Multi-trait and multi-environment genomic prediction for flowering traits in maize: a deep learning approach.

Maize (Zea mays L.), the third most widely cultivated cereal crop in the world, plays a critical role in global food security. To improve the efficiency of selecting superior genotypes in breeding programs, researchers have aimed to identify key genomic regions that impact agronomic traits. In this study, the performance of multi-trait, multi-environment deep learning models was compared to that of Bayesian models (Markov Chain Monte Carlo generalized linear mixed models (MCMCglmm), Bayesian Genomic Genotype-Environment Interaction (BGGE), and Bayesian Multi-Trait and Multi-Environment (BMTME)) in terms of the prediction accuracy of flowering-related traits (Anthesis-Silking Interval: ASI, Female Flowering: FF, and Male Flowering: MF). A tropical maize panel of 258 inbred lines from Brazil was evaluated in three sites (Cambira-2018, Sabaudia-2018, and Iguatemi-2020 and 2021) using approximately 290,000 single nucleotide polymorphisms (SNPs). The results demonstrated a 14.4% increase in prediction accuracy when employing multi-trait models compared to the use of a single trait in a single environment approach. The accuracy of predictions also improved by 6.4% when using a single trait in a multi-environment scheme compared to using multi-trait analysis. Additionally, deep learning models consistently outperformed Bayesian models in both single and multiple trait and environment approaches. A complementary genome-wide association study identified associations with 26 candidate genes related to flowering time traits, and 31 marker-trait associations were identified, accounting for 37%, 37%, and 22% of the phenotypic variation of ASI, FF and MF, respectively. In conclusion, our findings suggest that deep learning models have the potential to significantly improve the accuracy of predictions, regardless of the approach used and provide support for the efficacy of this method in genomic selection for flowering-related traits in tropical maize.

Application of Near-Infrared Reflectance Spectroscopy for Predicting Damage Severity in a Diverse Panel of Tectona grandis Caused by Ceratocystis fimbriata.

Tectona grandis Linn., also known as teak, is a highly valued species with adaptability to a wide range of climatic conditions and high tolerance to soil variations, making it an attractive option for both commercial and conservation purposes. In this sense, the classification of cultivated teak genotypes is crucial for both breeding programs and conservation efforts. This study examined the relationship between traits related to damage in the stem of teak plants caused by Ceratocystis fimbriata (a soil-borne pathogen that negatively impacts the productivity of teak plantations) and the spectral reflectance of 110 diverse clones, using near-infrared spectroscopy (NIRS) data and partial least squares regression (PLSR) analysis. Cross-validation models had R2 = 0.894 (ratio of standard error of prediction to standard deviation: RPD = 3.1), R2 = 0.883 (RPD = 2.7), and R2 = 0.893 (RPD = 2.8) for predicting stem lesion area, lesion length, and severity of infection, respectively. Teak genotypes (clones) can benefit from the creation of a calibration model utilizing NIRS-generated data paired with PLSR, which can effectively screen the magnitude of damage caused by the fungus. Overall, while the study provides valuable information for teak breeding and conservation efforts, a long-term perspective would be essential to evaluate the sustainability of teak genotypes over various growth stages and under continuous pathogen pressure.

Exploring the Potential of Heterosis to Improve Nitrogen Use Efficiency in Popcorn Plants.

Nitrogen is crucial for plant growth and development, and improving nitrogen use efficiency (NUE) is a viable strategy for reducing dependence on nitrogen inputs and promoting sustainability. While the benefits of heterosis in corn are well known, the physiological mechanisms underlying this phenomenon in popcorn are less understood. We aimed to investigate the effects of heterosis on growth and physiological traits in four popcorn lines and their hybrids under two contrasting nitrogen conditions. We evaluated morpho-agronomic and physiological traits such as leaf pigments, the maximum photochemical efficiency of PSII, and leaf gas exchange. Components associated with NUE were also evaluated. N deprivation caused reductions of up to 65% in terms of plant architecture, 37% in terms of leaf pigments, and 42% in terms of photosynthesis-related traits. Heterosis had significant effects on growth traits, NUE, and foliar pigments, particularly under low soil nitrogen conditions. N-utilization efficiency was found to be the mechanism favoring superior hybrid performance for NUE. Non-additive genetic effects were predominant in controlling the studied traits, indicating that exploring heterosis is the most effective strategy for obtaining superior hybrids to promote NUE. The findings are relevant and beneficial for agro farmers seeking sustainable agricultural practices and improved crop productivity through the optimization of nitrogen utilization.

Saponins: Research Progress and Their Potential Role in the Post-COVID-19 Pandemic Era.

In the post-COVID-19 pandemic era, the new global situation and the limited therapeutic management of the disease make it necessary to take urgent measures in more effective therapies and drug development in order to counteract the negative global impacts caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its new infectious variants. In this context, plant-derived saponins-glycoside-type compounds constituted from a triterpene or steroidal aglycone and one or more sugar residues-may offer fewer side effects and promising beneficial pharmacological activities. This can then be used for the development of potential therapeutic agents against COVID-19, either as a therapy or as a complement to conventional pharmacological strategies for the treatment of the disease and its prevention. The main objective of this review was to examine the primary and current evidence in regard to the therapeutic potential of plant-derived saponins against the COVID-19 disease. Further, the aim was to also focus on those studies that highlight the potential use of saponins as a treatment against SARS-CoV-2. Saponins are antiviral agents that inhibit different pharmacological targets of the virus, as well as exhibit anti-inflammatory and antithrombotic activity in relieving symptoms and clinical complications related to the disease. In addition, saponins also possess immunostimulatory effects, which improve the efficacy and safety of vaccines for prolonging immunogenicity against SARS-CoV-2 and its infectious variants.

Spectral-Based Classification of Genetically Differentiated Groups in Spring Wheat Grown under Contrasting Environments.

The global concern about the gap between food production and consumption has intensified the research on the genetics, ecophysiology, and breeding of cereal crops. In this sense, several genetic studies have been conducted to assess the effectiveness and sustainability of collections of germplasm accessions of major crops. In this study, a spectral-based classification approach for the assignment of wheat cultivars to genetically differentiated subpopulations (genetic structure) was carried out using a panel of 316 spring bread cultivars grown in two environments with different water regimes (rainfed and fully irrigated). For that, different machine-learning models were trained with foliar spectral and genetic information to assign the wheat cultivars to subpopulations. The results revealed that, in general, the hyperparameters ReLU (as the activation function), adam (as the optimizer), and a size batch of 10 give neural network models better accuracy. Genetically differentiated groups showed smaller differences in mean wavelengths under rainfed than under full irrigation, which coincided with a reduction in clustering accuracy in neural network models. The comparison of models indicated that the Convolutional Neural Network (CNN) was significantly more accurate in classifying individuals into their respective subpopulations, with 92 and 93% of correct individual assignments in water-limited and fully irrigated environments, respectively, whereas 92% (full irrigation) and 78% (rainfed) of cultivars were correctly assigned to their respective classes by the multilayer perceptron method and partial least squares discriminant analysis, respectively. Notably, CNN did not show significant differences between both environments, which indicates stability in the prediction independent of the different water regimes. It is concluded that foliar spectral variation can be used to accurately infer the belonging of a cultivar to its respective genetically differentiated group, even considering radically different environments, which is highly desirable in the context of crop genetic resources management.

Genome-Wide Characterization of the Sulfate Transporter Gene Family in Oilseed Crops: Camelina sativa and Brassica napus.

Sulfate transporters (SULTRs) are responsible for the uptake of sulfate (SO42-) ions in the rhizosphere by roots and their distribution to plant organs. In this study, SULTR family members in the genomes of two oilseed crops (Camelina sativa and Brassica napus) were identified and characterized based on their sequence structures, duplication events, phylogenetic relationships, phosphorylation sites, and expression levels. In total, 36 and 45 putative SULTR genes were recognized in the genomes of C. sativa and B. napus, respectively. SULTR proteins were predicted to be basophilic proteins with low hydrophilicity in both studied species. According to the observed phylogenetic relationships, we divided the SULTRs into five groups, out of which the SULTR 3 group showed the highest variation. Additionally, several duplication events were observed between the SULTRs. The first duplication event occurred approximately five million years ago between three SULTR 3.1 genes in C. sativa. Furthermore, two subunits were identified in the 3D structures of the SULTRs, which demonstrated that the active binding sites differed between C. sativa and B. napus. According to the available RNA-seq data, the SULTRs showed diverse expression levels in tissues and diverse responses to stimuli. SULTR 3 was expressed in all tissues. SULTR 3.1 was more upregulated in response to abiotic stresses in C. sativa, while SULTR 3.3 and SULTR 2.1 were upregulated in B. napus. Furthermore, SULTR 3 and SULTR 4.1 were upregulated in response to biotic stresses in B. napus. Additionally, the qPCR data showed that the SULTRs in C. sativa were involved in the plant's response to salinity. Based on the distribution of cis-regulatory elements in the promoter region, we speculated that SULTRs might be controlled by phytohormones, such as ABA and MeJA. Therefore, it seems likely that SULTR genes in C. sativa have been more heavily influenced by evolutionary processes and have acquired further diversity. The results reveal new insights of the structures and functions of SULTRs in oilseed crops. However, further analyses, related to functional studies, are needed to uncover the role of SULTRs in the plants' development and growth processes, as well as in their response to stimuli.

Effect of nano-silicon on the regulation of ascorbate-glutathione contents, antioxidant defense system and growth of copper stressed wheat (Triticum aestivum L.) seedlings.

Copper (Cu2+) toxicity can inhibit plant growth and development. It has been shown that silicon (Si) can relieve Cu2+ stress. However, it is unclear how Si-nanoparticles (SiNPs) relieve Cu2+ stress in wheat seedlings. Therefore, the current study was conducted by setting up four treatments: CK, SiNP: (2.5 mM), Cu2+: (500 µM), and SiNP+Cu2+: (2.5 mM SiNP+500 µM Cu2+) to explore whether SiNPs can alleviate Cu2+ toxicity in wheat seedlings. The results showed that Cu2+ stress hampered root and shoot growth and accumulated high Cu2+ concentrations in roots (45.35 mg/kg) and shoots (25.70 mg/kg) of wheat as compared to control treatment. Moreover, Cu2+ treatment inhibited photosynthetic traits and chlorophyll contents as well as disturbed the antioxidant defense system by accumulating malondialdehyde (MDA) and hydrogen peroxidase (H2O2) contents. However, SiNPs treatment increased root length and shoot height by 15.1% and 22%, respectively, under Cu2+ toxicity. Moreover, SiNPs application decreased MDA and H2O2 contents by 31.25% and 19.25%, respectively. SiNPs increased non-enzymatic compounds such as ascorbic acid-glutathione (AsA-GSH) and enhanced superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbic peroxidase (APX) activities by 77.5%, 141.7%, 68%, and 80%, respectively. Furthermore, SiNPs decreased Cu2+ concentrations in shoots by 26.2%, as compared to Cu2+ treatment alone. The results concluded that SiNPs could alleviate Cu2+ stress in wheat seedlings. The present investigation may help to increase wheat production in Cu2+ contaminated soils.

Challenges for a Massive Implementation of Phenomics in Plant Breeding Programs.

Due to climate change and expected food shortage in the coming decades, not only will it be necessary to develop cultivars with greater tolerance to environmental stress, but it is also imperative to reduce breeding cycle time. In addition to yield evaluation, plant breeders resort to many sensory assessments and some others of intermediate complexity. However, to develop cultivars better adapted to current/future constraints, it is necessary to incorporate a new set of traits, such as morphophysiological and physicochemical attributes, information relevant to the successful selection of genotypes or parents. Unfortunately, because of the large number of genotypes to be screened, measurements with conventional equipment are unfeasible, especially under field conditions. High-throughput plant phenotyping (HTPP) facilitates collecting a significant amount of data quickly; however, it is necessary to transform all this information (e.g., plant reflectance) into helpful descriptors to the breeder. To the extent that a holistic characterization of the plant (phenomics) is performed in challenging environments, it will be possible to select the best genotypes (forward phenomics) objectively but also understand why the said individual differs from the rest (reverse phenomics). Unfortunately, several elements had prevented phenomics from developing as desired. Consequently, a new set of prediction/validation methodologies, seasonal ambient information, and the fusion of data matrices (e.g., genotypic and phenotypic information) need to be incorporated into the modeling. In this sense, for the massive implementation of phenomics in plant breeding, it will be essential to count an interdisciplinary team that responds to the urgent need to release material with greater capacity to tolerate environmental stress. Therefore, breeding programs should (i) be more efficient (e.g., early discarding of unsuitable material), (ii) have shorter breeding cycles (fewer crosses to achieve the desired cultivar), and (iii) be more productive, increasing the probability of success at the end of the breeding process (percentage of cultivars released to the number of initial crosses).

Variation in Root-Related Traits Is Associated With Water Uptake in Lagenaria siceraria Genotypes Under Water-Deficit Conditions.

In many agricultural areas, crop production has decreased due to a lack of water availability, which is having a negative impact on sustainability and putting food security at risk. In plants, the plasticity of the root system architecture (RSA) is considered to be a key trait driving the modification of the growth and structure of roots in response to water deficits. The purpose of this study was to examine the plasticity of the RSA traits (mean root diameter, MRD; root volume, RV; root length, RL; and root surface area, SA) associated with drought tolerance in eight Lagenaria siceraria (Mol. Standl) genotypes, representing three different geographical origins: South Africa (BG-58, BG-78, and GC), Asia (Philippines and South Korea), and Chile (Illapel, Chepica, and Osorno). The RSA changes were evaluated at four substrate depths (from 0 to 40 cm). Bottle gourd genotypes were grown in 20 L capacity pots under two contrasting levels of irrigation (well-watered and water-deficit conditions). The results showed that the water productivity (WP) had a significant effect on plasticity values, with the Chilean accessions having the highest values. Furthermore, Illapel and Chepica genotypes presented the highest WP, MRD, and RV values under water-deficit conditions, in which MRD and RV were significant in the deeper layers (20-30 and 30-40 cm). Biplot analysis showed that the Illapel and Chepica genotypes presented a high WP, MRD, and RV, which confirmed that these may be promising drought-tolerant genotypes. Consequently, increased root diameter and volume in bottle gourd may constitute a response to a water deficit. The RSA traits studied here can be used as selection criteria in bottle gourd breeding programs under water-deficit conditions.

Corrigendum: The Impact of Bio-Stimulants on Cd-Stressed Wheat (Triticum aestivum L.): Insights Into Growth, Chlorophyll Fluorescence, Cd Accumulation, and Osmolyte Regulation.

[This corrects the article DOI: 10.3389/fpls.2022.850567.].

Heritable Variation of Foliar Spectral Reflectance Enhances Genomic Prediction of Hydrogen Cyanide in a Genetically Structured Population of Eucalyptus.

Plants produce a wide diversity of specialized metabolites, which fulfill a wide range of biological functions, helping plants to interact with biotic and abiotic factors. In this study, an integrated approach based on high-throughput plant phenotyping, genome-wide haplotypes, and pedigree information was performed to examine the extent of heritable variation of foliar spectral reflectance and to predict the leaf hydrogen cyanide content in a genetically structured population of a cyanogenic eucalyptus (Eucalyptus cladocalyx F. Muell). In addition, the heritable variation (based on pedigree and genomic data) of more of 100 common spectral reflectance indices was examined. The first profile of heritable variation along the spectral reflectance curve indicated the highest estimate of genomic heritability ( h g 2 =0.41) within the visible region of the spectrum, suggesting that several physiological and biological responses of trees to environmental stimuli (ex., light) are under moderate genetic control. The spectral reflectance index with the highest genomic-based heritability was leaf rust disease severity index 1 ( h g 2 =0.58), followed by the anthocyanin reflectance index and the Browning reflectance index ( h g 2 =0.54). Among the Bayesian prediction models based on spectral reflectance data, Bayes B had a better goodness of fit than the Bayes-C and Bayesian ridge regression models (in terms of the deviance information criterion). All models that included spectral reflectance data outperformed conventional genomic prediction models in their predictive ability and goodness-of-fit measures. Finally, we confirmed the proposed hypothesis that high-throughput phenotyping indirectly capture endophenotypic variants related to specialized metabolites (defense chemistry), and therefore, generally more accurate predictions can be made integrating phenomics and genomics.

The Impact of Bio-Stimulants on Cd-Stressed Wheat (Triticum aestivum L.): Insights Into Growth, Chlorophyll Fluorescence, Cd Accumulation, and Osmolyte Regulation.

It has been established that wheat (Triticum aestivum L.) has a higher Cd absorption capacity than other cereal crops causing an excess daily Cd intake and a huge threat for public health. Therefore, the reduction of Cd accumulation in wheat from the soil is a crucial food-security issue. A pot trial was performed on Cd-stressed wheat seedlings to evaluate the morphological and physio-biochemical responses via foliage spray of two different bio-stimulants, i.e., ascorbic acid (AsA) and moringa leaf extract (MLE). Two wheat cultivars (Fsd-08 and Glxy-13) were exposed to cadmium (CdCl2.5H2O) stress (0, 500, and 1,000 µM), along with foliar spray of AsA (0 and 50 mM) and MLE (0 and 3%). The most observable growth reduction was documented in plants that are exposed to a higher Cd concentration (1,000 µM), followed by the lower Cd level (500 µM). The wheat growth attributes, such as number of leaves per plant, number of tillers per plant, biomass yield, shoot/root length, and leaf area, were greatly depressed under the Cd stress, irrespective of the cultivar. Under the increasing Cd stress, a significant diminution was observed in maximum photochemical efficiency (Fv/Fm), photochemical quenching (qP), and electron transport rate (ETR) accompanied with reduced gas exchange attributes. However, Cd-induced phytotoxicity enhanced the non-photochemical quenching (NPQ) and internal carbon dioxide concentration (Ci), which was confirmed by their significant positive correlation with Cd contents in shoot and root tissues of both cultivars. The contents of proline, AsA, glycine betaine (GB), tocopherol, total free amino acid (TFAA), and total soluble sugar (TSS) were greatly decreased with Cd stress (1,000 µM), while MLE and AsA significantly enhanced the osmolytes accumulation under both Cd levels (especially 500 µM level). The Cd accumulation was predominantly found in the root as compared to shoots in both cultivars, which has declined after the application of MLE and AsA. Conclusively, MLE was found to be more effective to mitigate Cd-induced phytotoxicity up to 500 µM Cd concentration, compared with the AsA amendment.

Chemical role of α-tocopherol in salt stress mitigation by improvement in morpho-physiological attributes of sunflower (Helianthus annuus L.).

Elevated concentrations of salts in soil and water represent abiotic stresses. It considerably restricts plant productivity. However, the use of alpha-tocopherol (α-toc) as foliar can overcome this problem. It can improve crop productivity grown under salinity stress. Limited literature is documented regarding its optimum foliar application on sunflower. That's why the need for the time is to optimize α-toc foliar application rates for sunflower cultivated in salt-affected soil. A pot experiment was performed to select a better α-toc foliar application for mitigation of salt stress in different sunflower cultivars FH (572 and 621). There were 2 levels of salts, i.e., control (no salt stress) and sodium chloride (120 mM) and four α-toc foliar application (0, 100, 200, and 300 mg L-1). Results showed that foliar application of 100 mg/L- α-toc triggered the remarkable increase in fresh shoot weight, fresh root weight, shoot, and root lengths under salinity stress in FH-572 and FH-621 over 0 mg/L- α-toc. Foliar application of 200 mg/L- α-toc was most effective for improvement in chlorophyll a, chlorophyll b, total chlorophyll and carotenoids compared to 0 mg/L- α-toc. Furthermore, an increase in A was noted in FH-572 (17%) and FH-621 (22%) with α-toc (300 mg L-1) application under saline condition. In conclusion, the 100 and 200 mg/L- α-toc are the best application rates for the improvement in sunflower FH-572 and FH-621 growth, chlorophyll contents and gas exchange attributes. Further investigations are needed to select a better foliar application rate between 100 and 200 mg/L- α-toc at the field level under the different agro-climatic zone and soil types.

Revealing the differential protein profiles behind the nitrogen use efficiency in popcorn (Zea mays var. everta).

We investigated the proteomic profiles of two popcorn inbred lines, P2 (N-efficient and N-responsive) and L80 (N-inefficient and nonresponsive to N), under low (10% of N supply) and high (100% of N supply) nitrogen environments, associated with agronomic- and physiological-related traits to NUE. The comparative proteomic analysis allowed the identification of 79 differentially accumulated proteins (DAPs) in the comparison of high/low N for P2 and 96 DAPs in the comparison of high/low N for L80. The NUE and N uptake efficiency (NUpE) presented high means in P2 in comparison to L80 at both N levels, but the NUE, NUpE, and N utilization efficiency (NUtE) rates decreased in P2 under a high N supply. DAPs involved in energy and carbohydrate metabolism suggested that N regulates enzymes of alternative pathways to adapt to energy shortages and that fructose-bisphosphate aldolase may act as one of the key primary nitrate responsive proteins in P2. Proteins related to ascorbate biosynthesis and nitrogen metabolism increased their regulation in P2, and the interaction of L-ascorbate peroxidase and Fd-NiR may play an important role in the NUE trait. Taken together, our results provide new insights into the proteomic changes taking place in contrasting inbred lines, providing useful information on the genetic improvement of NUE in popcorn.

Exploring plant responses to abiotic stress by contrasting spectral signature changes.

In this study, daily changes over a short period and diurnal progression of spectral reflectance at the leaf level were used to identify spring wheat genotypes (Triticum aestivum L.) susceptible to adverse conditions. Four genotypes were grown in pots experiments under semi-controlled conditions in Chile and Spain. Three treatments were applied: i) control (C), ii) water stress (WS), and iii) combined water and heat shock (WS+T). Spectral reflectance, gas exchange and chlorophyll fluorescence measurements were performed on flag leaves for three consecutive days at anthesis. High canopy temperature ( H CT ) genotypes showed less variability in their mean spectral reflectance signature and chlorophyll fluorescence, which was related to weaker responses to environmental fluctuations. While low canopy temperature ( L CT ) genotypes showed greater variability. The genotypes spectral signature changes, in accordance with environmental fluctuation, were associated with variations in their stomatal conductance under both stress conditions (WS and WS+T); L CT genotypes showed an anisohydric response compared that of H CT , which was isohydric. This approach could be used in breeding programs for screening a large number of genotypes through proximal or remote sensing tools and be a novel but simple way to identify groups of genotypes with contrasting performances.

Antiviral Activities of Eucalyptus Essential Oils: Their Effectiveness as Therapeutic Targets against Human Viruses.

Given the limited therapeutic management of infectious diseases caused by viruses, such as influenza and SARS-CoV-2, the medicinal use of essential oils obtained from Eucalyptus trees has emerged as an antiviral alternative, either as a complement to the treatment of symptoms caused by infection or to exert effects on possible pharmacological targets of viruses. This review gathers and discusses the main findings on the emerging role and effectiveness of Eucalyptus essential oil as an antiviral agent. Studies have shown that Eucalyptus essential oil and its major monoterpenes have enormous potential for preventing and treating infectious diseases caused by viruses. The main molecular mechanisms involved in the antiviral activity are direct inactivation, that is, by the direct binding of monoterpenes with free viruses, particularly with viral proteins involved in the entry and penetration of the host cell, thus avoiding viral infection. Furthermore, this review addresses the coadministration of essential oil and available vaccines to increase protection against different viruses, in addition to the use of essential oil as a complementary treatment of symptoms caused by viruses, where Eucalyptus essential oil exerts anti-inflammatory, mucolytic, and spasmolytic effects in the attenuation of inflammatory responses caused by viruses, in particular respiratory diseases.

Comprehensive genomics and expression analysis of eceriferum (CER) genes in sunflower (Helianthus annuus).

Sunflower occupies the fourth position among oilseed crops the around the world. Eceriferum (CER) is an important gene family that plays critical role in very-long-chain fatty acids elongation and biosynthesis of epicuticular waxes under both biotic and abiotic stress conditions. The aim of present study was to investigate the effect of sunflower CER genes during drought stress condition. Thus, comparative analysis was undertaken for sunflower CER genes with Arabidopsis genome to determine phylogenetic relationship, chromosomal mapping, gene structures, gene ontology and conserved motifs. Furthermore, we subjected the sunflower cultivars under drought stress and used qRT-PCR analysis to explore the expression pattern of CER genes during drought conditions. We identified thirty-seven unevenly distributed CER genes in the sunflower genome. The phylogenetic analysis revealed that CER genes were grouped into seven clades in Arabidopsis, Helianthus annuus, and Gossypium hirsutum. Expression analysis showed that genes CER10 and CER60 were upregulated in sunflower during drought conditions, indicating that these genes are activated during drought stress. The results obtained will serve to characterize the CER gene family in sunflower and exploit the role of these genes in wax biosynthesis under limited water conditions. KEY MESSAGE: Cuticular waxes protect the plants from drought stress, so we observed the expression of wax bio synthesis genes in recently sequences genome of Helianthus annuus. We observed that expression of wax biosynthesis genes CER10 and CER60 was upregulated when the plants were subjected to drought stress.

Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed.

Yield is one of the most important agronomic traits for the breeding of rapeseed (Brassica napus L), but its genetic dissection for the formation of high yield remains enigmatic, given the rapid population growth. In the present review, we review the discovery of major loci underlying important agronomic traits and the recent advancement in the selection of complex traits. Further, we discuss the benchmark summary of high-throughput techniques for the high-resolution genetic breeding of rapeseed. Biparental linkage analysis and association mapping have become powerful strategies to comprehend the genetic architecture of complex agronomic traits in crops. The generation of improved crop varieties, especially rapeseed, is greatly urged to enhance yield productivity. In this sense, the whole-genome sequencing of rapeseed has become achievable to clone and identify quantitative trait loci (QTLs). Moreover, the generation of high-throughput sequencing and genotyping techniques has significantly enhanced the precision of QTL mapping and genome-wide association study (GWAS) methodologies. Furthermore, this study demonstrates the first attempt to identify novel QTLs of yield-related traits, specifically focusing on ovule number per pod (ON). We also highlight the recent breakthrough concerning single-locus-GWAS (SL-GWAS) and multi-locus GWAS (ML-GWAS), which aim to enhance the potential and robust control of GWAS for improved complex traits.