QTL and Candidate Genes: Techniques and Advancement in Abiotic Stress Resistance Breeding of Major Cereals

Variation analysis and quantitative trait loci mapping of 16 free amino acid traits in the tea plant (Camellia sinensis)

BACKGROUND

The levels of free amino acids (FAAs) and the timing of bud flush (TBF) are among the the most economic traits of tea plants (Camellia sinensis). Investigating the genetic variation characteristics of FAAs and their potential associations with TBF is critical for the breeding of new tea cultivars with high economic value.

METHODS

In this study, we utilized the 'Emei Wenchun' (♀) × 'Chuanmu 217' (♂) filial 1 (F1) genetic population (n = 208) and measured their FAA contents in the "one bud and two leaves" samples across two spring seasons and one summer season using high-performance liquid chromatography combined with the Waters AccQ-Tag method. The sprouting index (SPI) was observed over two springs to quantify the TBF trait. A genetic map previously constructed based on the same population was employed for quantitative trait loci (QTL) mapping.

RESULTS

A total of 16 FAAs were measured, and the average total FAA contents were 28.1 and 25.4 mg/g (dry weight) in the two spring seasons and 14.29 mg/g in the summer season. Within the population, the coefficients of variation (CV) for the FAAs ranged from 23 to 41% within each season, and the correlation coefficients (r) varied from 0.15 to 0.35 across seasons. ANOVA analyses revealed that 13 out of the 16 FAAs exhibited significant genetic variation, with the estimated broad-sense heritability (h2) ranging between 10.33% and 57.10%. Interestingly, three FAAs and the total FAA contents showed significant positive correlations (r = 0.21-0.34, P < 0.01) with the SPI trait in both spring seasons. QTL mapping identified 13 FAA-associated QTLs distributed across eight linkage groups.

CONCLUSION

Within the F1 population, the FAAs exhibited considerable variation across seasons, their heritabilities were generally low (most ≤ 50%). There was a weak but significant positive correlation between FAAs and TBF. Additionally, 13 FAA-associated QTLs were identified. The results of this study enhance our understanding of the genetic variation characteristics of FAAs and provide insights for breeding tea cultivars with both higher FAAs and earlier TBF.

Dissection of QTLs underlying the genetic basis of drought resistance in wheat: a meta-analysis

Wheat (Triticum aestivum L.) is one of the most important cereal crops, with its grain serving as a predominant staple food source on a global scale. However, there are many biotic and abiotic stresses challenging the stability of wheat production. Among the abiotic stresses, drought is recognized as a significant stress and poses a substantial threat to food production and quality throughout the world. Raising drought tolerance of wheat varieties through genetic regulation is therefore considered as one of the most effective ways to combat the challenges caused by drought stress. Meta-QTL analysis has demonstrated its effectiveness in identifying consensus QTL regions in wheat drought resistance in numerous instances. In this study, we present a comprehensive meta-analysis aimed at unraveling the drought tolerance genetic basis associated with agronomic traits in bread wheat. Extracting data from 34 previously published studies, we aggregated a corpus of 1291 Quantitative Trait Loci (QTL) pertinent to wheat drought tolerance. Then, the translation of the consensus genetic map yielded a comprehensive compendium of 49 distinct MQTLs, each associated with diverse agronomic traits. Prominently featured among the MQTLs were MQTLs 1.1, 1.7, 1.8 (1D), 4.1 (4A), 4.6 (4D), 5.2 (5B), 6.6 (6B), and 7.2 (7B), distinguished as pivotal MQTLs offering significant potential for application in marker-assisted breeding endeavors. Altogether, a total of 66 putative candidate genes (CGs)-related drought tolerance were identified. This work illustrates a translational research approach in transferring information from published mapping studies to genomic regions hosting major QTLs governing key agronomical traits in wheat.

Machine learning-enhanced multi-trait genomic prediction for optimizing cannabinoid profiles in cannabis

Cannabis sativa L., known for its medicinal and psychoactive properties, has recently experienced rapid market expansion but remains understudied in terms of its fundamental biology due to historical prohibitions. This pioneering study implements GS and ML to optimize cannabinoid profiles in cannabis breeding. We analyzed a representative population of drug-type cannabis accessions, quantifying major cannabinoids and utilizing high-density genotyping with 250K SNPs for GS. Our evaluations of various models-including ML algorithms, statistical methods, and Bayesian approaches-highlighted Random Forest's superior predictive accuracy for single and multi-trait genomic predictions, particularly for THC, CBD, and their precursors. Multi-trait analyses elucidated complex genetic interdependencies and identified key loci crucial to cannabinoid biosynthesis. These results demonstrate the efficacy of integrating GS and ML in developing cannabis varieties with tailored cannabinoid profiles.

Search of Reflectance Indices for Estimating Photosynthetic Activity of Wheat Plants Under Drought Stress

Global climate change and the associated increasing impact of droughts on crops challenges researchers to rapidly assess plant health on a large scale. Photosynthetic activity is one of the key physiological parameters related to future crop yield. The present study focuses on the search for reflectance parameters for rapid screening of wheat genotypes with respect to photosynthetic activity under drought conditions. The development of drought stress modelled in laboratory conditions by stopping irrigation caused changes in chlorophyll fluorescence parameters that corresponded to a decrease in photosynthetic activity. In particular, a decrease in the photochemical quantum yield of photosystem II (ΦPSII), which characterizes the rate of linear electron transport in the photosynthetic electron transport chain and is one of the most sensitive parameters responding at the early stages of drought stress, was observed. Along with the measurement of the photosynthetic activity, spectral characteristics of wheat plants were recorded using hyperspectral imaging. Normalized difference indices (NDIs) were calculated using the reflectance intensity of wheat shoots in the range from 400 to 1000 nm. Four NDIs that showed a strong correlation with the level of photosynthetic activity estimated by ΦPSII were selected from different wavelength ranges (NDI610/450, NDI572/545, NDI740/700, and NDI820/630). The indices NDI572/545 and NDI820/630 showed the best combination of sensitivity to soil moisture deficit and strong relationship with photosynthetic activity under drought stress. Possible molecular and physiological causes of this relationship are discussed. The use of the proposed indices will allow to monitor in detail the specific features of wheat plant response and can serve as one of the criteria for selection of the most promising genotypes in breeding of drought-tolerant cultivars.

GWAS combined with linkage analysis reveals major QTLs and candidate genes of salt tolerance in Japonica rice seedlings

Background

Soil salinization is one of the significant factors limiting high crop yields and expansion of arable land, seriously affecting global agricultural production. Rice is an essential food crop throughout the world, and its seedlings are particularly susceptible to salt stress, which can directly affect the growth and development of rice and its final yield. We used the natural population as the material for genome-wide association study (GWAS) and the recombinant inbred line (RIL) population from CD (salt sensitive)/WD20342 (salt tolerant) hybridization as the material for linkage analysis.

Results

The degree of salt tolerance was evaluated by using the relative root length (RRL), relative root number (RRN), relative root fresh weight (RRFW), and relative root dry weight (RRDW) as indicators. Fifteen and six major quantitative trait loci (QTLs) were identified by GWAS and linkage analysis, respectively. Meanwhile, the GWAS identified the lead SNP (Chr2_22340368), which was located within qRRL2 and qRRDW2 identified by linkage analysis. GWAS, combined with linkage analysis, selected a 196-kb overlapping region on chromosome 2, including 22 candidate genes. LOC_Os02g36880 was discovered as the candidate gene involved in salt tolerance by haplotype analysis, qRT-PCR, and sequence analysis. The score of salinity toxicity (SST) and seedling survival rate (SSR) were determined for CRISPR/Cas9 mutants (CR-1 and CR-15) and wild-type (ZH11), respectively.

Conclusion

The phenotypic validation indicated that LOC_Os02g36880 negatively regulated the salt tolerance at the seedling stage. This study provides resources for breeding Japonica rice to improve its response to salt stress.

Elucidating morphogenic and physiological traits of rice with nitrogen substitution through nano-nitrogen under salt stress conditions

BACKGROUND

Sustainable crop production along with best nutrient use efficiency is the key indicator of smart agriculture. Foliar application of plant nutrients can complement soil fertilization with improved nutrient uptake, translocation and utilization. Recent developments in slow releasing, nano-fertilizers in agriculture, begins a new era for sustainable use and management of natural resources. This study aims to explore the effectiveness of nano-nitrogen usage on plant growth, yield attributes and sustaining rice production while optimizing fertilizer N application through conventional (prilled urea) and nano-N source under salt stress conditions.

RESULTS

The strategic substitutions of traditional urea by nano-nitrogen was distributed from partial to complete with 33, 50, 66 and 100% applications. Further, the strategic substitutions were compared in saline (ECe ∼ 6.0 dSm- 1) and sodic stress (pH ∼ 9.1) conditions along with normal soils to dissect the beneficial response of nano-N in two rice varieties (CSR 30 and PB 1121). Salt stress affected the plant performance by decreasing leaf relative water content upto 10%, total chlorophyll content by 1.3-1.5%, leaf area upto 29.9%, gas exchange attributes by 10-39%, with concomitant yield reductions upto ∼ 4%. Collateral improvement in leaf greenness (SPAD index) crop growth rate and net assimilation rate was observed with foliar application of Nano-N. 0.2-1.64% enhancement in growth traits, 0.93-1.85% in physiological traits, and comparable yield gains with 100% recommended dose of prilled were comparative with nano-substitutions. Salt tolerant rice variety, CSR-30 performed better than PB 1121 with better expression of morphological, physiological and yield traits under stress conditions and nitrogen substitutions.

CONCLUSIONS

Overall, our experimental findings revealed agricultural use of nano-N in improving the plant physiological efficiency and optimizing rice yields with partial N substitution through nano fertilizers under salt stress conditions. These studies are further open for futuristic aspects of long term effects of nano-fertilizers on soil nutrient depletion in correlation to yield enhancement in salt affected soils.

Analysis of Rice Blast Fungus Genetic Diversity and Identification of a Novel Blast Resistance OsDRq12 Gene

The rice blast fungus Magnaporthe oryzae poses a significant challenge to maintaining rice production. Developing rice varieties with resistance to this disease is crucial for its effective control. To understand the genetic variability of blast isolates collected between 2015 and 2017, the 27 monogenic rice lines that carry specific resistance genes were used to evaluate blast disease reactions. Based on criteria such as viability, virulence, and reactions to resistance genes, 20 blast isolates were selected as representative strains. To identify novel resistance genes, a quantitative trait locus analysis was carried out utilizing a mixture of the 20 representative rice blast isolates and a rice population derived from crossing the blast-resistant cultivar 'Cheongcheong' with the blast-susceptible cultivar 'Nagdong'. This analysis revealed a significant locus, RM1227-RM1261 on chromosome 12, that is associated with rice blast resistance. Within this locus, 12 disease resistance-associated protein genes were identified. Among them, OsDRq12, a member of the nucleotide-binding, leucine-rich repeat disease resistance family, was chosen as the target gene for additional computational investigation. The findings of this study have significant implications for enhancing rice production and ensuring food security by controlling rice blast and developing resistant rice cultivars.

Genetic control of root morphology in response to nitrogen across rapeseed diversity

Rapeseed (Brassica napus L.) is an oil-containing crop of great economic value but with considerable nitrogen requirement. Breeding root systems that efficiently absorb nitrogen from the soil could be a driver to ensure genetic gains for more sustainable rapeseed production. The aim of this study is to identify genomic regions that regulate root morphology in response to nitrate availability. The natural variability offered by 300 inbred lines was screened at two experimental locations. Seedlings grew hydroponically with low or elevated nitrate levels. Fifteen traits related to biomass production and root morphology were measured. On average across the panel, a low nitrate level increased the root-to-shoot biomass ratio and the lateral root length. A large phenotypic variation was observed, along with important heritability values and genotypic effects, but low genotype-by-nitrogen interactions. Genome-wide association study and bulk segregant analysis were used to identify loci regulating phenotypic traits. The first approach nominated 319 SNPs that were combined into 80 QTLs. Three QTLs identified on the A07 and C07 chromosomes were stable across nitrate levels and/or experimental locations. The second approach involved genotyping two groups of individuals from an experimental F2 population created by crossing two accessions with contrasting lateral root lengths. These individuals were found in the tails of the phenotypic distribution. Co-localized QTLs found in both mapping approaches covered a chromosomal region on the A06 chromosome. The QTL regions contained some genes putatively involved in root organogenesis and represent selection targets for redesigning the root morphology of rapeseed.

Analysis of drought and heat stress response genes in rice using co-expression network and differentially expressed gene analyses

Studies on Oryza sativa (rice) are crucial for improving agricultural productivity and ensuring global sustenance security, especially considering the increasing drought and heat stress caused by extreme climate change. Currently, the genes and mechanisms underlying drought and heat resistance in rice are not fully understood, and the scope for enhancing the development of new strains remains considerable. To accurately identify the key genes related to drought and heat stress responses in rice, multiple datasets from the Gene Expression Omnibus (GEO) database were integrated in this study. A co-expression network was constructed using a Weighted Correlation Network Analysis (WGCNA) algorithm. We further distinguished the core network and intersected it with differentially expressed genes and multiple expression datasets for screening. Differences in gene expression levels were verified using quantitative real-time polymerase chain reaction (PCR). OsDjC53, MBF1C, BAG6, HSP23.2, and HSP21.9 were found to be associated with the heat stress response, and it is also possible that UGT83A1 and OsCPn60a1, although not directly related, are affected by drought stress. This study offers significant insights into the molecular mechanisms underlying stress responses in rice, which could promote the development of stress-tolerant rice breeds.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Systems biology of chromium-plant interaction: insights from omics approaches

Plants are frequently subjected to heavy metal (HM) stress that impedes their growth and productivity. One of the most common harmful trace metals and HM discovered is chromium (Cr). Its contamination continues to increase in the environment due to industrial or anthropogenic activities. Chromium is severely toxic to plant growth and development and acts as a human carcinogen that enters the body by inhaling or taking Cr-contaminated food items. Plants uptake Cr via various transporters, such as sulfate and phosphate transporters. In nature, Cr is found in various valence states, commonly Cr (III) and Cr (VI). Cr (VI) is soil's most hazardous and pervasive form. Cr elevates reactive oxygen species (ROS) activity, impeding various physiological and metabolic pathways. Plants have evolved various complex defense mechanisms to prevent or tolerate the toxic effects of Cr. These defense mechanisms include absorbing and accumulating Cr in cell organelles such as vacuoles, immobilizing them by forming complexes with organic chelates, and extracting them by using a variety of transporters and ion channels regulated by various signaling cascades and transcription factors. Several defense-related proteins including, metallothioneins, phytochelatins, and glutathione-S-transferases aid in the sequestration of Cr. Moreover, several genes and transcriptional factors, such as WRKY and AP2/ERF TF genes, play a crucial role in defense against Cr stress. To counter HM-mediated stress stimuli, OMICS approaches, including genomics, proteomics, transcriptomics, and metallomics, have facilitated our understanding to improve Cr stress tolerance in plants. This review discusses the Cr uptake, translocation, and accumulation in plants. Furthermore, it provides a model to unravel the complexities of the Cr-plant interaction utilizing system biology and integrated OMICS approach.

Glutaredoxin in Rice Growth, Development, and Stress Resistance: Mechanisms and Research Advances

Rice (Oryza sativa L.) is a staple food for more than half of the global population. Various abiotic and biotic stresses lead to accumulation of reactive oxygen species in rice, which damage macromolecules and signaling pathways. Rice has evolved a variety of antioxidant systems, including glutaredoxin (GRX), that protect against various stressors. A total of 48 GRX gene loci have been identified on 11 of the 12 chromosomes of the rice genome; none were found on chromosome 9. GRX proteins were classified into four categories according to their active sites: CPYC, CGFS, CC, and GRL. In this paper, we summarized the recent research advances regarding the roles of GRX in rice development regulation and response to stresses, and discussed future research perspectives related to rice production. This review could provide information for rice researchers on the current status of the GRX and serve as guidance for breeding superior varieties.

Meta-QTL analysis in wheat: progress, challenges and opportunities

Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.