Identification of a novel dwarfing gene, Rht_m097, on chromosome 4BS in common wheat

Abstract

Plant height is a crucial agronomic trait in wheat, regulated by multiple genes, and significantly influences plant architecture and wheat yield. In this study, a novel dwarf mutant, designated as m097, was developed and characterized through the treatment of seeds from the common wheat cultivar Jinmai47 with ethyl methanesulfonate (EMS). Microscopic analysis revealed that the dwarf phenotype was attributed to a reduction in the longitudinal cell size of the stem. Similar to the wild type, m097 exhibited sensitivity to exogenous gibberellic acid (GA). Genetic analysis indicated that the reduced plant height in m097 was regulated by a semi-dominant dwarfing gene, Rht_m097. Through bulk segregant analysis (BSA) utilizing the wheat 660K SNP array, Rht_m097 was mapped and confined to a region of approximately 2.58 Mb on chromosome arm 4BS, encompassing 16 high-confidence annotated genes. In addition, transcriptome sequencing (RNA-seq) was conducted on the first internode below the panicle of JM47 and m097 at the jointing stage, leading to the identification of two potential candidate genes exhibiting differential expression. Furthermore, the analysis of gene ontology and metabolic pathways from RNA-seq data indicated that the down-regulated differentially expressed genes (DEGs) in m097 were biologically classified as regulating actin cortical patch organization and assembly. Concurrently, it was observed that the up-regulated DEGs were significantly enriched in various phytohormone metabolic pathways, including those involved in indole-3-acetic acid (IAA) biosynthesis, jasmonic acid biosynthesis, and gibberellin signaling. Overall, this study provides a novel genetic resource for the breeding of dwarf wheat and establishes a foundation for subsequent gene cloning.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-025-01558-0.

Introduction

Common wheat (Triticum aestivum L.) is a pivotal cereal crop essential for global food security. Given the increasing global population and the challenges posed by climate change, there is an urgent need to enhance wheat yield potential to ensure adequate grain production (Jaggard et al. 2010; Naithani et al. 2019). Plant height (PH) is a critical agronomic trait that influences not only plant architecture but also wheat yield and stability (Hedden 2003; Song et al. 2023; Wang and Li 2008). Therefore, the identification of novel genetic factors that regulate plant height is crucial for enhancing our understanding of the developmental process governing plant height and for breeding high-yielding wheat through the molecular design of wheat ideotypes.

During the 1960s and 1970s, the introduction of two dwarfing genes, Rht-B1b (Rht1) and Rht-D1b (Rht2), into wheat breeding programs significantly enhanced lodging resistance and harvest index, leading to a substantial increase in grain yield—a phenomenon famously known as the ‘Green Revolution’ (Hedden 2003; Peng et al. 1999). However, plant height is a complex quantitative trait that is controlled by a large number of genes and influenced by environmental factors. To date, 27 reduced height (Rht) dwarfing genes (Rht1-Rht27) have been cataloged globally in wheat (Boden et al. 2023; Liu et al. 2024; Xu et al. 2023b). Additionally, numerous quantitative trait loci (QTL) and candidate genes have also been identified through linkage analysis and genome-wide association studies (GWAS) over the past two decades (Aleliunas et al. 2024; Guan et al. 2018; Li et al. 2023a; Marza et al. 2006; Singh et al. 2022; Wu et al. 2010; Xu et al. 2023b).

Based on their response to exogenous gibberellic acid (GA), the Rht genes in wheat are typically categorized into two groups, GA-insensitive and GA-responsive (Amram et al. 2015; Peng et al. 1999; Uppal and Gooding 2013). Rht1 and Rht2 alleles, which are homologous and located on chromosome arms 4BS and 4DS respectively, encode DELLA proteins that confer a GA-insensitive semi-dwarf phenotype (Liu et al. 2021; Peng et al. 1999). Conversely, Rht4 ~ Rht9, Rht11 ~ Rht16, Rht18 ~ Rht25, and Rht27 found on chromosome 3 of Triticum Urartu wheat, exhibit GA sensitivity (Borrill et al. 2022; Cui et al. 2022; Liu et al. 2024; Xu et al. 2023b). Notably, three loci, namely Rht14, Rht18, and Rht24, are all located on chromosome 6A within overlapping regions potentially associated with the same gene, GA2-oxidaseA9, which encodes the GA-inactivating enzyme GA2-oxidase (Duan et al. 2022; Ford et al. 2018; Tian et al. 2022). Recently, the Rht8 gene, which encodes an 808-amino acid protein with a predicted Ribonuclease H-like domain that modulates plant height by influencing bioactive GA content, was successfully cloned using a map-based approach (Chai et al. 2022; Xiong et al. 2022). Furthermore, the Rht23 gene has been confirmed to be allelic to the Q homologue, 5Dq', with increased expression level resulting from a point mutation in the miR172 binding site of Rht23, which reduces miRNA-dependent degradation (Chen et al. 2014; Zhao et al. 2018). In addition, the Tasg-D1 gene, which acts as a negative regulator of brassinosteroid signaling, was isolated through positional cloning in the semi-dwarf T. sphaerococcum (Cheng et al. 2020). Subsequent research has demonstrated that GSK3 interacts with and phosphorylates the Rht-B1b protein, thereby facilitating a reduction in plant height (Dong et al. 2023). Despite the identification of numerous dwarfing genes/loci, only a limited number, specifically Rht1, Rht2, Rht8 and Rht24, have been extensively utilized in wheat breeding programs (Tian et al. 2019; Wurschum et al. 2017; Xu et al. 2023b). Consequently, the discovery and application of additional novel dwarfing genes are crucial for advancing our understanding of the molecular mechanisms of underlying dwarfism and for high-yield molecular design breeding of wheat.

Jinmai47 (JM47) serves as an elite parental material for wheat breeding in the arid and infertile areas of China, functioning as the check variety characterized by light green leaves, high water and fertilizer use efficiency, robust stress resistance, and stable yield performance (Li et al. 2024; Yang et al. 2022). In this study, a dwarf mutant, designated as m097, was generated through ethyl methanesulfonate (EMS) mutagenesis against the JM47 background. We conducted a comprehensive field evaluation of the wildtype JM47 and the mutant m097 to elucidate the phenotypic effects of the dwarf gene on key agronomic traits. Moreover, genetic analysis and mapping of the dwarf gene were carried out using bulked segregant analysis (BSA) with the wheat 660K SNP array. In addition, mRNA sequencing was performed on the developing stems of JM47 and m097 to identify the putative underlying gene and the associated molecular regulatory network.

Materials and methods

Plant materials, segregation populations and phenotypic evaluation

The dwarf mutant m097 was derived from the common wheat cultivar JM47, following treatment with 0.6% ethyl mesylate according to the protocol described in the previous report (Zhang et al. 2021). For genetic analysis, the m097 mutant was crossed with the wildtype JM47 and the common wheat variety Zhengmai 1860 (ZM1860) to generate F₂ populations and the corresponding F_2:3 families. JM47 and m097 were planted in double-row plots, with 20 plants in a row of 2 m with three repeats, and phenotyped at the Xingyang and Xuchang experimental stations in Henan province, China, during 2020–2021 and 2021–2022 growing seasons. The F₂ and F_2:3 lines were sown at the Xingyang field during the 2021–2022 and 2022–2023 growing seasons. Irrigation and other management practices adhered to local agricultural standards.

Plant height was measured as the distance from the ground to the tip of the tallest culm without awn. The PH of each line was determined for the two F₂ populations (JM47/m097 and ZM1860/m097). For wildtype JM47 and mutant m097, the main agronomic traits, including internode length (1st, 2nd, 3rd, 4th and 5th internode length below the peduncle), spike length (SL), total spikelet number per spike (TSN), fertile spikelet number per spike (FSN), sterile spikelet number per spike (SSN), seeds per spikelet (SPS), spikelet density (SD), and grain number per spike (GNS), were determined as the mean values of ten representative plants per replicate. Moreover, thousand grain weight (TGW), grain surface area (GA), grain circumference (GC), grain length (GL), grain width (GW) were measured using the rapid SC-G grain appearance quality image analysis system (www.wseen.com) according to the previous study (Guan et al. 2020).

Microscopy analysis

Stem tissues, specifically 1 cm above the first internode (from top to bottom), were collected from JM47 and m097 during the early stage of grain filling to analyze intercellular characteristics. These tissues were subsequently fixed in FAA solution, embedded in paraffin, and subjected to dehydration and decolorization following the protocols described by previous methods (Song et al. 2023). The paraffin-embedded samples were sectioned into 6-mm slices using a Leica Ultracut rotary microtome (Leica Biosystems). Staining was performed with Safranin O/Fast Green (Wuhan Servicebio Technology Co., Ltd., China). A BX60 light microscope (Olympus) was employed to capture images of the sections, and the cell lengths were quantified using CaseViewer version 2.3.0 (3DHistech).

Bulked segregation analysis (BSA)

The BSA strategy was used to map the dwarf gene in this study. To construct extreme bulked DNA pools, 20 extremely tall and 20 extremely dwarf plants were selected from the ZM1860/m097 F₂ segregating population based on F_2:3 phenotype validation. The cetyltrimethylammonium bromide (CTAB) method was used to extract genomic DNA from seedling leaves of each plant, as previously described by (Guan et al. 2018). The two DNA pools were then genotyped using the wheat 660K SNP array at Beijing Compass Biotechnology Co., Ltd. China. Additionally, genotyping of JM47, ZM1860 and m097 was also conducted using the wheat 55K SNP array by China Gold Marker (Beijing) Biotechnology Co., Ltd.

InDel marker development

Based on the resequencing data from JM47 and ZM1860, insertion-deletion (InDel) sequence information within the mapping interval was obtained through the SnpHub platform (Guo et al. 2020; Wang et al. 2020). The flanking sequences of these InDel sites were subsequently retrieved from the RefSeq v1.1 version of the Chinese Spring hexaploid wheat reference genome via the WheatOmics platform (Ma et al. 2021). Using the obtained wheat genome sequences, specific InDel markers were developed with the PrimerServer (BETA): PCR Primers Batch Design & Specificity Check tool, accessible on the WheatOmics1.0 website (http://202.194.139.32/). The parameters for primer design were as follows: primer length between 18–22 bp, uniform distribution of bases at the 3' end to prevent secondary structure formation, GC content ranging from 40–60%, and a melting temperature (Tm) between 55 °C and 60 °C. PCR was conducted and PCR products were separated using 8% non-denaturing polyacrylamide gel electrophoresis (PAGE) as previously described (Guan et al. 2020).

GA sensitivity assays

At the seedling stage, the responses of wildtype JM47 and mutant m097 to GA were evaluated. Firstly, healthy seeds from both JM47 and m097 were selected and immersed in 1% H₂O₂ for 12 h to overcome dormancy. The seeds were then placed in petri dishes with a light incubator set to a photoperiod of 16 h of light and 8 h of darkness at a temperature of 22 °C. Subsequently, 10 mmol/L GA₃ was added to the experimental group, while an equivalent volume of ddH₂O was provided to the control group. After 7 days of culture, at least 10 plants were taken from three replicates to measure seedling and coleoptile lengths.

RNA extraction and transcriptome analysis

Total RNA was extracted from the first internode stems (from top to bottom) of JM47 and m097 at the jointing stage with three biological replicates using the RNAprep Pure Plant Kit (Tiangen, Beijing, China) in accordance with the manufacturer's protocol. DNA contamination was eliminated using DNase I (Takara) and RNA purification was conducted with an RNA purification kit (Tiangen Biotech, Beijing, Co., Ltd.). The concentration and purity of RNA were quantified using the NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA). RNA integrity was evaluated with the RNA Nano 6000 Assay Kit on the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Subsequently, RNA samples meeting quality criteria were subjected to library construction. Library construction and transcriptome sequencing were performed using the Illumina HiSeq 4000 platform in paired-end 150 bp (PE150) mode.

After removing adapter, ploy-N sequences, and low-quality reads from the raw data using Fastp (v0.12.4), the clean reads were aligned to the wheat reference genome (IWGSC RefSeq v2.1). Differentially expressed genes (DEGs) were identified using the DESeq2 tool (version 1.34.0) with a false discovery rate (FDR) < 0.05 and |log₂(fold-change)|> 1. Gene Ontology (GO) annotation and enrichment analysis of DEGs were conducted using the Triticeae-GeneTribe (http://wheat.cau.edu.cn/TGT/) database (Chen et al. 2020). Metabolic pathways analyses, including PlantCyc, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Plant Reactome, were conducted using the WheatCENet platform (Li et al. 2023b; Naithani et al. 2019). The raw sequencing data have been deposited at the National Center for Biotechnology Information (NCBI) under accession number PRJNA1201746.

Statistical analysis

Phenotypic data of JM47 and m097 were statistically analyzed by Student’s t test using SPSS version 22.0 software (SPSS Inc., Chicago, USA). The Chi-square (χ²) test and the Shapiro–Wilk test to assess the normality were performed on PH of F₂ and F_2:3 populations using R.

Results

Phenotypic characterization of the dwarf mutant m097

An EMS mutant library was previously generated on the genetic background of the common wheat variety JM47. Compared with wildtype JM47, mutant m097 exhibited a dwarf phenotype across two different field environments, with plant height approximately half that of the wild type (Fig. 1A and B, Table S1). Genotyping results from the wheat 55K SNP array indicated a genetic background similarity of 99.08% between m097 and JM47. Notably, the length of each internode below the peduncle in m097 was significantly shorter than that of the wildtype, although the number of internodes remained comparable. Furthermore, the length of parenchyma cells in the stem of JM47 was significantly greater than that in m097, consistent with the observed differences in internode length (Fig. 1C and D). For other agronomic traits, compared with JM47, grain number per spike, grain weight and grain shape related traits (ie. GL, GW, GA and GC) were significantly decreased in m097 (Table S1). Although the total spikelet number of m097 decreased, the spike density increased significantly due to the markedly shortened spike length (Fig. 1B, Table S1). In addition, the flag leaf length of m097 exceeded that of that of JM47, whereas the flag leaf width was reduced compared to the wild type, resulting in an unchanged flag leaf area (Table S1). Overall, the mutant m097 exhibited pleiotropic effects on a range of agronomic traits, including plant height, spike length, grain weight, and grain size, among others.

Fig. 1.

Phenotypic comparison between wildtype Jinmai47 (JM47) and dwarf mutant m097. A Phenotypes of JM47 and m097 in the field. Bar = 5 cm. B Comparison of spike length and five internodes (1IL, 2IL, 3IL, 4IL and 5IL) length between JM47 and m097. Values are mean ± standard deviation (SD). C Observation of stem cell paraffin sections. Bar = 100 μm. D Stem cell length and width (average value of twenty cells) comparison of WT and m097. ** P < 0.01

GA sensitivity analysis of the dwarf mutant m097

To evaluate the sensitivity of mutant m097 to GA, both wildtype JM47 and mutant m097 were treated with exogenous GA₃ during the seedling stage. One week after the treatment, we measured the coleoptile length and seedling height of both JM47 and m097 (Fig. 2A). Compared to the control, both JM47 and m097 showed a significant increase in coleoptile length and seedling height following GA₃ treatment. Notably, the coleoptile length and seedling height of mutant m097 were restored to levels comparable to those observed in the wild type under normal conditions after GA₃ application. In particular, the seedling height of JM47 and m097 increased by 27.64% and 51.70%, while the coleoptile length increased by 11.56% and 27.34%, respectively (Fig. 2B and C). Therefore, both JM47 and m097 showed sensitivity to exogenous GA₃ at the seedling stage.

Fig. 2.

GA sensitivity analysis between the wildtype Jinmai47 (JM47) and the dwarf mutant m097. A Phenotypes of JM47 and m097 after 7 days of exogenous GA₃ treatment. Bar = 2 cm. B Comparison of seeding length between JM47 and m097. C Comparison of coleoptile length between JM47 and m097. Values are mean ± standard deviation (SD). Asterisks indicate statistically significant differences by t-test. * P < 0.05; ** P < 0.01; ns, not significant

Genetic analysis of the dwarf gene in m097

To investigate the genetic basis underlying the dwarf phenotype of m097, two F₂ segregating population were developed by crossing m097 with wildtype JM47 and another genetic background, ZM1860. In the F₂ (JM47/m097) population, which displayed a bimodal distribution, 106 plants exhibited dwarf and semi-dwarf phenotypes, while 44 plants showed normal height, consistent with an expected segregation ratio of 3:1 (χ² = 1.28 < χ² _0.05(1) = 3.84) (Fig. 3A). Similarly, the F₂ (ZM1860/m097) population, consisting of 103 randomly selected individual plants, also showed an abnormal distribution. The F_2:3 population revealed 25, 51, and 27 genotypes corresponding to tall, intermediate, and dwarf phenotypes, respectively, aligning with a segregation ratio of 1:2:1 (χ² = 0.087 < χ² _0.05(2) = 5.99) (Fig. 3B). Therefore, these findings suggest that the m097 mutant phenotype is likely attributable to a mutation in a single semidominant gene, designated as Rht_m097.

Fig. 3.

Plant height in two F₂ populations. A Frequency distribution histogram of plant height of Jinmai47/m097 F₂ population. B Frequency distribution histogram of plant height of ZM1860/m097 F₂ population

Dwarf gene mapping using 660K SNP array-based BSA

Based on the BSA method, extremely tall and dwarf plants were selected from the ZM1860/m097 F₂ population to construct DNA mixing pools for genotyping with the wheat 660K SNP array. A total of 870 homozygous polymorphic SNPs were identified between the two mixed pools, which were distributed across all 21 chromosomes. Notably, 330 of these SNPs were located on chromosome 4B, accounting for 38.37% (Fig. 4A). After filtering these differential SNPs based on the parental genotypes of ZM1860 and m097, it was observed that chromosome 4B exhibited the highest enrichment of SNPs, suggesting that the Rht_m097 gene was likely located on chromosome 4B (Fig. 4B). Further analysis of the SNP distribution on chromosome 4B revealed a peak physical region between 141.42 Mb and 164.98 Mb according to the reference genome of Chinese Spring (IWGSC RefSeq v1.0) (Fig. 4C). Taken together, the Rht_m097 gene was mapped on the short arm of chromosome 4B.

Fig. 4.

Mapping of the dwarf gene in m097 using BSA based on the wheat 660K SNP array. A Distribution of homozygous polymorphic SNPs across 21 chromosomes between the two DNA pools of extremely tall and dwarf plants. B Chromosomal distribution of homozygous polymorphic SNPs after filtering differential SNPs based on genotypes between parents ZM1860 and m097. C The location distribution of SNPs on chromosome 4B. D Fine mapping of the dwarf gene in m097 using the key recombinants

Validation of fine mapping by development of molecular markers

To further delimit the mapping region of the Rht_m097 gene, eight polymorphic InDel molecular makers were developed, and subsequently genotyped in the F₂ (ZM1860/m097) population. Fortunately, three categories of recombinants (R1-R3, R4-R5 and R6) were identified. By integrating the genotypic data of these recombinants with the phenotypic information from the F₂ population and the F_2:3 families, we defined the Rht_m097 gene to a physical interval of approximately 2.6 Mb flanked by the markers 4B-InDel-3 and 4B-InDel-4, corresponding to the Chinese Spring reference genome (IWGSC RefSeq v1.0) region of 143.8–146.5 Mb (Fig. 4D) with 16 high-confidence annotated genes (Table S2). Additionally, these 16 genes were expressed in stem tissue during at least one of three different developmental periods (Table S3), as indicated by the Chinese Spring expression database (International Wheat Genome Sequencing 2014).

Candidate gene identification and micro-collinearity analysis

To predict putative candidate genes, the “QTG miner” tool in the wGRN platform (http://wheat.cau.edu.cn/wGRN/) was used to refine the search scope (Chen et al. 2023). For prioritizing high-confidence candidates, the top three genes identified were TraesCS4B03G0282400, encoding the ethylene-responsive transcription factor CRF4; TraesCS4B03G0284000, encoding the cytochrome P450 714C3 protein; and TraesCS4B03G0283400, encoding the coiled-coil domain-containing protein SCD2 (Fig. 5A, Table S4). In addition, micro-collinearity analysis of the fine-mapped region showed that there is a good correspondence between B and D subgenomes, but an inversion with the A subgenome (Fig. 5B). Notably, the number of annotated genes was comparable across all three subgenomes.

Fig. 5.

Candidate gene prediction and micro-collinearity analysis. A Prediction of the candidate genes by means of the “QTG miner” tool in the wGRN platform (http://wheat.cau.edu.cn/wGRN/). B Micro-collinearity analysis of fine-mapped region across A, B, D subgenomes

Transcriptome sequencing (RNA-seq) was conducted on the first internode below the panicle of wildtype JM47 and m097 at the jointing stage to identify potential candidate genes (Table S5). Comparing the genome-wide gene expression profiles of JM47 and m097, a total of 3310 differentially expressed genes (DEGs) were identified across all 21 chromosomes. Of these, 1937 DEGs were found to be up-regulated in m097 relative to JM47, while 1373 DEGs were down-regulated (Fig. 6A). Moreover, the fold changes in gene expression determined by qRT-PCR were consistent with the changes in normalized expression levels (FPKM) obtained from RNA-Seq analysis (Fig. S1, Table S8). The number of DEGs was highest in wheat homologous group 3 and lowest in wheat homologous group 6 (Fig. 6B). Notably, 75 DEGs were identified on chromosome 4BS, with only 2 DEGs (TraesCS4B03G0282800 and TraesCS4B03G0283800) located in the fine-mapping interval (Fig. 6C, Fig. S1), suggesting that they were the most promising candidates for further investigation.

Fig. 6.

Identification of differentially expressed genes (DEGs). A The number of up- and down-regulated DEGs in m097 compared to wildtype Jinmai47 (JM47). B The chromosomal distributions of DEGs. C Expression of high-confidence annotated genes in the fine-mapped region. Two candidate genes in bold are differentially expressed

Functional categorization of differentially expressed genes

For functional annotation of DEGs, gene ontology and metabolic pathways were performed to investigate the molecular regulatory mechanism of the dwarf gene. GO analysis revealed that up-regulated DEGs in m097 were significantly enriched in several biological process terms, including lipid transport (GO:0006869), salicylic acid mediated signaling pathway (GO:0009862), response to jasmonic acid (GO:0009753), etc. (Fig. 7A, Table S6). Meanwhile, GO analysis indicated that down-regulated DEGs were significantly enriched in glycolytic process (GO:0006096), tricarboxylic acid cycle (GO:0006099), protein localization involved in auxin polar transport (GO:1901703), etc. (Fig. 7B, Table S6). For metabolic and regulatory pathways, enrichment analysis was performed using three different databases: PlantCyc, KEGG, and Plant Reactome (Fig. 7C and D, Table S7). The KEGG pathway results indicated that up-regulated DEGs were significantly enriched in glyoxylate and dicarboxylate metabolism (tae00630), carbon fixation in photosynthetic organisms (tae00710), and phenylpropanoid biosynthesis (taes00940), while down-regulated DEGs were significantly enriched in the citrate cycle (TCA cycle) (tae00020), glycolysis/gluconeogenesis (tae00010), and protein processing in endoplasmic reticulum (tae04141). Similarly, the PlantCyc pathway analysis indicated that up-regulated DEGs were significantly enriched in calvin-benson-bassham cycle, rubisco shunt, and dhurrin biosynthesis, whereas down-regulated DEGs were significantly enriched in gluconeogenesis I, TCA cycle II (plants and fungi), and glycolysis IV (plant cytosol). In addition, the PlantReactome pathway analysis identified significant enrichment of up-regulated DEGs in pathways such as IAA biosynthesis I (R-TAE-1119486.1), jasmonic acid biosynthesis (R-TAE-1119332.1), and gibberellin signaling (R-TAE-5679411.1), while TCA cycle (plant) (R-TAE-1119533.1), cytosolic glycolysis (R-TAE-1119570.1), S-adenosyl-L-methionine cycle (R-TAE-1119501.1) were the top three significantly enriched pathways for down-regulated DEGs in m097.

Fig. 7.

Functional classification of differentially expressed genes (DEGs). A Top 20 significant gene ontology (GO) enriched terms of up-regulated DEGs in m097 compared to wildtype Jinmai47 across three categories, including biological processes (BP), cellular locations (CC) and molecular functions (MF). B Top 20 significant GO enriched terms of down-regulated DEGs in m097 compared to wildtype Jinmai47. C Top 10 significantly enriched metabolic pathways of up-regulated DEGs in m097 compared to wildtype Jinmai47, including PlantCyc, KEGG, and Plant Reactome classification. D Top 10 significantly enriched metabolic pathways of down-regulated DEGs in m097 compared to wildtype Jinmai47

Discussion

The dwarf gene in m097 exhibited pleiotropic effects on yield-related traits

Plant height is a critical objective in modern wheat breeding programs due to its significant impact on lodging, yield, quality traits and disease resistance (Casebow et al. 2016; Hedden 2003; Hu et al. 2024; Miedaner and Voss 2008; Velu et al. 2017). Although the positive role of ‘Green Revolution’ genes in increasing grain yield potential is well established, the GA-insensitive Rht1 and Rht2 have been associated with certain adverse effects on coleoptile length, early seedling vigor, root elongation, grain size and weight, and protein content (Casebow et al. 2016; Guan et al. 2020; Ingvordsen et al. 2022; Rebetzke et al. 2007; Xu et al. 2023a). Subsequently, GA-sensitive dwarfing genes, such as Rht8, were reported to have the ability to enhance the early vigor of semi-dwarf wheat, making them more suitable for cultivation in high-temperature and arid environments (Chai et al. 2022; Xiong et al. 2022).

In the present study, we identified a new GA-sensitive dwarf mutant, m097, in the wheat cultivar JM47. Previous studies have demonstrated that changes in various agronomic traits are linked to the reduction in plant height induced by Rht genes (Chen et al. 2014; Lu et al. 2015; Xu et al. 2017). Similarly, the Rht_m097 gene exhibited a semi-dominant inheritance pattern, leading to a decrease in PH as well as reductions in TGW and GNS in comparison to the wildtype JM47 (Fig. 1, Table  S1). Therefore, when the Rht_m097 gene is used in wheat breeding, it is essential to consider its potential negative impact on yield-related traits. In addition, the enhancer loci present potential utility for the development of high-yielding semi-dwarf genotypes incorporating the dwarfing gene allele in m097 (Agarwal et al. 2020). Alternatively, the Rht_m097 gene could be employed in conjunction with other plant architecture-related genes to achieve optimal plant height and higher yield in wheat breeding programs.

Discovery of a novel dwarfing locus on chromosome 4BS

Compared to traditional genetic linkage mapping, BSA using extreme individual variants offers a rapid and efficient approach for mapping key genes associated with important agronomic traits, as it reduces both scale and cost by simplifying procedures (Cui et al. 2022; Wang et al. 2023; Zou et al. 2016). In the present study, the Rht_m097 gene was located in the region of 141.42–164.98 Mb (IWGSC RefSeq v2.1) on chromosome 4BS using the 660K SNP array-based BSA (Fig. 4). Furthermore, InDel markers within the region were developed based on parental resequencing data, leading to the mapping of the dwarf gene to a physical interval of approximately 2.7 Mb flanked by 4B-InDel-3 and 4B-InDel-4. Previous research has demonstrated that all 21 wheat chromosomes harbor QTL associated with PH, with chromosome-biased loci distribution (Xu et al. 2023b). Notably, a QTL-rich cluster (QRC) was detected on chromosome 4B, comprising QRC-4B-I (24.2–37.0 Mb), QRC-4B-II (101.7–106.3 Mb), QRC-4B-III (426.5–441.6 Mb), QRC-4B-IV (543.7–552.0 Mb), and QRC-4B-V (638.8–650.1 Mb) based on IWGSC RefSeq Annotations v2.1 (Xu et al. 2023b). Consequently, it is speculated that the Rht_m097 gene may be a novel dwarfing locus regulating plant height and other important agronomic traits.

Functional prediction of putative candidate genes

Based on the annotation of the Chinese Spring reference genome, we identified 16 high-confidence candidate genes within the 2.7 Mb physical interval (Table S2). Using the “QTG miner” tool, we mined high-confidence candidate genes in the fine-mapped interval. Notably, the candidate gene with the highest score, TraesCS4B03G0282400, encodes an ethylene-responsive transcription factor, cytokinin response factor 4 (CRF4) (Fig. 5A). The cytokinin response factor is an important branch of the APETALA2/ethylene responsive factor (AP2/ERF) supergene family, which plays an essential role in plant growth and development (Hallmark and Rashotte 2019; Raines et al. 2016). Recent studies have shown that an AP2/ERF transcription factor GmCRF4a regulates soybean plant height and auxin biosynthesis (Xu et al. 2022). Meanwhile, TraesCS4B03G0282800 and TraesCS4B03G0283800 were found to be differentially expressed between the wildtype JM47 and the mutant m097 in the results of the transcriptome analysis, which were suggested as the potential candidate genes of m097 (Fig. 6C). Specifically, TraesCS4B03G0282800 encodes a phototropic-responsive NPH3 family protein. NPH3 is a crucial determinant for phototropic growth and the formation of the lateral phytohormone auxin gradients, which facilitate increased cell expansion on the shaded side of the hypocotyl1 (Sullivan et al. 2021). Moreover, NPY1, a BTB-NPH3-like protein that cooperates with the protein kinase PID, plays a pivotal role in auxin-regulated plant development (Cheng et al. 2007). The other differentially expressed gene, TraesCS4B03G0283800, encodes a cytochrome P450-like protein. The flexible catalytic cytochrome P450 (CYP) superfamily is the largest family of enzymatic proteins in plants and is essential for the production of secondary metabolites and phytohormones that regulate many vital cellular processes affecting cell division and cell expansion, plant growth and development (Chakraborty et al. 2023; Xu et al. 2015). Furthermore, OsCYP51G1 (Os11g0525200), the homologous gene of TraesCS4B03G0283800 in rice, encodes an ER-localized obtusifoliol 14α-demethylase, is involved in phytosterol synthesis and affects pollen and seed development (Inagaki et al. 2011; Jiao et al. 2020; Nelson et al. 2004). Similarly, the OsCYP51G3 gene also encodes an obtusifoliol 14α-demethylase, and its reduced expression leads to decreased phytosterol and BR concentrations, resulting in a dwarf phenotype, erect leaves, semi-sterile pollen, and short cells (Xia et al. 2015). However, although regulation of gene expression plays an important role in phenotypic variation, further transgenic experiments are needed to verify gene function.

Plant height has been demonstrated to have a significant correlation with phytohormone biosynthesis and signaling pathways, particularly those involving gibberellin (GA) and brassinosteroid (BR) (Niu et al. 2021). Notably, a recent study identified an r-e-z locus comprising three contiguous genes (Rht-B1, EamA-B, and ZnF-B) that regulated plant growth and development by inhibiting GA signaling while promoting BR signaling, resulting in semi-dwarf plant height, nitrogen use efficiency (NUE) and a significant yield increase in wheat (Song et al. 2023). Moreover, the semi-dwarfing gene TaACTIN7-D regulates plant height and grain morphology in bread wheat by affecting the response to BR, GA, and auxin hormone signals (Li et al. 2023a). Interestingly, the down-regulated DEGs in m097 were biologically categorized as being involved in actin cortical patch organization and actin cortical patch assembly (Fig. 6B, Table S6). Meanwhile, we found that up-regulated DEGs were also enriched in multiple phytohormone metabolic pathways, including IAA biosynthesis, jasmonic acid biosynthesis, and gibberellin signaling (Fig. 6C, Table S7). In addition, for three different metabolic databases, the down-regulated DEGs were consistently enriched in energy metabolism processes, including citrate cycle (TCA cycle), glycolysis/gluconeogenesis, and oxidative phosphorylation. Consequently, we speculated that the dwarf gene in m097 influences multiple biological processes involved in plant hormones, actin protein and energy metabolism, ultimately regulating GA levels and cell elongation, thereby reducing plant height.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contribution

JZ and PG conceived and designed the experiments. RB, BY, and KP performed the experiments and wrote the paper. AX, ZW and ML participated in field trials. XZ and JZ analyzed the data. YZ assisted in writing and revising the paper.

Funding

This research was funded by the Scientific and Technological Research Project of Henan Province of China (242102111135), the Key Research and Development Project of Shanxi Province (202302140601001), the State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, Henan Agricultural University (39990105).

Data availability

The raw RNA-seq data in this study have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archives (SRA) under accession number PRJNA1201746.

Declarations

Conflict of interest

The authors declare that they have no conflict of interest.