Fine-mapping and validation of Gpc-5B as the locus responsible for increases in the grain protein content, grain size, and spike density in common wheat (Triticum aestivum L.)

doi:10.21203/rs.3.rs-4357624/v1

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Fine-mapping and validation of Gpc-5B as the locus responsible for increases in the grain protein content, grain size, and spike density in common wheat (Triticum aestivum L.)

https://doi.org/10.21203/rs.3.rs-4357624/v1

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Grain protein content (GPC), grain size, and spike morphology are important traits for common wheat (Triticum aestivum) breeding. However, few genes positively regulating these three traits have been reported. In this study, the gene responsible for increases in GPC, grain size, and spike density in the mutant S-Cp2 were mapped and cloned. This mutant was obtained by treating the common wheat cultivar ‘Shumai482’ with ethyl methanesulfonate (EMS). According to a genetic analysis, the increases in GPC and grain size and the formation of compact spikes in S-Cp2 were controlled by a single dominant locus (Gpc-5B) on chromosome 5BL. This locus was mapped to an 87.24 kb interval between markers KASP-58070 and KASP-58158, wherein 5Bq (homologous to Q on chromosome 5AL) was detected. One missense mutation (G-to-A) was detected within the microRNA172-binding site of 5Bq in S-Cp2 (i.e., 5BQ⁴ allele), suggesting that 5Bq is responsible for the mutant phenotype. This was confirmed by cloning 5Bq in revertants obtained by treating S-Cp2 with EMS. As expected, 5BQ⁴ in S-Cp2 was significantly more highly transcribed than 5Bq in ‘Shumai482’. Notably, 5Bq was positively selected during breeding. The study findings reflect the value of 5Bq for breeding novel wheat varieties.

Grain protein content

Grain size

Spike morphology

Gpc-5B

Fine-mapping

Q gene

A locus for increased wheat grain protein content, grain size, and spike density was mapped to an 87.24 kb interval on chromosome 5BL. TraesCS5B02G486900 was responsible for the target traits.

Grain protein content (GPC), which is the main indicator of the nutritional quality of cereals, is the most important factor influencing the utility of cereal grains for food processing. It is particularly important for wheat (Triticum aestivum; 2n = 6x = 42; AABBDD), which provides approximately 20% of the calories and 22% of the proteins consumed by humans (FAO 2022). Wheat is largely consumed by humans after being processed into bread and other foods. Notably, compared with other cereal crops, wheat has a unique processing quality (Shewry and Halford 2002; Wang et al. 2012; Ma et al. 2019).

Increasing GPC is an efficient way to improve wheat processing quality (Shiferaw et al. 2013; Zeibig et al. 2022). The unique processing quality of wheat is largely because of its seed storage proteins, including glutenins and gliadins, which contribute to dough rheological properties (He et al. 2005; Qi et al. 2006; Li et al. 2020). Glutenins and gliadins form a gluten protein network, which is conducive to the processing of dough into bread, noodles, and other food products (Wang et al. 2020). Wheat processing quality is the major determinant of consumer preferences for specific wheat cultivars. Wheat cultivars with a high GPC are urgently needed because of improved living conditions. Therefore, there has been considerable interest in genetic modifications associated with increased GPC (Kuchel et al. 2006; Suprayogi et al. 2009; Wang et al. 2018; Zhang et al. 2018; Lou et al. 2021).

Optimizing GPC through genetic changes is an important objective of wheat breeding programs because of the potential economic benefits associated with decreasing the frequency of nitrogen fertilizer applications and improving human nutrition and wheat processing quality (Distelfeld et al. 2005; Peng et al. 2022). However, increasing GPC using conventional breeding techniques is difficult because of the complexity of genetic systems, the strong influence of environmental conditions, and the negative correlation between GPC and grain yield (Wang et al. 2012; Zheng et al. 2018; Landolfi et al. 2021; Liu et al.2022). Gpc-B1 was the first gene related to GPC increases to be cloned by mapping. Unfortunately, Gpc-B1 expression also reportedly leads to accelerated senescence and adversely affects the grain yield (Kibite and Evans 1984; Joppa et al. 1997; Uauy et al. 2006; Brevis et al. 2010). In addition, several wheat genes that regulate GPC were revealed via a transgenic approach (Gao et al. 2021; Luo et al. 2021; Shen et al. 2021).

Increasing the grain yield is one of the primary goals of wheat breeders and growers because it affects the profitability of wheat production as well as food security. Grain yield is determined by the thousand kernel weight (TKW), grain number per spike, and spike number per unit area, among which TKW is a key factor for further improvements to wheat via breeding (Su et al. 2011; Nadolska-Orczyk et al. 2017). TKW is mainly determined by grain size, which is characterized by grain length, width, and thickness. Grain width and length are closely related to TKW (Cui et al. 2011; Yang et al. 2012; Xie et al. 2015). Increases in grain size generally lead to increases in grain yield, which also promotes seedling vigor and early growth. Therefore, relatively large grains were preferred during the domestication and breeding of cereal crops. Several genes associated with grain size have been reported in wheat, including TaDA1, TaGW2, and TaVRT-A2^pet (Zhang et al. 2018; Liu et al. 2020; Xiao et al. 2021).

In wheat, Q, which is the most important domestication-related gene, is located on chromosome 5AL and encodes an APETALA2 (AP2) transcription factor (Endo and Gill 1996; Simons et al. 2006). The Q allele arose following a spontaneous mutation to the microRNA172-binding region of the q allele during wheat evolution (Simons et al. 2006). Q influences many domestication-related traits, including threshability, spike morphology, plant height, rachis fragility, and flowering time (Förster et al. 2013; Faris et al. 2014; Xie et al. 2018; Jiang et al. 2019). Moreover, Q is an ideal target for wheat breeders because its favorable alleles can increase GPC, grain size, and grain yield (Xu et al. 2018; Chen et al. 2022; Guo et al. 2022). Q has homoeoalleles on wheat chromosomes 5BL (5Bq) and 5DL (5Dq). An introduced point mutation in the microRNA172-binding region of 5Dq increases threshability and spike density (Zhao et al. 2018), similar to the Q gene on 5AL (Schmid et al. 2003; Debernardi et al. 2017; Xu et al. 2018). Another study revealed 5Bq is a pseudogene because it does not encode a full-length functional protein (Zhang et al. 2011). A functional 5Bq allele has yet to be reported.

In this study, the S-Cp2 mutant with increased GPC, grain size, and spike density was screened from an ethyl methanesulfonate (EMS)-treated population of common wheat cultivar ‘Shumai482’. The results of a genetic analysis suggested that the mutant phenotype of S-Cp2 was controlled by a single dominant nuclear locus (Gpc-5B), which was mapped to a narrow region on chromosome 5BL. Additionally, TraesCS5B02G486900 (5Bq) was identified as the gene underlying Gpc-5B. According to a haplotype analysis, 5Bq was positively selected during wheat breeding. The study findings have enhanced our understanding of the potential utility of 5Bq for wheat breeding. Furthermore, the germplasm included in this study is useful for optimizing 5Bq via chemical mutagenesis in future studies.

Plant materials and growth conditions

The S-Cp2 mutant with increased GPC, grain size, and spike density was isolated from a common wheat cultivar ‘Shumai482’ population treated with 0.6% EMS (Sigma-Aldrich, St. Louis, MO, USA). S-Cp2 and the corresponding wild-type (WT) control were isolated from an M₉ heterozygous plant. S-Cp2 seeds were treated with 0.4% EMS to obtain revertants.

S-Cp2 was used as the male parent for a cross with ‘Br196’ (common wheat line) to construct a segregating population. The F₂ population derived from the S-Cp2 × ‘Br196’ cross was used for mapping. The F₃ population comprising 2,450 individuals derived from the F₂ heterozygous individuals (S-Cp2 × ‘Br196’) was used for fine-mapping. For the genetic analysis, another two F₂ populations were prepared by crossing S-Cp2 (male) with the common wheat cultivars ‘Mianmai112’ and ‘Shumai133’. Wheat plants were grown at the experimental farm of Sichuan Agricultural University in Wenjiang (103° 51ʹ E, 30° 43ʹ N), with a row spacing of 20 cm × 10 cm. Their spike density was analyzed at GS87 (Zadoks et al. 1974).

To determine the effects of Gpc-5B on agronomic traits and processing quality parameters, a field experiment involving S-Cp2 and WT plants was performed (five replicates and a randomized block design) during the 2021–2022 and 2022–2023 wheat growing seasons. Each replicate was planted in a 2 m × 2 m plot with a row spacing of 20 cm × 5 cm. A nitrogen:phosphorous:potassium (15:15:15) compound fertilizer was applied (750 kg per hectare) before sowing. Pest control and weed management practices were in accordance with those used in local fields.

A total of 400 common wheat materials, including 210 landraces and 190 cultivars (Table S1), were used for the haplotype analysis. Twenty seeds for each material were germinated in Petri dishes, after which leaves were collected from seedlings at GS10 for the subsequent extraction of DNA.

Examination of agronomic traits and processing quality

S-Cp2 and WT plants were randomly selected at GS87 for an analysis of the following agronomic traits: plant height (cm), spike length (cm), spikelet number per spike, grain number per spike, effective tiller number, flag leaf length (cm), and flag leaf width (cm). Spike density was calculated as the ratio of the spike length to the spikelet number per spike. An SC-G automatic seed analyzer (Wanshen, Hangzhou, China) was used to measure the post-harvest TKW (g), grain length (mm), and grain width (mm).

Harvested grain samples were stored at room temperature for 2 months before being milled using the CD1 Laboratory Mill (Chopin, Villeneuve-la-Garenne Cedex, France). The wet gluten content was determined using the Glutomatic 2200 system (Perten, Huddinge, Sweden), whereas the GPC (dry weight), Zeleny sedimentation value, and dough rheological properties were measured using a Kjelec 8400 automatic azotometer (FOSS, Bremen, Denmark), a Zeleny analysis system (CAU-B, Beijing, China), and a standard farinograph (Brabender, Duisburg, Germany), respectively. Bread quality parameters were measured using a BVM6630 volume meter (Perten, Stockholm, Sweden). The glutenin and gliadin contents in whole wheat flour samples were determined using an Agilent 1260 Infinity system with the Zorbax 300SB-C18 stable bond analytical column (4.6 × 250 mm, 5 µm) (Agilent, Palo Alto, CA, USA). Experiments were conducted as described by Zheng et al. (2018) and Wang et al. (2023).

Mapping

Genomic DNA was extracted from fresh leaves according to the cetyltrimethylammonium bromide method (Murray and Thompson 1980). Equal amounts of genomic DNA isolated from 30 homozygous individuals with a compact spike and from 30 plants with a normal spike in the S-Cp2 × ‘Br196’ F₂ population were used to produce two pooled genomic DNA samples for the bulked segregant exome capture sequencing (BSE-seq) analysis, which was performed by Tcuni Bioscience Inc. (Chengdu, China; Zhang et al. 2021; http://www.wheatgmap.org.cn/). Single nucleotide polymorphisms (SNPs) in the two pools were converted into kompetitive allele-specific PCR (KASP) markers, which were used to genotype the mapping population (Ramirez-Gonzalez et al 2015; http://www.polymarker.info/). The PCR amplifications were completed in a 10 µL reaction volume using HiGeno 2× Probe Mix B (JasonGen, Beijing, China). All experiments were performed according to the manufacturer’s instructions. Selected markers along with JoinMap (version 4.0) were used to generate a genetic map (Van Ooijen 2006).

Gene cloning and expression analysis

Total RNA was extracted and then reverse transcribed to cDNA using a Plant RNA Extraction kit (version 1.5) (Biofit, Chengdu, China) and a HiScript III 1st Strand cDNA Synthesis Kit (Vazyme, Nanjing, China), respectively. Both kits were used as recommended by the manufacturers.

Primers (Table S2) were designed according to the ‘Chinese Spring’ and ‘Kenong 9024’ reference sequences (IWGSC 2018; Shi et al. 2022) using Premier 5.0 (Premier Biosoft, San Francisco, CA, USA). PCR amplifications were performed in a 50 µL reaction volume using Phanta Mix Super-Fidelity DNA Polymerase P505 (Vazyme) and a Veriti™ 96-Well Thermal Cycler. The PCR conditions were as follows: 95°C for 5 min; 35 cycles of 95°C for 30 s, 60°C for 30 s, and 72°C for 90 s; 72°C for 10 min; and 12°C (hold). Amplified target fragments were inserted into the pCE2 TA/Blunt-Zero vector using the 5 min TA/Blunt-Zero Cloning Kit (Vazyme). Positive colonies were sequenced by Sangon Biotech (Chengdu, China). The cloning and sequencing experiments were repeated at least three times. Sequences were analyzed using DNAMAN (version 8) (Lynnon Biosoft, San Ramon, CA, USA).

S-Cp2 and WT plants were grown in a glasshouse with a 12-h light (25°C):12-h dark (20°C) cycle. Root, stem, and leaf samples were collected at GS13. The 5Bq expression levels in S-Cp2 and WT plants were analyzed by qRT-PCR, which was completed using the Hieff® qPCR SYBR Green Master Mix (Yeasen Biotechnology, Shanghai, China), with wheat GAPDH (GenBank No. XM-044566753) and β-tubulin (GenBank No. NM-001427965) genes selected as the reference controls for normalizing expression data (Table S2). All experiments were completed according to the manufacturer’s instructions.

Statistical analysis

Data were calculated and compiled using Excel 2010 (Microsoft 2010, Redmond, WA, USA). IBM SPSS Statistics 26 (SPSS Inc., Chicago, IL, USA) was used for Student’s t-test as well as the Chi-squared (χ²) test and analysis of variance. Data were recorded as the mean ± standard deviation.

GPC, grain size, and spike density increased in S-Cp2

The agronomic traits and processing quality parameters of S-Cp2 and its WT control were evaluated in the 2021–2022 and 2022–2023 growing seasons. The comparison with the WT control revealed grain length, grain width, TKW, and spike density were higher in S-Cp2, whereas the opposite trend was observed for volume weight, plant height, spike length, spikelet number per spike, and grain number per spike (Fig. 1; Tables 1 and 2).

Table 1

Comparison of the agronomic traits of *S-Cp2* and the WT control
Traits	Growing season	WT	S-Cp2	E	G	E × G
Plant height (cm)	2021‒2022	72.30 ± 1.51	49.43 ± 1.96**	2365.86**	6423.19**	85.30**
Plant height (cm)	2022‒2023	82.39 ± 1.92	64.24 ± 1.81**	2365.86**	6423.19**	85.30**
Spike length (cm)	2021‒2022	12.37 ± 0.91	6.53 ± 0.50**	0.03	4267.80**	10.78**
Spike length (cm)	2022‒2023	12.69 ± 0.74	6.24 ± 0.37**	0.03	4267.80**	10.78**
Spikelet number per spike	2021‒2022	21.26 ± 0.90	20.74 ± 1.26*	36.40**	23.63**	3.30
Spikelet number per spike	2022‒2023	22.60 ± 1.09	21.46 ± 1.50**	36.40**	23.63**	3.30
Spike density	2021‒2022	1.72 ± 0.10	3.19 ± 0.25**	276.80**	58.78**	37.90**
Spike density	2022‒2023	1.78 ± 0.09	3.44 ± 0.15**	276.80**	58.78**	37.90**
Grain number per spike	2021‒2022	58.02 ± 5.88	44.70 ± 2.40**	361.21**	1366.07**	132.66**
Grain number per spike	2022‒2023	54.10 ± 2.91	28.72 ± 2.45**	361.21**	1366.07**	132.66**
Grain length (cm)	2021‒2022	7.34 ± 0.22	7.48 ± 0.24*	18.19**	26.27**	0.61
Grain length (cm)	2022–2023	7.45 ± 0.20	7.64 ± 0.22**	18.19**	26.27**	0.61
Grain width (cm)	2021‒2022	3.29 ± 0.12	3.69 ± 0.15**	23.84**	192.26**	19.59**
Grain width (cm)	2022‒2023	3.49 ± 0.12	3.70 ± 0.21**	23.84**	192.26**	19.59**
Leaf length (cm)	2021‒2022	18.17 ± 1.65	21.91 ± 2.70*	6725.31**	55.58**	84.86**
Leaf length (cm)	2022‒2023	19.65 ± 2.05	22.35 ± 2.37**	6725.31**	55.58**	84.86**
Leaf width (cm)	2021‒2022	2.12 ± 0.14	1.65 ± 0.13**	1580.20**	1051.49**	3407.83**
Leaf width (cm)	2022‒2023	1.85 ± 0.18	1.45 ± 0.11**	1580.20**	1051.49**	3407.83**
Thousand kernel weight (g)	2021‒2022	50.77 ± 0.79	55.97 ± 0.60**	10.02**	440.06**	9.46**
Thousand kernel weight (g)	2022‒2023	50.80 ± 0.46	57.79 ± 0.70**	10.02**	440.06**	9.46**
Productive tiller number	2021‒2022	3.86 ± 0.86	3.98 ± 0.94	5112.06**	34.84**	29.16**
Productive tiller number	2022‒2023	4.14 ± 1.03	4.30 ± 1.05	5112.06**	34.84**	29.16**
*, P < 0.01; , P < 0.05; E, environment; G, genotype; E × G, interaction between the environment and genotype. Data are presented as the mean ± standard deviation.

Table 2

Comparison of the processing quality parameters of *S-Cp2* and the WT control
Traits	Growing season season	WT	S-Cp2	E	G	E × G
Grain protein content (%, dry weight)	2021‒2022	12.50 ± 0.37	14.81 ± 0.38**	354.72**	142.60**	1.19
Grain protein content (%, dry weight)	2022‒2023	16.27 ± 0.55	19.05 ± 0.57**	354.72**	142.60**	1.19
Zeleny sedimentation value (mL)	2021‒2022	14.22 ± 0.53	17.41 ± 0.40**	1127.91**	87.79**	1.05
Zeleny sedimentation value (mL)	2022‒2023	24.84 ± 0.83	27.40 ± 0.87**	1127.91**	87.79**	1.05
Wet gluten content (%)	2021‒2022	20.77 ± 1.10	25.20 ± 1.04**	689.96**	149.31**	8.90**
Wet gluten content (%)	2022‒2023	31.95 ± 0.86	39.25 ± 1.25**	689.96**	149.31**	8.90**
Water absorption (%)	2021‒2022	55.62 ± 0.46	59.12 ± 0.83**	2.08	190.10**	9.24**
Water absorption (%)	2022‒2023	55.10 ± 0.67	60.58 ± 0.88**	2.08	190.10**	9.24**
Development time (min)	2021‒2022	1.49 ± 0.08	2.03 ± 0.09**	173.17**	294.95**	72.92**
Development time (min)	2022‒2023	1.78 ± 0.16	3.40 ± 0.20**	173.17**	294.95**	72.92**
Volume weight (g)	2021‒2022	799.90 ± 5.85	784.90 ± 3.96**	17.88**	244.15**	52.97**
Volume weight (g)	2022‒2023	805.38 ± 3.01	764.22 ± 2.37**	17.88**	244.15**	52.97**
Loaf height (mm)	2021‒2022	54.20 ± 2.59	64.00 ± 4.18**	2.06	49.69**	0.88
Loaf height (mm)	2022‒2023	55.00 ± 4.00	67.80 ± 3.35**	2.06	49.69**	0.88
Loaf volume (mL)	2021‒2022	166.00 ± 13.04	198.40 ± 16.44**	0.91	31.87**	0.11
Loaf volume (mL)	2022‒2023	169.80 ± 12.21	206.20 ± 12.38**	0.91	31.87**	0.11
*, P < 0.01; , P < 0.05; E, environment; G, genotype; E × G, interaction between the environment and genotype. Data are presented as the mean ± standard deviation.

To determine whether Gpc-5B affects wheat processing quality, quality-related parameters were compared between S-Cp2 and the WT control. In addition to GPC, the gliadin, high-molecular-weight glutenin subunit (HMW-GS), low-molecular-weight glutenin subunit (LMW-GS), and glutenin contents were significantly higher for S-Cp2 than for the WT control (Fig. 2c). As expected, the Zeleny sedimentation value, wet gluten content, development time, water absorption, and loaf volume were higher for S-Cp2 than for the WT control (Fig. 2a, b; Table 2).

Mutant phenotype of S-Cp2 was controlled by a single dominant nuclear locus

S-Cp2 was reciprocally backcrossed with ‘Shumai482’ to clarify the genetic basis of the mutant phenotype. All BC₁F₁ plants had a compact spike, suggesting that the mutant phenotype was controlled by at least one nuclear gene. The mutant traits of S-Cp2, especially the increases in GPC, grain size, and spike density, were not separated in the BC₁F₂ population (S-Cp2 × ‘Shumai482’; 400 individuals), implying these traits were controlled by the same locus. To facilitate genetic research, compact spike was selected as the target trait for the subsequent χ² test. S-Cp2 was crossed with three common wheat lines (i.e., ‘Br196’, ‘Mianmai112’, and ‘Shumai133’). In the S-Cp2 × ‘Br196’ F₂ population, 134 plants had a compact spike and 46 plants had a normal spike, which was consistent with the theoretical 3:1 segregation ratio (χ² = 0.03 < χ²_0.05 = 3.84). Similarly, the corresponding ratios in the S-Cp2 × ‘Mianmai112’ F₂ population (207 plants with a compact spike and 73 plants with a normal spike; χ² = 0.17 < 3.84) and the S-Cp2 × ‘Shumai133’ F₂ population (174 plants with a compact spike and 55 plants with a normal spike; χ² = 0.12 < 3.84) also fit the expected 3:1 segregation ratio. These results suggest the mutant phenotype of S-Cp2 was controlled by a single dominant nuclear locus (Gpc-5B).

Mapping of Gpc-5B

The F₂ population derived from the S-Cp2 × ‘Br196’ cross was used to map Gpc-5B according to the BSE-seq analysis. After filtering for read-depth quality, 16,900 SNPs between the wild bulk and mutant bulk were concentrated in the 655–665 Mb region of wheat chromosome 5B (Fig. S1a). The analysis of Euclidean distance revealed a continuous distribution peak on chromosome 5BL (Fig. S1b), indicating that Gpc-5B was located on 5BL. Using KASP markers (Table S2), Gpc-5B was mapped between markers KASP5771 and KASP6597, with a genetic distance of 1.5 cM (Fig. 3a, b).

To more precisely map Gpc-5B, 130 F₂ heterozygous plants from the S-Cp2 × ‘Br196’ cross were self-pollinated to generate an F₃ population consisting of 2,450 individuals. Six newly developed KASP markers (Table S2) were used for screening recombinants (RM1–RM6). Finally, Gpc-5B was delimited to an 87.24 kb interval between markers KASP58070 and KASP58158 (Fig. 3c, d). This region included three high-confidence predicted genes (TraesCS5B02G486800, TraesCS5B02G486900, and TraesCS5B02G487000; Fig. 3e).

5 Bq is the gene underlying the Gpc-5B locus

Among the three high-confidence predicted genes, TraesCS5B02G486900 (5Bq), which is homologous to the Q gene on 5AL, was hypothesized to be the candidate gene for Gpc-5B. To test this hypothesis, 5Bq cDNA and genomic sequences were cloned for both S-Cp2 and ‘Shumai482’. A missense mutation (G-to-A) was detected in the microRNA172-binding site of the 5Bq coding sequence in S-Cp2 (Figs S2–S4), resulting in an amino acid change from alanine to threonine. This mutant 5Bq allele in S-Cp2 was named 5BQ⁴ (GenBank No. PP584578). A qRT-PCR analysis of the roots, stems, and leaves indicated 5BQ⁴ transcript levels in S-Cp2 were significantly higher (P < 0.01) than 5Bq transcript levels in ‘Shumai482’ (Fig. 2d).

To further assess whether 5Bq is the gene responsible for the mutant phenotype, S-Cp2 seeds were treated with EMS to obtain revertants, among which three (S-Cp2-rev1, S-Cp2-rev2, and S-Cp2-rev3) had a normal spike (Fig. 4). The mutant 5Bq alleles in S-Cp2-rev1 (nonsense mutation revealed by the comparison with 5BQ⁴), S-Cp2-rev2 (nonsense mutation), and S-Cp2-rev3 (missense mutation) were designated as 5BQ⁴-S3 (GenBank No. PP584579), 5BQ⁴-S201 (GenBank No. PP584581), and 5BQ⁴-N9 (GenBank No. PP584580), respectively (Figs S2–S4).

Haplotype analysis

To clarify haplotype variations, 5Bq coding sequences in 30 common wheat accessions were cloned and analyzed (Table S1). Three haplotypes (haplotypes 1 [functional], 2 [pseudogene], and 3 [pseudogene]) were identified (Figs S5 and S6). Two specific markers (5BqDNA-1 and 5BqDNA-3) were developed to distinguish haplotypes (Fig. 5). We performed a haplotype analysis of 5Bq in 210 landraces and 190 cultivars (Table S1). Notably, the proportion of functional haplotype 1 increased from 4.76% in landraces to 39.48% in modern cultivars.

S-Cp2 mutant phenotype is due to an overexpressed 5Bq allele

Common wheat is a hexaploid (AABBDD; 2n = 6x = 42) that contains three homologous genomes. The overexpression of Q on chromosome 5AL reportedly leads to increases in GPC, grain size, and spike density, but a decrease in plant height (Mallory et al. 2006; Debernardi et al. 2017; Xu et al. 2018). MicroRNAs regulate gene expression mainly by eliminating DNA, cleaving mRNA, and repressing translation. The Q gene on 5AL has a microRNA172-binding site in its tenth exon. Point mutations in the microRNA172-binding site disrupt the interaction between microRNA172 and Q transcripts. The resulting increase in Q expression affects multiple traits, including GPC, grain size, and spike density (Mallory et al. 2006; Simons et al. 2006; Debernardi et al. 2017; Liu et al. 2020; Xu et al. 2018).

S-Cp2 is a common wheat mutant with increased GPC, grain size, and spike density (Fig. 1). The gene controlling these traits was mapped to an 87.24 kb interval on chromosome 5BL, where 5Bq (homologous to Q on 5AL) is located. One missense mutation was detected within the microRNA172-binding site of 5Bq in S-Cp2 (i.e., 5BQ⁴ allele). As expected, 5BQ⁴ transcription in S-Cp2 exceeded 5Bq transcription in the WT control (Fig. 2d). Furthermore, the mutants with non-functional 5Bq alleles (5BQ⁴-S3 and 5BQ⁴-S201; Figs S2–S4) had normal plant morphological characteristics, similar to those of ‘Shumai482’. These observations suggest 5BQ⁴ is an overexpressed 5Bq allele that is responsible for the mutant phenotype of S-Cp2.

5Bq is a valuable target for breeders

A previous study identified 5Bq as a pseudogene in ‘Chinese Spring’ (haplotype 3) and in the tetraploid Triticum turgidum (haplotype 2) (Zhang et al. 2011). In the current study, we identified a functional 5Bq haplotype (haplotype 1; Figs S5 and S6; Table S1). The proportion of haplotype 1 increased from 4.76% in Chinese landraces to 39.48% in Chinese modern cultivars, suggestive of the long-term existence of haplotype 1 in cultivated wheat as well as the gradual accumulation of this haplotype during the wheat breeding process. Compared with the plants with non-functional alleles (5BQ⁴-S3 and 5BQ⁴-S201; Figs S2–S4), the plants with 5Bq were slightly shorter (Fig. 4), suggesting that 5Bq may be useful for decreasing the risk of lodging. Therefore, we speculate that haplotype 1 was selected by breeders to decrease plant height. Notably, the overexpressed allele (5BQ⁴) of haplotype 1 may be used to increase GPC, grain size, and spike density, while also further decreasing plant height (Figs. 1 and 2). These results reflect the potential utility of 5Bq for wheat breeding. However, there is a need for identifying additional favorable 5Bq allele(s) on the basis of 5BQ⁴.

Generation of favorable 5Bq alleles for breeding

Similar to the reported Q^c1 allele on 5AL (Xu et al. 2018), 5BQ⁴ on 5BL is associated with a compact spike (Fig. 1), which is an unfavorable trait in most wheat-growing areas. Introducing amino acid changes in the AP2 domain of the protein encoded by Q on 5AL can lead to decreases in spike density (Simon et al. 2006; Greenwood et al. 2017; Chen et al. 2022). Hence, EMS was used to generate the favorable Q^c1-N8 allele from Q^c1 (Chen et al. 2022). A comparison with Q^c1 revealed Q^c1-N8 contains a missense mutation in its second AP2-encoding domain; this mutation results in simultaneous increases in GPC and grain yield (Chen et al. 2022). Similarly, we obtained 5BQ⁴-N9 by introducing a point mutation in the first AP2-encoding domain of 5BQ⁴ (Figs S2–S4). Wheat plants carrying 5BQ⁴-N9 had much better agronomic traits than S-Cp2 (Fig. 4), indicating its potential value for wheat breeding.

S-Cp2 is a common wheat mutant with increased GPC, grain size, and spike density. Our genetic analysis indicated that the changes to these traits are controlled by a single dominant locus (Gpc-5B) on chromosome 5BL. More specifically, Gpc-5B was precisely mapped to an 87.24 kb interval containing three high-confidence predicted genes, including 5Bq (TraesCS5B02G486900). One missense mutation was found within the microRNA172-binding site of 5Bq (i.e., 5BQ⁴ allele), which is responsible for the mutant phenotype of S-Cp2. As expected, the 5BQ⁴ transcript level in S-Cp2 was significantly higher than the 5Bq transcript level in ‘Shumai482’. According to a haplotype analysis, 5Bq was positively selected during breeding. Considered together, the research findings demonstrate the value of 5Bq for wheat breeding, while also highlighting the potential utility of the favorable 5Bq allele in breeding programs.

Acknowledgments

We thank Liwen Bianji (Edanz) (www.liwenbianji.cn) for editing the English text of a draft of this manuscript.

Author contributions

PFQ and QC prepared plant materials. QCL conducted experiments and drafted this manuscript. YL, JZ, ZRG, SLC, MT, YZF, RL, TG, and LK examined phenotypes and analyzed data. YFJ, GYC, QTJ, YZZ, QX, JM, and YMW supervised the study and revised the manuscript. YLZ, QC, and PFQ designed the experiments, supervised the study, participated in data analysis, and extensively revised this manuscript.

Funding

This study was supported by the National Key Research and Development Program of China (2023YFD1200404) and the National Natural Science Foundation of China (32072054).

Compliance with ethical standards

Conflict of interest

All authors declare that there is no conflict of interest.

Ethical standards

All experiments and data analyses were conducted in Sichuan. All authors contributed to the study and approved the final version of the manuscript, which has not been submitted to any other journal.

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Fig.S1new.jpg
Fig. S1 Mapping of the Gpc-5B locus using SNPs from the exome capture sequencing of two DNA pools derived from plants with a compact spike and plants with a normal spike. (a) SNP density index between the two DNA pools. Each vertical line represents the number of SNPs in a 1 Mb segment. (b) Euclidean distance (ED) analysis. The upper and lower figures were drawn on the basis of the fitted and original data, respectively. Dots represent SNPs.
Fig.S2new.jpg
Fig. S2 Alignment of the deduced amino acid sequences encoded by 5Bq (GenBank No. PP584577), 5BQ⁴ (PP584578), 5BQ⁴-S3 (PP584579), 5BQ⁴-S201 (PP584581), and 5BQ⁴-N9 (PP584580). Seven previously described conserved domains (motif 1, motif 2, nuclear localization signal, AP2 domain R1, AP2 domain R2, motif 3, and AASSGF box) are presented. Asterisks indicate the stop codon.
Fig.S3new.jpg
Fig. S3 Alignment of the coding sequences of 5Bq (GenBank No. PP584577), 5BQ⁴ (PP584578), 5BQ⁴-S3 (PP584579), 5BQ⁴-S201 (PP584581), and 5BQ⁴-N9 (PP584580). Red arrows indicate point mutations.
Fig.S4new.jpg
Fig. S4 Alignment of the DNA sequences of 5Bq (GenBank No. PP584577), 5BQ⁴ (PP584578), 5BQ⁴-S3 (PP584579), 5BQ⁴-S201 (PP584581), and 5BQ⁴-N9 (PP584580). Red arrows indicate point mutations.
Fig.S5new.jpg
Fig. S5 Differences in the DNA sequences of 5Bqhaplotype 1 (GenBank No. PP584577), haplotype 2 (PP584582), and haplotype 3 (PP584583).
Fig.S6new.jpg
Fig. S6 Differences in the coding sequences of 5Bq haplotype 1 (GenBank No. PP584577), haplotype 2 (PP584582), and haplotype 3 (PP584583).
TableS1new.xlsx
Supplementary Tables Table S1. Details regarding the wheat materials used for the haplotype analysis.
TableS2new.xlsx
Table S2. Details regarding the primers used in this study.

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Fine-mapping and validation of Gpc-5B as the locus responsible for increases in the grain protein content, grain size, and spike density in common wheat (Triticum aestivum L.)

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