to the complex interplay of several abiotic factors across our trial locations. In Krasnodar 2019, the combination of elevated temperatures during critical developmental windows and potential moisture limitations likely constrained photosynthetic capacity and assimilate partitioning to developing grains [55,56], thereby reducing both TKW and grain number per spike. Additionally, photoperiod differences between locations may have interacted with temperature to influence developmental timing and sink strength [57], presumably further modulating the expression of the GRF9-6Ab compensatory mechanism. The observed environment-specific performance underscores that the efficacy of genetic compensation is contingent upon the broader physiological context imposed by the growing environment.
Furthermore, the interaction had a profound effect on phenology. The GRF9-6Ab allele substantially shortened the time to heading in Ddw1 plants. Given that Ddw1 is known to delay heading and thereby extend the window of susceptibility to Fusarium head blight [8,10], this corrective effect of GRF9-6Ab is critically important for enhancing disease avoidance and overall adaptability. The physiological mechanism may involve the well-documented role of GRF transcription factors in regulating meristematic activity and phase transitions, potentially through interactions with KNOX genes and gibberellin signaling pathways [58,59].
Our findings, when viewed alongside prior studies, reveal a picture of functional diversification within the GRF family in triticale. While TaGRF3-2A acts as a potent regulator of grain size [9], and ScGRF3-2R provides compensation with an additional dwarfing effect [16], GRF9-6A emerges as a specialized “regulator of earliness and spike morphogenesis.” This specialization opens avenues for strategic gene pyramiding.
Another important consideration is the potential influence of vernalization (Vrn) and photoperiod (Ppd) response genes on heading date in our study. While the parental lines differed in growth habit (winter vs. spring), we specifically selected against winter types in the F2 generation [6], establishing a spring-type RIL population. Nevertheless, we cannot completely rule out that residual variation in Vrn or Ppd alleles contributed to the observed variation in days to heading, particularly given the photoperiod differences between locations (Moscow ~17–18 h day length vs. Krasnodar ~15–16 h day length during heading period). However, several lines of evidence suggest that the GRF9-6Ab-mediated acceleration of heading is a genuine effect: first, the compensation was specifically evident in ddw1 carriers across multiple environments; second, the effect showed consistent magnitude in Moscow across years (6.3–6.5 days); and third, GRF transcription factors are known to participate directly in reproductive development and flower organogenesis, as demonstrated by their regulation by key floral identity proteins and their effects on inflorescence architecture in multiple species [59]. While future studies could explicitly characterize Vrn and Ppd alleles in this population, our data strongly indicate that GRF9-6Ab possesses intrinsic capacity to modulate heading date in triticale.
The practical application of these findings is enabled by the development of a co-dominant PCR marker for Ddw1 [45] and, as a key outcome of this study, a robust molecular marker that distinguishes the durum wheat-derived GRF9-6Ab allele from the bread wheat variant. This marker provides an efficient tool for marker-assisted selection, allowing breeders to introgress the “ideal” haplotype (Ddw1 + GRF9-6Ab) into elite germplasm. The recommended breeding strategy is to pyramid this module with other valuable genes, such as TaGRF3-2A for further grain yield enhancement and major Fusarium head blight resistance QTLs to create resilient, high-yielding triticale cultivars tailored for sustainable agriculture for food and forage purposes. Future research should include a broader survey of GRF9-6A haplotypes across diverse triticale germplasm to determine the frequency of the beneficial GRF9-6Ab allele and its historical correlation with Ddw1 deployment in breeding programs.

5. Conclusions

In conclusion, our study provides a multifaceted characterization of the GRF9-6A gene in triticale and identifies the GRF9-6Ab allele as a key genetic modifier capable of compensating for the major pleiotropic deficits associated with the widely used dwarfing gene Ddw1. We demonstrate that the pyramiding of Ddw1 with the GRF9-6Ab allele not only restores grain yield potential by enhancing grain number and weight but also confers a critical advantage by significantly accelerating heading date, thereby mitigating the Ddw1-associated developmental delay and potential disease susceptibility window. Furthermore, our multi-environment trials reveal that the stability of both the Ddw1 and GRF9-6Ab effects is subject to genotype-by-environment interactions, a crucial consideration for breeding programs targeting specific agro-ecological zones. The practical application of these findings is enabled by the robust diagnostic marker developed in this study, which allows for efficient marker-assisted selection of the ideal Ddw1/GRF9-6Ab haplotype. This strategy provides a clear and valuable pathway for developing resilient, high-yielding, and early-maturing triticale cultivars tailored for both food and forage production.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15122701/s1, Table S1. Weather conditions during the growing seasons of 2018 and 2019 at the Moscow and Krasnodar experimental sites; Table S2. Analysis of variance (ANOVA) for the effect of the Ddw1 gene on agronomic traits in spring triticale across locations and years; Table S3. Mean values (±standard deviation) of agronomic traits for Ddw1 and ddw1 homozygous genotypes in different environments; Table S4. Analysis of variance (ANOVA) for the effect of the GRF9-6A gene on agronomic traits in spring triticale across locations and years; Table S5. Mean values (±standard deviation) of agronomic traits for GRF9-6Aa and GRF9-6Ab homozygous genotypes in different environments; Table S6. Two-way analysis of variance (ANOVA) for the individual and interactive effects of the Ddw1 and GRF9-6A genes on agronomic traits; Table S7. Mean values (±standard deviation) of agronomic traits for the four homozygous genotypic classes resulting from the combination of Ddw1 and GRF9-6A alleles in Moscow; Table S8. Mean values (±standard deviation) of agronomic traits for the four homozygous genotypic classes resulting from the combination of Ddw1 and GRF9-6A alleles in Krasnodar.

Author Contributions

Conceptualization, M.G.D.; methodology, T.D.M., Y.S.M., L.A.B., A.G.C., V.Y.K. and A.Y.K.; software, P.Y.K. and M.S.B.; validation, P.Y.K., T.D.M., A.G.C., M.S.B. and A.Y.K.; formal analysis, P.Y.K., M.S.B. and A.Y.K.; investigation, T.D.M., V.V.P., Y.S.M., L.A.B., A.G.C., M.S.B., V.Y.K. and A.Y.K.; resources, L.A.B., V.Y.K., G.I.K. and M.G.D.; data curation, P.Y.K., V.V.P., A.G.C. and M.G.D.; writing—original draft preparation, P.Y.K., T.D.M. and M.S.B.; writing—review and editing, P.Y.K., L.A.B. and M.G.D.; visualization, M.S.B.; supervision, L.A.B., G.I.K. and M.G.D.; project administration, G.I.K. and M.G.D.; funding acquisition, G.I.K. and M.G.D. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Ministry of Science and Higher Education of the Russian Federation (Federal Scientific and Technical Program for the Development of Genetic Technologies for 2019–2030, Agreement No. 075-15-2025-528 by 29 May 2025.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. The scheme of GRF9-6A (TraesCS6A02G269600) gene based on Augustus [24] annotation. Exons are shown as large orange boxes, untranslated regions—as smaller blue boxes, introns as lines. Green arrow at the end shows the 5′->3′ direction of RNA transcript. Positions of primers used for gene cloning are shown as small red arrows. The position of a 12 bp deletion in the promoter that was used for PCR marker development is shown as black vertical bar, and primers developed for its detection are designated as blue arrows.
Figure 1. The scheme of GRF9-6A (TraesCS6A02G269600) gene based on Augustus [24] annotation. Exons are shown as large orange boxes, untranslated regions—as smaller blue boxes, introns as lines. Green arrow at the end shows the 5′->3′ direction of RNA transcript. Positions of primers used for gene cloning are shown as small red arrows. The position of a 12 bp deletion in the promoter that was used for PCR marker development is shown as black vertical bar, and primers developed for its detection are designated as blue arrows.
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Figure 2. Alignment of (a) nucleotide sequence at the binding site of miR396 (highlighted blue) in the GRF9-6A gene sequences of triticale ‘Dublet’ compared to bread wheat ‘Chinese Spring’ and (b) deduced GRF9 protein sequence in triticale ‘Dublet’ against ‘Chinese Spring’ bread wheat reference; conserved domains highlighted with colors: QLQ—green, WRC—yellow. The numbers on top and the right side indicate positions in the alignment, while asterisks (*) represent each 10th position.
Figure 2. Alignment of (a) nucleotide sequence at the binding site of miR396 (highlighted blue) in the GRF9-6A gene sequences of triticale ‘Dublet’ compared to bread wheat ‘Chinese Spring’ and (b) deduced GRF9 protein sequence in triticale ‘Dublet’ against ‘Chinese Spring’ bread wheat reference; conserved domains highlighted with colors: QLQ—green, WRC—yellow. The numbers on top and the right side indicate positions in the alignment, while asterisks (*) represent each 10th position.
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Figure 3. Alignment of GRF9-6A promoter fragments with cis-regulatory elements specific to the ‘Dublet’ allele (GRF9-6Ab), shown above the alignment, and specific to ‘Chinese Spring’ (CS) allele (GRF9-6Aa), shown below. The cis-regulatory elements are highlighted in random colors. Triticale ‘Dublet’, compared to wheat ‘Chinese Spring’, lost a single CTCC element, while gained four new detected elements (TGA-box, as-1, CGTCA-motif and TGACG-motif). No more differences in cis-elements were detected between alleles. The shown fragment is about 800 bp from the transcription start site. The names of motifs and strand of detection (+ or −) are indicated. The cis-regulatory elements were detected by PlantCARE.
Figure 3. Alignment of GRF9-6A promoter fragments with cis-regulatory elements specific to the ‘Dublet’ allele (GRF9-6Ab), shown above the alignment, and specific to ‘Chinese Spring’ (CS) allele (GRF9-6Aa), shown below. The cis-regulatory elements are highlighted in random colors. Triticale ‘Dublet’, compared to wheat ‘Chinese Spring’, lost a single CTCC element, while gained four new detected elements (TGA-box, as-1, CGTCA-motif and TGACG-motif). No more differences in cis-elements were detected between alleles. The shown fragment is about 800 bp from the transcription start site. The names of motifs and strand of detection (+ or −) are indicated. The cis-regulatory elements were detected by PlantCARE.
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Figure 4. Evolutionary analysis of GRF9-6A gene sequences conducted by Maximum Likelihood method. Sequences from wild emmer ‘Zavitan’ (Triticum dicoccoides), bread wheat ‘Chinese Spring’ (T. aestivum), durum wheat cultivar Cappelli (T. durum), hexaploid triticale ‘Dublet’ (× Triticosecale neoblaringhemii), Urartian wheat (T. urartu) and einkorn wheat (T. monococcum) were used for analysis. The most similar gene of rye Lo7 (Secale cereale) was used as outgroup. The percentage of trees in which the associated taxa clustered together is shown above the branches.
Figure 4. Evolutionary analysis of GRF9-6A gene sequences conducted by Maximum Likelihood method. Sequences from wild emmer ‘Zavitan’ (Triticum dicoccoides), bread wheat ‘Chinese Spring’ (T. aestivum), durum wheat cultivar Cappelli (T. durum), hexaploid triticale ‘Dublet’ (× Triticosecale neoblaringhemii), Urartian wheat (T. urartu) and einkorn wheat (T. monococcum) were used for analysis. The most similar gene of rye Lo7 (Secale cereale) was used as outgroup. The percentage of trees in which the associated taxa clustered together is shown above the branches.
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Figure 5. The compensatory effect of GRF9-6Ab on grain weight in a Ddw1 background is modulated by environment in triticale. Data from recombinant inbred lines (RILs) grown in Moscow and Krasnodar (2018, 2019) are shown. Alleles are denoted as follows: Ddw1/ddw1; GRF9-6Aa/GRF9-6Ab (a/b). Different letters above bars indicate statistically significant differences between means (p < 0.05).
Figure 5. The compensatory effect of GRF9-6Ab on grain weight in a Ddw1 background is modulated by environment in triticale. Data from recombinant inbred lines (RILs) grown in Moscow and Krasnodar (2018, 2019) are shown. Alleles are denoted as follows: Ddw1/ddw1; GRF9-6Aa/GRF9-6Ab (a/b). Different letters above bars indicate statistically significant differences between means (p < 0.05).
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Figure 6. A schematic model summarizing the pleiotropic effects of the Ddw1 dwarfing gene and the compensatory role of the GRF9-6Ab allele in triticale. The model illustrates how Ddw1 reduces plant height and improves lodging resistance but imposes yield penalties and delays heading. The GRF9-6Ab allele, when combined with Ddw1, mitigates these negative effects by increasing grain number and weight and accelerating development, with its efficacy being greater under favorable conditions. This visual synthesis highlights the potential of pyramiding these genes as a targeted breeding strategy.
Figure 6. A schematic model summarizing the pleiotropic effects of the Ddw1 dwarfing gene and the compensatory role of the GRF9-6Ab allele in triticale. The model illustrates how Ddw1 reduces plant height and improves lodging resistance but imposes yield penalties and delays heading. The GRF9-6Ab allele, when combined with Ddw1, mitigates these negative effects by increasing grain number and weight and accelerating development, with its efficacy being greater under favorable conditions. This visual synthesis highlights the potential of pyramiding these genes as a targeted breeding strategy.
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Table 1. Primers developed for amplification of GRF9-6A gene by fragments for sequencing, and primers for the marker of 12 bp deletion in promoter.
Table 1. Primers developed for amplification of GRF9-6A gene by fragments for sequencing, and primers for the marker of 12 bp deletion in promoter.
PairNameSequence, 5′-3′Tm 1Amplicon Size, bp
1GRF9-6A-F1CCTAAGGATGCCAATCCTACGAA60953
GRF9-6A-R1GAAGCGTCTTTAATGGGGTTCC60
2GRF9-6A-F2ATCTACTCCTCCTCGCTACTACC60924
GRF9-6A-R2ATCCCGGATTAACAAAAGACCGA60
3GRF9-6A-F3TCCTTCATCATCACCGCAAATCT601110
GRF9-6A-R3AGCACTGTGCATAGAGGAACAAAT61
4GRF9-12del-FCCGAGACATCGCTTTCATATTTGG60203/191
GRF9-12del-RACTATGTGCTTGCTTCTTGTGTC60
1 Tm—is a calculated melting temperature of primers according to SantaLucia method [23].
Table 2. Mutations in protein-coding sequence of GRF9-6A gene in triticale ‘Dublet’ relative to reference bread wheat genome (‘Chinese Spring’, RefSeq1.0).
Table 2. Mutations in protein-coding sequence of GRF9-6A gene in triticale ‘Dublet’ relative to reference bread wheat genome (‘Chinese Spring’, RefSeq1.0).
MutationAmino-Acid SubstitutionSIFT Prediction
ActionScoreConfidence
c.143C>Gp.(Pro48Arg)Tolerated0.73Normal
c.562G>Ap.(Gly188Ser)Tolerated0.20Normal
c.583G>Ap.(Val195Ile)Tolerated1.00Normal
c.716G>Ap.(Gly239Asp)Affect function0.01Low
Table 3. Mutations in non-coding regions of GRF9-6A gene in triticale ‘Dublet’ relative to reference bread wheat genome (‘Chinese Spring’, RefSeq1.0).
Table 3. Mutations in non-coding regions of GRF9-6A gene in triticale ‘Dublet’ relative to reference bread wheat genome (‘Chinese Spring’, RefSeq1.0).
Mutations in Non-Coding Regions Region
chr6A:g.496018063_496018064delinsTTpromoter
chr6A:g.496018059C>Tpromoter
chr6A:g.496018053A>Gpromoter
chr6A:g.496018042C>Tpromoter
chr6A:g.496018023C>Tpromoter
chr6A:g.496017978A>Cpromoter
chr6A:g.496017943C>Tpromoter
chr6A:g.496017831_496017842delpromoter
chr6A:g.496017813T>Gpromoter
chr6A:g.496017811G>Apromoter
chr6A:g.496017788G>Apromoter
chr6A:g.496017595T>Cpromoter
chr6A:g.496017420G>Apromoter
chr6A:g.496017265G>Cpromoter
chr6A:g.496015567A>G5′-UTR
Table 4. Number of homozygous plants of recombinant inbred lines (RILs) for each genotypic class across different environments.
Table 4. Number of homozygous plants of recombinant inbred lines (RILs) for each genotypic class across different environments.
Ddw1 GenotypeGRF9-6A GenotypeValid N
MoscowKrasnodar
2018201920182019
ddw1 a 306308255302
ddw1 b 183203152153
Ddw1 a 671147657
Ddw1 b 8016074138
Table 5. Mean values (±standard deviation) of agronomic traits for Ddw1 and ddw1 homozygous genotypes in different environments.
Table 5. Mean values (±standard deviation) of agronomic traits for Ddw1 and ddw1 homozygous genotypes in different environments.
TraitMoscow 2018Moscow 2019Krasnodar 2018Krasnodar 2019
Ddw1ddw1Ddw1 vs. ddw1 (%)Ddw1ddw1Ddw1 vs. ddw1 (%)Ddw1ddw1Ddw1 vs. ddw1 (%)Ddw1ddw1Ddw1 vs. ddw1 (%)
Plant height, cm54.7 e ± 7.880.8 c ± 12.3−26.1 (−32.3)57.1 e ± 8.484.6 b ± 13.3−27.5 (−32.5)64.7 d ± 8.594.8 a ± 13.9−30.1 (−31.8)95.9 a ± 19.994.2 a ± 20.3+1.7 (+1.8)
Grain weight per
main spike, g		1.61 d ± 0.641.92 c ± 0.76−0.31 (−16.1)2.20 b ± 0.772.53 a ± 0.92−0.33 (−13.0)1.95 c ± 0.592.30 b ± 0.66−0.35 (−15.2)1.92 c ± 0.661.97 c ± 0.63−0.05 (−2.5)
Grain number
per main spike		45.6 d ± 12.546.6 d ± 14.1−1.0 (−2.1)48.0 cd ± 13.048.3 c ± 14.4−0.3 (−0.6)57.1 b ± 12.657.1 b ± 13.10.0 (0.0)60.4 a ± 13.961.4 a ± 12.4−1.0 (−1.6)
1000-kernel weight, g34.3 d ± 7.140.3 c ± 8.3−6.0 (−14.9)45.7 b ± 7.551.8 a ± 8.7−6.1 (−11.8)33.8 d ± 5.540.1 c ± 6.3−6.3 (−15.7)31.4 e ± 6.431.6 e ± 6.0−0.2 (−0.6)
Note: The relative effect of the Ddw1 allele (Ddw1 vs. ddw1 (%)) was calculated as ((Ddw1 − ddw1)/ddw1) × 100. Different lowercase letters within a row for a specific trait indicate statistically significant differences between means (p < 0.05, Fisher’s LSD test).
Table 6. Mean values (±standard deviation) of agronomic traits for the four homozygous genotypic classes resulting from the combination of Ddw1 and GRF9-6A alleles in Moscow.
Table 6. Mean values (±standard deviation) of agronomic traits for the four homozygous genotypic classes resulting from the combination of Ddw1 and GRF9-6A alleles in Moscow.
TraitMoscow 2018Moscow 2019
Ddw1ddw1Ddw1ddw1
GRF9-6AaGRF9-6Abb vs. a (%)GRF9-6AaGRF9-6Abb vs. a (%)GRF9-6AaGRF9-6Abb vs. a (%)GRF9-6AaGRF9-6Abb vs. a (%)
Grain weight per
main spike, g		1.46 i ± 0.601.74 h ± 0.64+0.28 (+19.2)1.98 fe ± 0.741.81 hg ± 0.79−0.17 (−8.6)2.01 fe ± 0.722.35 cb ± 0.78+0.34 (+16.9)2.56 a ± 0.882.47 ba ± 0.97−0.09 (−3.5)
1000-kernel
weight, g		32.3 jih ± 6.636.0 g ± 7.1+3.7 (+11.5)40.5 fe ± 7.739.9 fe ± 9.2−0.6 (−1.5)44.0 d ± 7.246.9 c ± 7.5+2.9 (+6.6)51.2 b ± 7.652.7 a ± 10.1+1.5 (+2.9)
Heading time
(days after sowing)		62.9 a ± 7.356.6 cb ± 2.4−6.3 (−10.0)54.7 d ± 4.254.8 d ± 1.6+0.1 (+0.2)63.8 a ± 6.357.3 b ± 3.5−6.5 (−10.2)56.3 c ± 4.056.2 c ± 3.1−0.1 (−0.2)
Note: The relative effect of the GRF9-6Ab allele within each Ddw1 background (b vs. a (%)) was calculated as ((GRF9-6Ab − GRF9-6Aa)/GRF9-6Aa) × 100. Different lowercase letters within a row for a specific trait indicate statistically significant differences between all genotypic classes within that environment and year (p < 0.05, Fisher’s LSD test).
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Kroupin, P.Y.; Mokhov, T.D.; Panchenko, V.V.; Meglitskaya, Y.S.; Bespalova, L.A.; Chernook, A.G.; Bazhenov, M.S.; Kovtunenko, V.Y.; Kroupina, A.Y.; Karlov, G.I.; et al. The GRF9-6Ab Allele Compensates for the Pleiotropic Deficits of the Ddw1 Dwarfing Gene in Triticale. Agronomy 2025, 15, 2701. https://doi.org/10.3390/agronomy15122701

AMA Style

Kroupin PY, Mokhov TD, Panchenko VV, Meglitskaya YS, Bespalova LA, Chernook AG, Bazhenov MS, Kovtunenko VY, Kroupina AY, Karlov GI, et al. The GRF9-6Ab Allele Compensates for the Pleiotropic Deficits of the Ddw1 Dwarfing Gene in Triticale. Agronomy. 2025; 15(12):2701. https://doi.org/10.3390/agronomy15122701

Chicago/Turabian Style

Kroupin, Pavel Yu., Timofey D. Mokhov, Vladimir V. Panchenko, Yana S. Meglitskaya, Ludmila A. Bespalova, Anastasiya G. Chernook, Mikhail S. Bazhenov, Victor Ya. Kovtunenko, Aleksandra Yu. Kroupina, Gennady I. Karlov, and et al. 2025. "The GRF9-6Ab Allele Compensates for the Pleiotropic Deficits of the Ddw1 Dwarfing Gene in Triticale" Agronomy 15, no. 12: 2701. https://doi.org/10.3390/agronomy15122701

APA Style

Kroupin, P. Y., Mokhov, T. D., Panchenko, V. V., Meglitskaya, Y. S., Bespalova, L. A., Chernook, A. G., Bazhenov, M. S., Kovtunenko, V. Y., Kroupina, A. Y., Karlov, G. I., & Divashuk, M. G. (2025). The GRF9-6Ab Allele Compensates for the Pleiotropic Deficits of the Ddw1 Dwarfing Gene in Triticale. Agronomy, 15(12), 2701. https://doi.org/10.3390/agronomy15122701

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