Genome-wide association study of agronomic traits related to nitrogen use efficiency in wheat

A genome-wide association study reveals the genetic architecture of 19 agronomic traits in broomcorn millet (Panicum miliaceum L.)

KEY MESSAGE

The genetic architecture of 19 growth and development and yield-related traits was dissected by a GWAS in multi-environment of a diverse population consisting of 301 broomcorn millet accessions. Broomcorn millet (Panicum miliaceum L.) is an ideal replant crop due to its advantages of drought resistance, short growth period, and strong adaptability. Understanding the genetic basis of agronomic traits is crucial for improving the efficiency of molecular breeding in broomcorn millet. In this study, a natural population consisting of 301 worldwide broomcorn millet accessions was genotyped using 208,169 high-quality single-nucleotide polymorphisms (SNPs). Nineteen agronomic traits, including growth period, plant architecture, and yield-related traits, were investigated across ten environments. Based on genomic and phenotypic data, a genome-wide association study (GWAS) was performed to identify significant marker-trait associations (MTAs) affecting these traits. Using the linear mixed model, 662 significant MTAs were identified for 19 traits, with 56 stable MTAs repeatedly identified over two environments. Among these stable SNPs, 40 were located in genomic regions where no relevant loci had been reported previously. Notably, superior alleles of four significant SNPs chr1_2925777, chr7_157147, chr4_3971792, and chr5_2126999 associated with panicle length (PL) and the whole growth period (GP) exhibited significantly higher phenotypic levels. Ultimately, 174 genes within the flanking regions of these four significant SNPs were annotated. Among these, six genes were identified as candidate genes associated with PL and GP. Further haplotype analysis identified seven haplotypes for longmi011379 and longmi011388. Phenotypic assessment of major haplotypes revealed significant differences between Hap1 and Hap2. These results provide a valuable resource for understanding the genetic mechanisms of growth and development and yield-related traits and developing marker-assisted selection breeding in broomcorn millet.

From Images to Loci: Applying 3D Deep Learning to Enable Multivariate and Multitemporal Digital Phenotyping and Mapping the Genetics Underlying Nitrogen Use Efficiency in Wheat

The selection and promotion of high-yielding and nitrogen-efficient wheat varieties can reduce nitrogen fertilizer application while ensuring wheat yield and quality and contribute to the sustainable development of agriculture; thus, the mining and localization of nitrogen use efficiency (NUE) genes is particularly important, but the localization of NUE genes requires a large amount of phenotypic data support. In view of this, we propose the use of low-altitude aerial photography to acquire field images at a large scale, generate 3-dimensional (3D) point clouds and multispectral images of wheat plots, propose a wheat 3D plot segmentation dataset, quantify the plot canopy height via combination with PointNet++, and generate 4 nitrogen utilization-related vegetation indices via index calculations. Six height-related and 24 vegetation-index-related dynamic digital phenotypes were extracted from the digital phenotypes collected at different time points and fitted to generate dynamic curves. We applied height-derived dynamic numerical phenotypes to genome-wide association studies of 160 wheat cultivars (660,000 single-nucleotide polymorphisms) and found that we were able to locate reliable loci associated with height and NUE, some of which were consistent with published studies. Finally, dynamic phenotypes derived from plant indices can also be applied to genome-wide association studies and ultimately locate NUE- and growth-related loci. In conclusion, we believe that our work demonstrates valuable advances in 3D digital dynamic phenotyping for locating genes for NUE in wheat and provides breeders with accurate phenotypic data for the selection and breeding of nitrogen-efficient wheat varieties.

Domestication and the evolution of crops: variable syndromes, complex genetic architectures, and ecological entanglements

Domestication can be considered a specialized mutualism in which a domesticator exerts control over the reproduction or propagation (fitness) of a domesticated species to gain resources or services. The evolution of crops by human-associated selection provides a powerful set of models to study recent evolutionary adaptations and their genetic bases. Moreover, the domestication and dispersal of crops such as rice, maize, and wheat during the Holocene transformed human social and political organization by serving as the key mechanism by which human societies fed themselves. Here we review major themes and identify emerging questions in three fundamental areas of crop domestication research: domestication phenotypes and syndromes, genetic architecture underlying crop evolution, and the ecology of domestication. Current insights on the domestication syndrome in crops largely come from research on cereal crops such as rice and maize, and recent work indicates distinct domestication phenotypes can arise from different domestication histories. While early studies on the genetics of domestication often identified single large-effect loci underlying major domestication traits, emerging evidence supports polygenic bases for many canonical traits such as shattering and plant architecture. Adaptation in human-constructed environments also influenced ecological traits in domesticates such as resource acquisition rates and interactions with other organisms such as root mycorrhizal fungi and pollinators. Understanding the ecological context of domestication will be key to developing resource-efficient crops and implementing more sustainable land management and cultivation practices.

Genome-wide association study of agronomic traits related to nitrogen use efficiency in Henan wheat

BACKGROUND

Nitrogen use efficiency (NUE) is closely related to crop yield and nitrogen fertilizer application rate. Although NUE is susceptible to environments, quantitative trait nucleotides (QTNs) for NUE in wheat germplasm populations have been rarely reported in genome-wide associated study.

RESULTS

In this study, 244 wheat accessions were phenotyped by three NUE-related traits in three environments and genotyped by 203,224 SNPs. All the phenotypes for each trait were used to associate with all the genotypes of these SNP markers for identifying QTNs and QTN-by-environment interactions via 3VmrMLM. Among 279 QTNs and one QTN-by-environment interaction for low nitrogen tolerance, 33 were stably identified, especially, one large QTN (r2 > 10%), qPHR3A.2, was newly identified for plant height ratio in one environment and multi-environment joint analysis. Among 52 genes around qPHR3A.2, four genes (TraesCS3A01G101900, TraesCS3A01G102200, TraesCS3A01G104100, and TraesCS3A01G105400) were found to be differentially expressed in low-nitrogen-tolerant wheat genotypes, while TaCLH2 (TraesCS3A01G101900) was putatively involved in porphyrin metabolism in KEGG enrichment analyses.

CONCLUSIONS

This study identified valuable candidate gene for low-N-tolerant wheat breeding and provides new insights into the genetic basis of low N tolerance in wheat.

The Genetic Dissection of Nitrogen Use-Related Traits in Flax (Linum usitatissimum L.) at the Seedling Stage through the Integration of Multi-Locus GWAS, RNA-seq and Genomic Selection

Nitrogen (N), the most important macro-nutrient for plant growth and development, is a key factor that determines crop yield. Yet its excessive applications pollute the environment and are expensive. Hence, studying nitrogen use efficiency (NUE) in crops is fundamental for sustainable agriculture. Here, an association panel consisting of 123 flax accessions was evaluated for 21 NUE-related traits at the seedling stage under optimum N (N+) and N deficiency (N-) treatments to dissect the genetic architecture of NUE-related traits using a multi-omics approach integrating genome-wide association studies (GWAS), transcriptome analysis and genomic selection (GS). Root traits exhibited significant and positive correlations with NUE under N- conditions (r = 0.33 to 0.43, p < 0.05). A total of 359 QTLs were identified, accounting for 0.11% to 23.1% of the phenotypic variation in NUE-related traits. Transcriptomic analysis identified 1034 differentially expressed genes (DEGs) under contrasting N conditions. DEGs involved in N metabolism, root development, amino acid transport and catabolism and others, were found near the QTLs. GS models to predict NUE stress tolerance index (NUE_STI) trait were tested using a random genome-wide SNP dataset and a GWAS-derived QTLs dataset. The latter produced superior prediction accuracy (r = 0.62 to 0.79) compared to the genome-wide SNP marker dataset (r = 0.11) for NUE_STI. Our results provide insights into the QTL architecture of NUE-related traits, identify candidate genes for further studies, and propose genomic breeding tools to achieve superior NUE in flax under low N input.

Genetic regions determine tolerance to nitrogen deficiency in European elite bread wheats grown under contrasting nitrogen stress scenarios

KEY MESSAGE

Clustering 24 environments in four contrasting nitrogen stress scenarios enabled the detection of genetic regions determining tolerance to nitrogen deficiency in European elite bread wheats. Increasing the nitrogen use efficiency of wheat varieties is an important goal for breeding. However, most genetic studies of wheat grown at different nitrogen levels in the field report significant interactions with the genotype. The chromosomal regions possibly involved in these interactions are largely unknown. The objective of this study was to quantify the response of elite bread wheat cultivars to different nitrogen field stress scenarios and identify genomic regions involved in this response. For this purpose, 212 elite bread wheat varieties were grown in a multi-environment trial at different nitrogen levels. Genomic regions associated with grain yield, protein concentration and grain protein deviation responses to nitrogen deficiency were identified. Environments were clustered according to adjusted means for grain yield, yield components and grain protein concentration. Four nitrogen availability scenarios were identified: optimal condition, moderate early deficiency, severe late deficiency, and severe continuous deficiency. A large range of tolerance to nitrogen deficiency was observed among varieties, which were ranked differently in different nitrogen deficiency scenarios. The well-known negative correlation between grain yield and grain protein concentration also existed between their respective tolerance indices. Interestingly, the tolerance indices for grain yield and grain protein deviation were either null or weakly positive meaning that breeding for the two traits should be less difficult than expected. Twenty-two QTL regions were identified for the tolerance indices. By selecting associated markers, these regions may be selected separately or combined to improve the tolerance to N deficiency within a breeding programme.

Identification and validation of new quantitative trait loci for spike-related traits in two RIL populations

Wheat (Triticum aestivum L.) is one of the most important cereal crops for ensuring food security worldwide. Identification of major quantitative trait loci (QTL) for spike-related traits is important for improvement of yield potential in wheat breeding. In this study, by using the wheat 55K single nucleotide polymorphism (SNP) array and diversity array technology (DArT), two recombinant inbred line populations derived from crosses avocet/chilero and avocet/huites were used to map QTL for kernel number per spike (KNS), total spikelet number per spike (TSS), fertile spikelet number per spike (FSS), and spike compactness (SC). Forty-two QTLs were identified on chromosomes 2A (4), 2B (3), 3A (2), 3B (7), 5A (11), 6A (4), 6B, and 7A (10), explaining 3.13-21.80% of the phenotypic variances. Twelve QTLs were detected in multi-environments on chromosomes 2A, 3B (2), 5A (4), 6A (3), 6B, and 7A, while four QTL clusters were detected on chromosomes 3A, 3B, 5A, and 7A. Two stable and new QTL clusters, QKns/Tss/Fss/SC.haust-5A and QKns/Tss/Fss.haust-7A, were detected in the physical intervals of 547.49-590.46 Mb and 511.54-516.15 Mb, accounting for 7.53-14.78% and 7.01-20.66% of the phenotypic variances, respectively. High-confidence annotated genes for QKns/Tss/Fss/SC.haust-5A and QKns/Tss/Fss.haust-7A were more highly expressed in spike development. The results provide new QTL and molecular markers for marker-assisted breeding in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01401-4.

A Gene from Ganoderma lucidum with Similarity to nmrA of Filamentous Ascomycetes Contributes to Regulating AreA

Fungal AreA is a key nitrogen metabolism transcription factor in nitrogen metabolism repression (NMR). Studies have shown that there are different ways to regulate AreA activity in yeast and filamentous ascomycetes, but in Basidiomycota, how AreA is regulated is unknown. Here, a gene from Ganoderma lucidum with similarity to nmrA of filamentous ascomycetes was identified. The NmrA interacted with the C-terminal of AreA according to yeast two-hybrid assay. In order to determine the effect of NmrA on the AreA, 2 nmrA silenced strains of G. lucidum, with silencing efficiencies of 76% and 78%, were constructed using an RNA interference method. Silencing nmrA resulted in a decreased content of AreA. The content of AreA in nmrAi-3 and nmrAi-48 decreased by approximately 68% and 60%, respectively, compared with that in the WT in the ammonium condition. Under the nitrate culture condition, silencing nmrA resulted in a 40% decrease compared with the WT. Silencing nmrA also reduced the stability of the AreA protein. When the mycelia were treated with cycloheximide for 6 h, the AreA protein was almost undetectable in the nmrA silenced strains, while there was still approximately 80% of the AreA protein in the WT strains. In addition, under the nitrate culture, the content of AreA protein in the nuclei of the WT strains was significantly increased compared with that under the ammonium condition. However, when nmrA was silenced, the content of the AreA protein in the nuclei did not change compared with the WT. Compared with the WT, the expression of the glutamine synthetase gene in nmrAi-3 and nmrAi-48 strains increased by approximately 94% and 88%, respectively, under the ammonium condition, while the expression level of the nitrate reductase gene in nmrAi-3 and nmrAi-48 strains increased by approximately 100% and 93%, respectively, under the nitrate condition. Finally, silencing nmrA inhibited mycelial growth and increased ganoderic acid biosynthesis. Our findings are the first to reveal that a gene from G. lucidum with similarity to the nmrA of filamentous ascomycetes contributes to regulating AreA, which provides new insight into how AreA is regulated in Basidiomycota.

Current Progress and Future Prospect of Wheat Genetics Research towards an Enhanced Nitrogen Use Efficiency

To improve the yield and quality of wheat is of great importance for food security worldwide. One of the most effective and significant approaches to achieve this goal is to enhance the nitrogen use efficiency (NUE) in wheat. In this review, a comprehensive understanding of the factors involved in the process of the wheat nitrogen uptake, assimilation and remobilization of nitrogen in wheat were introduced. An appropriate definition of NUE is vital prior to its precise evaluation for the following gene identification and breeding process. Apart from grain yield (GY) and grain protein content (GPC), the commonly recognized major indicators of NUE, grain protein deviation (GPD) could also be considered as a potential trait for NUE evaluation. As a complex quantitative trait, NUE is affected by transporter proteins, kinases, transcription factors (TFs) and micro RNAs (miRNAs), which participate in the nitrogen uptake process, as well as key enzymes, circadian regulators, cross-talks between carbon metabolism, which are associated with nitrogen assimilation and remobilization. A series of quantitative genetic loci (QTLs) and linking markers were compiled in the hope to help discover more efficient and useful genetic resources for breeding program. For future NUE improvement, an exploration for other criteria during selection process that incorporates morphological, physiological and biochemical traits is needed. Applying new technologies from phenomics will allow high-throughput NUE phenotyping and accelerate the breeding process. A combination of multi-omics techniques and the previously verified QTLs and molecular markers will facilitate the NUE QTL-mapping and novel gene identification.