Hongxia Liu,Xuemei Si,Zhenyu Wang,Liangjing Cao,Lifeng Gao,Xiaolong Zhou,Wenxi Wang,Ke Wang,Chengzhi Jiao,Lei Zhuang,Yunchuan Liu,Jian Hou,Tian Li,Chenyang Hao,Weilong Guo,Jun Liu,Xueyong Zhang
TaTPP‐7A positively feedback regulates grain filling and wheat grain yield through T6P‐SnRK1 signalling pathway and sugar–ABA interaction Hongxia Liu et al.
wheat,yield,grain filling,T6P,sucrose feedback regulation,ABA
Summary Grain size and filling are two key determinants of grain thousand‐kernel weight (TKW) and crop yield, therefore they have undergone strong selection since cereal was domesticated. Genetic dissection of the two traits will improve yield potential in crops. A quantitative trait locus significantly associated with wheat grain TKW was detected on chromosome 7AS flanked by a simple sequence repeat marker of Wmc17 in Chinese wheat 262 mini‐core collection by genome‐wide association study. Combined with the bulked segregant RNA‐sequencing (BSR‐seq) analysis of an F2 genetic segregation population with extremely different TKW traits, a candidate trehalose‐6‐phosphate phosphatase gene located at 135.0 Mb (CS V1.0), designated as TaTPP‐7A, was identified. This gene was specifically expressed in developing grains and strongly influenced grain filling and size. Overexpression (OE) of TaTPP‐7A in wheat enhanced grain TKW and wheat yield greatly. Detailed analysis revealed that OE of TaTPP‐7A significantly increased the expression levels of starch synthesis‐ and senescence‐related genes involved in abscisic acid (ABA) and ethylene pathways. Moreover, most of the sucrose metabolism and starch regulation‐related genes were potentially regulated by SnRK1. In addition, TaTPP‐7A is a crucial domestication‐ and breeding‐targeted gene and it feedback regulates sucrose lysis, flux, and utilization in the grain endosperm mainly through the T6P‐SnRK1 pathway and sugar–ABA interaction. Thus, we confirmed the T6P signalling pathway as the central regulatory system for sucrose allocation and source–sink interactions in wheat grains and propose that the trehalose pathway components have great potential to increase yields in cereal crops.
TaTPP‐7A positively feedback regulates grain filling and wheat grain yield through T6P‐SnRK1 signalling pathway and sugar–ABA interaction Hongxia Liu et al.

Grain size and filling are two key determinants of grain thousand‐kernel weight (TKW) and crop yield, therefore they have undergone strong selection since cereal was domesticated. Genetic dissection of the two traits will improve yield potential in crops. A quantitative trait locus significantly associated with wheat grain TKW was detected on chromosome 7AS flanked by a simple sequence repeat marker of Wmc17 in Chinese wheat 262 mini‐core collection by genome‐wide association study. Combined with the bulked segregant RNA‐sequencing (BSR‐seq) analysis of an F2 genetic segregation population with extremely different TKW traits, a candidate trehalose‐6‐phosphate phosphatase gene located at 135.0 Mb (CS V1.0), designated as TaTPP‐7A, was identified. This gene was specifically expressed in developing grains and strongly influenced grain filling and size. Overexpression (OE) of TaTPP‐7A in wheat enhanced grain TKW and wheat yield greatly. Detailed analysis revealed that OE of TaTPP‐7A significantly increased the expression levels of starch synthesis‐ and senescence‐related genes involved in abscisic acid (ABA) and ethylene pathways. Moreover, most of the sucrose metabolism and starch regulation‐related genes were potentially regulated by SnRK1. In addition, TaTPP‐7A is a crucial domestication‐ and breeding‐targeted gene and it feedback regulates sucrose lysis, flux, and utilization in the grain endosperm mainly through the T6P‐SnRK1 pathway and sugar–ABA interaction. Thus, we confirmed the T6P signalling pathway as the central regulatory system for sucrose allocation and source–sink interactions in wheat grains and propose that the trehalose pathway components have great potential to increase yields in cereal crops.

Bread wheat (Triticum aestivum L.) is the most important staple food in the world that provides approximately 20% of calories for the global population (Pfeifer et al., 2014). In China, wheat holds the third position in crop productivity and contributes about 130 million tonnes of grain per year (http://www.fao.org/worldfoodsituation/csdb/en/). However, the world population is expected to reach approximately 9 billion by 2050, and it demands at least a 50% increase in the production of major crops (Godfray et al., 2010), including wheat, rice (Oryza sativa L.), and maize (Zea mays L.). Therefore, there is an urgent need to discover novel key genes and elucidate the complicated molecular mechanisms of sustainably improving yield for developing high‐yielding and widely adapted wheat varieties. In wheat, yield depends primarily on spike number per unit area, grain number per spike, and thousand kernel weight (TKW) (Xiao and He, 2003). Among these, TKW is the most stable and heritable characteristic (Xiao and He, 2003) and is mainly determined by grain size (volume) and grain filling (plumpness) (Sakamoto and Matsuoka, 2008). Grain size is characterized by a combination of grain length (GL), grain width (GW), grain thickness (GT), and grain length‐to‐width ratio, which positively affects yield (Zuo and Li, 2014). In rice, more than 400 quantitative trait loci (QTLs) associated with grain traits have been identified, and dozens of related genes, such as Dwarf1 (Ashikari et al., 1999), GS3 (Fan et al., 2006), GW2 (Song et al., 2007), GW5 (Weng et al., 2008), GS5 (Li et al., 2011), GW8 (Wang et al., 2012b), and GIF1 (Wang et al., 2008), have been cloned. These genes mainly regulate cell division, proliferation, and elongation and are involved in multiple signalling pathways, such as ubiquitination‐mediated proteasomal degradation, G protein signalling, MAPK signalling, and phytohormone signalling (Zuo and Li, 2014), indicating a complex mechanism regulating grain size in crops. However, studies on the molecular cloning of genes associated with grain weight in wheat are limited. Currently, only 15 genes, including TaGW2 (6A, 240.3 Mb; Su et al., 2011), TaGS5‐3A (3A, 188.2 Mb; Ma et al., 2016), TaCKX6‐D1 (3D, 106.2 Mb; Zhang et al., 2012), TaGASR7 (7A, 176.0 Mb; Zhang et al., 2015a), TaTGW‐7A (7A, 211.6 Mb; Hu et al., 2016), TaGW8 (7A, 257.3 Mb; Yan et al., 2019), TaGW7 (2A, 139.7 Mb; Wang et al., 2019a), TaDA1 (2A, 8.3 Mb; Liu et al., 2020), and TaIAA21 (7A, 488.5 Mb; Jia et al., 2021), have been reported to contribute to grain size and/or weight in wheat. Research has also indicated that the mechanism regulating grain size is conserved across cereal crops (Zuo and Li, 2014); however, the mechanism underlying an increase in grain yield, especially grain filling, in rice, wheat, and other cereal crops remains elusive. Grain filling is a complex process that involves the remobilization of photoassimilates, mainly sucrose, to the developing grains, where sucrose is converted to starch through a series of enzymatic reactions. In wheat endosperm, starch content accounts for 65%–80% of the mature grains; therefore, grain filling is a crucial determinant of wheat yield. Besides, sucrose, the primary photosynthetic product that moves a long distance from green leaves to various sink organs via the phloem, is the substrate of starch synthesis and therefore plays a vital role in determining grain TKW and wheat yield (Figueroa and Lunn, 2016; Hou et al., 2014); however, the specific molecular mechanism regulating sucrose unloading and metabolism in grains remains largely unknown. Therefore, finding the key regulator of sucrose metabolism will help for the regulation of yield improvement in wheat. In recent years, trehalose (Tre) metabolism components, especially trehalose‐6‐phosphate (T6P), have gained much research attention due to their roles in regulating plant growth and development, as well as the newly identified potential role of T6P in regulating yield in major cereal crops (Nuccio et al., 2015; Paul et al., 2020; Zhang et al., 2017). In higher plants, Tre and T6P, which exist in trace amounts, are formed mainly via a two‐step pathway and serve as energy sources and signalling components (Paul, 2008; Schluepmann et al., 2003). First, T6P is formed from UDP‐glucose and glucose‐6‐phosphate (G6P) under the action of trehalose‐6‐phosphate synthase (TPS). Subsequently, trehalose‐6‐phosphate phosphatase (TPP) dephosphorylates T6P to Tre. However, studies have indicated that T6P is more important than Tre as a sugar signal in plants, which acts as a key and specific signal for sucrose abundance and carbon availability (O'Hara et al., 2013; Paul, 2008; Schluepmann et al., 2003). T6P has been implicated in sucrose and starch regulation in Arabidopsis thaliana leaves (Lunn et al., 2006; Schluepmann and Paul, 2009) and wheat grains (Martínez‐Barajas et al., 2011). In addition, several studies have highlighted the central role of T6P in regulating crop productivity. A RAMOSA3 (RA3) gene encoding a TPP protein in maize determines inflorescence architecture (Satoh‐Nagasawa et al., 2006). In addition, overexpression (OE) of a rice TPP gene in the developing maize ear increased kernel set and harvest index and improved yield under drought conditions (Nuccio et al., 2015). Meanwhile, in wheat, changes in the single nucleotide polymorphism (SNP) in the TaTPP‐6AL genome have been correlated with yield (Zhang et al., 2017). However, the exact molecular basis of T6P‐mediated regulation of sucrose level, sugar flow from T6P to starch synthesis, and eventually yield improvement remains unclear yet. In the present study, we used a genome‐wide association study (GWAS) in Chinese 262 mini‐core collection (MCC) combined with bulked segregant RNA‐sequencing (BSR‐seq) analysis in an F2 biparental progeny with extremely different TKW traits to identify the key genes associated with TKW and regulating sucrose metabolism in wheat grain. We detected a gene, TaTPP‐7A ( Triticum aestivum trehalose‐6‐phosphate phosphatase), on chromosome 7AS significantly associated with grain TKW and found it as a member of HAD superfamily IIB subfamily of the Tre pathway. OE of TaTPP‐7A in wheat resulted in higher TKW, longer grains, and quicker grain filling, whereas the TaTPP‐7A RNAi lines or gene‐edited mutants displayed lower TKW, shorter grains, and slower filling. Results demonstrated that TaTPP‐7A feedback regulates sucrose lysis, flux, and utilization in the grain endosperm and consequently affects grain filling and yield mainly through the T6P‐SnRK1 (sucrose non‐fermenting (SNF1)‐related protein kinase 1) pathway and sugar–ABA interaction. The work highlights the importance of the T6P signalling pathway, and established it as the central regulatory system for sucrose allocation and source–sink interactions in wheat grains and proposes TaTPP‐7A and Tre pathway components as candidates for improving grain size and yield in wheat.

Chinese 262 MCC, representing more than 70% of the diversity in Chinese wheat and with highly heritable, domesticated traits, have been proven to be a suitable natural population for primary QTL mapping or gene identification in wheat (Wang et al., 2012a). In the present study, a QTL significantly associated with TKW was identified on Chr.7AS (−log10 P > 4.07) under four environments by GWAS among 262 MCC (Figure 1a). During 2005–2006, this locus was anchored by four peak SNPs closely clustered within a 339 bp distance (Table S1). The associated physical distance of the peaked SNPs (−log10 P > 4.38, at 127.76 (CS V1.0)/131.21 (CS V2.1) Mb) was estimated as 8.88 Mb when r 2 of the linkage disequilibrium (LD) decayed to 0.2 (Figure 1b). Therefore, we choose the 9.0 Mb physical distance (at 127–136 Mb, CS V1.0) as the candidate region to identify the associated candidate genes. We found that a simple sequence repeat (SSR) marker of Wmc17, previously reported significantly associated with TKW among 262 MCC under four environments by Wang et al. (2012a), falls within this reasonable LD attenuation range and has a physical distance of about 7.4 Mb to the peaked GWAS loci. Compared with the other unfavoured alleles, the favoured allele of the Wmc17 marker showed a mean TKW difference of 5.32 g (P < 0.001) and explained more than 19.62% of the total phenotypic variation (Wang et al., 2012a). In addition, as an SSR marker, we further proved that Wmc17 was only located on the short arm of Chr.7A at 135.0/138.61 Mb (CS V1.0/2.1) (Figures S1, S2 and Table S2). Thus, we assumed that one major TKW‐associated candidate gene was located near or within this GWAS loci. To further solidify the above speculation and identify the candidate genes, an F2 segregation population with a mean TKW difference of 35.37 g between the two parents was developed (Figure 1c, Figure S3), followed by BSR‐seq analysis in developing grains to identify the candidate differentially expressed genes (DEGs) in the associated interval (127–136/131–140 Mb for Chines spring (CS) V1.0/V2.1, respectively) using two bulks with extremely different TKW. Totally, we identified 10 149 DEGs from the two parents (PH/PL) and the two bulks. Among them, 9276 DEGs were detected between PH and PL and 1255 between the two bulks. The KEGG pathway enrichment analysis using all the DEGs highlighted the starch and sucrose metabolism pathway (P < 0.0001), which was the most predominant both in parents (177/3346) and bulks (47/464) among the top 20 enriched pathways (Figure S4). The analysis of the expression pattern of the DEGs among the parent pool and the bulks identified only three DEGs (red circle), with a significant expression difference and the same expression trend, as candidates in the associated genomic interval (Figure 1d). Gene annotation showed that the first candidate TraesCS7A03G0413600 encodes a mitochondrial chaperone protein DNA J1 in Arabidopsis, which is uncharacterized in wheat; genotyping showed no SNP variation in this gene within the landraces (Figure 1f). The second candidate TraesCS7A03G0422300 (TaTPP‐7A) encodes a TPP in rice and wheat and is involved in carbohydrate transport and metabolism pathway (GO: 0005975); genotyping showed that this gene formed three haplotypes in the Chinese landraces and modern cultivars and was significantly associated with TKW under four environments (Figure 1f). In 2005, the differences in TKW between the highest (Haplotype 1 (Hap 1)) and the lowest (Hap 2) TaTPP‐7A haps were about 4.26 and 4.74 g for the landraces and the modern cultivars, respectively (P < 0.001). The third candidate TraesCS7A03G0422700 encodes an AP2 domain‐containing ethylene‐responsive transcription factor (ERF) in Arabidopsis and is uncharacterized in wheat; genotyping showed no SNP variation of this gene in the 262 MCC. Moreover, among the three candidate genes, the π of TraesCS7A03G0422300 (TaTPP‐7A) was much higher in landraces than in modern cultivars and fell within the breeding selection sweep in this interval (Figure 1e). Thus, we assumed TaTPP as the likely candidate. For further confirmation, we analysed the expression patterns of the three candidate genes by RNA‐seq in the developing grains (10 days postanthesis (DPA), derived from F2 segregation progeny) with a mean TKW difference of 3.12–4.25 g between the high‐TKW and the low‐TKW ones. As shown in Figure 1g, only TaTPP‐7A showed a high expression difference between these two sets of grains (P < 0.05), consistent with the BSR‐seq data (Figure S5). Digital gene expression transcriptome data obtained from different tissues or different developmental stage grains of CS confirmed that TaTPP‐7A is the only gene specifically expressed in wheat grains compared with the other genes located within the 2 Mb region (134.0–136.0/137.61–139.61 Mb for CS V1.0/V2.1, respectively) near the Wmc17 (Figure S6). These observations confirmed TaTPP‐7A as the TKW‐associated candidate gene in this interval and were used for further confirmation by transgenic experiments.

Analysis of the predicted protein sequences revealed that TaTPP‐7A and its homoeologs TaTPP‐7B/7D are members of the IIB subfamily of HAD superfamily (http://www.ebi.ac.uk/InterProScan/), with the conserved TPP domains (Figure 2a). The genomic structures of the three homoeologous TaTPP‐7A/7B/7D, were all comprised of ten exons and nine introns with the genomic sequence length of 2162, 2181 and 2118 bp, respectively. Full‐length cDNA sequences of TaTPP‐7A/7B/7D were 1083, 1092, and 1089 bp, respectively, which encoded 361, 364, and 363 amino acids (aa) (Figure 2b). The alignment of the TaTPP‐7A/7B/7D protein sequences showed a high 97.53% similarity among them, with a 100% similarity for the four enzyme active sites, motifs I (DYDGTL, 110–115), II (TG, 148–149), III (K, 270), and IV (GD‐nDh, 295–296 and 300), indicating a conserved and redundant function among the three homoeologs (Figure 2a). The phylogenetic tree constructed using the TPP proteins of various species presented wheat in a specific branch for cereals with rice and maize (Figure 2c) together and separated from the adjacent Arabidopsis clade (AtTPPJ and AtTPPI), indicating a new role of TaTPPs in cereals. Further expression analysis of the three homoeologous genes showed high and specific expression of TaTPPs in the young spikes and the developing grains (Figure 2d). The transcript level of TaTPPs in the grain tissues increased towards the filling stage (10–15 DPA), with at least three times higher expression than in the other tissues and developmental stages. Digital expression transcriptome data of CS showed that TaTPPs were specifically expressed in the aleurone layer of grains, and the expression abundance of TaTPP‐7A at the filling stage (10–20 DPA) was much higher than the other two homoeologous genes (Figure S7), validating our results. Further, we found that the expression level of TaTPPs in the high TKW varieties with Hap I was 2–3 times higher than in the low TKW varieties with Hap II (Figure 2e), indicating TaTPP‐7A as a TKW‐associated, functional gene positively related to grain filling in wheat.

Subsequent transgenic experiments showed that the OE of TaTPP‐7A in wheat resulted in stable and significantly greater TKW (P < 0.01), longer GL (P < 0.01 or P < 0.05), and quicker filling (P < 0.01) compared with the WT and RNAi transformants (Figure 3a–d); however, other traits such as plant height (PH), spikelet number (SLN), spike number per plant (SN), and grain number (GN) showed no difference in three environments (Figures S8a and S9). The OE lines showed maximal 11.5 g higher TKW and 0.33 mm longer grains than the wide‐type (WT), while the RNAi lines had 6.9 g lower TKW and 0.32 mm shorter grains. Yield per plant and estimated grain yield of the transgenic OE lines were enhanced by 24% while the RNAi lines declined by 20.4% compared with those of WT in 2017 (Figure S8b; P < 0.01). In addition, grain filling in the OE lines started 2–5 days earlier than in the WT and RNAi ones; the peak filling rate in the OE lines was 10.58% and 35.29% higher than in the WT and RNAi lines, respectively (Figure 3d). Huge differences were detected in TKW and other traits (P < 0.05 and P < 0.01) of the developing grains of the transgenic lines as early as 5 DPA (Figure 3c, Figure S10), with a good linear correlation (R2 = 1) between filling rate and the expression level of TaTPP‐7A in these transgenic lines (Figure 3d). Furthermore, the size changes in the lemma and palea of the transgenic lines confirmed the role of TaTPP‐7A in regulating TKW; the OE of TaTPP‐7A led to wider lemma and palea compared with the WT (P < 0.01; Figure S11), while RNAi resulted in shorter lemma and palea (P < 0.01). Meanwhile, CriTaTPPs (Figure S12) showed a significant 82%, 44.8%, and 28% decrease in GN, SLN, and spike length (SL), respectively, compared with the WT (P < 0.01; Figure 3e–g). Similarly, the K‐TaTPPs also exhibited a significant decrease in grain size, GN, and yield (Figure 3h, Figure S13). These observations suggested that TaTPP‐7A is the TKW‐associated gene within the GWAS loci and positively regulates grain filling in wheat.

Subsequently, to verify the molecular mechanism of TaTPP‐7A regulating TKW or grain filling in wheat, we evaluated the total starch and amylose content in these transgenic lines and analysed the starch granules in the grain endosperm. Results showed that the OE of TaTPP‐7A led to lower amylose content and amylose/amylopectin ratio compared with the WT (P < 0.05), but with no statistically significant difference in the total starch content though it increased by 2.53% compared to WT (Figure 4a). The OE lines had more number of spherical A‐type starch granules (P < 0.05), which were arranged regularly and packed densely (Figure 4b), compared with those in WT and RNAi lines. While in the RNAi lines, the starch granules were arranged irregularly and stacked loosely; these lines had three times more A‐type starch granules, which appeared distorted with an obvious surface sunk (P < 0.05) compared with those in the OE lines and WT. Meanwhile, both single and double mutants of CriTaTPPs had flat and smaller grains and showed a decrease in the total number and diameter of the starch granules (P < 0.001; Figure 4c,f), with an apparent large cavity in the endosperm. However, the total granule number difference reached statistically significant levels only in the 7A/7b/7d double mutants compared with the WT, indicating a more substantial effect of TaTPP‐7A on grain filling than GN. Furthermore, we analysed the physicochemical properties, including thermal and pasting properties, of starches in the transgenic lines to investigate the effect of the increase in grain size and the decrease in amylose content on the starch processing qualities (Figure 4d,e, Table S3). The OE lines had significantly lower thermal and pasting parameters, including the peak onset (To), maximum (Tp), and conclusion (Tc) temperature, peak area (enthalpy, ΔH), trough viscosity (TV), final viscosity (FV), pasting peak time (TPV), and the average chain length, than the WT and RNAi lines (P < 0.05); however, the RNAi lines showed the lowest pasting temperature (PT), the highest peak viscosity (PV), and delayed TPV onset; the other thermal parameters and the average chain length showed no remarkable differences between WT and RNAi lines, indicating the role of TaTPP‐7A in inducing changes in starch PT and physicochemical properties, which profoundly influenced wheat quality.

Transcriptome sequencing was performed to elucidate the molecular mechanism of TaTPP‐7A regulating starch synthesis. Totally, 11 339 DEGs were found commonly expressed among the OE, RNAi lines, and WT plants, while 1479 and 661 were specifically expressed in the OE and RNAi lines compared to WT plants (Figure 5a). KEGG pathway analysis of all these DEGs highlighted an enrichment of carbohydrate metabolism and transportation pathways, such as carbohydrate phosphorylation, cellular glucose homeostasis, and trehalose biosynthetic process (Figure 5a). These observations led us to establish a positive expression association between TaTPP‐7A in the Tre pathway and SnRK family members involved in the carbohydrate energy metabolism pathway since several studies have reported that the sugar signal of T6P directly inhibited SnRK1 activity in vitro both in Arabidopsis (Zhang et al., 2009) and wheat grains (Martínez‐Barajas et al., 2011). As shown in Figure 5b, the association coefficient between TaTPP‐7A and SnRK2‐2B expressions in the transgenic OE lines (R 2 = 0.8208) was much higher than that in WT plants (R 2 = 0.6275), indicating it was the OE of TaTPP‐7A and the decrease in T6P that caused the increase in the association coefficient, and thus proved the possibility of T6P–SnRK1 interaction in vivo. Subsequently, based on the T6P–SnRK1 interaction model and the pioneering results on T6P accumulation in developing wheat grains by Martínez‐Barajas et al. (2011), we found that about 7.69%–50% of the genes in different metabolic pathways may be regulated by SnRK1 (Figure 5c, Figure S14, SnRK1‐dependent genes indicated by red dot); this set included genes related to sucrose lysis and transport and starch regulation (especially senescence‐ or abscisic acid (ABA) and ethylene pathway‐associated genes). Detailed analysis revealed that the expression levels of the sucrose synthase (SUS) gene SUS‐2D, sucrose transport (SUT) gene SUT‐2B, ABA receptor gene PYL3‐7D, and ethylene signal‐responsive factor (ERF) gene ERF‐7D enhanced about 9.4, 6.2, 13.1, and 272 times, respectively, at 5 DPA in the OE lines compared with the WT. One senescence‐related gene DUF581‐6A/6B/6D, with higher transcript levels in OE lines (75.57/70.10/59.55 times) than in WT at 5 DPA (P < 0.05 or P < 0.01; Figure 5c, starch regulation clade), also showed a clear SnRK1‐dependent expression profile. These observations implied that TaTPP‐7A might regulate grain filling and maturity by affecting the levels of senescence hormones or/and senescence‐related genes, consistent with the rapid grain filling phenotype of the OE lines (starting as early as 5 DPA). However, we also found about 58.4%–92.3% of DEGs were independent of this model. These DEGs included Myb transcription factor (TF) gene Myb‐1A, Gibberellin 20 oxidase (GA20ox) gene GA20ox‐3B, and Aldose 1‐epimerase (AEP) gene AEP‐7B, with 911.2, 377.9, and 823.9 times higher expression levels in the OE lines than those in WT at 5 DPA; their expression trends showed neither positive nor negative downstream genes associated with SnRK1. Surprisingly, we found that dozens of starch synthesis‐related genes, such as ADP‐glucose pyrophosphorylase (AGPase) gene AGPase‐1B/7D, soluble starch synthase (SS) gene SS3‐1A, granule‐bound starch synthase (GBSS) gene GBSS1‐7A, starch branching enzyme (SBE) gene SBE3‐2A, and starch‐debranching enzyme (DBE) gene DBE‐7D, displayed significantly higher expression levels in transgenic OE lines than those in WT at 5 DPA; however, only SBE3‐2A and ADPG transporter gene TaBT1‐6A/6B showed SnRK1‐dependent expression pattern, while the others did not, indicating T6P may directly regulate the expression of these genes or through some other unknown mechanism. Thus, our observations suggested that both T6P and T6P–SnRK1 interactions are important components regulating wheat grain development. We then evaluated the content of soluble carbohydrates in flag leaves, spikes, and grains to verify if TaTPP‐7A affects sugar metabolism. We found significantly higher total soluble sugar, sucrose, and trehalose content in the leaves, spikes, and 10 DPA grains of the OE lines than in the WT (P < 0.05 and P < 0.01; Figure 5d,e), but significantly lower sucrose content in 5 DPA grains (P < 0.01). However, these observations are consistent with the expression of SUS genes and confirmed that TaTPP‐7A affects sucrose lysis and utilization in wheat grains.

Genomic diversity and haps evolution of TaTPP‐7A were evaluated using 262 MCC, 1347 modern cultivars, and a data set of 387 tetraploid/hexaploid accessions. Eight SNP variations, including three at the coding region and five at the promoter region, were found in the TaTPP‐7A genomic sequence. These variations caused a mutation at 466 bp, changing Asp to Glu (aa 112), and 1278 bp, changing Ala to Val (aa 241), resulting in three haps among the 262 MCC (Figure 6a). Meanwhile, the five SNP variations in the promoter region affected the expression levels of TaTPP‐7A, which was proven by the fluorescent signal in tobacco leaves carrying constructs with Hap I and Hap II promoters (Figure 6b). The Haps association analysis showed that TaTPP‐7A was significantly associated with high TKW and long GL (P < 0.01) both among the landraces and the modern cultivars under four environments (Table S4). Varieties with Hap I showed the highest TKW and the longest GL, whereas those with Hap II showed the lowest TKW and shortest grains. Meanwhile, varieties with Hap III displayed a moderate phenotype. The average difference in TKW and GL between Hap I and Hap II was about 8.25 g (7.63–8.94 g) and 6.6 mm (6.2–7.5 mm), respectively, within the landraces and 5.70 g (4.06–6.32 g) and 4.2 mm (3.5–4.8 mm), respectively, within the modern cultivars. In China, the frequency of Hap I has increased dramatically since the 1940s from 10.5% (0%–21.4%) in landraces to 65.4% (20%–100%) in modern cultivars across the ten wheat zones (Figure 6c,d, Figures S15, S16), whereas that of Hap II and Hap III decreased obviously from 58.3% (7.1%–100%) and 31.3% (0%–71%), respectively, in landraces, to 22.5% (0%–80%) and 12.0% (0%–50%), in modern cultivars. These observations indicated that TaTPP‐7A had undergone an intense artificial selection during breeding in China. However, for the 384 foreign cultivars, especially for the germplasms in Mexico, Australia, Europe, and North America, the proportions of Hap III were higher than Hap I and Hap II (Figure 6f), indicating the differences in the haplotypes favoured in China and foreign countries. Furthermore, results showed that the π value of TaTPP‐7A decreased dramatically from landraces (0.0018) to modern cultivars (0.00139) (P < 0.01; Figure 1e). In addition, two dramatic declines in TaTPP‐7A Haps diversity (H value) occurred during the Triticum genus evolution (Figure 6e, Figure S17), one at the tetraploid domestication stage (P < 0.001) and the other at the hexaploid breeding stage (P < 0.01); meanwhile, the gHaps (haps in hexaploid wheat) were derived clearly from the aHaps (haps in Emmer). These observations proved that TaTPP‐7A is a crucial targeted gene continuously selected in wheat domestication and breeding.

In wheat, grain TKW is a crucial factor influencing yield. Sucrose plays a vital role in determining TKW, however, the specific molecular mechanism regulating sucrose unloading and metabolism in grains remains largely unknown. In this study, we report firstly that the wheat gene TaTPP‐7A feedback regulates sucrose lysis, flux, and utilization in grain endosperm through T6P‐SnRK1 pathway and sugar–ABA interaction (Figure 7), and thus significantly enhanced grain filling and wheat yield under field condition. In Arabidopsis and rice, dozens of TKW‐associated genes have been cloned and the possible mechanisms regulating grain size or filling were further analysed (Ashikari et al., 1999; Song et al., 2007; Wang et al., 2008, 2012b; Weng et al., 2008), but none of these genes have been identified as components of the Tre pathway. In addition, Tre components (T6P, TPS, and TPP) have been associated with an increase in yield in wheat (Zhang et al., 2017) and maize (Nuccio et al., 2015); however, the molecular mechanisms underlying these functions remain unclear. In the present study, the OE of TaTPP‐7A in wheat resulted in a maximal 11.5 g higher TKW, and grain yield was enhanced by 24% compared with the WT. Further study demonstrated that Tre metabolic pathway might be the central regulatory system for sucrose allocation and sugar–ABA interactions in wheat grains. Therefore, our work highlights the importance of the T6P signalling pathway and reveals the role of the Tre pathway components in yield improvement.

In plants, T6P has been widely accepted as an indicator of sucrose status and carbon availability in various plant species, such as potato (Solanum tuberosum) (Debast et al., 2011), cucumber (Cucumis sativus) (Zhang et al., 2015b), maize (Z. mays) (Henry et al., 2014), and wheat (Martínez‐Barajas et al., 2011). In this study, we expected limited T6P content in the grains of the OE lines throughout the developing stages since TaTPP‐7A directly dephosphorylates T6P, leading to low sucrose and high Tre content due to sucrose breakdown for subsequent grain filling. However, a significantly higher accumulation of both Tre and sucrose was detected in the OE wheat tissues, except for the grains at 5 DPA. The Tre and sucrose content in the developing grains (10 DPA) and flag leaves of OE lines were respectively about 22.1% and 8.1% (P < 0.05), 45.8% (P < 0.05) and 22.9% (P < 0.01) higher than those in the WT. Moreover, the sucrose content in the flag leaves and 10 DPA grains of the transgenic OE lines were 288 times and 93 times higher than the Tre content. Therefore, here sucrose content was more likely linked to the overall sugar status and response to low T6P levels than Tre content both in the source (leaves) and the sink (developing grains). In addition, we found the highest difference in the expression of sucrose lysis‐related genes TaSUS‐2A/2B/2D and TaSUS‐7D in the grains at 5 DPA compared to the WT plants, which explains the great decrease in sucrose content of the OE lines at 5 DPA. Moreover, this difference suggests that the reduced T6P and sucrose level or T6P/sucrose ratio at 5 DPA signals a low sugar level or energy status to the source, leading to a continuous sucrose flux from leaves to grains. This conclusion is proved by the fact that the high expression levels of sucrose transporters, such as TaSUT1‐4A/4B/4D, TaSUT2‐2B, and SWEET‐7A/7B/6A, were detected at 5 DPA in the OE lines. TaSUT1 is a plasma membrane‐localized transporter involved in the phloem loading of sucrose (Aoki et al., 2002), while TaSUT2 controls the cytosolic sucrose homeostasis in flag leaves and grains (Deol et al., 2013). Therefore, the enhanced expression of TaSUT1 and TaSUT2 indicated the allocation of assimilates from the source to the sink (Aoki et al., 2002; Deol et al., 2013). In addition, this conclusion was also solidly supported by the effect of a rice TPP1 on sucrose transport in maize, which highlighted seven SWEETs upregulated by TPP1 in carbon partitioning for maize seed development (Oszvald et al., 2018). Thus, the increase in the sucrose content in wheat grains was more likely due to carbohydrate flux and not de novo synthesis. In most plants, higher sucrose content is associated with the induction of starch synthesis. In this process, SUS, AGPase, or TaBT1 plays essential roles (Kumar et al., 2018). Studies have shown that the OE of SUS, AGPase, or TaBT1 in potato and wheat increased the starch content and TKW (Baroja‐Fernández et al., 2009; Smidansky et al., 2002), which is consistent with our observations. The transgenic OE grains exhibited higher expression levels of TaSUS‐7D/2A, TaAGPase‐S‐7A/7B/7D, TaAGPase‐L‐1A/1B/1D, TaBT1, and other starch synthesis‐related genes, such as SS, GBSS, SBE, and DBE, especially at 5 DPA, indicating these genes as the targets of TaTPP‐7A. Additionally, sucrose lysis at 5 DPA might have provided more UDPG substrate for starch synthesis than other DPA. Consistently, the total starch content of the OE lines was 2.53% higher than that of WT, indicating TaTPP‐7A affects sucrose lysis and starch synthesis synchronously. In this study, we also detected a significant decrease in amylose content (13.2%) in the OE line compared with the WT. Moreover, the expression levels of GBSS1‐7A, involved in amylose synthesis, were 3.14 times higher than the WT at 5 DPA, whereas that of SBE3‐2A, responsible for amylopectin synthesis (Pérez et al., 2019), was 44.4 times higher and showed SnRK1‐dependence. Thus, the higher expression difference in these genes might have resulted in starch granules with very low amylose but a higher amylopectin content in the grains of OE lines.

Based on our findings and other reports, we confirmed the possibility of T6P–SnRK1 interaction in regulating wheat grain development in vivo. We found that most of the sucrose lysis and transport genes and several TFs showed a jumped and SnRK1‐dependent expression pattern. In rice, maize, and wheat, SnRK1 directly activates the expression of genes encoding sucrose synthase (SuSy) (Smidansky et al., 2002, 2003) and sugar transporter (SUT1) (Bledsoe et al., 2017). Meanwhile, OE of SnRK1 stimulated starch synthesis in potato tubers and barley, leading to high starch accumulation through the redox activation of AGPase (McKibbin et al., 2006; Sreenivasulu et al., 2006). Thus, our observations might suggest that SnRK1 could also directly regulate sucrose metabolism‐related genes in wheat, proving the role of T6P–SnRK1 interaction in grains. In addition, the high expression of the senescence‐related protein gene, DUF581‐6A/6B/6D, may also imply the role of T6P‐SnRK1 pathways in regulating wheat grain filling. In Arabidopsis, this protein interacts with the catalytic α subunits of SnRK1 (AKIN10/11) (Nietzsche et al., 2016) and acts as a mediator or scaffold connecting the SnRK1 pathway with other signalling pathways, such as hormone, TOR, and MAP‐kinase signalling pathways. Therefore, the DUF581 protein might have a function similar to that in Arabidopsis and confer stimulus‐specific and tissue‐specific differences in SnRK1 regulation in wheat. In plants, the SnRK family comprises three subfamilies: SnRK1, SnRK2, and SnRK3. SnRK1 plays a major role in regulating carbon metabolism, while SnRK2 and SnRK3 have been implicated in ABA‐mediated signalling pathways (Kong et al., 2015). Generally, SnRK2 activation is dependent on the breakdown of SnRK1 (Coello et al., 2012; Cutler et al., 2010). The present study found SnRK1‐dependent expression for PYL3‐7D, PP2C‐7D, and SnRK2‐1B, with 13, 11, and 3.2 times higher levels in OE lines than those in WT at 5 DPA. In addition, the expression levels of NCED‐5A/5B/5D, the key speed‐limiting enzyme of the ABA biosynthetic pathway, were also higher (5.0, 6.1, and 3.5 times) than those of WT at 5 DPA. These observations suggest that SnRK1 activated ABA signalling pathways during grain filling, and thus ABA plays important role in regulating grain filling. Therefore, TFs involved in the ABA pathway and regulated by SnRK1 might more likely contribute to the regulation of grain filling. The present study found higher expression of bZIP‐2B (basic leucine zipper) and Myb‐2D/4A/7A at 5 DPA in the OE lines (218.0 and 361.6/132.2/120.4 times) than those in WT, clearly indicating SnRK1‐dependent expression pattern. Studies have shown that SnRK1 mainly targets the members of the bZIP TF family in regulating plant growth and stress response under sugar starvation conditions (Hanson et al., 2008). Many ABA‐regulated genes also contain binding sites for the MYB and MYC protein families (Cutler et al., 2010). Moreover, ABA has been demonstrated that involved in SnRK‐related sugar signalling and promotes starch accumulation in developing seeds (Cutler et al., 2010). Thus, the enhanced TFs or genes controlled by SnRK1 in the OE lines may regulate grain filling too through the ABA pathway. In barley, ABA‐responsive and dehydration‐responsive cis‐elements have been found in the promoters of key genes involved in starch biosynthesis (HvSUS1 and HvAGP‐L1) and degradation (HvBAM1) (Govind et al., 2011). In wheat and rice, ABA affects the transcriptional regulation of SUS (Yang et al., 2006; Zhu et al., 2011). In barley seeds, ABA homeostasis regulates starch accumulation rate and grain filling under drought (Govind et al., 2011) and modulates starch synthesis via SNF1 kinase and a few TFs (Sreenivasulu et al., 2006). These earlier reports support our results and confirm the role of SnRK1 or the ABA pathway in regulating starch synthesis. Thus, the present study proves that TaTPP‐7A enhances wheat yield through senescence‐related hormone biosynthesis and signalling and sugar–ABA interaction.

ABA and ethylene are the major regulators of plant senescence (Cutler et al., 2010; Yang et al., 2006). Studies have shown that at the rapid grain‐filling stages, ABA accumulation in the developing seeds regulates reserve remobilization and grain filling in barley, rice, and wheat (Govind et al., 2011; Yang et al., 2004, 2006). Meanwhile, the grain ethylene concentration has been negatively correlated with the grain‐filling rate. In rice, ethylene concentrations are high at the early grain‐filling stages and decrease sharply during the linear growth phase (Yang et al., 2004). However, in the present study, both ABA and ethylene appeared to play positive roles in regulating grain filling. The expression levels of ethylene biosynthesis‐related genes ACS‐7D (ACC synthase gene) and ACO‐1D (ACC oxidase gene) and the ethylene‐responsive factor ERF‐7D enhanced synchronously with the ABA pathway‐associated genes (more than five times) at 5 DPA and remained high till 15 DPA in the transgenic OE lines compared with those in WT. Especially for ERF‐7D, the expression levels were 272 and 2.3 times higher at 5 and 15 DPA, indicating that the ethylene levels may not decrease during the early and late grain filling stages, which is in contrast to the findings of Yang et al. (2004) in rice. However, we found that the expression trends of ABA‐related and ethylene‐related genes in the OE grains were quite different; a gradual decrease was observed for the ABA signalling‐related genes, such as PYR‐4D, PP2C‐7D, and SnRK2‐1B, after anthesis, whereas a sharp decline was observed for the ethylene pathway‐related genes, such as ERF‐7D and ACO‐1D, until 15 DPA, indicating that the concentrations and the balance between ethylene and ABA in the grains are necessary for grain filling. These findings suggest that accelerating the biosynthesis or signal transduction of senescence‐related hormones at grain filling may be one of the ways via which TaTPP‐7A synchronously enhanced grain filling and maturation.

Grain filling is a key determinant of wheat productivity. A growing body of research has highlighted the link between genes regulating grain filling and domestication traits since the crops with larger seeds and higher yield have been selected as per human demands. In maize, the genes of the Tre pathway have been listed as candidates for domestication improvement; however, the link with the traits has not been reported (Hufford et al., 2012). The present study found that the wheat grain‐filling gene, TaTPP‐7A, has already been targeted during domestication and breeding in China, contributing to higher TKW and earlier maturity date (MD) traits. However, the importance of Tre pathway‐related genes has just been recognized. We found that the H value of TaTPP‐7A haps diversity in wild emmer wheat was significantly higher than that in the tetraploid and hexaploid wheat, which means TaTPP‐7A was continuously under intense breeding selection, together with the downstream starch and sucrose metabolism‐related genes (TaAGPase‐L and TaAGPase‐S (Hou et al., 2017), TaSUS1 and TaSUS2 (Hou et al., 2014)) and ADP‐glucose transport gene TaBT1 (Wang et al., 2019b), contributing to wheat yield improvement. Thus, the Tre pathway may be central in regulating sugar utilization and starch synthesis in wheat grains. Furthermore, we found that the Hap III of TaTPP‐7A in foreign wheat germplasm, especially the cultivars in Mexico, Europe, and North America, was favoured differently with China. Among the landraces of China, Hap II and Hap III of TaTPP‐7A showed remarkable differences (P < 0.01) in heading date (HD) and MD under three environments. The HD and MD in varieties with Hap III were delayed by about 3.72 days (2.79–4.9 days) and 3.37 days (2.05–5.25 days), respectively, compared with the ones with Hap II (Table S4), thus, Hap III is beneficial for grain filling. However, the ongoing climate changes, such as high temperature and drought, occur more frequently and severely than before at wheat heading and filling stages (Marmai et al., 2022), and has posed a significant threat to wheat production. During 1964–2007, about 497 droughts and 138 extreme heat weather disasters occurred worldwide, leading to a 9%–10% decrease in cereal production (Lesk et al., 2016). A 4.1%–6.4% decrease in wheat production is estimated for every 1°C increase in global temperature due to climate change (Liu et al., 2016). Therefore, the development and utilization of early maturing varieties that ‘escape’ better than ‘tolerate’ heat stress and drought in hotter and drier summers are crucial for high crop yield; thus, the different haps of TaTPP‐7A may be considered to improve wheat adaptation or output under climate changes. The present study found that the haplotype diversity of the TaTPP‐7A gene between the domesticated tetraploid wheat and hexaploid landraces was almost the same, which indicates that this gene maintained abundant genetic diversity in landraces and thus could be further utilized for breeding other traits. In conclusion, TaTPP‐7A is a crucial domestication‐ and breeding‐targeted gene in China and feedback regulates sucrose lysis, flux, and utilization in the grain endosperm mainly through T6P‐SnRK1 pathway and sugar–ABA interaction. Thus, the present paper highlights the importance of the T6P signalling pathway and establishes Tre metabolic pathway as the central regulatory system for sucrose allocation and source–sink interactions in wheat grains. The study also proposes Tre pathway components as potential targets to increase grain size and yield in wheat. However, the direct regulatory effect of SnRK1 or TaTPP‐7A on the sucrose metabolism gene should be further investigated.

Chinese wheat 262 MCC (Hou et al., 2014; Su et al., 2011) was used for candidate gene association mapping, 1347 modern cultivars (348 Chinese, 384 European, 429 North American, 53 CIMMYT, 82 Russian, and 51 Australian) for genotyping and haplotype association analysis, and 716 F2 lines of the biparental population for BSR‐seq derived from 2840 F2 individuals produced by crossing ‘Zhongyou9507’ cultivar with ‘Hongjinmai’ landraces (Table S5, Figure S18), were cultivated in the fields of Luoyang (112°45′E, 34°62′N; Henan, China) during 2001–2002, 2004–2005, and 2005–2006 and Shunyi (116°43′E, 40°09′N; Beijing, China) and Xinxiang (113°54′E, 35°18′N; Henan, China) during 2014–2015, 2015–2016, and 2016–2017, under local water (2–3 times for each crop season) and fertilizer management practices. The planting was carried out as described by Su et al. (2011) and Li et al. (2022). During the growing seasons, the average temperature was 10–22 °C in Shunyi and 12–24 °C in Luoyang and Xinxiang. The TaTPP‐7A OE or RNAi transgenic wheat lines were planted in the Shunyi fields at the year of 2016–2017, 2017–2018, and 2018–2019 following local water and fertilizer management practices as above. The seeds of the transgenic lines were sown in four 2 m long rows with a row spacing of 30 cm; 20 seeds were sown per row. The CRISPR/Cas9‐mediated TaTPP edited wheat lines (Cri‐TaTPPs), the TaTPP mutant in the tetraploid spring wheat cultivar Kronos background (K‐TaTPPs), and tobacco (Nicotiana benthamiana) plants to analyse the gene function and promoter activity were cultivated in the greenhouse with a 16 h/8 h photoperiod; the temperature of the greenhouse was maintained at 22/20 °C ± 1 °C for wheat and 24 °C ± 1°C for tobacco. The K‐TaTPP and Cri‐TaTPP mutants were self‐pollinated to M3 or T3–T4 generations for phenotype evaluation; PCR and sequencing were used to detect the targeted genome variations in each generation, using the WT Kronos or Fielder (FD) as control.

Plants from the homozygous transgenic OE and RNAi lines (T7–T9; 5–7 independent transgenic lines, with 10–20 individuals per line; 94 OE and 123 RNAi individuals in total), Cri‐TaTPP mutants (30 individuals), and FD (41 plants) were randomly selected to investigate the agronomic traits, including SN, PH, SL, SLN, GN, TKW, GL, and GW (Figure S8, Table S6). TKW was measured using a WSEEN Rice Test System (Wseen, Zhejiang, China). The images of the developing grains were captured using a stereomicroscope (SteREo Discovery V20, Zeiss, Germany). The size and shape of the starch granules were observed with a scanning electron microscope (SEM; SU8010, Hitachi, Japan), following the Wang et al. (2019b) protocol. Image J software (V1.48, National Institutes of Health) was used to measure cell size and number.

The full‐length of TaTPP‐7A cDNA (1086 bp) was amplified and sequentially cloned into the pWMB110 vector (BamH I/EcoR I sites) to obtain the TaTPP‐7A OE construct; A 309 bp fragment derived from the TaTPP‐7A cDNA (7–315 nucleotides) was amplified and sequentially cloned into the pWMB006 vector respectively at BamH I/Kpn I and Sac I/Spe I sites in opposite directions, with an intron between them to create a hairpin structure, and then inserted into the binary vector pWMB111 to obtain the TaTPP‐7A‐RNAi construct. The single guide RNA (sgRNA) sequences were designed to target a conserved region in the third exon of TaTPPs, and the fragments of the active TaU6‐sgRNA were amplified and inserted into CRISPR/Cas9 vector pJIT163‐2NLSCas9 to obtain the fused expression vector pGE‐sgRNA, this construct was used to edit TaTPP‐7A/7B/7D and generate the CriTaTPPs lines. All constructs (OE/RNAi/CRISPR/Cas9) were transformed into the immature embryos of the wheat cultivar FD using Agrobacterium‐mediated transformation, following the protocols described by Wang et al. (2017) and Wang et al. (2014). All primers used in constructing the above vectors and selecting the lines are listed in Table S7.

Total RNA was isolated from the wheat leaf, stem, root, and grain tissues using the TIANGEN RNA Extraction Kit (Tiangen, Beijing, China). Approximately 2 μg of total RNA was reverse transcribed into the cDNA using the SuperScript III RT system (Invitrogen, Madison, WI), according to the manufacturer's instructions. Then, qRT‐PCR was performed as described by Wang et al. (2019b) on an Applied Biosystems 7500 Real‐time PCR system (Thermo Fisher), using actin as the housekeeping gene. The primers used are listed in Table S8.

Total RNA was extracted from the grains of the F2 biparental progeny ten DPA as described above. For RNA‐seq, three independent progeny with grain TKW ≥45 g (HG 1–3) or < 35 g (LG 1–3) were randomly selected and sequenced separately. Meanwhile, for BSR‐seq, RNA samples were extracted from the pooled grains of 32 progeny with TKW ≥58 g or <28 g at equimolar amounts to obtain the highest bulks (CH) and the lowest bulks (CL), respectively. Six (HG 1–3 and LG 1–3, RNA‐seq) and four (two bulks and two parents, BSR‐seq) cDNA libraries were constructed using the TruSeq Stranded mRNA LT Sample Prep Kit (Illumina, San Diego, CA) according to the manufacturer's instructions, and sequenced separately on an Illumina platform (Illumina novaseq™ 6000) at the Beijing Biomics Technology Company Limited (Beijing, China) using the paired‐end technology. The clean reads (Table S9) were assembled and aligned to the CS wheat reference genome sequence (RefSeq V1.0 and V2.1) released from the International Wheat Genome Sequencing Consortium (IWGSC) in 2018 (Appels et al., 2018). The genes with a fold change (FC) ≥ 2 in RNA‐seq data or ≥1.5 in BSR‐seq data and a false discovery rate (FDR) < 0.01 were identified as the DEGs by DESeq2 (V1.10.1) (Anders and Huber, 2010). The differences in FPKM (the fragments per kilobase of transcript per million mapped reads) or TPM (transcripts per million reads) values were calculated using the EBseq software (V1.12.0) (Leng et al., 2013). DEGs were annotated based on the GO, COG (Clusters of Orthologous Groups of proteins), KOG (EuKaryotic Orthologous Groups), and KEGG (Kyoto Encyclopedia of Genes and Genomes) public databases. For BSR‐seq analysis, the expression differences of the DEGs between the parents (PL_vs_PH_log2 (FC)) and the bulks (CL_vs_CH_log2 (FC)) were determined and compared, and those with a threshold log2 (FC) ≥ 0.5 and an expression difference consistent for the parents and bulks were considered as the candidate genes. Further, to analyse the downstream genes regulated by TaTPP‐7A, total RNA was extracted from the transgenic and FD grains at 5, 10, 15, and 20 DPA and analysed via RNA‐seq. The expression levels of DEGs (TPM) between the transgenic OE lines and the FD plants (Table S10) were presented as a cluster heat map using the Edge R software (V1.3.1093.0).

Chinese 262 MCC was chosen for GWAS of TKW using 984 034 SNPs captured by exome sequencing (Li et al., 2022). The association analysis was performed using the EMMAX software package (Kang et al., 2010). The pairwise LD coefficient (r 2) between SNPs was calculated using Plink (Purcell et al., 2007). Nucleotide diversity (π) was estimated using VCFtools (V 0.1.14) to assess the degree of variability within the landraces and the modern cultivars. The mean value and the best linear unbiased prediction (BLUP) value for the TKW trait at the same site and at different ages were calculated to perform GWAS.

Protein sequences of TPPs in wheat, rice, Arabidopsis, and maize were retrieved from the Ensemble Plants public database (http://plants.ensembl.org/) and aligned using ClustalX, and the phylogenetic tree was constructed based on the neighbour‐joining method with 1000 bootstrap replicates using MEGA 7.0 software (V 7.0.26). The TaTPP homoeologous protein sequences were aligned using DNAMAN software (Lynnon Biosoft, Quebec, Canada). The accession numbers of the genes used in the phylogenetic analysis are listed in Table S11.

Genomic variations in TaTPPs were detected by aligning the 2.3 kb long genomic sequence and 2.5 kb long promoter sequence amplified from 34 wheat varieties (22 modern cultivars and 12 landraces from 262 MCC; primers are listed in Table S12). The resulting fragments were cloned and sequenced on an ABI3730 XI DNA Analyser (Applied Biosystems), and the sequence variants (SNPs/Indel) were detected using DNASTAR (http://www.dnastar.com/). Three pairs of Kompetetive allele‐specific PCR (KASP) markers (Table S13) were designed to genotype the Haps of TaTPP‐7A in 262 MCC and 1347 modern cultivars of wheat. The Haps association analysis was conducted following the method described by Ma et al. (2016). Haps evolution was analysed using 387 tetraploid/hexaploid wheat accessions divided into four groups as follows: wild emmer (n = 61), domesticated tetraploid (n = 98), hexaploid landrace (n = 140), and hexaploid cultivar (n = 88). The ancestral‐haps (aHaps) were inferred by IntroBlocker as described by Wang et al. (2022), while the germplasm‐based haps (gHaps) for each 1 Mb bin were inferred using ggComp with default parameters as described by Yang et al. (2022). Finally, the Shannon diversity index of each group was calculated to determine the significance of the haps differences using the following formula:where L refers to the count of gHaps for each bin, and p i refers to the proportion of accessions in the i th gHap in the whole panel. The luciferase complementation imaging (LCI) assay was carried out to compare the promoter activities of the TaTPP‐7A haps. Briefly, the Hap 1 or Hap 2 promoter sequence associated with the highest or lowest TKW was amplified by PCR as above and then introduced into the plant binary vector pGWB35‐LUC to generate the fusion construct TaTPP‐Hap1pro::LUC or TaTPP‐Hap2pro::LUC, following the methods described by He et al. (2021). The A. tumefaciens (strain GV3101) cells carrying different constructs were infiltrated into N. benthamiana leaves, using cells with an empty vector (EV) as the negative control. The luciferase images were captured using a low‐light‐cooled CCD imaging apparatus (Night SHADE LB 985, Berthold, Bad Wildbad, Germany) and analysed with INDIGO software.

Soluble carbohydrates (sucrose, glucose, fructose, and trehalose) were extracted from 300 mg of the transgenic fresh leaves/grains/spikes following the method described by Lunn et al. (2006). The sugar content in the extract was determined by high‐performance liquid chromatography (HPLC, Waters 600 controller) with an NH2 column (5 mL, 4.6 mm × 250 mm I.D., Inertsil@ HPLC column) following the procedure described by Chang et al. (2013). Total starch and amylose in the endosperm were extracted and quantified following the Chinese national standard (NY/T11‐1985, NY/T11‐1987) for cereals with the optical rotation method. The thermal characteristics of the starch samples were analysed using a differential scanning calorimeter (DSC Q2000; TA Instruments, DE) according to the methods described by Lai et al. (2016). The gelatinization temperature and enthalpy were calculated using the Universal Analysis 2000 software (TA Instruments), and the pasting properties of the starch suspensions were determined using a Rapid Visco Analyser (RVA, MCR302, Anton Paar, Austria).

One‐way analysis of variance (ANOVA) and Tukey's multiple comparison test were performed to determine data variance and significance (*P < 0.05, **P < 0.01, and ***P < 0.001) using the SPSS 16.0 (SPSS). The Hutcheson t‐test (Hutcheson, 1970) was applied to analyse statistical differences in the Shannon diversity index values between groups, using the P‐value of a two‐tailed test. All experiments were performed using no less than three replicates per sample, and the data were presented as the mean values ± standard deviation.

The authors declare no competing interests of this work.

H.X.L. conceived of the project, performed most experiments, and wrote the manuscript; X.M.S. constructed the F2 segregation population and performed phenotype evaluation and genotype verification experiment; Z.Y.W. performed GWAS and fine‐mapped the QTL; L.Y.C. performed grain quality experiment and transcriptome analysis; X.L.Z. and C.Z.J. assisted in BSR sequencing and data analysis; W.X.W. and W.L.G. conducted the analysis of haplotype domestication and polyploidization; L.F.G. and L.Z. assisted in genotyping and RNA‐Seq. H.X.L. and K.W. developed the transgenic and CRISPR/Cas9 edited lines and performed the wheat transformation; Y.C.L. and J.H. performed qRT‐PCR and phenotyping evaluation of transgenic lines in the laboratory and fields; C.Y.H., T.L., J.L., and W.L.G. provided advice about the experiments; X.Y.Z. revised the manuscript; all authors have read and approved the manuscript.

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