Root system architecture of historical spring wheat cultivars is associated with alleles and transcripts of major functional genes

Decreased root hydraulic traits in German winter wheat cultivars over 100 years of breeding

Wheat (Triticum aestivum L.) plays a vital role in global food security, and understanding its root traits is essential for improving water uptake under varying environmental conditions. This study investigated how over a century of breeding has influenced root morphological and hydraulic properties in 6 German winter wheat cultivars released between 1895 and 2002. Field and hydroponic experiments were used to measure root diameter, root number, branching density, and whole root system hydraulic conductance (Krs). The results showed a significant decline in root axes number and Krs with release year, while root diameter remained stable across cultivars. Additionally, dynamic functional-structural modeling using the whole-plant model CPlantBox was employed to simulate Krs development with root system growth, revealing that older cultivars consistently had higher hydraulic conductance than modern ones. The combined approach of field phenotyping and modeling provided a comprehensive view of the changes in root traits arising from breeding. These findings suggest that breeding may have unintentionally favored cultivars with smaller root systems and more conservative water uptake strategies under the high-input, high-density conditions of modern agriculture. The results of this study may inform future breeding efforts aimed at optimizing wheat root systems, helping to develop cultivars with water uptake strategies better tailored to locally changing environmental conditions.

Plasticity of Root System Architecture and Whole Transcriptome Responses Underlying Nitrogen Deficiency Tolerance Conferred by a Wild Emmer Wheat QTL

Our aim was to elucidate mechanisms underlying nitrogen (N)-deficiency tolerance in bread wheat (cultivar Ruta), conferred by a wild emmer wheat QTL (WEW; IL99). We hypothesised that the tolerance in IL99 is driven by enhanced N-uptake through modification of root system architecture (RSA) underscored by transcriptome modifications. Severe N-deficiency (0.1 N for 26 days) triggered significantly higher plasticity in IL99 compared to Ruta by modifying 16 RSA traits; nine of which were IL99-specific. The change in root growth in IL99 was collectively characterised by a transition in root orientation from shallow to steep, increased root number and length, and denser networks, enabling nutrient acquisition from a larger volume and deeper soil layers. Gene ontology and KEGG-enrichment analyses highlighted IL99-specific pathways and candidate genes elevated under N-deficiency. This included Jasmonic acid metabolism, a key hormone mediating RSA plasticity (AOS1, TIFY, MTB2, MYC2), and lignification-mediated root strengthening (CYP73A, 4CL). 'N-metabolism' was identified as a main shared pathway to IL99 and Ruta, with enhanced nitrate uptake predominant in IL99 (NRT2.4), while remobilisation was the main strategy in Ruta (NRT2.3). These findings provide novel insights into wheat plasticity response underlying tolerance to N-deficiency and demonstrate the potential of WEW for improving N-uptake under suboptimal conditions.

Research on the regulation mechanism of drought tolerance in wheat

Wheat (Triticum aestivum L.) is one of the most important crops in arid and semi-arid areas of the world, and its sustainable and efficient production is essential for ensuring food security in China and globally. However, with the global climate change, wheat production is increasingly endangered by abiotic stress, and drought stress has become the main abiotic stress factor restricting wheat production efficiently. Therefore, investigating drought resistance genes and elucidating the mechanisms underlying drought resistance regulation is crucial for the genetic enhancement of drought resistance and the development of new drought-resistant wheat varieties. This paper reviews the majority of research conducted on wheat drought resistance over the past five years, focusing on aspects, such as transcriptional regulation, protein post-translational modifications, and other regulatory mechanisms related to drought resistance in wheat. Additionally, this paper discusses future directions for the genetic improvement of drought resistance and the breeding of new drought-resistant wheat varieties.

High-throughput root phenotyping and association analysis identified potential genomic regions for phosphorus use efficiency in wheat (Triticum aestivum L.)

MAIN CONCLUSION

Association analysis identified 77 marker-trait associations (MTAs) for PUE traits, of which 10 were high-confidence MTAs. Candidate-gene mining and in-silico expression analysis identified 13 putative candidate genes for PUE traits. Bread wheat (Triticum aestivum L.) is a major cereal crop affected by phosphorus (P) deficiency, which affects root characteristics, plant biomass, and other attributes related to P-use efficiency (PUE). Understanding the genetic mechanisms of PUE traits helps in developing bread wheat cultivars that perform well in low-P environments. With this objective, we evaluated a bread wheat panel comprising 304 accessions for 14 PUE traits with high-throughput phenotyping under low-P and optimum-P treatments and observed a significant genetic variation among germplasm lines for studied traits. Genome-wide association study (GWAS) using 14,025 high-quality single-nucleotide polymorphisms identified 77 marker-trait associations (MTAs), of which 10 were chosen as high-confidence MTAs as they had > 10% phenotypic variation with logarithm of odds (LOD) scores of more than five. Candidate-gene (CG) mining from high-confidence MTAs identified 180 unique gene models, of which 78 were differentially expressed (DEGs) with at least twofold change in expression under low-P over optimum-P. Of the 78-DEGs, 13 were thought to be putative CGs as they exhibited functional relevance to PUE traits. These CGs mainly encode for important proteins and their products involved in regulating root system architecture, P uptake, transport, and utilization. Promoter analysis from 1500 bp upstream of gene start site for 13 putative CGs revealed the presence of light responsive, salicylic-acid responsive, gibberellic-acid (GA)-responsive, auxin-responsive, and cold responsive cis-regulatory elements. High-confidence MTAs and putative CGs identified in this study can be employed in breeding programs to improve PUE traits in bread wheat.

PEG treatment is unsuitable to study root related traits as it alters root anatomy in barley (Hordeum vulgare L.)

BACKGROUND

The frequency and severity of abiotic stress events, especially drought, are increasing due to climate change. The plant root is the most important organ for water uptake and the first to be affected by water limitation. It is therefore becoming increasingly important to include root traits in studies on drought stress tolerance. However, phenotyping under field conditions remains a challenging task. In this study, plants were grown in a hydroponic system with polyethylene glycol as an osmotic stressor and in sand pots to examine the root system of eleven spring barley genotypes. The root anatomy of two genotypes with different response to drought was investigated microscopically.

RESULTS

Root diameter increased significantly (p < 0.05) under polyethylene glycol treatment by 54% but decreased significantly (p < 0.05) by 12% under drought stress in sand pots. Polyethylene glycol treatment increased root tip diameter (51%) and reduced diameter of the elongation zone (14%) compared to the control. Under drought stress, shoot mass of plants grown in sand pots showed a higher correlation (r = 0.30) with the shoot mass under field condition than polyethylene glycol treated plants (r = -0.22).

CONCLUSION

These results indicate that barley roots take up polyethylene glycol by the root tip and polyethylene glycol prevents further water uptake. Polyethylene glycol-triggered osmotic stress is therefore unsuitable for investigating root morphology traits in barley. Root architecture of roots grown in sand pots is more comparable to roots grown under field conditions.

Applications of Artificial Intelligence in Wheat Breeding for Sustainable Food Security

In agriculture, especially in crop breeding, innovative approaches are required to address the urgent issues posed by climate change and global food security. Artificial intelligence (AI) is a revolutionary technology in wheat breeding that provides new approaches to improve the ability of crops to withstand and produce higher yields in response to changing climate circumstances. This review paper examines the incorporation of artificial intelligence (AI) into conventional wheat breeding methods, with a focus on the contribution of AI in tackling the intricacies of contemporary agriculture. This review aims to assess the influence of AI technologies on enhancing the efficiency, precision, and sustainability of wheat breeding projects. We conduct a thorough analysis of recent research to evaluate several applications of artificial intelligence, such as machine learning (ML), deep learning (DL), and genomic selection (GS). These technologies expedite the swift analysis and interpretation of extensive datasets, augmenting the process of selecting and breeding wheat varieties that are well-suited to a wide range of environmental circumstances. The findings from the examined research demonstrate notable progress in wheat breeding as a result of artificial intelligence. ML algorithms have enhanced the precision of predicting phenotypic traits, whereas genomic selection has reduced the duration of breeding cycles. Utilizing artificial intelligence, high-throughput phenotyping allows for meticulous examination of plant characteristics under different stress environments, facilitating the identification of robust varieties. Furthermore, AI-driven models have exhibited superior predicted accuracies for crop productivity and disease resistance in comparison to conventional methods. AI technologies play a crucial role in the modernization of wheat breeding, providing significant enhancements in crop performance and adaptability. This integration not only facilitates the growth of wheat cultivars that provide large yields and can withstand stressful conditions but also strengthens global food security in the context of climate change. Ongoing study and collaboration across several fields are crucial to improving and optimizing these AI applications, ultimately enhancing their influence on sustainable agriculture.

Evaluation of functional kompetitive allele-specific PCR (KASP) markers for selection of drought-tolerant wheat (Triticum aestivum) genotypes

Wheat (Triticum aestivum ) is a major crop around the globe and different techniques are being used for its productivity enhancement. Germplasm evaluation to improve crop productivity mainly depends on accurate phenotyping and selection of genotypes with a high frequency of superior alleles related to the trait of interest. Therefore, applying functional kompetitive allele-specific PCR (KASP) markers for drought-related genes is essential to characterise the genotypes for developing future climate-resilient wheat crop. In this study, eight functional KASP markers and nine morphological traits were employed to evaluate the 40 wheat genotypes for drought tolerance. Morphological traits showed significant variation (P ≤0.05) among the genotypes, except tiller count (TC), fresh root weight (FRW) and dry root weight (DRW). PCA biplot showed that 63.3% phenotypic variation was explained by the first two PCs under control treatment, while 70.8% variation was explained under drought treatment. It also indicated that root length (RL) and primary root (PR) have considerable variations among the genotypes under both treatments and are positively associated with each other. Hence, the findings of this study suggested that both these traits could be used as a selection criterion to classify the drought-tolerant wheat genotypes. KASP genotyping accompanied by morphological data revealed that genotypes Markaz, Bhakar Star, China 2, Aas and Chakwal-50 performed better under drought stress. These outperforming genotypes could be used as parents in developing drought-tolerant wheat genotypes. Hence, KASP genotyping assay for functional genes or significant haplotypes and phenotypic evaluation are prerequisites for a modern breeding program.

Genetic Signature Controlling Root System Architecture in Diverse Spring Wheat Germplasm

Roots are the main sensing organ, initiating multiple signaling pathways in response to abiotic factors, including nutrients, drought, and salt stress. A focus on improving the root system architecture is a key strategy to mitigate these stresses in wheat crop. In the present study, a diversity panel comprising indigenous landraces and historical cultivars from Pakistan was characterized for the root system architecture (RSA) and important loci were identified using a genome-wide association study (GWAS). RSA of the diversity panel was characterized 30 days after sowing in brunch tubes, and root images were taken. A high-throughput root imaging analysis using Rhizovision software was performed by setting the scale to extract the eight RSA traits and four plant biomass-related traits. GWAS identified 323 association signals for 12 root and biomass traits present on all wheat chromosomes, while the most important and reliable genetic loci (based on pleotropic loci and candidate genes) were identified on chromosomes 2A, 2B, 5A, 5D, 6A, 7B, and 7D for RSA. SNP annotation and transcriptome profiling identified nine candidate genes regulating the RSA and plant biomass traits, including ROOTLESS WITH UNDETECTABLE MERISTEM1, MYB TRANSCRIPTION FACTOR4, BRASSINOSTEROID INSENSITIVE1, SLENDER RICE1, AUXIN-RESPONSIVE FACTOR25, SCARECROW, NARROW LEAF2, PIN-FORMED1 AND PHOSPHATE TRANSCRIPTION FACTOR1. This study provided pre-breeding information for deep-rooting genotypes and associated markers that will accelerate the incorporation of such traits in breeding.

RNAseq of diverse spring wheat cultivars released during last 110 years

Here, we performed RNA-seq based expression analysis of root and leaf tissues of a set of 24 historical spring wheat cultivars representing 110 years of temporal genetic variations. This huge 130 tissues RNAseq dataset was initially used to study expression pattern of 97 genes regulating root growth and development in wheat. Root system architecture (RSA) is an important target for breeding stress-resilient and high-yielding wheat cultivars under climatic fluctuations. However, root transcriptome analysis is usually obscured due to challenges in root research due to their below ground presence. We also validated the dataset by performing correlation analysis between expression of RSA related genes in roots and leaves with 25 root traits analyzed under varying moisture conditions and 10 yield-related traits. The Pearson's correlation coefficients between root phenotypes and expression of root-specific genes varied from -0.72 to 0.78, and strong correlations with genes such as DRO1, TaMOR, ARF4, PIN1 was observed. The presented datasets have multiple uses such as a) studying the change in expression pattern of genes during time, b) differential expression of genes in two very important tissues of wheat i.e., leaf and roots, and c) studying customized expression of genes associated with important phenotypes in diverse wheat cultivars. The initial findings presented here provided key insights into understanding the transcriptomic basis of phenotypic variability of RSA in wheat cultivars.

Genome-wide linkage mapping of root system architecture-related traits in common wheat (Triticum aestivum L.)

Identifying loci for root system architecture (RSA) traits and developing available markers are crucial for wheat breeding. In this study, RSA-related traits, including total root length (TRL), total root area (TRA), and number of root tips (NRT), were evaluated in the Doumai/Shi4185 recombinant inbred line (RIL) population under hydroponics. In addition, both the RILs and parents were genotyped using the wheat 90K single-nucleotide polymorphism (SNP) array. In total, two quantitative trait loci (QTLs) each for TRL (QTRL.caas-4A.1 and QTRL.caas-4A.2), TRA (QTRA.caas-4A and QTRA.caas-4D), and NRT (QNRT.caas-5B and QNRT.caas-5D) were identified and each explaining 5.94%-9.47%, 6.85%-7.10%, and 5.91%-10.16% phenotypic variances, respectively. Among these, QTRL.caas-4A.1 and QTRA.caas-4A overlapped with previous reports, while QTRL.caas-4A.2, QTRA.caas-4D, QNRT.caas-5B, and QNRT.caas-5D were novel. The favorable alleles of QTRL.caas-4A.1, QTRA.caas-4A, and QTRA.caas-5B were contributed by Doumai, whereas the favorable alleles of QTRL.caas-4A.2, QTRA.caas-4D, and QTRA.caas-5D originated from Shi 4185. Additionally, two competitive allele-specific PCR (KASP) markers, Kasp_4A_RL (QTRA.caas-4A) and Kasp_5D_RT (QNRT.caas-5D), were developed and validated in 165 wheat accessions. This study provides new loci and available KASP markers, accelerating wheat breeding for higher yields.