The excessive application of nitrogen fertilizers has led to ecological pollution and waste of agricultural resources. Developing nitrogen-efficient wheat varieties and improving nitrogen use efficiency are effective approaches for achieving sustainable agricultural development and environmental protection. Screening low-nitrogen-tolerant germplasm resources and identifying genetic loci and candidate genes associated with low-nitrogen tolerance can provide materials and theoretical foundations for breeding nitrogen-efficient wheat varieties.

A natural population consisting of 389 wheat varieties was cultivated under high-nitrogen (HN) and low-nitrogen (LN) treatments in 10 field environments. Grain yield per plant (GYP) was measured to calculate the stress tolerance index (STI), thereby enabling the classification of varieties with differential low-nitrogen tolerance. Genome-wide association studies (GWAS) were conducted using 660K SNP array genotyping data to identify stable genetic loci associated with low-nitrogen tolerance. Candidate genes were prioritized through haplotype analysis, expression profiling, and functional annotation.

Twelve wheat varieties with strong low-nitrogen tolerance were identified, including Zhongluo 08-1, Jimai 15, Jinghua 2, Kehong 1, Mianyang 19, Jimai 22, Zhenmai 4, Yumai 35, Fengkang 7, Mianyang 11, Jinmai 31, and Lumai 5. Fourteen loci significantly associated with STI were detected, among which four (qSTI1A.1, qSTI3B, qSTI6A, and qSTI7A.2) overlapped with previously reported low-nitrogen tolerance or yield-related QTLs. Notably, qSTI3B-replicated across three environments-was identified as a key locus governing low-nitrogen tolerance. Functional annotation revealed that its candidate gene, TraesCS3B02G042400, encodes an AP2/EREBP (APETALA2/ethylene-responsive element-binding protein) transcription factor. Haplotype analysis showed significant STI divergence among varieties carrying distinct haplotypes, while expression levels of TraesCS3B02G042400 exhibited nitrogen dose-responsive upregulation.

Twelve wheat varieties with strong low-nitrogen tolerance were screened. A stable genetic locus, qSTI3B, and a candidate gene, TraesCS3B02G042400, associated with low-nitrogen tolerance were identified.

Drought is one of the foremost abiotic stress limiting global wheat production. Exploring the molecular mechanism of wheat response to drought stress have great significance in wheat molecular breeding. Circular RNAs (circRNAs) have been proved to play an important role in the process of plants tolerance to environmental stresses. Therefore, identifying circRNAs involved in drought stress response will help to construct a regulatory network of wheat drought tolerance, and lay a foundation for analyzing the drought resistance mechanism in wheat.

In this study, two wheat varieties (Zhoumai13 and Jimai38) with significant differences in drought resistance were used and circRNA-seq was performed on their root samples under well-watered and drought conditions. Differentially expressed circRNAs related to drought stress response were screened based on the identified circRNAs and their microRNAs (miRNAs) targets were predicted. Further, potential circRNA-miRNA-mRNA regulatory modules related to wheat drought stress response were constructed according to the expression patterns of miRNAs and their target genes under drought stress.

A total of 1 409 wheat circRNAs were identified, most of which (68.91%) were exonic circRNAs. Only 133 circRNAs were simultaneously identified in both varieties. A total of 239 differentially expressed circRNAs were identified under drought stress, of which 138 circRNAs were specifically differentially expressed in the drought-resistant variety Zhoumai 13 (ZM13), and 19 circRNAs were differentially expressed simultaneously in both varieties. Besides, 34 targeted miRNAs and 1 408 miRNA target genes were predicted. Based on the expression patterns of these differentially expressed circRNAs, targeted miRNAs, and miRNA target genes, five potential circRNA-miRNA-mRNA regulatory modules centered on tae-miR9664-3p, tae-miR1122b-3p, tae-miR9662a-3p, tae-miR6197-5p and tae-miR1120c-5p in response to drought stress were screened.

Wheat circRNAs have obvious specificity in different cultivars and different expression patterns among different drought-tolerant wheat cultivars. A total of 239 wheat circRNAs and 5 potential circRNA-miRNA-mRNA regulatory modules in response to drought stress were identified in the present study.

To evaluate the drought resistance of synthetic wheat germplasm based on multi-source images collected by unmanned aerial vehicle (UAV) and yield data, explore high-throughput indices for drought resistance evaluation, and identify synthetic wheat germplasm resources with drought resistance. This provides technical support and germplasm materials for accelerating the expansion of drought-resistant genetic resources for wheat and enhancing the level of breeding for dryland wheat.

Eighty synthetic wheat germplasm and the control variety Xin Chun 37 were used as plant materials, which were sown in the field and treated with a water regime of drought stress and irrigation. Multi-source images of test materials during filling stage were collected by multi-spectral and thermal infrared cameras equipped with unmanned aerial vehicle, and the spectral index of each test material was extracted by threshold segmentation. The analyses of Pearson’s correlation and principal component were performed to identify drought resistance-related spectral indices, and the drought resistance of each synthetic wheat germplasm was determined by single index and comprehensive evaluation methods.

The drought resistance coefficients of 19 spectral indices of 80 synthetic wheat germplasm were calculated based on multisource imagery data obtained from unmanned aerial vehicles. The correlation analysis between the spectral indices and the yield-based drought index (DRI) showed that among the drought resistance coefficients of the 19 spectral indices, OSAVI exhibited the highest correlation with the drought index, while NDVI, CI_re, and NDRE demonstrated relatively strong associations with the drought index. However, the different drought indices showed a high correlation, resulting in redundant information. The drought resistance coefficients of the 19 spectral indices were transformed into three independent comprehensive indicators through principal component analysis, with contribution rates of 59.6%, 12.0% and 9.6%, respectively. The comprehensive drought resistance index (D) for each synthetic wheat germplasm were calculated by aggregating the three independent comprehensive indicators using the weighted membership function method. 6 and 5 synthetic wheat germplasms with strong drought resistance were identified based on DRI and D, respectively. Among them, 2 germplasms (SW004 and SW009) with high drought resistance were detected based on both DRI and D. Furthermore, the drought resistance of the 80 synthetic wheat germplasms was graded based on the drought resistance coefficient of OSAVI, and the grading results were found to be consistent with that based on the D value. Among the six strongly drought-resistant germplasms identified based on the drought resistance coefficient of OSAVI, five of them were also classified as strongly drought-resistant germplasms based on comprehensive drought resistance evaluation.

The spectral indices NDVI, OSAVI, CI_re and NDRE extracted from UAV-based multi-source images, as well as the drought resistance comprehensive evaluation value can be used to assist in the identification of drought resistance of wheat germplasm.