An elite allele TaDT1-AhapI enhances drought tolerance via mediating autophagic pathways in wheat

Liu, Xingbei; Li, Jinpeng; Zhang, Chenji; Zhao, Danyang; Peng, Xiao; Yang, Qun; Liu, Zehui; Miao, Lingfeng; Chu, Wei; Lin, Jingchen; Chang, Shumin; Liu, Debiao; Liu, Xiaoyu; Wang, Wenxi; Wang, Xiaobo; Xin, Mingming; Yao, Yingyin; Guo, Weilong; Xie, Xiaodong; Peng, Huiru; Ni, Zhongfu; Sun, Qixin; Hu, Zhaorong

doi:10.1038/s41467-025-61943-3

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Published: 16 July 2025

An elite allele TaDT1-A^hapI enhances drought tolerance via mediating autophagic pathways in wheat

Nature Communications volume 16, Article number: 6563 (2025) Cite this article

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Abstract

Drought stress constitutes a major threat to global wheat production. Identification of the genetic components underlying drought tolerance in wheat is highly important. Through a genome-wide association study, we identify a natural allele of the zinc finger-type transcription factor TaDT1-A on chromosome 2 A of the wheat genome that confers drought tolerance without imposing trade-offs between tolerance and yield. This allele, named TaDT1-A^hapI, causes an 899-bp deletion in the promoter of the TaDT1-A gene, which results in increased expression of the gene through escape of the repressive MYC transcription factor and, consequently, the promotion of stomatal dynamics and water use efficiency via increased autophagy activity. Our findings provide genetic insights into the natural variation in wheat drought tolerance. The identified loci or genes can serve as direct targets for both genetic engineering and selection for wheat trait improvement.

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Introduction

Drought imposes escalating constraints on global agriculture and it may become even more grievous due to global climate change and erratic precipitation patterns¹. Wheat (Triticum aestivum L.), while providing 20% of humanity’s caloric intake, faces an existential paradox: over 60% of its cultivation occurs in drought-prone regions where seasonal yield losses exceed 20%^2,3,4. This geographical vulnerability demands urgent identification of excellent genetic regulators that confer drought resilience without compromising grain yield—a fundamental challenge for crop improvement⁵.

Drought tolerance involves quantitative traits regulated by morphological adaptations (root architecture, leaf hydraulics) and physiological processes⁶. Although numerous quantitative trait loci (QTLs) have been mapped, their functional validation remains limited^{7,8,9,10,11,12,13,14,15}. Genome-wide association studies (GWAS) offer advantages over linkage analysis by leveraging historical recombination and allelic diversity^16,17, yet their application in wheat lags behind crops like maize and rice^{18,19,20,21,22}. Only a few GWAS-validated drought regulators (e.g., TaNAC071-A, TaWD40-4B.1, TabHLH27) have been characterized^23,24,25, highlighting critical knowledge gaps in wheat’s drought regulatory networks.

Autophagy, an evolutionarily conserved cellular recycling mechanism in eukaryotes, mediates the degradation of cytoplasmic components and damaged cellular materials. This essential subcellular pathway plays crucial roles in plant development and stress adaptation, particularly under drought conditions^26,27,28,29. Research demonstrates that autophagy enhances drought tolerance through multiple mechanisms: eliminating protein aggregates, regulating aquaporin-mediated water transport, modulating phytohormone signaling, reprogramming cellular homeostasis, and maintaining growth-stress response equilibrium^{30,31,32,33,34,35}. These findings highlight the potential of precisely regulating autophagy activity to improve crop drought resilience without compromising yield.

The conserved autophagy machinery comprises autophagy-related (ATG) proteins that orchestrate different stages of autophagosome formation^{36,37,38,39,40,41,42}. In wheat, autophagy modulates responses to various environmental stresses^{43,44,45,46,47}. Drought stress upregulates ATG6/ATG8 expression and induces autophagosome formation, while ATG6 silencing renders wheat hypersensitive to drought⁴⁸. Similarly, ATG2/ATG7 suppression compromises autophagy activity and salt stress tolerance⁴⁹. Although post-translational regulators like TORC and SnRK kinases are known to modulate ATG activities during abiotic stress^{50,51,52,53,54}, the transcriptional regulation of autophagy under drought conditions remains poorly understood.

Zinc finger transcription factors, with DNA/RNA/protein interaction domains^55,56, regulate stress responses in plants but remain poorly characterized in wheat^57,58,59,60. Their roles in crop drought tolerance remain unclear. This study identifies a TaDT1-A allele encoding a zinc finger transcription factor that confers drought tolerance in wheat via GWAS. A promoter 899-bp deletion enables drought-inducible expression in tolerant varieties, and genetic selection of this TaDT1-A allele improved wheat drought tolerance. We reveal TaDT1-A’s dual regulatory mechanism: direct regulation by MYC2 transcription factors and interaction with TaCOS1 to coordinate autophagy-gene expression. This pathway synergistically enhances drought adaptation while maintaining growth, offering a strategy for breeding climate-resilient wheat.

Results

TaDT1-A confers drought tolerance in wheat

To investigate the genetic basis underlying the variation in wheat drought tolerance, an association panel consisting of 191 accessions of the wheat germplasm (143 cultivars, 48 landraces) representing geographical diversity, was collected. These accessions were genotyped via re-sequenced genomic data^61,62,63,64, and a total of 42,744,325 filtered single-nucleotide polymorphisms (SNPs) were employed for analysis (Supplementary Fig. 1a). These accessions were subsequently categorized into three subpopulations (Clade I, Clade II, and Clade III) by performing population structure and kinship analyses on the basis of these SNPs, which revealed that the set of 191 germplasms represented a structured population (Supplementary Fig. 1c). Next, we phenotyped the drought tolerance of these accessions to severe drought stress at the seedling stage because of the relatively high reproducibility of the phenotype under these conditions^23,65. Large variations in the survival rate (SR) were observed in repeated phenotypic assays, with SRs ranging from 0 to 100%, and the correlation coefficient between two independent replicate experiments was 0.945 (Supplementary Data 1). The high phenotypic diversity and continuous variation of in the SR indicated that these germplasms contained multiple drought resistance QTLs. We conducted GWAS for drought tolerance under a compressed mixed linear model using these SNPs covering the entire wheat genome. We identified a major peak on chromosome 2 A, in which the top SNP (snp436749371) was highly associated with the SR (P = 2.3 × 10⁻¹⁰), and this peak explained 20.23% of the phenotypic variation (Fig. 1a, b and Supplementary Fig. 1b and Supplementary Data 2). To explore the genes underlying this site, we performed a local linkage disequilibrium (LD) analysis, and the leading SNP was located within an ~5.5 Mb block (Fig. 1a, b). This LD block spanned 11 genes (Fig. 1a, b). Given their association with the drought response, we analyzed expression of these 11 candidate genes under drought stress in two germplasms: drought-tolerant Jinmai50 (JM50) and drought-sensitive Lumai3 (LM3). In roots, only three of these genes were expressed: with TraesCS2A02G269900 showed no drought stress-inducible expression patterns both in JM50 and LM3, while TraesCS2A02G270100 and TraesCS2A02G270200 exhibited drought-induced transcriptional repression in the JM50 and LM3, respectively. In leaves, the expression of TraesCS2A02G269300, TraesCS2A02G269500, TraesCS2A02G269800, TraesCS2A02G269900 and TraesCS2A02G270000 was not detected, TraesCS2A02G269400 and TraesCS2A02G269600 responded to drought stress but showed no differential expression between the two cultivars. TraesCS2A02G269700, TraesCS2A02G270100, and TraesCS2A02G270300 exhibited no response to drought stress in either JM50 or LM3. Only TraesCS2A02G270200 showed drought-induced expression and differential expression across wheat varieties, correlating with drought tolerance divergence (Fig. 1c). Moreover, drought-tolerant varieties exhibited stronger TraesCS2A270200 upregulation under stress than did those of sensitive varieties, which is in accordance with their SR values (Fig. 1d, e). Thus, TraesCS2A270200, which we named TaDT1-A, might be the causal gene that underlies variation in wheat drought tolerance.

**Fig. 1: GWAS and fine mapping of the major locus that underlies wheat drought tolerance variation.**

TaDT1-A encodes a plant-specific transcription factor with a zinc finger and C2H2 domain, which belongs to the WRKY family (Supplementary Fig. 1e). TaDT1-A is localized mainly in the nucleus and is highly expressed in the leaves and roots (Supplementary Fig. 1f, g). In addition, drought strongly promoted TaDT1 expression (Supplementary Fig. 1h). To further assess the involvement of the TaDT1-A gene in drought tolerance in wheat, we generated transgenic wheat plants in which the TaDT1-A gene was overexpressed by introducing the TaDT1-A coding sequence driven by the ubiquitin promoter into the wheat variety Fielder (lines OE16, OE18 and OE20) (Supplementary Fig. 1l). We also generated tadt1 mutants in Fielder using the CRISPR-Cas9 system. The guide RNA was designed to target a highly conserved region in the first exon, and three homozygous mutants (ko12, ko13, and ko19) (Supplementary Fig. 1i) with simultaneous knockout of all three TaDT1 homologs were identified. Under drought stress conditions, the SR was significantly greater in the TaDT1-A OE lines than in the wild-type plants. In contrast, the SR of the knockout mutant plants was considerably reduced. The greater drought-stress survival of the TaDT1-A OE lines was associated with reduced water loss, reduced stomatal conductance, and stomatal aperture, but the knockout lines presented the opposite results (Fig. 2a–g and Supplementary Fig. 1j, k, m). Analysis of drought stress-related metabolic components in different TaDT1-A transgenic plants revealed that SOD and POD, for example, were actively involved in the regulation of drought stress by TaDT1-A (Supplementary Fig. 1n–t). Furthermore, we identified a mutant of TaDT1-A (C-to-T mutation resulting in premature termination) by screening an EMS-mutagenized wheat population (cv. Jing411), which exhibited significantly reduced drought tolerance compared to the wild type (Supplementary Fig. 1u, v). These results indicate that TaDT1-A acts as a positive regulator of drought tolerance in wheat.

**Fig. 2: TaDT1-A positively affects the drought tolerance of wheat by modulating stomatal closure under drought stress.**

Indel in the TaDT1-A promoter is associated with drought tolerance

To adequately resolve the DNA sequence variation in TaDT1-A that might have been missed by low-coverage genome sequencing, we resequenced the TaDT1-A gene from 115 wheat accessions, which were representative of the entire association population. Four SNPs (-217 C/−, -392 G/A, -747 C/G, and -792 C/−, referred to as snp217, snp392, snp747 and snp792, respectively) and one Indel (899-bp insertion/deletion at 819 bp upstream of the transcriptional start site) named Indel819, which contains an 899 bp insertion, was identified in the promoter region of TaDT1-A and showed stronger association signal with the SR (P = 3 × 10⁻¹⁵), whereas no differences were found in other regions, including the exons and introns of TaDT-A. In addition, we found that all these SNP or indel variations were located within a single LD block and that they were strongly genetically intercorrelated with each other (Fig. 3a).

Fig. 3: Indel of 899 bp in the *TaDT1-A* promoter confers drought stress responses and TaMYC2 works upstream of *TaDT1-A.*

Using the variants identified in TaDT1-A, we classified the gene allelic variations into two haplotypes: TaDT1-A^hapI and TaDT1-A^hapII (Fig. 3a). Among all the 191 accessions of the wheat germplasm, approximately three-quarters of the Clade I (70.21%) and most of the Clade II varieties (85.42%) belong to TaDT1-A^hapI, whereas most of the clade III varieties (76.04%) belong to TaDT1-A^hapII (Supplementary Fig. 1d). Since this gene is induced by drought stress, we performed a correlation analysis of its expression and survival differences between the two haplotypes and found that the germplasms harboring the TaDT1-A^hapI allele (without 899 bp) presented substantially higher expression levels and greater drought stress tolerance than those harboring the TaDT1-A^hapII allele (with 899 bp), indicating that this variant may affect gene expression and drought tolerance (Fig. 3b–d).

We developed near-isogenic lines (NILs) of the BC₄F₂ generation derived from two parental wheat lines, Jingdong6 (JD6) and Nongda3338 (ND3338), which harbor TaDT1-A^hapI and TaDT1-A^hapII, respectively (Supplementary Fig. 2a). These two lines presented extremely distinct SRs under drought stress, where JD6 presented high SRs and ND3338 presented low SRs. We further constructed a NIL in the background of the drought-sensitive variety Zhoumai26 (ZM26, one of the major high-yielding cultivars) that carries the TaDT1-A^hapI allele from ZM1817 (a breeding material with prominent drought tolerance). Compared with the respective NIL-TaDT1-A^hapII, both NIL-TaDT1-A^hapI presented significant increases in the SR and relative fresh weight, indicating that NIL-TaDT1-A^hapI were more tolerant to drought (Fig. 3e–g and Supplementary Fig. 2a). Moreover, the expression level of TaDT1-A was greater in both NIL-TaDT1-A^hapI lines than in NIL-TaDT1-A^hapII (Supplementary Fig. 2b). In addition, another NIL in the background of the drought tolerant variety Jin50, which carries the TaDT1-A^hapII allele from the drought-sensitive variety LM3, was generated. Compared with JM50, NIL-TaDT1-A^hapII plants presented lower TaDT1-A expression and a lower SR in response to drought stress (Supplementary Fig. 2c–e), indicating that different TaDT1-A alleles result in drought tolerance variation in wheat.

Given the expression of TaDT1-A is highly associated with drought tolerance, we cloned two haplotype promoters into a LUC reporter to compare their transcriptional activities. Compared with TaDT1-A^hapII, the TaDT1-A^hapI promoter exhibited higher activity in response to treatment, correlating with stronger TaDT1-A^hapI upregulation under drought (Supplementary Fig. 2f). To pinpoint the functional variant loci, we first amplified the partial promoter region of TaDT1-A contains four SNPs. LUC assays showed that no significant activity differences between the two haplotypes, suggesting Indel819 (899-bp deletion) could be the cause of the differential drought stress-induced expression of the two haplotypes (Supplementary Fig. 2f). Sequence analysis identified two G-box cis-elements in the 899 bp insertion within the TaDT1-A^hapII promoter, but absent in the TaDT1-A^hapI promoter. To confirm and pinpoint the functional mutation, we mutated the TaDT1-A^hapI promoter by introducing Indel819 from TaDT1-A^hapII, which we named TaDT1-A^mhapI. Moreover, we also mutated the G-box motif of TaDT1-A^hapII to generate a mutated promoter TaDT1-A^mhapII (Fig. 3a). Compared with the TaDT1-A^hapI promoter, the TaDT1-A^mhapI promoter resulted in a more significant decrease in activity in response to drought treatment, which is comparable to that of the TaDT1-A^hapII promoter. In contrast, the stress activation rate of the activity of the TaDT1-A^mhapII promoter was significantly enhanced by mutation of the G-box motif to a level that was comparable to that of the TaDT1-A^hapI promoter (Fig. 3h).

To identify upstream regulator that may regulate TaDT1-A^hapII, we performed Y1H screen with Indel819 as bait and identified TaMYC2, a nucleus-localized basic helix loop helix (BHLH) protein, as a putative G-box-binding transcription factor. The gel electrophoresis mobility shift assay (EMSA) and transcriptional activation assays revealed that TaMYC2 binds the G-Box motif in the promoter of TaDT1-A^hapII and suppress its under ABA treatment, but not TaDT1-A^hapI. In particular, when the G-box motif of the TaDT1-A^hapII sequence was mutated, the inhibitory effect of TaDT1-A^mhapII by the TaMYC2 was markedly attenuated (Fig. 3h–j, Supplementary Fig. 2g–i). These results indicate that the G-box within the 899-bp indel modulates TaMYC2-mediated repression of the TaDT1-A promoter. Considering that the coding sequence of the two TaDT1-A haplotypes is the same, these results together demonstrate that the 899-bp indel in the promoter region of TaDT1-A alters its transcription in response to drought stress, thereby conferring divergence in drought tolerance in different wheat varieties.

To investigate TaMYC2′s role in wheat drought tolerance, we generated TaMYC2-overexpression lines in wheat variety CB037 (harboring the TaDT1-A^hapII allele with an 899-bp insertion). qRT-PCR showed TaMYC2 transcript levels were significantly higher in the overexpression lines than in the wild-type, while TaDT1-A expression decreased (Supplementary Fig. 2j). Under drought stress, TaMYC2-overexpression lines exhibited decreased SR compared to wild type plants. Further chromatin immunoprecipitation (ChIP)-qPCR assays confirmed TaMYC2 binding to the G-Box-motif within the 899-bp insertion in TaDT1-A promoter, demonstrating TaMYC2 directly regulation of TaDT1-A ^hapII in planta (Fig. 3k–m).

TaDT1-A-TaATG module underlies drought tolerance regulation

On the basis of drought-treated RNA-sequencing analysis of wild-type (Fielder) and TaDT1-A-KO plants, we identified 23,252 differentially expressed genes (DEGs) in wild-type plants under drought stress treatment versus control conditions, including 11,010 upregulated and 12,242 downregulated genes, as drought response genes (Supplementary Fig. 2k and Supplementary Data 11). We then identified 10,756 DEGs between TaDT1-A-KO and WT plants under drought stress conditions (Supplementary Fig. 2k and Supplementary Data 12), and among them, 5971 DEGs were identified by W-box cis-element screening of the promoter region as potential target genes of TaDT1-A under drought stress (Supplementary Data 13). Furthermore, CUT&Tag assays with a specific antibody against the TaDT1-A was performed to analyze its regulated target genes. In total, 10,426 genes were identified as its downstream regulatory targets (Supplementary Data 14). Given that the transcript expression of TaDT1-A is tightly regulated by drought stress, its target genes should also be regulated by drought in correlation with TaDT1-A. Therefore, 580 genes were identified as the TaDT1-A-regulated target genes response to drought stress, combining the drought-responsive genes, W-box cis-element identification and candidate genes in CUT&tag analysis (Supplementary Fig. 2l and Supplementary Data 15). Gene Ontology (GO) enrichment analysis revealed that two pathways were associated with autophagy, indicating that TaDT1-A likely regulates wheat drought tolerance through autophagy pathway modulation (Supplementary Fig. 2m and Supplementary Data 16). Among them, TaATG8 and TaATG18 have previously been shown to play important roles in regulating autophagy and promoting drought tolerance^27,66,67, which makes them vital downstream components of TaDT1-A in modulating drought tolerance. The expression of TaATG8 and TaATG18 was upregulated in TaDT1-A-overexpressing lines but was repressed in its knockout mutants compared with that in wild-type plants (Supplementary Figs. 3a and 5n). The protein level of TaATG8 in TaDT1-A different transgenic plants revealed similar results (Supplementary Fig. 3b). Moreover, TaATG8 and TaATG18 promoter-LUC assays in wheat protoplasts suggested that TaDT1-A could activate the activity of the TaATG8 and TaATG18 promoters (Fig. 4a and Supplementary Fig. 5a). In addition, ChIP‒qPCR assays revealed that TaDT1-A was significantly enriched in the predicted binding sites of the TaATG8 and TaATG18 promoters (Fig. 4b and Supplementary Fig. 5b). Furthermore, EMSA assays demonstrated that TaDT1-A markedly reduced the migration of the probe that contains the predicted binding sites of the TaATG8 and TaATG18 promoters (Fig. 4c and Supplementary Fig. 5c), which indicates that TaDT1-A can directly bind to the TaATG8 and TaATG18 promoters. Considering the vital role of ATGs in autophagy and the increasing number of studies confirming that autophagy positively regulates drought tolerance in plants, we speculate that the occurrence of autophagy may be part of the drought tolerance mechanism mediated by TaDT1-A overexpression. Therefore, we examined the level of autophagy in TaDT1-A OE and knockout line leaves under drought treatment. The status of autophagy in both the TaDT1-A OE and knockout lines was different from that in the wild type under control conditions (Fig. 4d). Under drought stress conditions, both the wild-type plants and the transgenic lines presented more autophagosomes. However, the rates of increase in the number of autophagosomes in the TaDT1-A OE lines were much greater than those in the WT lines, whereas the TaDT1-A knockout lines presented fewer autophagosomes than did the wild-type plants (Fig. 4d, f). Investigation of the cellular ultrastructure through TEM revealed similar results (Fig. 4e and Supplementary Fig. 3d). The ATG8-phosphatidylethanolamine form (ATG8-PE) is a marker for autophagosome and is used as one of the principal methods for measurement of autophagic activity⁶⁸. The immunoblotting assays confirmed enhanced ATG8-PE levels in overexpression lines but reduced in knockout plants of TaDT1-A under drought stress (Supplementary Fig. 3i, j). In addition, we also examined the level of autophagy in the roots of TaDT1-A OE and knockout plants under drought treatment. Both MDC staining and TEM revealed that the number of autophagosomes increased in the roots of the TaDT1-A OE lines but decreased in the TaDT1-A knockout lines compared with the WT plants under drought conditions, which was in line with the change tendency in the leaves. Moreover, autophagy was obviously inhibited by 3-methyladenine (Supplementary Fig. 3e–h). Together, our results suggest that increased autophagic activity is associated with TaDT1-A-regulated drought tolerance.

Fig. 4: TaDT1-A positively improves the drought tolerance of wheat by affecting the generation of autophagosomes and works upstream of *TaATG8.*

TaATG8 and TaATG18 presented similar expression patterns and consistent drought-responsive expression patterns to those of TaDT1-A (Supplementary Figs. 3c and 5o). In addition to lower autophagy levels, both TaATG8 and TaATG18 knockout mutants also presented drought-sensitive phenotypes, including severely wilted leaves and lower SR and autophagy levels under drought stress, which highly resembled the phenotypes of TaDT1-A knockout plants. In contrast, the TaATG8 and TaATG18 overexpression lines presented a greater SR, fewer wilted leaves, and greater autophagy levels than did the wild-type plants under drought conditions, which strongly resembled the phenotypes of the TaDT1-A OE plants. In addition, the overexpression of TaATG8 rescued the drought-sensitive phenotypes as well as the low levels of autophagy in TaDT1-A knockout lines (Fig. 4g–i, Supplementary Fig. 3k–s and Supplementary Fig. 5d–m). Moreover, the expression of TaATG8 and TaATG18 was strongly correlated with TaDT1-A in both drought-tolerant and drought-sensitive varieties under drought stress, which was consistent with the variation in drought tolerance among the different varieties (Supplementary Figs. 4a and 6a). In the NIL-TaDT1-A^hapI, the expression of TaATG8 and TaATG18 also significantly increased under drought conditions (Supplementary Fig. 4b–d and 6b–d). Together, these results demonstrate that TaDT1-A can directly target TaATG8 and TaATG18 and activate their transcript expression, thus positively modulating drought tolerance. Furthermore, we found that water loss was decreased in TaDT1-A OE plants, and TaATG8 and TaATG18 overexpression lines but significantly increased in their knockout mutants (Fig. 2e, Supplementary Figs. 4e and 6e). Consistent with these findings, the leaf stomatal aperture was decreased in the OE lines and increased in the knockout lines compared with the wild-type plants under drought stress conditions, which indicates that TaDT1-A-TaATGs modulate drought tolerance by regulating the stomatal aperture (Fig. 2f, Supplementary Figs. 4f, g and 6f, g). Recent studies have revealed that autophagy modulates drought tolerance via stomatal movement regulation^69,70. In addition, the analysis of drought stress-related metabolic components in TaATG8 plants revealed that autophagy participated in wheat drought tolerance through a variety of metabolic pathways (Supplementary Fig. 4h–n). Our findings thus suggest integrated autophagy and water-use efficiency for modulating wheat drought tolerance by the TaDT1-A-TaATG module.

TaDT1-A and TaCOS1 antagonistically regulate drought tolerance

To further explore the regulatory mechanisms of TaDT1-A in the transcriptional regulation of TaATGs, we performed yeast-two-hybrid screening, and a putative plant-specific DUF641 family protein encoded by TraesCS4B02G134400 was confirmed to interact with TaDT1-A (Fig. 5 and Supplementary Fig. 7). Sequence alignment revealed that it shares the highest sequence identity with COS1 in Arabidopsis, which has been reported to be involved in autophagy in plants⁵²; thus, it was named TaCOS1 (Supplementary Fig. 7a). TaCOS1 was localized in the nucleus and cytoplasm, and its expression was strongly inhibited under drought conditions (Supplementary Fig. 7b, f). The interaction between TaDT1-A and TaCOS1 was further validated by bimolecular fluorescence complementation (BiFC), pull-down, Co-IP, and LCI assays (Fig. 5a–d and Supplementary Fig. 7d, e). TaATG8 and TaATG18 promoter-LUC assays in wheat protoplasts suggested that TaCOS1 could repress the activity of the TaATG8 promoter (Fig. 5h). In addition, TaCOS1 knockout mutants presented drought-tolerant phenotypes, whereas its overexpressing lines exhibited reduced drought tolerance (Fig. 5e, f and Supplementary Fig. 7g). Furthermore, the expression of TaATG8 and TaATG18 was repressed in TaCOS1 overexpressing lines, but upregulated in TaCOS1 knockout mutants, which further demonstrated that TaCOS1 negatively regulates downstream gene expression (Fig. 5g and Supplementary Fig. 7c).

**Fig. 5: TaDT1-A interacts with TaCOS1 and TaCOS1 negatively regulates the drought tolerance of wheat.**

TaDT1-A ^HapI has potential for improving drought tolerance

To determine the genetic effects of TaDT1-A in the vegetative and reproductive stages under drought stress conditions in the field, TaDT1-A OE and knockout plants were grown and compared with wild-type plants in well-watered and water-limited experiments. We monitored and calculated the WUE of all the TaDT1-A transgenic plants at the flowering and grain-filling stages. The WUE of the OE and knockout plants was comparable to that of the wild-type plants under normal conditions. However, under drought stress conditions, the WUE of the TaDT1-A OE plants was greater than that of the wild-type plants, whereas the knockout plants presented a lower WUE than did the wild-type plants (Fig. 6c). Furthermore, a comparison of yield-related traits under normal conditions revealed that the TaDT1-A OE and knockout plants were comparable to the wild-type plants in terms of seven important agronomic traits, including plant height, spike length, rachis number and grain number per spike, grain length, grain width, and thousand kernel weight (TKW), except for the D-O16 line. However, under drought stress conditions, the TaDT1-A OE plants produced longer and wider grains and had a greater TKW than wild-type, whereas knockout lines displayed smaller grain sizes and lower TKW (Fig. 6a–f and Supplementary Fig. 8a, c). As such, these results demonstrate that, in wheat, the expression of TaDT1-A confers a yield advantage under water deficit and does not cause a growth and development penalty under well-watered conditions.

**Fig. 6: *TaDT1-A*, especially haplotype I, significantly increases the drought tolerance of modern cultivars.**

The TaDT1-A^hapI allele enhances drought tolerance through expression regulation, suggesting significant breeding potential for wheat drought resilience. We performed the same field trials with two modified NILs (ZM26×ZM1817, ND3338×JD6). The field test consistently revealed that NIL-TaDT1-A^hapI significantly increased grain width (GW) and TKW (5.46% in ZM26 and 5.49% in ND3338) under water-limited conditions compared with NIL-TaDT1-A^hapII, whereas NIL-TaDT1-A^hapI and NIL-TaDT1-A^hapII plants did not substantially differ under well-watered conditions. The TaDT1-A^hapI allele boosted grain yield in NIL plants while enhancing drought tolerance without yield penalties, demonstrating its breeding potential for elite wheat cultivars. (Fig. 6g–n and Supplementary Fig. 8b, d, e).

Geographical distribution of the TaDT1-A allele

Because accessions harboring HapI and HapII of TaDT1-A presented notable differences in TKW under drought conditions and different drought tolerances, we tested whether this haplotype variation was already under artificial selection during past breeding activities. Haplotype analysis of 191 accessions of the wheat germplasm revealed that TaDT1-A^hapI is enriched in modern breeding cultivars, whereas TaDT1-A^hapII is predominantly found in landraces (Supplementary Data 3). We then extended this analysis to 1032 wheat accessions from the wheat resequencing project^{61,62,63,64,71,72}. Among the accessions from this panel, 81.3% of the cultivars contained the TaDT1-A^hapI allele, whereas only 25.3% of the landraces contained this allele (Fig. 6o). Moreover, we analyzed the relationship between the two haplotypes and geoclimatic information on the natural distribution of these wheat accessions. The frequency of occurrence of the TaDT1-A^hapI allele was highly variable in different regions worldwide and was widespread in Europe, North America, Africa, and Australia, but relatively low in Asia (Fig. 6p). In addition, our findings revealed that the average annual precipitation was significantly lower in natural habitat regions with a high-frequency distribution of the Hap^I subgroup than in those with a high-frequency distribution of the Hap^II subgroup (Supplementary Fig. 8f, g), which is associated with the elite allele of TaDT1-A and enhances WUE in wheat. Therefore, natural variations in TaDT1-A are linked to enhanced drought tolerance in wheat, and TaDT1-A^hapI, which is excellent for use in wheat breeding worldwide, still holds potential for application in specific areas.

Discussion

Exploration of natural elite variants of stress tolerance genes without growth trade-offs is expected to be an effective strategy for the genetic improvement of crops⁷³. In this study, we provide genetic and molecular evidence to demonstrate that the drought tolerance-associated locus TaDT1-A, located on chromosome 2 A of wheat, plays a critical role in mediating drought tolerance (Fig. 1). The drought resilience of this locus is attributed to TaDT1-A, as wheat accessions with TaDT1-A^hapI exhibited greater drought tolerance than TaDT1-A^hapII, along with significantly enhanced water-use efficiency and grain yield under water-withheld conditions. More importantly, NIL-TaDT1-A^hapI in different backgrounds had no adverse effects on plant growth or grain yield under well-watered conditions (Fig. 6 and Supplementary Fig. 8), demonstrating TaDT1-A^hapI as a breeding-elite haplotype that enhances drought tolerance in wheat without yield trade-offs. In addition, we discovered that TaDT1-A underlies the regulation of autophagy homeostasis under drought conditions. A naturally occurring 899-bp deletion in the promoter increases the transcription efficiency of TaDT1-A mRNA and then promotes autophagic activity under drought stress conditions (Figs. 3, 4, and 7). TaDT1-A serves as a breeding target for enhancing wheat drought tolerance through marker-assisted selection or gene editing.

**Fig. 7: A proposed model in which the *TaDT1-A*^hapI allele mediates drought tolerance in wheat.**

Autophagy is activated by multiple mechanisms during drought stress and several transcriptional and posttranslational factors that regulate autophagy in response to drought stress have been identified. One well-studied regulator is the TOR protein kinase, which plays a negative role in the drought response by inhibiting autophagy⁵⁰. KIN10, as the key catalytic subunit of SnRK1 kinase, promotes drought tolerance by affecting ATG1 phosphorylation and further positively regulating autophagy⁷⁴. To date, the bZIP protein TGA9, heat shock transcription factor HsfA1a, and ethylene response factor ERF5 have been revealed as transcription regulators and bind to the promoters of ATG genes to promote autophagy by upregulating ATG expression under drought or osmotic stress^40,75,76. Here, we have shown that the expression of TaATG8 and TaATG18 is induced under water deficit conditions and positively regulates drought responses, as indicated by the increased drought tolerance of TaATG8/TaATG18-overexpressing plants and the hypersensitivity of the taatg8 and taatg18 mutants to drought (Fig. 4 and Supplementary Figs. 3–6). Under drought stress, TaATG8 and TaATG18 exhibited stronger upregulation in TaDT1-A-overexpressing plants and weaker in TaDT1-A knockout plants compared to wild-type, demonstrating TaDT1-A-mediated regulation of these autophagy genes. Our study also revealed a regulatory cascade of the drought-modulated pathway: TaDT1-A is itself drought-regulated and targets TaATG8/18, a vital component of autophagy activity. The TaDT1-A-TaATG8/18 module thus integrates drought and autophagy activity to transduce an environmental stimulus to regulate the cytological process (Fig. 7). TaDT1-A is, therefore, a regulatory factor that modulates autophagy activity and provides a target for further understanding the molecular basis of autophagy during drought stress. These results, together with those of previous studies, suggest that the transcriptional and posttranscriptional activation of ATGs act together to ensure the establishment of autophagy activity and WUE under drought conditions)^69,70. Notably, the mechanisms by which autophagy activity controls and/or modulates stomatal movements remain enigmatic. In Arabidopsis, disruption of autophagy genes, including ATG2, ATG5 and other autophagy-related genes, causes similar stomatal defects and constitutively accumulates high levels of ROS in guard cells, suggesting that autophagy regulates ROS homeostasis in guard cells and modulates the stomatal aperture⁷⁷. In addition, abscisic acid (ABA) and its signaling kinase SnRK2 also have emerged as key players in the induction of autophagy under stress conditions⁵¹. As the major stress hormone, ABA initiates the adaptation of plants to drought stress through stomatal closure. We also speculate TaDT1-A may orchestrate crosstalk between autophagy and other pathways such as ROS homeostasis and ABA signaling. Hence, further investigations are needed to explore and decipher the accurate molecular mechanisms of the TaDT1-A-TaATG8/18 module underlying this dynamic paradigm of the rapid stomatal response to drought stress.

Precise control of autophagy homeostasis is essential for the organization and function of biological systems and is one of the means employed by plants to survive in an ever-changing environment^78,79. In Arabidopsis, the plant-specific protein COST1 inhibits autophagy by mediating the degradation of ATG8 under nonstress conditions, whereas under drought stress, COST1 is degraded by the 26S proteasome and autophagy, which releases ATG8, allows the activation of autophagy and improves drought tolerance⁵². Thus, COST1 is likely an important regulator that balances plant growth and stress responses by modulating autophagy. In this work, we revealed that TaDT1-A physically interacts with TaCOS1, a homolog of Arabidopsis COST1 in wheat, and demonstrated that the TaATG8/TaATG18 locus is the downstream target of TaCOS1 and plays a critical role in the drought tolerance of wheat (Fig. 5 and Supplementary Fig. 7). Unlike Arabidopsis COST1, which is localized mainly in the cytoplasm⁵², TaCOS1 is localized both in the nucleus and cytoplasm and has been revealed to act as a transcription inhibitor to downregulate the expression of the TaATG8/TaATG18 genes to reduce autophagy under drought stress (Fig. 5 and Supplementary Fig. 7). Together, TaDT1-A and TaCOS1 act as molecular switches, orchestrating the transcriptional regulation of TaATG8 and TaATG18, which are essential for autophagy homeostasis. This dynamic balance ensures proper autophagy under both normal and drought conditions (Fig. 7).

A proper balance between drought tolerance and growth is critical for achieving efficient crop improvement in sustainable agriculture to cope with the increasing prevalence of global water resource deficiency. Depending on the duration and severity of drought stress, plants must carefully coordinate their growth and stress responses. We note that some TaDT1-A-overexpressing lines with exceptionally high expression levels presented negative effects on several agronomic traits, such as plant height, under favorable growth conditions, whereas the same genotype presented greater drought tolerance under drought stress conditions. In contrast, TaDT1-A^hapI confers drought tolerance, as evaluated by seedling survival and grain yield under water-deficit conditions in both greenhouse and field tests, whereas, TaDT1-A^hapI-mediated tolerance to drought stress carries has no observable effect on plant growth or yield under favorable growth condition (Fig. 6 and Supplementary Fig. 8). The main difference is likely because the TaDT1-A allele has been selected for fitness through environmental challenge and breeding. Wheat cultivars, such as JM50 and ZM1817 have developed the TaDT1-A^hapI allele to counter drought stress because the TaMYC2 repressor cannot bind to the TaDT1-A^hapI promoter, blocking its induction by drought stress. Wheat is a typical allohexaploid species that combines the D genome from Ae. tauschii with the AB genomes from tetraploid wheat^80,81. Our Sanger sequencing results indicate that the alleles of TaDT1-A in the B and D subgenomes (TraesCS2B02G289000 and TraesCS2D02G269200) share high similarity in coding sequences and have no -899-bp indel haplotype variation in their promoters, suggesting that this natural variation is specific to the A subgenome. TaDT1-A is identical to the homologs (TRIDC2AG038820 and TRIDC2AG038820) of tetraploid emmer and durum wheat. The resequencing results suggest that the allele of TaDT1-A^hapI occurred during the formation of the tetraploid progenitor of wheat, since this haplotype appeared both in emmer and durum wheat but not in T. urartu, the diploid progenitor of the A genome (Supplementary Fig. 8h). Therefore, we speculated that TaDT1-A^hapI originated in allotetraploid progenitors and was selected as an adaptation to environmental challenges and for breeding in allopolyploid wheat. In fact, our further haplotype analysis of the 1256 resequenced wheat genomes available in the public database^{61,62,63,64,71,72} shows the presence of the TaDT-A^hapI allele in 863 wheat varieties distributed in 42 countries, particularly in arid and rain-fed regions (Fig. 6p and Supplementary Fig. 8f–h). These results indicate that this strategy has been selected during the process of breeding in some areas without knowledge of the allele. However, because it is present in only 41.7% of the actively-modern bred varieties in major-wheat producing areas in Asia, there is great potential in introducing this natural allele into other wheat varieties to achieve the current aim of obtaining higher yields with economical irrigation.

Methods

Plant materials

All wheat plants were grown in the experimental field of China Agricultural University in Beijing (39°57’N,116°17’E) and a greenhouse at a relative humidity of 75% and 26/20 °C day/night temperatures, with a light intensity of 3000 lux (Master GreenPower CG T 400 W E40; Philips). The surface-sterilized seeds were incubated at 4 °C for 3 d in the dark and then exposed to white light at room temperature. Germinated seeds were transplanted into pots. The materials were subject to different treatments including water deficit and ABA treatments. For the drought stress phenotype, materials are planted in Pindstrup turf mixed with vermiculite (2:1).

All the 191 accessions of the wheat germplasm which come from all over the world and include cultivars, landraces that are listed in Supplementary Data 1. The common wheat varieties Fielder, CB037, JM50, LM3, ND3338, JD6, ZM26, and ZM1817 were used in this study. The JM50, ZM1817, JD6, ND3338, ZM26 and LM3, which is abbreviation of JinMai50, ZhengMai1817, JingDong6, NongDa3338, ZhouMai26 and LuMai3, respectively. Among of them, JM50, ZM1817, and JD6 are drought-tolerant cultivars; ND3338, ZM26 and LM3 are drought-sensitive cultivars. ND3338 and ZM26 are cultivars with better agronomic traits and are used more in production. CB037 is a transgenic receptor that harboring the 899-bp insertion in the promoter of TaDT1-A. The TaDT1-A, TaATG8, TaATG18, and TaCOS1 knockout mutants and overexpression plants were generated in the Fielder background; The TaMYC2 overexpression plant was generated in the CB037 background. JM50^hapII and JM50^hapI were developed by backcrossing for four generations with LM3 (hapII) in the JM50 (hapI) background. ND3338^hapII and ND3338^hapI were developed by backcrossing for four generations with JD6 (hapI) in the ND3338 (hapII) background. ZM26^hapII and ZM26^hapI were developed by backcrossing for four generations with ZM1817 (hapI) in the ZM26 (hapII) background. Primer sequences used for genotyping are listed in Supplementary Data 9.

Water-deficit drought assays in the seedling stage

For GWAS assays, all the 191 accessions of the wheat germplasm were grown at the China Agricultural University in Beijing greenhouse. The seeds were sown on the cultivation pots (10 × 10 × 12 cm, length × width × depth) that were filled with 180 g of uniformly mixed soil (Pindstrup turf to vermiculite in a ratio of 2:1). Every accession set four pots including one control and three drought treatment, and total conduct two independent experiments. To make sure the different accessions being compared were all exposed to the same severity of soil drying, the soil was fully soaked up overnight, only irrigated once, before planting, and the excess water was removed the next day to ensure that the soil water content in different pots was consistent. Then, the soil water content was randomly measured by FieldScout® TDR 150 Soil Moisture Meter (Spectrum Technologies, Inc.) every day after the initiation to determine the period of re-watering, and the position of different pots was adjusted regularly to reduce environmental errors. The drought treatment was achieved by stopping irrigation from reaching ~3.5% VWC for 5 days, and then watering was resumed to allow plants to recover and the number of surviving plants was recorded 5 days later. Finally, the SR% of all accessions in different conditions were counted and analyzed.

For transgenic and NILs assays, the transgenic seeds of different genotypes with wild-type plants were transplanted side by side in a cultivation box (32 × 24 × 9 cm, length × width × depth) that was filled with 1.2 kg of uniformly mixed soil. The NIL plants were transplanted side by side in a cultivation box (48 × 32 × 12 cm, length × width × depth) that was filled with 3.0 kg of uniformly mixed soil. To make sure the different genotypes being compared were all exposed to the same severity of soil drying, the soil water content was recorded by FieldScout® TDR 150 Soil Moisture Meter every day after the initiation of water withholding to determine the period of re-watering. All drought treatment was achieved by stopping irrigation from reaching ~3.5% VWC for 5 days, and then watering was resumed to allow plants to recover and the number of surviving plants was recorded 5 days later. Statistical analyses were based on data obtained from three independent experiments.

Water-deficit drought assays in the field

For the reproductive stages of transgenic plants, the plots were designed for well-watered planting conditions and drought treatment conditions according to methods described previously²³. The drought treatment plot was separated by a 1.5 m deep waterproof layer to prevent plants from receiving irrigation. Well-watered plots were irrigated throughout the growth period, while the drought plot was subjected to drought treatment after the first irrigation. The plants that were subjected to drought treatment received ~40% of the water that the plants in the sufficiently irrigated plots received.

For the reproductive stages of NIL plants, large-scale field tests were performed at the drought demonstration field in the experimental station of the CangZhou Academy of Agriculture and Forestry Sciences in Cangzhou City, Hebei Province. Well-watered plots were irrigated throughout the growth period, while the drought plot was subjected to drought treatment after the first irrigation. The plants that were subjected to drought treatment received ~35% of the water that the plants in the sufficiently irrigated plots received.

The photosynthetic parameters were analyzed on the flag leaves at a predetermined date between 09:30 and 11:00 h using a LICOR-6400 CO₂ gas exchange analyzer (LICOR-6400, Lincoln, NE). Then, the photosynthesis rates (PSs) and transpiration rates (TRs) in all of the tested genotypes under different conditions were obtained. For the estimation of water use efficiency (WUE), the calculation was conducted by PSs in relation to TRs²³. Agronomic traits related to yield were analyzed following the maturation of the grains and the harvest.

Alignment and genomic variation calling

A panel of previously published resequencing data was used^61,62,63; and the raw genotyping data (coverage: c = 6×) in GVCF formats of the hexaploid wheats were submitted (Accession code: PRJCA033540). For the genotyping data, we trimmed the raw data using Trimmomatic software, and the remaining high-quality data were mapped to the CS wheat reference genome (IWGSC RefSeq v1.0) using BWA⁸². Duplicate reads were removed using samtools v1.4⁸³. SNPs and INDELs were identified using the HaplotypeCaller module (GATK v3.8)⁸⁴ and the GVCF model of the Genome Analysis Toolkit software. All GVCF files were merged. SNPs were preliminarily filtered using the GATK VariantFiltration function with the parameter “–filterExpression QD < 2.0| | FS > 60.0| | MQRankSum < −12.5| | ReadPosRankSum < −8.0| | SOR > 3.0| | MQ < 40.0| | DP > 30| | DP < 3.” The filtering settings for INDELs were “QD < 2.0, FS > 200.0,” and “ReadPosRankSum <−20.0| | DP > 30 | | DP < 3”. SNPs and INDELs that did not meet any of the following criteria were further discarded: (1) MAF ≥ 5% (2) Missing rate ≤ 40% (3) bi-allelic sites. The identified SNPs and InDels were further annotated using the SnpEff v4.3⁸⁵ software tool.

Sequence alignment, homology, and conserved domain analysis

The MYC2 and COS1 homologs were searched against the Ensembl-plants database (http://plants.ensembl.org/) using the BLAST program. Amino acid alignments and homology analyses were performed using the DNAMAN version of 5.0 (LynnonBiosoft, Canada) and MEGA 7 software based on observed divergence. Protein Domains of TaDT1-A, MYC2, and COS1 were searched against the National Center for Biotechnology Information (NCBI) Conserved Domain Search (https://www.ncbi.nlm.nih.gov/) and SMART programs (http://smart.embl-heidelberg.de/).

GWAS mapping

All 191 accessions of wheat germplasm re-sequencing data were used in this study. After quality control, only SNPs with minor allele frequency (MAF) > 0.05 and missing data <30% in the association panel were kept for GWAS analysis using Tassel software. Finally, we obtained 42,744,325 high-quality SNPs. Significant marker-trait associations were identified using a threshold cutoff of 2.339492e^-10, as determined by the average value of 1/effective number of SNPs for each A, B, and D subgenome. The pairwise LD coefficient (r²) between SNPs was calculated using LDBlockShow. The R package was used to make Manhattan and quantile-quantile plots.

Production of overexpression and knock-out mutants

The seedling leaves cDNA of wheat cultivar Chinese spring was used as the template to amplify the ORF of TaDT1-A, TaATG8, TaATG18, TaMYC2, and TaCOS1. Then all fragments were inserted into the pMWB110 vector to achieve the target constructs. For genome editing via CRISPR/Cas9, a sgRNA was designed based on the exon of TaDT1, TaATG8, TaATG18, and TaCOS1 using the ECRISP Design website (http://crispr.hzau.edu.cn/CRISPR-Cereal/index.php), respectively. In essence, reverse complementary sgRNA sequences with Bsa I cohesive ends were synthesized, then oligonucleotides were annealed and inserted into the terminal vector pBUE411. All binary vectors harboring the desired constructs were transferred into strain EHA105 and transformed into the wheat cultivar Fielder using Agrobacterium-mediated transformation.

Subcellular localization

The full-length open reading frame (ORF) of TaDT1-A, TaMYC2, and TaCOS1 were amplified from the Chinese spring genome using specific primers and 2×Hieff Canace® Gold PCR Master Mix (Cat No.10149; Yeasen, Shanghai, China) and inserted into the pCAMBIA1300-GFP vector, respectively. The resulting construct vector and the marker vector were co-introduced into wheat protoplasts or N. benthamiana leaves. Wheat protoplasts transformed with plasmid were cultured overnight and all the cells were then used to observe the GFP fluorescence accordingly (Carl Zeiss; LSM880). The N. benthamiana leaves transformed with plasmid were cultured for 36 h and then used to observe the GFP or RFP fluorescence accordingly (Carl Zeiss; LSM880). Primer sequences are listed in Supplementary Data 9.

RNA extraction and RT-qPCR

Total RNA was extracted from samples using VeZol Reagent (Vazyme Biotech Co., Ltd, R411) and first-strand cDNAs (20 μL) were synthesized from 1 μg starting total RNA using a reverse transcription kit (Vazyme Biotech, R433-01) according to the manufacturer’s instructions.

For RT-qPCR, the reaction mixture was composed of the 0.7 μL cDNA template, 0.2 mM primers, and 5 μL SYBR Green Mix (Vazyme Biotech, Q121-02/03) in a final volume of 10 μL. Amplification was performed using a CFX96 real-time system (Applied Biosystems). Differences in relative transcript levels were calculated using the 2^–ΔCT method. Primer sequences are listed in Supplementary Data 9.

RNA sequencing and statistical analysis

For RNA sequencing and statistical analysis, ten-day-old seedlings of the WT Fielder and TaDT1 knockout lines were treated under normal or drought conditions for RNA extraction. Three biological replicates were performed for each condition. Two micrograms of total RNA of each replication were used to construct RNA-Seq libraries using the NovaSeq platform, The RNA-seq reads were aligned with the Chinese Spring reference genome using STAR with default parameters. The read counts were normalized to fragments per kilobase of exon per million mapped fragments (FPKM) values to show the relative gene expression levels and a detailed analysis of RNA-seq data was conducted as previously described⁸¹. Analyses of enriched functional categories were performed using the Triticeae GeneTribe source option⁸⁶. The relevant data were submitted (Accession code: PRJCA033550).

Stomatal aperture measurement

Leaves of 2-weeks-old TaDT1-A, TaATG8, and TaATG18 transgenic lines and wild-type plants were collected and incubated in stomatal-incubation solution (0.05 M KNO₃/10 mM, MES/50 μM CaCl₂, pH = 6.15) under darkness for 1 h. The leaves were then exposed to air conditions for drought treatment for 10 min. Subsequently, the samples were incubated in the dark-to-light (300-500 μmol•m⁻²•s⁻¹, 25 °C) transition for 1 h. Then, the adaxial sides of the leaf epidermis were peeled off using a cutter blade and leaves were then mounted on slides and observed with an inverted microscope (AE31E, Motic, China), and the stomatal aperture (width/length) were analyzed using the Motic Images Plus 3.0(x64). Two images for each leaf, two leaves for each plant, and five plants for each genotype were used for analysis.

Stomatal conductance measurement

The first fully expanded leaves of 2-weeks-old TaDT1-A overexpression, knockout and wild-type plants, the widest part of the leaf, were applied to measure stomatal conductance with a portable gas analysis system (SC-1, Decagon Devices, Inc.). Three leaves for each plant and three plants for each genotype were used for analysis.

Yeast one-hybrid (Y1H) assays

The promoter fragment for TaDT1-A was amplified and cloned into the Kpn I/Xho I-digested pAbAi vector (BGI, China). The construct was linearized with the restriction enzyme BstB I and then transformed into yeast (Saccharomyces cerevisiae) Y1HGold cells to generate a bait-specific reporter strain. The transformants were selected on a synthetic defined medium lacking Ura and Leu (SD/−Ura/−Leu) and containing 250 ng/mL aureobasidin A (AbA).

Transient dual luciferase reporter assay

The wild-type or mutated promoter sequences of TaDT1-A, TaATG8, and TaATG18 were cloned into the BamHI-digested pGreen II 0800-LUC vector to generate the reporter plasmids. The full-length coding sequences of TaDT1-A, TaCOS1, and TaMYC2 were individually cloned into the XbaI-digested pCAMBIAsuper1300 vector to yield effector constructs. Relative LUC activity assays were performed in wheat protoplasts, with different combinations of constructs co-transfected. Wheat protoplasts were then incubated in darkness for 15 h at 22 °C. For ABA treatment, wheat protoplasts were incubated in darkness for 11 h at 22 °C and then treated with an incubation solution with 200 mM ABA for 4 h. The detection of firefly luciferase (LUC) and Renilla luciferase (REN) activity was performed as described previously⁸¹. Each sample consisted of three independent transfection reactions. Primer sequences are listed in Supplementary Data 9.

Electrophoretic mobility shift assay (EMSA)

The full-length coding sequence of TaMYC2, and TaDT1-A were cloned into the pGEX6p-1 vector using a Seamless Cloning and Assembly Kit (Biomed, China) to generate TaMYC2-GST and TaDT1-A-GST. GST alone was produced from the empty vector and purified for use as a negative control. For EMSA, a 30-bp promoter fragment of TaDT1-A containing one G-box motif, in addition, TaATG8, and TaATG18 containing two W-box motifs was synthesized as a biotin-labeled probe. Unlabeled probes containing the wild-type, mutated G-box, or mutated W-box motif were used as competitors. The assays were performed using a Light Shift Chemiluminescent EMSA Kit (20148; Thermo Fisher Scientific) following the manufacturer’s instructions. Recombinant TaMYC2-GST, TaDT1-A-GST, and GST were added to the reaction mixture (1× binding buffer, 50 ng poly(dl·dC), 2.5% [v/v] glycerol, 0.05% [v/v] NP-40, 50 mM KCl, 5 mM MgCl₂, 2 mM EDTA [pH 8.0], and 1 nM biotin-labeled probe), followed by incubation at 25 °C for 20 min. The reaction products were separated by 6% PAGE and transferred to a nylon membrane; detection of biotin-labeled DNA was performed according to the manufacturer’s instructions.

Chromatin immunoprecipitation (ChIP) assay

ChIP assays were performed as described previously⁸¹. Briefly, 2 g of 10-day-old wheat seedlings were collected and subjected to vacuum infiltration in 1% (v/v) formaldehyde for 20 min at 25 °C. After isolation and lysis of nuclei, chromatin was sonicated and incubated with the anti-GFP antibody (ABclonal, China, 1:2000), and the anti-TaDT1-A antibody (Homemade specific antibody, Wuxi Pharma Tech Company, Shanghai, China, 1:500). The immunoprecipitated DNA fragments were then purified and the enriched DNA fragments were analyzed by qPCR. Amplified DNA from the chromatin fractions before antibody incubation was used as a control. The relative enrichment at each target site was normalized to the input sample. Primer sequences are listed in Supplementary Data 9.

CUT&tag assay and data analysis

The CUT&Tag assays were conducted according to the previously described⁸⁷. Wheat seedlings that treated in different conditions were cleaved into nucleus suspension, and approximately 100,000 nuclei were harvested and incubated with concanavalin A coated magnetic beads for 15 min at RT. Then, bead-bound cells were resuspended and incubated with the anti-TaDT1-A antibody (Homemade specific antibody, Wuxi Pharma Tech Company, Shanghai, China, 1:500) overnight at 4 °C⁸⁸. DNA from CUT&Tag was used to construct sequencing libraries following the protocol provided with NovoNGS® CUT&Tag 4.0 High-Sensitivity Kit (for Illumina®) (Cat#N259-YH01-01A, Shanghai, China). Trimmomatic (version 0.36) was used to filter out low-quality reads⁸⁹. Clean reads were mapped to the Chinese Spring reference genome (IWGSC, RefSeq v1.1) by Bowtie2. MACS2 software (version 2.1.1.20160309) was used to call peaks by default parameters (bandwidth, 300 bp; model fold, 5, 50; p value, 0.00001).

The ATG8 lipidation assay

The analysis of autophagic activity using ATG8 lipidation assay in wheat were conducted according to the previously described⁶⁸. Wheat seedlings that treated in different conditions were grinding and isolated the total proteins. Then analyzed by western blot using anti-ATG8 (AS142769, Agrisera, 1:1000).

MDC Staining

To visualize the accumulation of autophagosomes, 10-day seedlings of wheat leaves and 7-day seedlings of wheat roots from different genotypes were treated in incubated buffer (as the control), 300 mM mannitol, and 300 mM mannitol with 5 mM 3-MA in incubated buffer for 6 h. 3-MA means 3-methyladenine, which is an autophagy inhibitor. Then the leaves of different genotypes in normal or drought conditions were excised and followed by incubation with 0.05 mM MDC (MedChemExpress, Monmouth Junction, NJ, USA) for 30 min in the dark. After three brief washes with 1× PBS, the samples were observed with a confocal microscope (LSM880; Carl Zeiss, Heidenheim, Germany) using a DAPI-specific filter to visualize MDC fluorescence.

Electron microscopy

Samples from differently treated leaves were fixed overnight at 4 °C in 3% glutaraldehyde and 0.1 M sodium cacodylate buffer (pH 6.9) and then processed for electron microscopy according to Xu et al.⁹⁰. Ultrathin sections, cut with an ultramicrotom, were observed with a transmission electron microscope (HITACHI, HT7700, Japan) operating at 75 kV.

Split-luciferase complementation (LCI) assays

For the split-luciferase assays, the indicated genes were separately fused with the N- or C-terminal of the reporter LUC. The coding sequences of TaDT1-A and TaCOS1 were used in LCI assays. The constructs were transformed into the Agrobacterium strain GV3101 and then infiltrated into N. benthamiana leaves. LUC signal was collected after 2 days by using a cooled charge-coupled device camera (NightSHADE LB 985; Berthold Technologies, Bad Wildbad, Germany) after spraying 1 mM of D-luciferin on the leaves (Coolaber; CL6928). Primer sequences are listed in Supplementary Data 9.

Bimolecular fluorescence complementation (BiFC) assay

For the bimolecular fluorescence complementation assays, the coding sequence of TaDT1-A was amplified and cloned into the nYFP vector and the coding sequence of TaCOS1 was amplified and cloned into the cYFP vector. The constructs were transformed into the Agrobacterium strain GV3101 and then infiltrated into N.benthamiana leaves. After 48 h post infiltration, the green fluorescent protein fluorescence signals for tobacco leaves were imaged with a confocal microscope (LSM880; Carl Zeiss, Heidenheim, Germany). Primer sequences are listed in Supplementary Data 9.

Co-immunoprecipitation (Co-IP) assay

For the Co-IP assay, the TaDT1-A-Myc and TaCOS1-GFP fusion constructs were prepared. Then different pairs of specific constructs were co-transformed into the Agrobacterium strain GV3101 and then infiltrated into N. benthamiana leaves. Total proteins were isolated from different positive transformants and incubated with anti-GFP beads at 4 °C for 4 to 6 h with gentle shaking. Then get the corresponding protein after a series of washing steps and elution processes. The gel was prepared by SDS-PAGE kits (Cat No. ZD304C-10, ZOMANBIO, Beijing, China). Input and eluted protein were then analyzed by western blot using anti-GFP (mouse, 1:2000; Abclonal, AE012) or anti-c-Myc (mouse, 1:2000; TransGen Biotech, HT101-01). Primer sequences are listed in Supplementary Data 9.

In vitro pull-down assay

His-TaCOS1 protein, in combination with GST or GST-TaDT1-A, was incubated and immunoprecipitated by GST resin (TransGen Biotech, ProteinIso® GST Resin, DP201-01) at 4 °C for 2 h. The mixture was gathered by centrifugation at 500 g for 5 min, followed by washing with PBS buffer five times. Proteins were separated on 10% (w/v) SDS-PAGE and detected with anti-GST (TransGen Biotech, ProteinFind® Anti-GST Mouse Monoclonal Antibody, HT601, 1:2000) and anti-His (TransGen Biotech, ProteinFind® Anti-His Mouse Monoclonal Antibody, HT501, 1:2000) antibodies. The coding sequences of TaDT1-A and TaCOS1 were used in pull-down assays. Primer sequences are listed in Supplementary Data 9.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

Correspondence and requests for materials should be addressed to Zhaorong Hu. Accession codes: The resequencing genome data, RNA sequencing and CUT&Tag data for this research have been obtained from the WheatUnion (http://wheat.cau.edu.cn/WheatUnion) or deposited in the National Genomics Data Center (https://ngdc.cncb.ac.cn/) under accession code PRJCA033540, PRJCA033550, PRJCA040507 and PRJCA040061, respectively. Source data are provided with this paper.

References

Ault, T. R. On the essentials of drought in a changing climate. Science 368, 256–260 (2020).
Article MathSciNet CAS PubMed ADS Google Scholar
Hazard, B. et al. Strategies to improve wheat for human health. Nat. Food 1, 475–480 (2020).
Article PubMed Google Scholar
Lesk, C., Rowhani, P. & Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 529, 84–87 (2016).
Article CAS PubMed ADS Google Scholar
Langridge, P. & Reynolds, M. Breeding for drought and heat tolerance in wheat. Theor. Appl Genet. 134, 1753–1769 (2021).
Article PubMed Google Scholar
Snowdon, R. J., Wittkop, B., Chen, T. W. & Stahl, A. Crop adaptation to climate change as a consequence of long-term breeding. Theor. Appl. Genet. 134, 1613–1623 (2021).
Article PubMed Google Scholar
Gupta, A., Rico-Medina, A. & Caño-Delgado, A. I. The physiology of plant responses to drought. Science 368, 266–269 (2020).
Article CAS PubMed ADS Google Scholar
Kirigwi, F. M. et al. Markers associated with a QTL for grain yield in wheat under drought. Mol. Breed. 20, 401–413 (2007).
Article CAS Google Scholar
Mathews, K. L. et al. Multi-environment QTL mixed models for drought stress adaptation in wheat. Theor. Appl. Genet. 117, 1077–1091 (2008).
Article PubMed Google Scholar
Kadam, S. et al. Genomic associations for drought tolerance on the short arm of wheat chromosome 4B. Funct. Integr. Genom. 12, 447–464 (2012).
Article CAS Google Scholar
Li, L. et al. Genetic dissection of drought and heat-responsive agronomic traits in wheat. Plant Cell Environ. 42, 2540–2553 (2019).
Article CAS PubMed PubMed Central Google Scholar
Dolferus, R. et al. Determining the genetic architecture of reproductive stage drought tolerance in wheat using a correlated trait and correlated marker effect model. G3 9, 473–489 (2019).
Article CAS PubMed Google Scholar
Pshenichnikova, T. A. et al. Regions of Chromosome 2A of Bread Wheat (Triticum aestivum L.) associated with variation in physiological and agronomical traits under contrasting water regimes. Plants 10, 1023 (2021).
Rabbi, S. et al. Identification of main-effect and environmental interaction QTL and their candidate genes for drought tolerance in a wheat RIL population between two elite spring cultivars. Front Genet. 12, 656037 (2021).
Article PubMed PubMed Central Google Scholar
Sallam, A., Eltaher, S., Alqudah, A. M., Belamkar, V. & Baenziger, P. S. Combined GWAS and QTL mapping revealed candidate genes and SNP network controlling recovery and tolerance traits associated with drought tolerance in seedling winter wheat. Genomics 114, 110358 (2022).
Article CAS PubMed Google Scholar
Zhao, J. et al. Identification of structural variations related to drought tolerance in wheat (Triticum aestivum L.). Theor. Appl. Genet. 136, 37 (2023).
Article CAS PubMed Google Scholar
Liu, H. J. & Yan, J. Crop genome-wide association study: a harvest of biological relevance. Plant J. 97, 8–18 (2019).
Article CAS PubMed Google Scholar
Wang, Q., Tang, J., Han, B. & Huang, X. Advances in genome-wide association studies of complex traits in rice. Theor. Appl. Genet 133, 1415–1425 (2020).
Article PubMed Google Scholar
Wang, X. et al. Genetic variation in ZmVPP1 contributes to drought tolerance in maize seedlings. Nat. Genet. 48, 1233–1241 (2016).
Article CAS PubMed Google Scholar
Yano, K. et al. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nat. Genet. 48, 927–934 (2016).
Article CAS PubMed Google Scholar
Cao, Y. et al. Natural variation of an EF-hand Ca(2+)-binding-protein coding gene confers saline-alkaline tolerance in maize. Nat. Commun. 11, 186 (2020).
Article CAS PubMed PubMed Central ADS Google Scholar
Zeng, R. et al. Natural variation in a type-A response regulator confers maize chilling tolerance. Nat. Commun. 12, 4713 (2021).
Article CAS PubMed PubMed Central ADS Google Scholar
Yu, J. et al. Genome-wide association studies identify OsWRKY53 as a key regulator of salt tolerance in rice. Nat. Commun. 14, 3550 (2023).
Article CAS PubMed PubMed Central ADS Google Scholar
Mao, H. et al. Variation in cis-regulation of a NAC transcription factor contributes to drought tolerance in wheat. Mol. Plant 15, 276–292 (2022).
Article CAS PubMed Google Scholar
Tian, G. et al. Allelic variation of TaWD40-4B.1 contributes to drought tolerance by modulating catalase activity in wheat. Nat. Commun. 14, 1200 (2023).
Article CAS PubMed PubMed Central ADS Google Scholar
Wang, D. et al. TabHLH27 orchestrates root growth and drought tolerance to enhance water use efficiency in wheat. J. Integr. Plant Biol. 66, 1295–1312 (2024).
Article CAS PubMed Google Scholar
Rodriguez, E. et al. Autophagy mediates temporary reprogramming and dedifferentiation in plant somatic cells. Embo J. 39, e103315 (2020).
Article CAS PubMed PubMed Central Google Scholar
Tang, J. & Bassham, D. C. Autophagy during drought: function, regulation, and potential application. Plant J. 109, 390–401 (2022).
Article CAS PubMed Google Scholar
Zhou, J. et al. A non-canonical role of ATG8 in Golgi recovery from heat stress in plants. Nat. Plants 9, 749–765 (2023).
Article CAS PubMed Google Scholar
Zhou, J. et al. NBR1-mediated selective autophagy targets insoluble ubiquitinated protein aggregates in plant stress responses. PLoS Genet. 9, e1003196 (2013).
Article CAS PubMed PubMed Central Google Scholar
Vanhee, C., Zapotoczny, G., Masquelier, D., Ghislain, M. & Batoko, H. The Arabidopsis multistress regulator TSPO is a heme binding membrane protein and a potential scavenger of porphyrins via an autophagy-dependent degradation mechanism. Plant Cell 23, 785–805 (2011).
Article CAS PubMed PubMed Central Google Scholar
Hachez, C. et al. The Arabidopsis abiotic stress-induced TSPO-related protein reduces cell-surface expression of the aquaporin PIP2;7 through protein-protein interactions and autophagic degradation. Plant Cell 26, 4974–4990 (2014).
Article CAS PubMed PubMed Central Google Scholar
Nolan, T. M. et al. Selective aAutophagy of BES1 mediated by DSK2 balances plant growth and survival. Dev. Cell 41, 33–46.e37 (2017).
Article CAS PubMed PubMed Central Google Scholar
Sun, X. et al. Improvement of drought tolerance by overexpressing MdATG18a is mediated by modified antioxidant system and activated autophagy in transgenic apple. Plant Biotechnol. J. 16, 545–557 (2018).
Article CAS PubMed Google Scholar
Li, X. et al. Dehydrin MtCAS31 promotes autophagic degradation under drought stress. Autophagy 16, 862–877 (2020).
Article CAS PubMed Google Scholar
Wu, X. et al. A viral small interfering RNA-host plant mRNA pathway modulates virus-induced drought tolerance by enhancing autophagy. Plant Cell 36, 3219–3236 (2024).
Article CAS PubMed PubMed Central Google Scholar
Phillips, A. R., Suttangkakul, A. & Vierstra, R. D. The ATG12-conjugating enzyme ATG10 Is essential for autophagic vesicle formation in Arabidopsis thaliana. Genetics 178, 1339–1353 (2008).
Article CAS PubMed PubMed Central Google Scholar
Chung, T., Phillips, A. R. & Vierstra, R. D. ATG8 lipidation and ATG8-mediated autophagy in Arabidopsis require ATG12 expressed from the differentially controlled ATG12A AND ATG12B loci. Plant J. 62, 483–493 (2010).
Article CAS PubMed Google Scholar
Suttangkakul, A., Li, F., Chung, T. & Vierstra, R. D. The ATG1/ATG13 protein kinase complex is both a regulator and a target of autophagic recycling in Arabidopsis. Plant Cell 23, 3761–3779 (2011).
Article CAS PubMed PubMed Central Google Scholar
Zhuang, X. et al. ATG9 regulates autophagosome progression from the endoplasmic reticulum in Arabidopsis. Proc. Natl. Acad. Sci. USA 114, E426–e435 (2017).
Article CAS PubMed PubMed Central Google Scholar
Zhu, T. et al. Mitochondrial alternative oxidase-dependent autophagy involved in ethylene-mediated drought tolerance in Solanum lycopersicum. Plant Biotechnol. J. 16, 2063–2076 (2018).
Article CAS PubMed PubMed Central Google Scholar
Osawa, T. et al. Atg2 mediates direct lipid transfer between membranes for autophagosome formation. Nat. Struct. Mol. Biol. 26, 281–288 (2019).
Article CAS PubMed Google Scholar
Matoba, K. et al. Atg9 is a lipid scramblase that mediates autophagosomal membrane expansion. Nat. Struct. Mol. Biol. 27, 1185–1193 (2020).
Article CAS PubMed Google Scholar
Zhou, L. L. et al. Short-term waterlogging-induced autophagy in root cells of wheat can inhibit programmed cell death. Protoplasma 258, 891–904 (2021).
Article CAS PubMed Google Scholar
Yue, W. et al. The landscape of Autophagy-Related (ATG) genes and functional characterization of TaVAMP727 to Autophagy In Wheat. Int. J. Mol. Sci. 23, 891 (2022).
Shen, C., Wei, C. & Wu, Y. Barley yellow dwarf Virus-GAV movement protein activating wheat TaATG6-Mediated antiviral autophagy pathway. Plant Physiol. Biochem 200, 107771 (2023).
Article CAS PubMed Google Scholar
Hickey, K. et al. Drought tolerance strategies and autophagy in resilient wheat genotypes. Cells 11, 1765 (2022).
Hickey, K. et al. Genotype-specific activation of autophagy during heat wave in wheat. Cells 13, 1226 (2024).
Li, Y. B. et al. Autophagic survival precedes programmed cell death in wheat seedlings exposed to drought stress. Int. J. Mol. Sci. 20, 5777 (2019).
Yue, J. Y., Wang, Y. J., Jiao, J. L. & Wang, H. Z. Silencing of ATG2 and ATG7 promotes programmed cell death in wheat via inhibition of autophagy under salt stress. Ecotoxicol. Environ. Saf. 225, 112761 (2021).
Article CAS PubMed Google Scholar
Pu, Y., Luo, X. & Bassham, D. C. TOR-dependent and -independent pathways regulate autophagy in arabidopsis thaliana. Front. Plant Sci. 8, 1204 (2017).
Article PubMed PubMed Central Google Scholar
Signorelli, S., Tarkowski, P., Van den Ende, W. & Bassham, D. C. Linking autophagy to abiotic and biotic stress responses. Trends Plant Sci. 24, 413–430 (2019).
Article CAS PubMed PubMed Central Google Scholar
Bao, Y. et al. COST1 regulates autophagy to control plant drought tolerance. Proc. Natl. Acad. Sci. USA 117, 7482–7493 (2020).
Article CAS PubMed PubMed Central ADS Google Scholar
Laureano-Marín, A. M. et al. Abscisic acid-triggered persulfidation of the Cys protease ATG4 mediates regulation of autophagy by Sulfide. Plant Cell 32, 3902–3920 (2020).
Article PubMed PubMed Central Google Scholar
Yang, C. et al. A positive feedback regulation of SnRK1 signaling by autophagy in plants. Mol. Plant 16, 1192–1211 (2023).
Article CAS PubMed Google Scholar
Wang, K., Ding, Y., Cai, C., Chen, Z. & Zhu, C. The role of C2H2 zinc finger proteins in plant responses to abiotic stresses. Physiol. Plant 165, 690–700 (2019).
Article CAS PubMed Google Scholar
Dong, J. et al. The C(2)H(2)-type zinc finger transcription factor ZmDi19-7 regulates plant height and organ size by promoting cell size in maize. Plant J. 120, 2700–2722 (2024).
Article CAS PubMed Google Scholar
Yuan, X. et al. A zinc finger transcriptional repressor confers pleiotropic effects on rice growth and drought tolerance by down-regulating stress-responsive genes. Plant Cell Physiol. 59, 2129–2142 (2018).
Article CAS PubMed Google Scholar
Huang, R. et al. Zinc finger transcription factor MtZPT2-2 negatively regulates salt tolerance in Medicago truncatula. Plant Physiol. 194, 564–577 (2023).
Article PubMed Google Scholar
Wang, X. et al. Brassinosteroid signaling represses ZINC FINGER PROTEIN11 to regulate ovule development in Arabidopsis. Plant Cell 36, 5004–5022 (2024).
Article CAS PubMed Google Scholar
Zhang, Y., Xiao, W., Wang, M., Khan, M. & Liu, J. H. A C2H2-type zinc finger protein ZAT12 of Poncirus trifoliata acts downstream of CBF1 to regulate cold tolerance. Plant J. 117, 1317–1329 (2024).
Article CAS PubMed Google Scholar
Cheng, H. et al. Frequent intra- and inter-species introgression shapes the landscape of genetic variation in bread wheat. Genome Biol. 20, 136 (2019).
Article PubMed PubMed Central Google Scholar
Guo, W. et al. Origin and adaptation to high altitude of Tibetan semi-wild wheat. Nat. Commun. 11, 5085 (2020).
Article CAS PubMed PubMed Central ADS Google Scholar
Hao, C. et al. Resequencing of 145 landmark cultivars reveals asymmetric sub-genome selection and strong founder genotype effects on wheat breeding in China. Mol. Plant 13, 1733–1751 (2020).
Article CAS PubMed Google Scholar
Zhou, Y. et al. Triticum population sequencing provides insights into wheat adaptation. Nat. Genet. 52, 1412–1422 (2020).
Article CAS PubMed Google Scholar
Fleury, D., Jefferies, S., Kuchel, H. & Langridge, P. Genetic and genomic tools to improve drought tolerance in wheat. J. Exp. Bot. 61, 3211–3222 (2010).
Article CAS PubMed Google Scholar
Liu, Y., Xiong, Y. & Bassham, D. C. Autophagy is required for tolerance of drought and salt stress in plants. Autophagy 5, 954–963 (2009).
Article CAS PubMed Google Scholar
Kuzuoglu-Ozturk, D. et al. Autophagy-related gene, TdAtg8, in wild emmer wheat plays a role in drought and osmotic stress response. Planta 236, 1081–1092 (2012).
Article CAS PubMed Google Scholar
Luo, M. & Zhuang, X. Analysis of autophagic activity using ATG8 lipidation assay in Arabidopsis thaliana. Bio Protoc. 8, e2880 (2018).
CAS PubMed PubMed Central Google Scholar
Jia, X. et al. Overexpression of MdATG8i improves water use efficiency in transgenic apple by modulating photosynthesis, osmotic balance, and autophagic activity under moderate water deficit. Hortic. Res. 8, 81 (2021).
Article CAS PubMed PubMed Central Google Scholar
Xiang, W. et al. The apple autophagy-related gene MdATG10 improves drought tolerance and water use efficiency in transgenic apple plants. Plant Physiol. Biochem. 206, 108214 (2024).
Article CAS PubMed Google Scholar
Schulthess, A. W. et al. Genomics-informed prebreeding unlocks the diversity in genebanks for wheat improvement. Nat. Genet. 54, 1544–1552 (2022).
Article CAS PubMed Google Scholar
Niu, J. et al. Whole-genome sequencing of diverse wheat accessions uncovers genetic changes during modern breeding in China and the United States. Plant Cell 35, 4199–4216 (2023).
Article CAS PubMed PubMed Central Google Scholar
Bailey-Serres, J., Parker, J. E., Ainsworth, E. A., Oldroyd, G. E. D. & Schroeder, J. I. Genetic strategies for improving crop yields. Nature 575, 109–118 (2019).
Article CAS PubMed PubMed Central ADS Google Scholar
Chen, L. et al. The AMP-activated protein kinase KIN10 is involved in the regulation of autophagy in Arabidopsis. Front Plant Sci. 8, 1201 (2017).
Article PubMed PubMed Central Google Scholar
Wang, Y. et al. Tomato HsfA1a plays a critical role in plant drought tolerance by activating ATG genes and inducing autophagy. Autophagy 11, 2033–2047 (2015).
Article CAS PubMed PubMed Central Google Scholar
Wang, P., Nolan, T. M., Yin, Y. & Bassham, D. C. Identification of transcription factors that regulate ATG8 expression and autophagy in Arabidopsis. Autophagy 16, 123–139 (2020).
Article CAS PubMed Google Scholar
Yamauchi, S. et al. Autophagy controls reactive oxygen species homeostasis in guard cells that is essential for stomatal opening. Proc. Natl. Acad. Sci. USA 116, 19187–19192 (2019).
Article CAS PubMed PubMed Central ADS Google Scholar
Qi, H., Xia, F. N. & Xiao, S. Autophagy in plants: physiological roles and post-translational regulation. J. Integr. Plant Biol. 63, 161–179 (2021).
Article CAS PubMed Google Scholar
Huang, L. & Guo, H. Acetylation modification in the regulation of macroautophagy. Adv. Biotechnol. 2, 19 (2024).
Article CAS Google Scholar
Berkman, P. J. et al. Dispersion and domestication shaped the genome of bread wheat. Plant Biotechnol. J. 11, 564–571 (2013).
Article CAS PubMed Google Scholar
Zheng, M. et al. Histone acetyltransferase TaHAG1 acts as a crucial regulator to strengthen salt tolerance of hexaploid wheat. Plant Physiol. 186, 1951–1969 (2021).
Article CAS PubMed PubMed Central Google Scholar
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Article PubMed PubMed Central Google Scholar
International Wheat Genome Sequencing Consortium (IWGSC). Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 361, eaar7191 (2018).
McKenna, A. et al. The genome analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
Article CAS PubMed PubMed Central Google Scholar
Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80–92 (2012).
Article CAS PubMed PubMed Central Google Scholar
Chen, Y. et al. A Collinearity-Incorporating Homology Inference Strategy for Connecting Emerging Assemblies in the Triticeae Tribe as a Pilot Practice in the Plant Pangenomic Era. Mol. Plant 13, 1694–1708 (2020).
Article CAS PubMed Google Scholar
Kaya-Okur, H. S. et al. CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nat. Commun. 10, 1930 (2019).
Article PubMed PubMed Central ADS Google Scholar
Chang, S. et al. Lysine deacetylase TaSRT1 mediates wheat drought tolerance by deacetylating TaDT-A to reduce its protein stability and transcriptional activity. Plant Biotechnol. J. 23, 1650–1667 (2025).
Article CAS PubMed PubMed Central Google Scholar
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Article CAS PubMed PubMed Central Google Scholar
Xu, F. et al. A novel role for cyanide in the control of cucumber (Cucumis sativus L.) seedlings response to environmental stress. Plant Cell Environ. 35, 1983–1997 (2012).
Article CAS PubMed Google Scholar

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Acknowledgements

We thank Dr. Xiangfeng Wang (China Agricultural University) for helpful suggestions and discussions for measurement of autophagic activity on the text. This work was supported by the Major Project on Agricultural Bio-breeding of China (2023ZD04026, Z.H.), the National Natural Science Foundation of China (32130078, Q.S. and Z.H., 32441061, Z.H., 32072001, Z.H.), the National Key Research and Development Program of China (2022YFF1001604, Z.H., 2021YFD1200603, Z.H.), Chinese Universities Scientific Fund (2024TC188, Z.H.) and Pinduoduo-China Agricultural University Research Fund (PC2024A01002, H.P and Z.H.).

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These authors contributed equally: Xingbei Liu, Jinpeng Li.

Authors and Affiliations

State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping/Frontiers Science Center for Molecular Design Breeding/Key Laboratory of Crop Heterosis and Utilization (MOE)/College of Agronomy and Biotechnology, China Agricultural University, Beijing, PR China
Xingbei Liu, Jinpeng Li, Chenji Zhang, Danyang Zhao, Xiao Peng, Qun Yang, Zehui Liu, Lingfeng Miao, Wei Chu, Jingchen Lin, Shumin Chang, Debiao Liu, Xiaoyu Liu, Wenxi Wang, Xiaobo Wang, Mingming Xin, Yingyin Yao, Weilong Guo, Huiru Peng, Zhongfu Ni, Qixin Sun & Zhaorong Hu
International Joint Center for the Mechanismic Dissection and Genetic Improvement of Crop Stress Tolerance, College of Agriculture & Resources and Environmental Sciences, Tianjin Agricultural University, Tianjin, PR China
Xiaodong Xie

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Contributions

Z.H. and Q.S. led and supervised this project. X.B.L. and J.L. performed most of the experiments. C.Z., D.Z., X.P., Q.Y., Z.L., L.M., W.C., J.Lin., S.C., D.L., X.Y.L., W.W., and X.W. helped with propagation and genotyping of the materials. M.X., Y.Y., W.G., X.X., H.P., Z.N. and Q.S. provided the wheat materials, and the SNP information and helpful comments on the work. Z.H. designed the research and wrote the manuscript.

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Correspondence to Zhaorong Hu.

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Nature Communications thanks Sanu Arora, Hao Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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Liu, X., Li, J., Zhang, C. et al. An elite allele TaDT1-A^hapI enhances drought tolerance via mediating autophagic pathways in wheat. Nat Commun 16, 6563 (2025). https://doi.org/10.1038/s41467-025-61943-3

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Received: 30 July 2024
Accepted: 04 July 2025
Published: 16 July 2025
Version of record: 16 July 2025
DOI: https://doi.org/10.1038/s41467-025-61943-3