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Article

Genetic Mapping by 55K Single-Nucleotide Polymorphism Array Reveals Candidate Genes for Tillering Trait in Wheat Mutant dmc

by
Kemeng Jiao
1,
Guojun Xia
1,2,
Yuan Zhou
1,
Chenyu Zhao
1,
Huiyuan Yan
1,
Menglei Qi
1,
Pingfan Xie
1,
Yongjing Ni
3,
Jingxue Zhao
1,
Jishan Niu
1,2,
Zhaofei Chao
4,
Jiangping Ren
1,2 and
Lei Li
1,2,*
1
Henan Technology Innovation Centre of Wheat/National Engineering Research Centre for Wheat, Henan Agricultural University, Zhengzhou 450046, China
2
National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450046, China
3
Henan Engineering Research Centre of Wheat Spring Freeze Injury Identification, Shangqiu Academy of Agriculture and Forestry Sciences, Shangqiu 476000, China
4
Jiaozuo Seed Industry Development Center, Jiaozuo 454150, China
*
Author to whom correspondence should be addressed.
Genes 2024, 15(12), 1652; https://doi.org/10.3390/genes15121652
Submission received: 26 November 2024 / Revised: 15 December 2024 / Accepted: 20 December 2024 / Published: 22 December 2024
(This article belongs to the Section Plant Genetics and Genomics)
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Versions Notes

Abstract

:
Background: The tiller number is a key agronomic trait for increasing the yield potential of wheat (Triticum aestivum L.). A number of quantitative trait loci (QTLs) and key genes controlling tillering have been identified, but the regulatory mechanisms remain unclear. Methods: In this study, we utilized the dwarf-monoculm mutant (dmc) obtained from the ethyl methane sulfonate (EMS)-treated wheat cultivar Guomai 301. The F2 populations were constructed using the dmc mutant crossed to multiple tiller parents. The F2 populations were surveyed for tillering traits at the critical fertility stage for genetic analyses. The extreme-tillering-phenotype plants from the F2 population were used to construct mixing pools that were analyzed by a wheat 55K SNP array. The tillering genes of dmc were mapped using the wheat 55K SNP array combined with transcriptomic data. Results: The results showed that the genetic phenotype of dmc is controlled by two dominant genes. The tillering genes of dmc were mapped on the 60–100 Mb region of chromosome 5B and the 135–160 Mb region of chromosome 7A. A total of sixteen candidate genes associated with the tillering trait of dmc were identified. Two candidate genes, TraesCS5B02G058800 and TraesCS7A02G184200, were predicted to be involved in indole acetic acid (IAA) response and transport, which were considered as potential regulatory genes. Conclusions: This study elucidated the genetic basis of the dmc mutant and provided two valuable reference genes for studying the development and regulatory mechanisms of wheat tillering.

1. Introduction

Wheat plays a crucial role in global food security, serving as a vital food crop that feeds billions of people worldwide [1,2,3]. According to relevant studies, global grain trade will be affected by both climate extremes and population growth, with a reduction in wheat supply capacity in key supply regions [4,5,6,7]. Tillering is a critical aspect of plant development, particularly in grasses and cereal crops, as it significantly influences biomass production and yield [8]. Tiller formation has a significant effect on wheat in terms of building a rational population, increasing the number of effective spikes and grain yield [9,10]. Therefore, it is necessary to excavate the key genes of tiller regulation and study the mechanism of tiller formation in wheat.
The regulation of tillering involves a complex interplay of genetic factors, hormonal signaling, and environmental conditions [11,12,13]. The continued growth of tillers requires a steady supply of sugar. The early cessation of tillering in the tiller inhibition mutant (tin) mutant leads to a reduction in the number of tillers [14]. High-density planting reduces photosynthetically active radiation (PAR) intensity and causes the earlier cessation of tiller development [8]. Cytokinin (CK)-mediated signaling effects of fertilizer nitrogen forms can be employed as a management tool to regulate the tiller number in cereal crops [15]. Gibberellins (GAs) and strigolactones (SLs) are the two major phytohormones determining plant tillering, Oryza sativa GROWTH-REGULATING FACTOR7(OsGRF7) alters the endogenous strigolactone content, which rendered repression of the outgrowth of the axillary buds [16]. The TILLER NUMBER 1(TN1) gene promotes wheat tillering, at least partially, through two layers of molecular mechanisms via repressing abscisic acid (ABA) biosynthesis and inhibiting ABA signaling through preventing the binding of PYR-like (TaPYL) to PROTEIN PHOSPHATASE 2C (TaPP2C) [17]. Gibberellins also play a role in stimulating tiller development, although their effects can vary between species [18,19]. Previous correlative studies of dmc mutants have shown that tillering is associated with the IAA biosynthesis pathway [20]. Studying the dmc mutant could enhance our understanding of the complex regulatory network of tillering development.
Tillering originates from the axillary meristem (AM), and its formation and development primarily occur in two stages: (1) the development of the axillary meristem, which begins with the formation of a boundary between the shoot apex and the leaf primordia, followed by the initiation of meristematic cells in the axillary region near the leaf axil; (2) the elongation of the axillary bud, leading to the formation of tillers [21,22]. Many crops with tiller-related genes have been reported. Regulator genes in rice (Oryza sativa L.) influencing AM formations include O. sativa homeobox1 (OSH1) [23], LAX PANICLE1 (LAX1) [24], LAX PANICLE2 (LAX2) [25], MONOCULM1 (MOC1) [26,27,28], MOC1 interacting protein1 (MIP1) [29], Tillering and Dwarf1 (TAD1) [30], SLENDER RICE1 (SLR1) [28], MONOCULM3 (MOC3) [31], RICE FLORICULA/LEAFY (RFL) [32], Oryza sativa CUP-SHAPED COTYLEDON1 (OsCUC1) [33], and FRIZZLE PANICLE (FZP) [34], while regulator genes influencing AM growth into tillers include DWARF3 (D3) [35], DWARF10 (D10) [36], DWARF14 (D14) [37], HIGH TILLERING DWARF1 (HTD1) [38], DWARF27 (D27) [39], O. sativa MORE AXILLARY GROWTH1a (OsMAX1a) [40], O. sativa MORE AXILLARY GROWTH1e (OsMAX1e) [40], DWARF53 (D53) [37], (O. sativa MINICHROMOSOME MAINTENANCE1, AGAMOUS, DEFICIENS and SERUM RESPONSE FACTOR57) (OsMADS57) [41], O. sativa TEOSINTE BRANCHED1 (OsTB1) [41], IDEAL PLANT ARCHITECTUTRE1 (IPA1) [42], O. sativa DENSE AND ERECT PANICLE1 (DEP1) [42], O. sativa SHORT INTERNODES1OsDEP1 (OsSHI1) [42], O. sativa CIRCADIAN CLOCK ASSOCIATED1 (OsCCA1) [43], Heading date 3a (Hd3a) [44], O. sativa Domains Rearranged Methyltransferase2 (OsDRM2) [45], FLORAL ORGAN NUMBER1 (FON1) [31], TILLER NUMBER 1 (TN1) [46], and TN1 interaction factor 1 (TIF1) [46]. Regulator genes in wheat regulating tillering include TILLER NUMBER 1 (TN1), tiller inhibition mutant (tin), tin2, tin3, tin4, tin5, tin6, fertile tiller inhibition gene (ftin), and oligo-tillering mutant (ot1), having diverse effects on axillary bud development and overall wheat growth [8,14,47,48,49,50,51,52].
Tillering mutants are crucial for understanding the genetic and physiological mechanisms that regulate tillering in various plant species, particularly in crops like wheat and rice. These mutants provide valuable insights into the factors that influence tiller development. Morphological studies indicate that mutants like tin, tin4, tin5, ftin, and TN1 exhibit decreased tiller numbers due to inhibited or abnormal axillary bud development [17,47,48,49,53]. In tin mutants, tiller growth ceases when the plant transitions from the vegetative to the reproductive stage [14,54,55]. The ftin mutants show normal tiller numbers at the seedling stage, but exhibit a significant reduction at heading, suggesting that the reduction is due to delayed tiller outgrowth rather than inhibited axillary bud differentiation [49]. In tin4, tin5, and TN1, the decreased tiller number results from the inhibition of secondary tiller bud development [17,47,48]. The ot1 mutant maintained an average of three tillers [52]. Meanwhile, in dmc, a non-tillering mutant from EMS-treated wheat cultivar Guomai 301, both tiller bud differentiation and development are inhibited [56,57]. This means that our material, dmc mutants, is different from the mutants that have been reported.
In this study, we combined transcriptomic information by wheat 55K SNP array sequencing [56], and sixteen candidate genes were predicted within the two target interval segments. Two of them, TraesCS5B02G058800 and TraesCS7A02G184200, are tillering regulatory genes, which were predicted to be involved in IAA response and transport.

2. Materials and Methods

2.1. Plant Material

The dwarf-monoculm mutant dmc was obtained from an EMS-mutagenized population of the wheat variety Guomai 301. Through consecutive years of single-plant selection, we successfully obtained genetically stable strains of dmc. The hybridization of the dmc mutant with Aikang 58, Chinese Spring, Guomai 301, Zhengmai 379, and Zhengmai 9405 produced 15, 6, 17, 27, and 21 F1 individuals, respectively. The F1 individual, self-pollinated dmc mutant and Aikang 58, Chinese Spring, and Guomai 301 produced 460, 811, and 1041 F2 individuals, respectively. These F1 individuals and F2 populations were planted in Xiaowu Village, Yuanyang City, Henan, China (35°6′ N, 113°56′ E, 70 m a.s.l.). All materials were sown in mid-October and harvested in June of the following year in 2023 and 2024 wheat growth seasons. All F1 and F2 individuals were sown in 2 m rows with 25 cm row spacing, leaving approximately 10 cm between plants. Varieties were obtained from the National Engineering Research Centre for Wheat. Fertilizer and weed management were similar to wheat breeding [58].

2.2. Phenotypic Investigations and Genetic Analysis

At least 30 plants of the dmc mutant and wheat cultivar Guomai 301 were surveyed phenotypically at the tillering stage and filling stages. A statistical analysis was conducted using Origin 2022 software. All lines of the F2 population were surveyed for the tiller number in each April of 2023 and 2024. The data were statistically analyzed using SPSS v20 software.

2.3. Cytological Karyotype Analysis

Chromosome configurations and a high-resolution chromosome painting analysis of plants derived from the dmc mutant at the metaphase of mitosis: Chromosome samples were prepared as previously described [59]. For chromosome painting, eight single-strand oligonucleotides were used to form modified multiplex probes for the karyotype analysis in wheat, which included TAMRA (6-carboxytetramethylrhodamine)-modified oligonucleotides pAs1-1, pAs1-3, pAs1-4, pAs1-6, AFA-3, and AFA-4, and two FAM (6-carboxyfluorescein)-modified oligonucleotides, pSc119.2-1 and (GAA)10 [59]. Oligonucleotide probes used for FISH are listed in Table S1. The FISH procedure was tested as previously described [59]. Chromosomes were visualized with microscope Olympus BX51 (Olympus, Beijing, China) and pictures were captured with SPOT CCD (SPOT Cooled Color Digital Camera, Leica, Germany). An image analysis was conducted using Photoshop v6.0.

2.4. Wheat 55K SNP Array Analysis

Nine no-tillering and thirty multi-tillering individuals with extreme phenotypes from the Aikang58 × dmc F2 populations were prepared to construct two pools. Genomic DNA was extracted by Nakayukin Marker Company (http://www.cgmb.com.cn/, accessed on 26 April 2023) (Beijing, China). The bulked samples were genotyped with the Axiom® Wheat 55K SNP array. The work was mainly conducted at Nakayukin Marker Company (http://www.cgmb.com.cn/, accessed on 26 April 2023). We performed an SNP gene analysis and cluster analysis using Biosearch’s high-throughput genotyping assay platform (https://www.biosearchtech.com/, accessed on 26 April 2023). We excluded SNP markers with deletion rates greater than 20%, allele frequencies less than 5%, and those that could not be localized to chromosomes. We screened SNP markers with differences in the mixed pools that corresponded to the extreme phenotypes. We compared and analyzed the sequences of the selected SNP markers with the Chinese Spring Genome Version 1.0 (http://www.wheatgenome.org/, accessed on 26 April 2023) for chromosome localization.

2.5. Expression Analysis

We collected tiller nodes from the dmc and Guomai 301 varieties separately. RNA was extracted using a Trizol reagent (TransGen Biotech, Beijing, China) according to the manufacturer’s protocol. RNA concentration was measured using a NanoDrop 2000 (NanoDrop Technologies, Wilmington, DE, USA). RNA integrity was assessed using the RNA Nano 6000 Assay Kit on the Agilent Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA). We used Primer5 software to design gene-specific primers (Table S2). The wheat actin gene was used as an internal control gene. The qRT-PCR reactions were performed in 20 µL volumes containing 10 µL Hieff® qPCR SYBR Green Master Mix (Yeasen Biotech, Shanghai, China), 0.8 µL primer mix (10 µM), 1 µL cDNA (50 ng), and 8.8 µL ddH2O. The PCR parameters were 94 °C for 30 s, and then 40 cycles of 94 °C for 5 s, and 60 °C for 30 s. All qRT-PCR reactions were replicated three times. The gene expression levels were calculated according to the 2−∆∆Ct method [60].

3. Results

3.1. Identification of dmc Mutants

The dmc mutant was previously characterized from the EMS-treated wheat cultivar Guomai 301. At the tillering stage, Guomai 301 exhibited 9–12 tillers, whereas the dmc mutant displayed only one main stem (Figure 1A,C). At the filling stage, Guomai 301 produced approximately 20 tillers, while the dmc mutant developed only one main stem (Figure 1B,D). During the three-leaf stage, the dmc mutant presented a small tiller bud compared to the multiple tiller buds of Guomai 301 (Figure 1E).

3.2. Fluorescence In Situ Hybridization Analysis of dmc Mutant Chromosomes

To validate and identify the chromosome constitution of the dmc mutant, high-resolution chromosome painting was applied using eight single-strand oligonucleotide probes. The result of the fluorescence in situ hybridization analysis of chromosomes revealed that the A, B, and D genomes of the dmc mutant were structurally normal. There is no large segment deletions compared to the control Guomai 301 (Figure 2A,B). This finding indicates that the phenotype of the dmc mutant is not attributable to chromosomal structural variations.

3.3. Genetic Analysis of Tiller Number of dmc Mutant

The dmc mutant was crossed with several multi-tiller parents (Table 1). The F1 generation was examined for a genetic analysis of the tiller number associated with the dmc mutant. The tiller count in the F1 generation was intermediate between that of the dmc mutant and the multi-tiller parents. This suggests that the dmc mutant may be regulated by a semi-dominant gene.
The dmc mutant showed only one main stem but with an ineffective tiller. In the experiment, the number of effective tillers greater than one was defined as multiple tillers, and only one main stem was defined as a no-tiller plant. Assuming that the no-tiller trait is controlled by two genes, the survey showed that the F2 populations of dmc × Aikang 58 in 2023, dmc × Chinese Spring in 2023 and 2024, and dmc × Guomai 301 in 2024 had 36, 27, 20, 21, and 50 no tillers, respectively (Table 2). The multiple tillers had 424, 396, 368, 380, and 385 tillers, respectively (Table 2). The result of the χ2 test showed that the number of effective tillers was χ2 < P0.05, which is consistent with the Mendelian two-gene inheritance of a 15:1 segregation ratio. It was concluded that the no-tiller phenotype of the dmc mutant was controlled by two genes.
It shows that in the F2 populations from the crosses of dmc × Chinese Spring, dmc × Aikang 58, and dmc × Guomai 301, a greater number of plants exhibited fewer tillers than those with a higher number of tillers (Figure 3). This observation supports the involvement of semi-dominant genes in the F1 generation. We supposed that two semi-dominant genes regulate the no-tillering trait. The number of dominant genes associated with this trait varies by phenotype. For instance, the AABB genotype is characterized by the no-tillering trait.

3.4. Analysis of Gene Microarrays

An F2 population consisting of 460 individuals derived from the cross between Aikang58 and the dmc mutant was used for the analysis. We first conducted a bulked segregant analysis and wheat 55K SNP array-based genotyping using the individuals with extreme phenotypes from the F2 progenies. A total of 491 SNPs were polymorphic, of which 169 were located on chromosome 5B and 58 were located on chromosome 7A (Figure 4A). A further analysis showed that 58 SNPs are enriched over a 60 to 100 Mb interval on the short arm of chromosome 5B, and 21 SNPs are enriched over a 135 to 160 Mb interval on the short arm of chromosome 7A (Figure 4B,C).

3.5. Candidate Gene Prediction

Combined with the transcriptome data, the differential genes contained in the two candidate intervals were analyzed and annotated [56,61]. A total of sixteen differentially expressed genes were identified (Table 3). According to transcriptome data, seven candidate genes on chromosome 5B and TraesCS7A02G184200 are upregulated in the dmc mutant, while the remaining eight genes on chromosome 7A are downregulated in the dmc mutant. The gene annotation revealed that TraesCS5B02G058800 is involved in regulating growth hormone response proteins. And TraesCS7A02G184200 encodes a protein featuring the BTB structural domain, which plays a role in the transport of growth hormones. This finding aligns with our previous studies where IAA metabolism and signaling affected tillering development of the dmc mutant [20]. Consequently, TraesCS5B02G058800 and TraesCS7A02G184200 are two potential candidate genes regulating tillering development for further research.
We performed a qRT-PCR analysis of sixteen candidate genes’ expression during the tillering stage of Guomai 301 and dmc for the validation of transcriptome data (Figure 5). It showed that the qRT-PCR results matched well with the transcriptome data.

4. Discussion

Increasing wheat yield is an important means to cope with future food shortages [62,63,64]. It is an effective way to increase wheat yield to study the mechanism of tillering control and increase the amount of effective tillering [47,65]. In the dmc mutant, the growth of tiller buds and plant development are inhibited (Figure 1A,B). Most of the primordia could not grow or stopped developing, which resulted in no tillers [56].The dmc mutant exhibits a dwarf phenotype with no tillers, making it an excellent material for studying tiller suppression.
Previous studies have reported eight tillering inhibition genes of wheat (tin1, tin2, tin3, ftin, TIN4, TIN5, tin6, TN1) [8,14,17,47,48,49,50,51]. Among these, the natural mutants tin, tin2, ftin, and TIN4 are located on 1AS, 2A, 1AS, and 2DL, respectively [8,14,47,49]. The EMS-treated mutants tin3, TIN5, tin6, and TN1 are located on chromosomes 3A, Tu7, 2DL, and 6BS, respectively [8,17,48,50,51]. The QTL associated with the tiller number in wheat is located on chromosomes 1A, 1B, 2B, 2D, 4A, 4B, 4D, 5A, 6B, and 7D [66,67,68,69,70,71,72]. In this study, we predicted two new wheat tiller inhibition genes, whose physical locations are different from those of pin-formed 1 (TaPIN1) [73], dwarf (TaD27-B) [39], ovarian tumor domain-containing proteases 1 (TaOTUB1) [74], and squamosa promoter binding-like 14 (TaSPL14) [75] found previously on chromosomes 5B and 7A. This study contains a new finding of a tillering inhibition mutant (Figure 4B,C).
The downregulated gene expressions related to phytohormone syntheses of auxin, zeatin, cytokinin, and some transcription factor (TF) families of TALE, and WOX, might be the major causes of non-tillering in mutant dmc [20,56,57,76]. The gene tin reduces tillering by controlling the early maturation of internodes, causing a competition for sucrose between the internodes and tiller buds [14,53]. Similarly, TN1 inhibits tillering by regulating the levels of ABA [17]. The ot1 gene revealed the upregulation of genes associated with SL and ABA biosynthesis and signaling [52]. Previous studies have proved that IAA contents in dmc were significantly less than that in Guomai 301 at tillering stages [56]. In this study, TraesCS5B02G058800 and TraesCS7A02G184200 are related to IAA regulation and transport among the sixteen candidate genes identified in the positional cloning prediction. We predict that they are candidate genes of non-tillering in the dmc mutant (Table 3).
Using homologous gene cloning methods, several genes related to wheat tillering have been identified [77,78]. These genes act at different developmental stages of wheat growth and participate in the regulation of tillering through interactions with various genetic factors or exogenous hormones. For instance, MOC1 encodes a putative GRAS family nuclear protein that is expressed mainly in the axillary buds and functions to initiate axillary buds and to promote wheat outgrowth [28]. In contrast, the TaTB1 gene overexpression in wheat results in reduced tillers and spike numbers [79]. Additionally, phytochrome-interacting factor-like 1 (TaPIL1) activates the transcriptional expression of wheat TaTB1, reducing the wheat tiller number [80]. Moreover, the PLANT ARCHITECTURE AND YIELD 1 (TaPAY1) gene could improve the tiller number via affecting polar IAA transport activity and altering endogenous IAA distribution [81]. The TaPIN1s indicating that IAA might mediate the axillary bud production and reduction in TaPIN1 expression increased the tiller number and grain yield per plant of wheat [73,82,83]. The application of SL inhibits shoot branching in plants [84]. The TaD27-B modulates tillering by participating in the biosynthesis of SL, while TaD53 acts as a repressor in the SL signaling pathway, interacting with the transcriptional co-repressor Topless (TaTPL) [39]. The TERMINAL FLOWER 1 (TaTFL1) was implicated in tiller regulation by IAA and CK signaling [85]. These examples illustrate the complexity of factors regulating wheat tillering. However, only the mechanisms of ABA and SL in tiller regulation have been reported, while the role of IAA in this process remains unclear. Our previous studies have shown that IAA expression in dmc is suppressed, which is a critical factor causing the dwarfing and no tillering in this mutant [20,56]. Therefore, dmc provides a valuable new mutant material for studying the mechanisms of tillering in wheat, holding significant implications for molecular breeding in the crop.

5. Conclusions

In this study, F1 individuals and F2 populations of the dmc mutant obtained by multi-tillering varieties were constructed for a genetic analysis and oligotillering gene mapping. The populations showed that the genetic phenotype of the dmc mutant was controlled by two dominant genes. The analysis of a wheat 55K SNP array showed that the dmc tiller gene was located on the 60–100 MB region of chromosome 5B and the 135–160 MB region of chromosome 7A. A total of sixteen candidate genes related to dmc tillering traits were identified in the candidate region by combining the wheat 55K SNP array results with the transcriptome information of dmc mutants. Among them, TraesCS5B02G058800 and TraesCS7A02G184200 genes are predicted to be involved in the response and transport of IAA, and are considered as potential regulatory genes of tillering. Cloning the dmc tillering gene could aid in developing tillering-related markers for wheat breeding and enhance our understanding of the biological mechanisms underlying this complex trait.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes15121652/s1, Table S1: Oligonucleotide probes used for FISH; Table S2: Primers used in the experiment and their sequence information.

Author Contributions

K.J. performed all the experiments pertaining to trait observation, photograph taking, and qRT-PCR and also analyzed the data and drafted the manuscript. Y.Z., C.Z., H.Y., G.X. and Z.C. helped with sowing and sample preparation. M.Q. and P.X. helped with sowing, trait observation, and figure drawing. Y.N. and J.Z. contributed to sowing and the data analysis. J.R., J.N. and L.L. helped with writing—review and editing. L.L. designed the whole study, and contributed to conceptualization, project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Key R&D Program of China (Program No. 2023YFD2301500, No. 2017YFD0301101), the National Natural Science Foundation of China (NSFC, 32171972), the Project of Zhongyuan Scholars Workstation (224400510001), and the Key Research Project of the Shennong Laboratory (SN01-2022-01).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

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. Phenotypes of the dmc mutant; (A) Guomai 301 (left) and the dmc mutant (right) at the tillering stage, and the scale bar is 5 cm; (B) Guomai 301 (left) and the dmc mutant (right) at the filling stage, and the scale bar is 10 cm; (C) the number of tillers at the tillering stage of Guomai 301 and the dmc mutant, and the data are the mean ± SD (n = 30 biologically independent samples); (D) the number of tillers at the filling stage of Guomai 301 and the dmc mutant, and the data are the mean ± SD (n = 30 biologically independent samples); (E) the tiller buds at the three-leaf stage of Guomai 301 (left) and the dmc mutant (right), the scale bar is 0.5 cm, and red arrows indicate the position of axillary buds.
Figure 1. Phenotypes of the dmc mutant; (A) Guomai 301 (left) and the dmc mutant (right) at the tillering stage, and the scale bar is 5 cm; (B) Guomai 301 (left) and the dmc mutant (right) at the filling stage, and the scale bar is 10 cm; (C) the number of tillers at the tillering stage of Guomai 301 and the dmc mutant, and the data are the mean ± SD (n = 30 biologically independent samples); (D) the number of tillers at the filling stage of Guomai 301 and the dmc mutant, and the data are the mean ± SD (n = 30 biologically independent samples); (E) the tiller buds at the three-leaf stage of Guomai 301 (left) and the dmc mutant (right), the scale bar is 0.5 cm, and red arrows indicate the position of axillary buds.
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Figure 2. The high-resolution chromosome painting analysis of the plants derived from the dmc mutant at the metaphase of mitosis. (A) One karyotype of Guomai 301, which had 42 normal chromosomes. (B) One karyotype of the dmc mutant, which had 42 normal chromosomes. Blue color, chromosomes counterstained with DAPI; green, signals of oligos pSc119.2-1, (GAA)10; red, signals of oligos AFA-3, AFA-4, pAs1-1, pAs1-3, pAs1-4, and pAs1-6. Scale bar = 10 µm.
Figure 2. The high-resolution chromosome painting analysis of the plants derived from the dmc mutant at the metaphase of mitosis. (A) One karyotype of Guomai 301, which had 42 normal chromosomes. (B) One karyotype of the dmc mutant, which had 42 normal chromosomes. Blue color, chromosomes counterstained with DAPI; green, signals of oligos pSc119.2-1, (GAA)10; red, signals of oligos AFA-3, AFA-4, pAs1-1, pAs1-3, pAs1-4, and pAs1-6. Scale bar = 10 µm.
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Figure 3. The effective tiller number and distribution frequency of the F2 population; (A) the F2 population of dmc × Guomai 301 in 2023; (B) the F2 population of dmc × Aikang 58 in 2023; (C) the F2 population of dmc × Chinese Spring in 2024; (D) the F2 population of dmc × Chinese Spring in 2023.
Figure 3. The effective tiller number and distribution frequency of the F2 population; (A) the F2 population of dmc × Guomai 301 in 2023; (B) the F2 population of dmc × Aikang 58 in 2023; (C) the F2 population of dmc × Chinese Spring in 2024; (D) the F2 population of dmc × Chinese Spring in 2023.
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Figure 4. Distribution of single-nucleotide polymorphisms (SNPs) on different chromosomes and polymorphic SNP sites on chromosomes 5B and 7A in wheat; (A) number of polymorphic SNPs on each chromosome; (B) distribution of polymorphic SNP sites on chromosome 5B; (C) distribution of polymorphic SNP sites on chromosome 7A.
Figure 4. Distribution of single-nucleotide polymorphisms (SNPs) on different chromosomes and polymorphic SNP sites on chromosomes 5B and 7A in wheat; (A) number of polymorphic SNPs on each chromosome; (B) distribution of polymorphic SNP sites on chromosome 5B; (C) distribution of polymorphic SNP sites on chromosome 7A.
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Figure 5. The qRT-PCR analysis of sixteen candidate genes. (A) TraesCS5B02G058800 (Auxin-responsive protein IAA31); (B) TraesCS5B02G059300 (CBL-interacting protein kinase 4); (C) TraesCS5B02G059800 (Tuliposide A-converting enzyme 2); (D) TraesCS5B02G060200 (Dolabradiene monooxygenase); (E) TraesCS5B02G060300 (Dolabradiene monooxygenase); (F) TraesCS5B02G061600 (11-beta-hydroxysteroid dehydrogenase A); (G) TraesCS5B02G062500 (Methylcrotonoyl-CoA carboxylase subunit alpha); (H) TraesCS7A02G184200 (Protein containing a BTB complex and an NPH3 domain (BTBN), regulation of auxin transport); (I) TraesCS7A02G184600 (Shikimate kinase domain-containing protein); (J) TraesCS7A02G187800 (Aquaporin NIP III subfamily protein); (K) TraesCS7A02G188100 (Amino acid transporter); (L) TraesCS7A02G188400 (Plant regulator RWP-RK domain-containing protein); (M) TraesCS7A02G191400 (Small GTP-binding protein OsRac3); (N) TraesCS7A02G191700 (Domain of unknown function DUF23); (O) TraesCS7A02G196100 (TGF-beta receptor, type I/II extracellular region family protein); (P) TraesCS7A02G197900 (Similar to CEL5 = CELLULASE 5). The left y-axis represents relative expression, and relative expressions are shown by histograms. The right y-axis represents the expression value (FPKM) of transcriptome sequencing, and expression values are shown by lines. Error bars indicate the standard deviation. The x-axis indicates the samples of Guomai 301 and dmc.
Figure 5. The qRT-PCR analysis of sixteen candidate genes. (A) TraesCS5B02G058800 (Auxin-responsive protein IAA31); (B) TraesCS5B02G059300 (CBL-interacting protein kinase 4); (C) TraesCS5B02G059800 (Tuliposide A-converting enzyme 2); (D) TraesCS5B02G060200 (Dolabradiene monooxygenase); (E) TraesCS5B02G060300 (Dolabradiene monooxygenase); (F) TraesCS5B02G061600 (11-beta-hydroxysteroid dehydrogenase A); (G) TraesCS5B02G062500 (Methylcrotonoyl-CoA carboxylase subunit alpha); (H) TraesCS7A02G184200 (Protein containing a BTB complex and an NPH3 domain (BTBN), regulation of auxin transport); (I) TraesCS7A02G184600 (Shikimate kinase domain-containing protein); (J) TraesCS7A02G187800 (Aquaporin NIP III subfamily protein); (K) TraesCS7A02G188100 (Amino acid transporter); (L) TraesCS7A02G188400 (Plant regulator RWP-RK domain-containing protein); (M) TraesCS7A02G191400 (Small GTP-binding protein OsRac3); (N) TraesCS7A02G191700 (Domain of unknown function DUF23); (O) TraesCS7A02G196100 (TGF-beta receptor, type I/II extracellular region family protein); (P) TraesCS7A02G197900 (Similar to CEL5 = CELLULASE 5). The left y-axis represents relative expression, and relative expressions are shown by histograms. The right y-axis represents the expression value (FPKM) of transcriptome sequencing, and expression values are shown by lines. Error bars indicate the standard deviation. The x-axis indicates the samples of Guomai 301 and dmc.
Genes 15 01652 g005
Table 1. The amount of tillering in the F1 generation of the different hybrid combinations.
Table 1. The amount of tillering in the F1 generation of the different hybrid combinations.
Hybrid CombinationNumber of
Individual F1 Plants		Number of Tillers of
Multi-Tiller Parent		Number of Tillers
in the F1 Generation 1
dmc × Zhengmai 9405413 ± 1.489.75 ± 5.58
Zhengmai 9405 × dmc1713 ± 1.484.64 ± 1.93
dmc × Aikang 58322 ± 2.235 ± 2
Aikang 58 × dmc1322 ± 2.245.53 ± 1.39
dmc × Zhengmai 3791714 ± 1.148.9 ± 3.73
Zhengmai 379 × dmc1014 ± 1.145.23 ± 2.07
dmc × Guomai 3011123 ± 2.2211.75 ± 2.06
Guomai 301 × dmc623 ± 2.226.18 ± 4.52
1 The data are the means ± SD.
Table 2. Genetic analysis of tillering traits in F2 populations.
Table 2. Genetic analysis of tillering traits in F2 populations.
Hybrid CombinationYearMultiple TillersNo TillerExpected Ratioχ2p-Value 1
χ2 (15:1)P *0.05
dmc × Aikang 5820234243615:11.953.84
dmc × Chinese Spring20233962715:10.00133.84
20243682015:10.7953.84
dmc × Guomai 30120233802115:10.7023.84
20245855015:12.8583.84
1 When df is 1, the significance value of P *0.05 is 3.84.
Table 3. Gene annotation of differentially expressed genes in candidate intervals on 5B and 7A.
Table 3. Gene annotation of differentially expressed genes in candidate intervals on 5B and 7A.
#GeneAnnotationExpression in dmc
1TraesCS5B02G058800Auxin-responsive protein IAA31up
2TraesCS5B02G059300CBL-interacting protein kinase 4up
3TraesCS5B02G059800Tuliposide A-converting enzyme 2, chloroplasticup
4TraesCS5B02G060200Dolabradiene monooxygenaseup
5TraesCS5B02G060300Dolabradiene monooxygenaseup
6TraesCS5B02G06160011-beta-hydroxysteroid dehydrogenase Aup
7TraesCS5B02G062500Methylcrotonoyl-CoA carboxylase subunit alphaup
8TraesCS7A02G184200Protein containing a Bric-a-Brac/Tramtrack/Broad (BTB) complex and an NPH3 domain (BTBN), regulation of auxin transportdown
9TraesCS7A02G184600Shikimate kinase domain-containing proteinup
10TraesCS7A02G187800Aquaporin NIP III subfamily proteindown
11TraesCS7A02G188100Amino acid transporterdown
12TraesCS7A02G188400Plant regulator RWP-RK domain-containing proteindown
13TraesCS7A02G191400Small GTP-binding protein OsRac3down
14TraesCS7A02G191700Domain of unknown function DUF23down
15TraesCS7A02G196100TGF-beta receptor, type I/II extracellular region family proteindown
16TraesCS7A02G197900Similar to CEL5=CELLULASE 5 (fragment)down
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MDPI and ACS Style

Jiao, K.; Xia, G.; Zhou, Y.; Zhao, C.; Yan, H.; Qi, M.; Xie, P.; Ni, Y.; Zhao, J.; Niu, J.; et al. Genetic Mapping by 55K Single-Nucleotide Polymorphism Array Reveals Candidate Genes for Tillering Trait in Wheat Mutant dmc. Genes 2024, 15, 1652. https://doi.org/10.3390/genes15121652

AMA Style

Jiao K, Xia G, Zhou Y, Zhao C, Yan H, Qi M, Xie P, Ni Y, Zhao J, Niu J, et al. Genetic Mapping by 55K Single-Nucleotide Polymorphism Array Reveals Candidate Genes for Tillering Trait in Wheat Mutant dmc. Genes. 2024; 15(12):1652. https://doi.org/10.3390/genes15121652

Chicago/Turabian Style

Jiao, Kemeng, Guojun Xia, Yuan Zhou, Chenyu Zhao, Huiyuan Yan, Menglei Qi, Pingfan Xie, Yongjing Ni, Jingxue Zhao, Jishan Niu, and et al. 2024. "Genetic Mapping by 55K Single-Nucleotide Polymorphism Array Reveals Candidate Genes for Tillering Trait in Wheat Mutant dmc" Genes 15, no. 12: 1652. https://doi.org/10.3390/genes15121652

APA Style

Jiao, K., Xia, G., Zhou, Y., Zhao, C., Yan, H., Qi, M., Xie, P., Ni, Y., Zhao, J., Niu, J., Chao, Z., Ren, J., & Li, L. (2024). Genetic Mapping by 55K Single-Nucleotide Polymorphism Array Reveals Candidate Genes for Tillering Trait in Wheat Mutant dmc. Genes, 15(12), 1652. https://doi.org/10.3390/genes15121652

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