Genome-Wide Association Studies Reveal Genetic Variation and Candidate Genes of Drought Stress Related Traits in Cotton (Gossypium hirsutum L.)

Comprehensive evaluation of phosphate deficiency tolerance in common vetch germplasms and the adaption mechanism to phosphate deficiency

Common vetch (Vicia sativa L.) is widely planted as forage, green manure and food. Phosphate (Pi) deficiency is an important constraint for legume crop production. In this study, P-deficiency tolerance in 40 common vetch collections was evaluated under hydroponic condition. The collections were clustered into three groups based on the tolerance level. Physiological responses to P-deficiency in two tolerant collections (418 and 426) in comparison with one sensitive collection (415) were investigated. Greater growth inhibition was observed in sensitive collection compared with two tolerant collections, although the inorganic phosphorus (P) content in sensitive collection was higher than those in tolerant collections. The internal and external purple acid phosphatase activity in plants showed no significant difference between 418 and 415 under low phosphate condition. Transcriptomic analysis in the tolerant collection 426 in response to Pi starvation showed that many common adaptive strategies were applied and PHOSPHATE STARVATION RESPONSE (PHR)-related Pi signaling and transporter genes were altered. VsPHT1.2 had the highest expression level in root among all VsPHT1s, and it was remarkably upregulated after short time of P-deficiency treatment in tolerant collections compared with sensitive collection. In conclusion, common vetch response to P starvation by altering the expressions of core genes involved in Pi transport and signaling, and the elevated expression of VsPHT1.2 gene might contribute to higher Pi acquisition efficiency in P-deficiency tolerant collections.

Dissecting the Superior Drivers for the Simultaneous Improvement of Fiber Quality and Yield Under Drought Stress Via Genome-Wide Artificial Introgressions of Gossypium barbadense into Gossypium hirsutum

Global water scarcity and extreme weather intensify drought stress, significantly reducing cotton yield and quality worldwide. Drought treatments are conducted using a population of chromosome segment substitution lines generated from E22 (G. hirsutum) and 3-79 (G. barbadense) as parental lines either show superior yields or fiber quality under both control and drought conditions. Fourteen datasets, covering 4 yields and 4 quality traits, are compiled and assessed for drought resistance using the drought resistance coefficient (DRC) and membership function value of drought resistance (MFVD). Genome-wide association studies, linkage analysis, and bulked segregant analysis are combined to analyze the DR-related QTL. A total of 121 significant QTL are identified by DRC and MFVD of the 8 traits. CRISPR/Cas9 and virus-induced gene silencing techniques verified DRR1 and DRT1 as pivotal genes in regulating drought resistant of cotton, with hap3-79 exhibiting greater drought resistance than hapE22 concerning DRR1 and DRT1. Moreover, 14 markers with superior yield and fiber quality are selected for drought treatment. This study offers valuable insights into yield and fiber quality variations between G. hirsutum and G. barbadense amid drought, providing crucial theoretical and technological backing for developing cotton varieties resilient to drought, with high yield and superior fiber quality.

Genetic Analysis of an F2 Population Derived from the Cotton Landrace Hopi Identified Novel Loci for Boll Glanding

Landraces are an important reservoir of genetic variation that can expand the narrow genetic base of cultivated cotton. In this study, quantitative trait loci (QTL) analysis was conducted using an F2 population developed from crosses between the landrace Hopi and inbred TM-1. A high-density genetic map spanning 2253.11 and 1932.21 cM for the A and D sub-genomes, respectively, with an average marker interval of 1.14 cM, was generated using the CottonSNP63K array. The linkage map showed a strong co-linearity with the physical map of cotton. A total of 21 QTLs were identified, controlling plant height (1), bract type (1), boll number (1), stem color (2), boll pitting (2), fuzz fiber development (2), boll shape (3), boll point (4), and boll glanding (5). In silico analysis of the novel QTLs for boll glanding identified a total of 13 candidate genes. Analysis of tissue-specific expression of the candidate genes suggests roles for the transcription factors bHLH1, MYB2, and ZF1 in gland formation. Comparative sequencing of open reading frames identified early stop codons in all three transcription factors in Hopi. Functional validation of these genes offers avenues to reduce glanding and, consequently, lower gossypol levels in cottonseeds without compromising the defense mechanisms of the plant against biotic stresses.

Salicylic Acid Priming Improves Cotton Seedling Heat Tolerance through Photosynthetic Pigment Preservation, Enhanced Antioxidant Activity, and Osmoprotectant Levels

The escalating global temperatures associated with climate change are detrimental to plant growth and development, leading to significant reductions in crop yields worldwide. Our research demonstrates that salicylic acid (SA), a phytohormone known for its growth-promoting properties, is crucial in enhancing heat tolerance in cotton (Gossypium hirsutum). This enhancement is achieved through modifications in various biochemical, physiological, and growth parameters. Under heat stress, cotton plants typically show significant growth disturbances, including leaf wilting, stunted growth, and reduced biomass. However, priming cotton plants with 1 mM SA significantly mitigated these adverse effects, evidenced by increases in shoot dry mass, leaf-water content, and chlorophyll concentrations in the heat-stressed plants. Heat stress also prompted an increase in hydrogen peroxide levels-a key reactive oxygen species-resulting in heightened electrolyte leakage and elevated malondialdehyde concentrations, which indicate severe impacts on cellular membrane integrity and oxidative stress. Remarkably, SA treatment significantly reduced these oxidative stresses by enhancing the activities of critical antioxidant enzymes, such as catalase, glutathione S-transferase, and ascorbate peroxidase. Additionally, the elevated levels of total soluble sugars in SA-treated plants enhanced osmotic regulation under heat stress. Overall, our findings reveal that SA-triggered protective mechanisms not only preserve photosynthetic pigments but also ameliorate oxidative stress and boost plant resilience in the face of elevated temperatures. In conclusion, the application of 1 mM SA is highly effective in enhancing heat tolerance in cotton and is recommended for field trials before being commercially used to improve crop resilience under increasing global temperatures.

New Insights into the Genetic Basis of Lysine Accumulation in Rice Revealed by Multi-Model GWAS

Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation. In this study, five grain and three leaf lysine content datasets and 4,630,367 single nucleotide polymorphisms (SNPs) of 387 rice accessions were used to perform a genome-wide association study (GWAS) by ten statistical models. A total of 248 and 71 common QTNs associated with grain/leaf lysine content were identified. The accuracy of genomic selection/prediction RR-BLUP models was up to 0.85, and the significant correlation between the number of favorable alleles per accession and lysine content was up to 0.71, which validated the reliability and additive effects of these QTNs. Several key genes were uncovered for fine-tuning lysine accumulation. Additionally, 20 and 30 QTN-by-environment interactions (QEIs) were detected in grains/leaves. The QEI-sf0111954416 candidate gene LOC_Os01g21380 putatively accounted for gene-by-environment interaction was identified in grains. These findings suggested the application of multi-model GWAS facilitates a better understanding of lysine accumulation in rice. The identified QTNs and genes hold the potential for lysine-rich rice with a normal phenotype.

Genome-wide association study of drought tolerance in wheat (Triticum aestivum L.) identifies SNP markers and candidate genes

Drought stress poses a severe threat to global wheat production, necessitating an in-depth exploration of the genetic basis for drought tolerance associated traits. This study employed a 90 K SNP array to conduct a genome-wide association analysis, unravelling genetic determinants of key traits related to drought tolerance in wheat, namely plant height, root length, and root and shoot dry weight. Using the mixed linear model (MLM) method on 125 wheat accessions subjected to both well-watered and drought stress treatments, we identified 53 SNPs significantly associated with stress susceptibility (SSI) and tolerance indices (STI) for the targeted traits. Notably, chromosomes 2A and 3B stood out with ten and nine associated markers, respectively. Across 17 chromosomes, 44 unique candidate genes were pinpointed, predominantly located on the distal ends of 1A, 1B, 1D, 2A, 3A, 3B, 4A, 6A, 6B, 7A, 7B, and 7D chromosomes. These genes, implicated in diverse functions related to plant growth, development, and stress responses, offer a rich resource for future investigation. A clustering pattern emerged, notably with seven genes associated with SSI for plant height and four genes linked to both STI of plant height and shoot dry weight, converging on specific regions of chromosome arms of 2AS and 3BL. Additionally, shared genes encoding polygalacturonase, auxilin-related protein 1, peptide deformylase, and receptor-like kinase underscored the interconnectedness between plant height and shoot dry weight. In conclusion, our findings provide insights into the molecular mechanisms governing wheat drought tolerance, identifying promising genomic loci for further exploration and crop improvement strategies.

Genome-wide association studies using multi-models and multi-SNP datasets provide new insights into pasmo resistance in flax

Introduction

Flax (Linum usitatissimum L.) is an economically important crop due to its oil and fiber. However, it is prone to various diseases, including pasmo caused by the fungus Septoria linicola.

Methods

In this study, we conducted field evaluations of 445 flax accessions over a five-year period (2012-2016) to assess their resistance to pasmo A total of 246,035 single nucleotide polymorphisms (SNPs) were used for genetic analysis. Four statistical models, including the single-locus model GEMMA and the multi-locus models FarmCPU, mrMLM, and 3VmrMLM, were assessed to identify quantitative trait nucleotides (QTNs) associated with pasmo resistance.

Results

We identified 372 significant QTNs or 132 tag QTNs associated with pasmo resistance from five pasmo resistance datasets (PAS2012-PAS2016 and the 5-year average, namely PASmean) and three genotypic datasets (the all SNPs/ALL, the gene-based SNPs/GB and the RGA-based SNPs/RGAB). The tag QTNs had R2 values of 0.66-16.98% from the ALL SNP dataset, 0.68-20.54%from the GB SNP dataset, and 0.52-22.42% from the RGAB SNP dataset. Of these tag QTNs, 93 were novel. Additionally, 37 resistance gene analogs (RGAs)co-localizing with 39 tag QTNs were considered as potential candidates for controlling pasmo resistance in flax and 50 QTN-by-environment interactions(QEIs) were identified to account for genes by environmental interactions. Nine RGAs were predicted as candidate genes for ten QEIs.

Discussion

Our results suggest that pasmo resistance in flax is polygenic and potentially influenced by environmental factors. The identified QTNs provide potential targets for improving pasmo resistance in flax breeding programs. This study sheds light on the genetic basis of pasmo resistance and highlights the importance of considering both genetic and environmental factors in breeding programs for flax.

Deciphering the complex cotton genome for improving fiber traits and abiotic stress resilience in sustainable agriculture

BACKGROUND

Understanding the complex cotton genome is of paramount importance in devising a strategy for sustainable agriculture. Cotton is probably the most economically important cash crop known for its cellulose-rich fiber content. The cotton genome has become an ideal model for deciphering polyploidization due to its polyploidy, setting it apart from other major crops. However, the main challenge in understanding the functional and regulatory functions of many genes in cotton is still the complex cotton polyploidy genome, which is not limited to a single role. Cotton production is vulnerable to the sensitive effects of climate change, which can alter or aggravate soil, pests, and diseases. Thus, conventional plant breeding coupled with advanced technologies has led to substantial progress being made in cotton production.

GENOMICS APPROACHES IN COTTON

In the frontier areas of genomics research, cotton genomics has gained momentum accomplished by robust high-throughput sequencing platforms combined with novel computational tools to make the cotton genome more tractable. Advances in long-read sequencing have allowed for the generation of the complete set of cotton gene transcripts giving incisive scientific knowledge in cotton improvement. In contrast, the integration of the latest sequencing platforms has been used to generate multiple high-quality reference genomes in diploid and tetraploid cotton. While pan-genome and 3D genomic studies are still in the early stages in cotton, it is anticipated that rapid advances in sequencing, assembly algorithms, and analysis pipelines will have a greater impact on advanced cotton research.

CONCLUSIONS

This review article briefly compiles substantial contributions in different areas of the cotton genome, which include genome sequencing, genes, and their molecular regulatory networks in fiber development and stress tolerance mechanism. This will greatly help us in understanding the robust genomic organization which in turn will help unearth candidate genes for functionally important agronomic traits.

Genome-Wide Association Study of Phenolic Content and Antioxidant Properties in Eggplant Germplasm

The phenolic compounds in eggplant offer potential natural antioxidants for improved health. A large number of samples were examined in order to find eggplant germplasm with a high potential for health promotion. A genome-wide association study (GWAS) was conducted to identify single nucleotide polymorphisms (SNPs) associated with variations in total phenolic content (TPC) and antioxidant activity in eggplants, including ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) scavenging activity and ferric reducing antioxidant power (FRAP). TPC values varied from 14.19 to 842.90 mg gallic acid equivalent (GAE)/100 g of dry weight of eggplant fruit powder. TPC showed a strong positive correlation with both FRAP and ABTS (r = 0.89 *** and 0.77 ***, respectively). The GWAS identified 20 SNPs that were significantly associated out of 29,183 SNPs. Out of the 20 significant SNPs, 11 showed associations with TPC, 4 with ABTS activity, and 5 with FRAP. Among the SNPs associated with TPC, one SNP was found on each of Chromosomes 3, 4, 7, and 12. In contrast, Chromosome 5 comprised two SNPs associated to TPC. Furthermore, the gene encoding IRX12 laccase-4 on Chromosome 10 was found to contain five SNPs associated with TPC. Four significantly linked SNPs on Chromosomes 1 (1 SNP), 4 (2 SNPs), and 10 (1 SNP) were found to be related to ABTS activity. The identified SNPs will be further examined as markers for selecting desirable eggplant varieties and exploring the links between candidate genes, phenolic content, and antioxidant activity. The findings of this study could assist in further study and the development of eggplants with improved health advantages through targeted breeding.

Grafting enhances drought tolerance by regulating and mobilizing proteome, transcriptome and molecular physiology in okra genotypes

Drought stress poses a serious concern to the growth, development, and quality of the okra crop due to factors including decreased yield, inadequate development of dietary fibre, increased mite infestation, and decreased seed viability. Grafting is one of the strategies that have been developed to increase the drought stress tolerance of crops. We conducted proteomics, transcriptomics and integrated it with molecular physiology to assess the response of sensitive okra genotypes; NS7772 (G1), Green gold (G2) and OH3312 (G3) (scion) grafted to NS7774 (rootstock). In our studies we observed that sensitive okra genotypes grafted to tolerant genotypes mitigated the deleterious effects of drought stress through an increase in physiochemical parameters, and lowered reactive oxygen species. A comparative proteomic analysis showed a stress responsive proteins related to Photosynthesis, energy and metabolism, defence response, protein and nucleic acid biosynthesis. A proteomic investigation demonstrated that scions grafted onto okra rootstocks increased more photosynthesis-related proteins during drought stress, indicating an increase in photosynthetic activity when plants were subjected to drought stress. Furthermore, transcriptome of RD2, PP2C, HAT22, WRKY and DREB increased significantly, specifically for grafted NS7772 genotype. Furthermore, our study also indicated that grafting improved the yield components such as number of pods and seeds per plant, maximum fruit diameter, and maximum plant height in all genotypes which directly contributed towards their high resistance towards drought stress.

Multi-locus genome-wide association study of chickpea reference set identifies genetic determinants of Pratylenchus thornei resistance

Pratylenchus thornei is an economically important species of root-lesion nematode adversely affecting chickpea (Cicer arietinum) yields globally. Integration of resistant crops in farming systems is recognised as the most effective and sustainable management strategy for plant-parasitic nematodes. However, breeding for P. thornei resistance in chickpea is limited by the lack of genetic diversity. We deployed a genome-wide association approach to identify genomic regions and candidate genes associated with P. thornei resistance in 285 genetically diverse chickpea accessions. Chickpea accessions were phenotyped for P. thornei resistance in replicated glasshouse experiments performed for two years (2018 and 2020). Whole genome sequencing data comprising 492,849 SNPs were used to implement six multi-locus GWAS models. Fourteen chickpea genotypes were found to be resistant to P. thornei. Of the six multi-locus GWAS methods deployed, FASTmrMLM was found to be the best performing model. In all, 24 significant quantitative trait nucleotides (QTNs) were identified, of which 13 QTNs were associated with lower nematode population density and 11 QTNs with higher nematode population density. These QTNs were distributed across all of the chickpea chromosomes, except chromosome 8. We identified, receptor-linked kinases (RLKs) on chromosomes 1, 4 and 6, GDSL-like Lipase/Acylhydrolase on chromosome 3, Aspartic proteinase-like and Thaumatin-like protein on chromosome 4, AT-hook DNA-binding and HSPRO2 on chromosome 6 as candidate genes for P. thornei resistance in the chickpea reference set. New sources of P. thornei resistant genotypes were identified that can be harnessed into breeding programs and putative candidate P. thornei resistant genes were identified that can be explored further to develop molecular markers and accelerate the incorporation of improved P. thornei resistance into elite chickpea cultivars.

Recent progression and future perspectives in cotton genomic breeding

Upland cotton is an important global cash crop for its long seed fibers and high edible oil and protein content. Progress in cotton genomics promotes the advancement of cotton genetics, evolutionary studies, functional genetics, and breeding, and has ushered cotton research and breeding into a new era. Here, we summarize high-impact genomics studies for cotton from the last 10 years. The diploid Gossypium arboreum and allotetraploid Gossypium hirsutum are the main focus of most genetic and genomic studies. We next review recent progress in cotton molecular biology and genetics, which builds on cotton genome sequencing efforts, population studies, and functional genomics, to provide insights into the mechanisms shaping abiotic and biotic stress tolerance, plant architecture, seed oil content, and fiber development. We also suggest the application of novel technologies and strategies to facilitate genome-based crop breeding. Explosive growth in the amount of novel genomic data, identified genes, gene modules, and pathways is now enabling researchers to utilize multidisciplinary genomics-enabled breeding strategies to cultivate "super cotton", synergistically improving multiple traits. These strategies must rise to meet urgent demands for a sustainable cotton industry.

Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions

Drought is one of the major abiotic stresses seriously affecting cotton yield. At present, the main cotton-producing areas in China are primarily arid and semiarid regions. Therefore, the identification of molecular markers and genes associated with cotton yield traits under drought conditions is of great importance for stabilize cotton yield under such conditions. In this study, resequencing data were used to conduct a genome-wide association study (GWAS) on 8 traits of 150 cotton germplasms. Under drought stress, 18 SNPs were significantly correlated with yield traits (single-boll weight (SBW) and seed (SC)), and 8 SNPs were identified as significantly correlated with effective fruit shoot number (EFBN) traits (a trait that is positively correlated with yield). Finally, a total of 15 candidate genes were screened. The combined results of the GWAS and transcriptome data analysis showed that four genes were highly expressed after drought stress, and these genes had significantly increased expression at 10, 15 and 25 DPA of fiber development. qRT-PCR was performed on two samples with drought tolerance extremes (drought-resistant Xinluzao 45 and drought-sensitive Xinluzao 26), revealing that three of the genes had the same differential expression pattern. This study provides a theoretical basis for the genetic analysis of cotton yield traits under drought stress, and provides gene resources for improved breeding of cotton yield traits under drought stress.

Genome-wide association studies of five free amino acid levels in rice

Rice (Oryza sativa L.) is one of the important staple foods for human consumption and livestock use. As a complex quality trait, free amino acid (FAA) content in rice is of nutritional importance. To dissect the genetic mechanism of FAA level, five amino acids' (Val, Leu, Ile, Arg, and Trp) content and 4,325,832 high-quality SNPs of 448 rice accessions were used to conduct genome-wide association studies (GWAS) with nine different methods. Of these methods, one single-locus method (GEMMA), seven multi-locus methods (mrMLM, pLARmEB, FASTmrEMMA, pKWmEB, FASTmrMLM, ISIS EM-BLASSO, and FarmCPU), and the recent released 3VmrMLM were adopted for methodological comparison of quantitative trait nucleotide (QTN) detection and identification of stable quantitative trait nucleotide loci (QTLs). As a result, 987 QTNs were identified by eight multi-locus GWAS methods; FASTmrEMMA detected the most QTNs (245), followed by 3VmrMLM (160), and GEMMA detected the least QTNs (0). Among 88 stable QTLs identified by the above methods, 3VmrMLM has some advantages, such as the most common QTNs, the highest LOD score, and the highest proportion of all detected stable QTLs. Around these stable QTLs, candidate genes were found in the GO classification to be involved in the primary metabolic process, biosynthetic process, and catalytic activity, and shown in KEGG analysis to have participated in metabolic pathways, biosynthesis of amino acids, and tryptophan metabolism. Natural variations of candidate genes resulting in the content alteration of five FAAs were identified in this association panel. In addition, 95 QTN-by-environment interactions (QEIs) of five FAA levels were detected by 3VmrMLM only. GO classification showed that the candidate genes got involved in the primary metabolic process, transport, and catalytic activity. Candidate genes of QEIs played important roles in valine, leucine, and isoleucine degradation (QEI_09_03978551 and candidate gene LOC_Os09g07830 in the Leu dataset), tryptophan metabolism (QEI_01_00617184 and candidate gene LOC_Os01g02020 in the Trp dataset), and glutathione metabolism (QEI_12_09153839 and candidate gene LOC_Os12g16200 in the Arg dataset) pathways through KEGG analysis. As an alternative of the multi-locus GWAS method, these findings suggested that the application of 3VmrMLM may provide new insights into better understanding FAA accumulation and facilitate the molecular breeding of rice with high FAA level.

Status and prospects of genome-wide association studies in cotton

Over the last two decades, the use of high-density SNP arrays and DNA sequencing have allowed scientists to uncover the majority of the genotypic space for various crops, including cotton. Genome-wide association study (GWAS) links the dots between a phenotype and its underlying genetics across the genomes of populations. It was first developed and applied in the field of human disease genetics. Many areas of crop research have incorporated GWAS in plants and considerable literature has been published in the recent decade. Here we will provide a comprehensive review of GWAS studies in cotton crop, which includes case studies on biotic resistance, abiotic tolerance, fiber yield and quality traits, current status, prospects, bottlenecks of GWAS and finally, thought-provoking question. This review will serve as a catalog of GWAS in cotton and suggest new frontiers of the cotton crop to be studied with this important tool.

Mechanism of cotton resistance to abiotic stress, and recent research advances in the osmoregulation related genes

Abiotic stress is an important factor affecting the normal growth and development of plants and crop yield. To reduce the impact of abiotic adversity on cotton growth and development, the material basis of cotton resistance and its physiological functions are analyzed at the molecular level. At the same time, the use of genetic engineering methods to recombine resistance genes has become a hot spot in cotton resistance research. This paper provides an overviews of the resistance mechanism of cotton against the threat of non-biological adversity, as well as the research progress of osmoregulation-related genes, protein-acting genes, and transcription regulatory factor genes in recent years, and outlines the explored gene resources in cotton resistance genetic engineering, with the aim to provide ideas and reference bases for future research on cotton resistance.

Comprehensive evaluation of the response to aluminum stress in olive tree (Olea europaea L.)

Olive (Olea europaea L.) is an ancient tree species in the Mediterranean, but the lack of knowledge about aluminum-resistant varieties limits its introduction to acidic soil. The objective of this study was to have a comprehensive evaluation of the response to aluminum stress in olive tree at germplasm, metabolome, and transcriptome levels. In this experiment, seedlings of 97 olive germplasm with 1.0-3.0 cm roots and two leaves were treated with 50 μM Al³⁺ (pH = 5.0). By factor analysis of the traits of defoliation rate, rooting rate, length of extended root, and length of new root, 97 germplasm were classified into five different groups according to their diverse responses to aluminum stress: 5 highly resistant (5.15%), 30 moderately resistant (30.93%), 31 general (31.96%), 23 moderately sensitive (23.71%), and 8 highly sensitive (8.25%) germplasm. The three most sensitive and three most resistant germplasm were further used for metabolome and transcriptome analysis. Exposed to aluminum stress, 96 differentially accumulated metabolites (DAMs)/4,845 differentially expressed genes (DEGs) and 66 DAMs/2,752 DEGs were identified in highly sensitive and resistant germplasm, respectively. Using multi-omics technology, the pathways and related DAMs/DEGs involved in cell wall/cytoplasm receptors, reactive oxygen species balance, hormone induction, synthesis of organic acids, Al³⁺ transport, and synthesis of metabolites were identified to mainly regulate the response to aluminum stress in olive. This study provides a theoretical guide and prior germplasm and genes for further genetic improvement of aluminum tolerance in the olive tree.

Arbuscular mycorrhizal fungi improve the growth and drought tolerance of Cinnamomum migao by enhancing physio-biochemical responses

Drought is the main limiting factor for plant growth in karst areas with a fragile ecological environment. Cinnamomum migao H.W. Li is an endemic medicinal woody plant present in the karst areas of southwestern China, and it is endangered due to poor drought tolerance. Arbuscular mycorrhizal fungi (AMF) are known to enhance the drought tolerance of plants. However, few studies have examined the contribution of AMF in improving the drought tolerance of C. migao seedlings. Therefore, we conducted a series of experiments to determine whether a single inoculation and coinoculation of AMF (Claroideoglomus lamellosum and Claroideoglomus etunicatum) enhanced the drought tolerance of C. migao. Furthermore, we compared the effects of single inoculation and coinoculation with different inoculum sizes (20, 40, 60, and 100 g; four replicates per treatment) on mycorrhizal colonization rate, plant growth, photosynthetic parameters, antioxidant enzyme activity, and malondialdehyde (MDA) and osmoregulatory substance contents. The results showed that compared with nonmycorrhizal plants, AMF colonization significantly improved plant growing status; net photosynthetic rate; superoxide dismutase, catalase, and peroxidase activities; and soluble sugar, soluble protein, and proline contents. Furthermore, AMF colonization increased relative water content and reduced MDA content in cells. These combined cumulative effects of AMF symbiosis ultimately enhanced the drought tolerance of seedlings and were closely related to the inoculum size. With an increase in inoculum size, the growth rate and drought tolerance of plants first increased and then decreased. The damage caused by drought stress could be reduced by inoculating 40-60 g of AMF, and the effect of coinoculation was significantly better than that of single inoculation at 60 g of AMF, while the effect was opposite at 40 g of AMF. Additionally, the interaction between AMF and inoculum sizes had a significant effect on drought tolerance. In conclusion, the inoculation of the AMF (Cl. lamellosum and Cl. etunicatum) improved photosynthesis, activated antioxidant enzymes, regulated cell osmotic state, and enhanced the drought tolerance of C. migao, enabling its growth in fragile ecological environments.

Genome-Wide Dissection of the Genetic Basis for Drought Tolerance in Gossypium hirsutum L. Races

Drought seriously threats the growth and development of Gossypium hirsutum L. To dissect the genetic basis for drought tolerance in the G. hirsutum L. germplasm, a population, consisting of 188 accessions of G. hirsutum races and a cultivar (TM-1), was genotyped using the Cotton80KSNP biochip, and 51,268 high-quality single-nucleotide polymorphisms (SNPs) were obtained. Based on the phenotypic data of eight drought relative traits from four environments, we carried out association mapping with five models using GAPIT software. In total, thirty-six SNPs were detected significantly associated at least in two environments or two models. Among these SNPs, 8 and 28 (including 24 SNPs in 5 peak regions) were distributed in the A and D subgenome, respectively; eight SNPs were found to be distributed within separate genes. An SNP, TM73079, located on chromosome D10, was simultaneously associated with leaf fresh weight, leaf wilted weight, and leaf dry weight. Another nine SNPs, TM47696, TM33865, TM40383, TM10267, TM59672, TM59675, TM59677, TM72359, and TM72361, on chromosomes A13, A10, A12, A5, D6, and D9, were localized within or near previously reported quantitative trait loci for drought tolerance. Moreover, 520 genes located 200 kb up- and down-stream of 36 SNPs were obtained and analyzed based on gene annotation and transcriptome sequencing. The results showed that three candidate genes, Gh_D08G2462, Gh_A03G0043, and Gh_A12G0369, may play important roles in drought tolerance. The current GWAS represents the first investigation into mapping QTL for drought tolerance in G. hirsutum races and provides important information for improving cotton cultivars.

Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress

Sunflower is one of the most important oil crops in the world, and drought stress can severely limit its production and quality. To understand the underlying mechanism of drought tolerance, and identify candidate genes for drought tolerance breeding, we conducted a combined genome-wide association studies (GWAS) and RNA-seq analysis. A total of 226 sunflower inbred lines were collected from different regions of China and other countries. Eight phenotypic traits were evaluated under control and drought stress conditions. Genotyping was performed using a Specific-Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 934.08 M paired-end reads were generated, with an average Q30 of 91.97%. Based on the 243,291 polymorphic SLAF tags, a total of 94,162 high-quality SNPs were identified. Subsequent analysis of linkage disequilibrium (LD) and population structure in the 226 accessions was carried out based on the 94,162 high-quality SNPs. The average LD decay across the genome was 20 kb. Admixture analysis indicated that the entire population most likely originated from 11 ancestors. GWAS was performed using three methods (MLM, FarmCPU, and BLINK) simultaneously. A total of 80 SNPs showed significant associations with the 8 traits (p < 1.062 × 10-6). Next, a total of 118 candidate genes were found. To obtain more reliable candidate genes, RNA-seq analysis was subsequently performed. An inbred line with the highest drought tolerance was selected according to phenotypic traits. RNA was extracted from leaves at 0, 7, and 14 days of drought treatment. A total of 18,922 differentially expressed genes were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed up-regulated genes were mainly enriched in the branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in the photosynthesis-related process. Six DEGs were randomly selected from all DEGs for validation; these genes showed similar patterns in RNA-seq and RT-qPCR analysis, with a correlation coefficient of 0.8167. Through the integration of the genome-wide association study and the RNA-sequencing, 14 candidate genes were identified. Four of them (LOC110885273, LOC110872899, LOC110891369, LOC110920644) were abscisic acid related protein kinases and transcription factors. These genes may play an important role in sunflower drought response and will be used for further study. Our findings provide new insights into the response mechanisms of sunflowers against drought stress and contribute to further genetic breeding.

Machine Learning for Plant Stress Modeling: A Perspective towards Hormesis Management

Plant stress is one of the most significant factors affecting plant fitness and, consequently, food production. However, plant stress may also be profitable since it behaves hormetically; at low doses, it stimulates positive traits in crops, such as the synthesis of specialized metabolites and additional stress tolerance. The controlled exposure of crops to low doses of stressors is therefore called hormesis management, and it is a promising method to increase crop productivity and quality. Nevertheless, hormesis management has severe limitations derived from the complexity of plant physiological responses to stress. Many technological advances assist plant stress science in overcoming such limitations, which results in extensive datasets originating from the multiple layers of the plant defensive response. For that reason, artificial intelligence tools, particularly Machine Learning (ML) and Deep Learning (DL), have become crucial for processing and interpreting data to accurately model plant stress responses such as genomic variation, gene and protein expression, and metabolite biosynthesis. In this review, we discuss the most recent ML and DL applications in plant stress science, focusing on their potential for improving the development of hormesis management protocols.

Morphological, physiological and molecular assessment of cotton for drought tolerance under field conditions

Climate change could be an existential threat to many crops. Drought and heat stress are becoming harder for cultivated crops. Cotton in Pakistan is grown under natural high temperature and low moisture, could be used as a source of heat and drought tolerance. Therefore, the study was conducted to morphological, physiological and molecular characterization of cotton genotypes under field conditions. A total of 25 cotton genotypes were selected from the gene pool of Pakistan based on tolerance to heat and drought stress. In field trail, the stress related traits like boll retention percentage, plant height, number of nodes and inter-nodal distance were recorded. In physiological assessment, traits such as photosynthesis rate, stomatal conductance, transpiration rate, leaf temperature, relative water content and excised leaf water loss were observed. At molecular level, a set of 19 important transcription factors, controlling drought/heat stress tolerance (HSPCB, GHSP26, HSFA2, HSP101, HSP3, DREB1A, DREB2A, TPS, GhNAC2, GbMYB5, GhWRKY41, GhMKK3, GhMPK17, GhMKK1, GhMPK2, APX1, HSC70, ANNAT8, and GhPP2A1) were analyzed from all genotypes. Data analyses depicted that boll retention percentage, photosynthesis, stomatal conductance, relative water content under the stress conditions were associated with the presence of important drought & heat TF/genes which depicts high genetic potential of Pakistani cotton varieties against abiotic stress. The variety MNH-886 appeared in medium plant height, high boll retention percentage, high relative water content, photosynthesis rate, stomatal conductance, transpiration rate and with maximum number transcription factors under study. The variety may be used as source material for heat and drought tolerant cotton breeding. The results of this study may be useful for the cotton breeders to develop genotype adoptable to environmental stresses under climate change scenario.

A type-2C protein phosphatase (GhDRP1) participates in cotton (Gossypium hirsutum) response to drought stress

GhDRP1 acts as a negatively regulator to participate in response to drought stress possibly by modulating ABA signaling pathway and flavonoid biosynthesis pathway which affects stomata movement and thus water loss, ROS scavenging enzymes, and proline accumulation in cotton. Type-2C protein phosphatases (PP2C) may play important roles in plant stress signal transduction. Here, we show the evidence that a cotton PP2C protein GhDRP1 participates in plant response to drought stress. GhDRP1 gene encodes an active type-2C protein phosphatase (PP2C) and its expression is significantly induced in cotton by drought stress. Compared with wild type, the GhDRP1 overexpression (OE) transgenic cotton and Arabidopsis displayed reduced drought tolerance, whereas GhDRP1-silenced (RNAi) cotton showed enhanced drought tolerance. Under drought stress, malondialdehyde content was lower, whereas superoxide dismutase and peroxidase activities, proline content, stomata closure and relative water content were higher in GhDRP1 RNAi plants compared with those in wild type. In contrast, GhDRP1 OE plants showed the opposite phenotype under the same conditions. Expression levels of some stress-related and flavonoid biosynthesis-related genes were altered in GhDRP1 transgenic plants under drought stress. Additionally, GhDRP1 protein could interact with other proteins such as PYLs, SNF1-related protein kinase and GLK1-like protein. Collectively, these data suggest that GhDRP1 participates in plant response to drought stress possibly by modulating ABA signaling pathway and flavonoid biosynthesis pathway which affects stomata movement and thus water loss, ROS scavenging enzymes, and proline accumulation in cotton.

Triacylglycerol biosynthesis in shaded seeds of tung tree (Vernicia fordii) is regulated in part by Homeodomain Leucine Zipper 21

Light quantity and quality affect many aspects of plant growth and development. However, few reports have addressed the molecular connections between seed oil accumulation and light conditions, especially dense shade. Shade-avoiding plants can redirect plant resources into extension growth at the expense of leaf and root expansion in an attempt to reach areas containing richer light. Here, we report that tung tree seed oil accumulation is suppressed by dense shade during the rapid oil accumulation phase. Transcriptome analysis confirmed that oil accumulation suppression due to dense shade was attributed to reduced expression of fatty acid and triacylglycerol biosynthesis-related genes. Through weighted gene co-expression network analysis, we identified 32 core transcription factors (TFs) specifically upregulated in densely shaded seeds during the rapid oil accumulation period. Among these, VfHB21, a class I homeodomain leucine zipper TF, was shown to suppress expression of FAD2 and FADX, two key genes related to α-eleostearic acid, by directly binding to HD-ZIP I/II motifs in their respective promoter regions. VfHB21 also binds to similar motifs in the promoters of VfWRI1 and VfDGAT2, two additional key seed lipid regulatory/biosynthetic genes. Functional conservation of HB21 during plant evolution was demonstrated by the fact that AtWRI1, AtSAD1, and AtFAD2 were downregulated in VfHB21-overexpressor lines of transgenic Arabidopsis, with concomitant seed oil reduction, and the fact that AtHB21 expression also was induced by shade. This study reveals some of the regulatory mechanisms that specifically control tung tree seed oil biosynthesis and more broadly regulate plant storage carbon partitioning in response to dense shade conditions.

Identification of Novel Quantitative Trait Nucleotides and Candidate Genes for Bacterial Wilt Resistance in Tobacco (Nicotiana tabacum L.) Using Genotyping-by-Sequencing and Multi-Locus Genome-Wide Association Studies

Tobacco bacterial wilt (TBW) is a devastating soil-borne disease threatening the yield and quality of tobacco. However, its genetic foundations are not fully understood. In this study, we identified 126,602 high-quality single-nucleotide polymorphisms (SNPs) in 94 tobacco accessions using genotyping-by-sequencing (GBS) and a 94.56 KB linkage disequilibrium (LD) decay rate for candidate gene selection. The population structure analysis revealed two subpopulations with 37 and 57 tobacco accessions. Four multi-locus genome-wide association study (ML-GWAS) approaches identified 142 quantitative trait nucleotides (QTNs) in E1-E4 and the best linear unbiased prediction (BLUP), explaining 0.49-22.52% phenotypic variance. Of these, 38 novel stable QTNs were identified across at least two environments/methods, and their alleles showed significant TBW-DI differences. The number of superior alleles associated with TBW resistance for each accession ranged from 4 to 24; eight accessions had more than 18 superior alleles. Based on TBW-resistant alleles, the five best cross combinations were predicted, including MC133 × Ruyuan No. 1 and CO258 × ROX28. We identified 52 candidate genes around 38 QTNs related to TBW resistance based on homologous functional annotation and KEGG enrichment analysis, e.g., CYCD3;2, BSK1, Nitab4.5_0000641g0050, Nitab4.5_0000929g0030. To the best of our knowledge, this is the first comprehensive study to identify QTNs, superior alleles, and their candidate genes for breeding TBW-resistant tobacco varieties. The results provide further insight into the genetic architecture, marker-assisted selection, and functional genomics of TBW resistance, improving future breeding efforts to increase crop productivity.

Multi-Omics-Based Identification and Functional Characterization of Gh_A06G1257 Proves Its Potential Role in Drought Stress Tolerance in Gossypium hirsutum

Cotton is one of the most important fiber crops globally. Despite this, various abiotic stresses, including drought, cause yield losses. We used transcriptome profiles to investigate the co-expression patterns of gene networks associated with drought stress tolerance. We identified three gene modules containing 3,567 genes highly associated with drought stress tolerance. Within these modules, we identified 13 hub genes based on intramodular significance, for further validation. The yellow module has five hub genes (Gh_A07G0563, Gh_D05G0221, Gh_A05G3716, Gh_D12G1438, and Gh_D05G0697), the brown module contains three hub genes belonging to the aldehyde dehydrogenase (ALDH) gene family (Gh_A06G1257, Gh_A06G1256, and Gh_D06G1578), and the pink module has five hub genes (Gh_A02G1616, Gh_D12G2599, Gh_D07G2232, Gh_A02G0527, and Gh_D07G0629). Based on RT-qPCR results, the Gh_A06G1257 gene has the highest expression under drought stress in different plant tissues and it might be the true candidate gene linked to drought stress tolerance in cotton. Silencing of Gh_A06G1257 in cotton leaves conferred significant sensitivity in response to drought stress treatments. Overexpression of Gh_A06G1257 in Arabidopsis also confirms its role in drought stress tolerance. L-valine, Glutaric acid, L-proline, L-Glutamic acid, and L-Tryptophan were found to be the most significant metabolites playing roles in drought stress tolerance. These findings add significantly to existing knowledge of drought stress tolerance mechanisms in cotton.

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.

GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton

A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01041-y.

Finding Needles in a Haystack: Using Geo-References to Enhance the Selection and Utilization of Landraces in Breeding for Climate-Resilient Cultivars of Upland Cotton (Gossypium hirsutum L.)

The genetic uniformity of cultivated cotton as a consequence of domestication and modern breeding makes it extremely vulnerable to abiotic challenges brought about by major climate shifts. To sustain productivity amidst worsening agro-environments, future breeding objectives need to seriously consider introducing new genetic variation from diverse resources into the current germplasm base of cotton. Landraces are genetically heterogeneous, population complexes that have been primarily selected for their adaptability to specific localized or regional environments. This makes them an invaluable genetic resource of novel allelic diversity that can be exploited to enhance the resilience of crops to marginal environments. The utilization of cotton landraces in breeding programs are constrained by the phenology of the plant and the lack of phenotypic information that can facilitate efficient selection of potential donor parents for breeding. In this review, the genetic value of cotton landraces and the major challenges in their utilization in breeding are discussed. Two strategies namely Focused Identification of Germplasm Strategy and Environmental Association Analysis that have been developed to effectively screen large germplasm collections for accessions with adaptive traits using geo-reference-based, mathematical modelling are highlighted. The potential applications of both approaches in mining available cotton landrace collections are also presented.

Crosstalk between phytohormones and secondary metabolites in the drought stress tolerance of crop plants: A review

Drought stress negatively affects crop performance and weakens global food security. It triggers the activation of downstream pathways, mainly through phytohormones homeostasis and their signaling networks, which further initiate the biosynthesis of secondary metabolites (SMs). Roots sense drought stress, the signal travels to the above-ground tissues to induce systemic phytohormones signaling. The systemic signals further trigger the biosynthesis of SMs and stomatal closure to prevent water loss. SMs primarily scavenge reactive oxygen species (ROS) to protect plants from lipid peroxidation and also perform additional defense-related functions. Moreover, drought-induced volatile SMs can alert the plant tissues to perform drought stress mitigating functions in plants. Other phytohormone-induced stress responses include cell wall and cuticle thickening, root and leaf morphology alteration, and anatomical changes of roots, stems, and leaves, which in turn minimize the oxidative stress, water loss, and other adverse effects of drought. Exogenous applications of phytohormones and genetic engineering of phytohormones signaling and biosynthesis pathways mitigate the drought stress effects. Direct modulation of the SMs biosynthetic pathway genes or indirect via phytohormones' regulation provides drought tolerance. Thus, phytohormones and SMs play key roles in plant development under the drought stress environment in crop plants.

Towards doubling fibre yield for cotton in the semiarid agricultural area by increasing tolerance to drought, heat and salinity simultaneously

Abiotic stresses such as extreme temperatures, water-deficit and salinity negatively affect plant growth and development, and cause significant yield losses. It was previously shown that co-overexpression of the Arabidopsis vacuolar pyrophosphatase gene AVP1 and the rice SUMO E3 ligase gene OsSIZ1 in Arabidopsis significantly increased tolerance to multiple abiotic stresses and led to increased seed yield for plants grown under single or multiple abiotic stress conditions. It was hypothesized that there might be synergistic effects between AVP1 overexpression and OsSIZ1 overexpression, which could lead to substantially increased yields if these two genes are co-overexpressed in real crops. To test this hypothesis, AVP1 and OsSIZ1 were co-overexpressed in cotton, and the impact of OsSIZ1/AVP1 co-overexpression on cotton's performance under normal growth and multiple stress conditions were analysed. It was found that OsSIZ1/AVP1 co-overexpressing plants performed significantly better than AVP1-overexpressing, OsSIZ1-overexpressing and wild-type cotton plants under single, as well as under multiple stress conditions in laboratory and field conditions. Two field studies showed that OsSIZ1/AVP1 co-overexpressing plants produced 133% and 81% more fibre than wild-type cotton in the dryland conditions of West Texas. This research illustrates that co-overexpression of AVP1 and OsSIZ1 is a viable strategy for engineering abiotic stress-tolerant crops and could substantially improve crop yields in low input or marginal environments, providing a solution for food security for countries in arid and semiarid regions of the world.

Full-length annotation with multistrategy RNA-seq uncovers transcriptional regulation of lncRNAs in cotton

Long noncoding RNAs (lncRNAs) are crucial factors during plant development and environmental responses. To build an accurate atlas of lncRNAs in the diploid cotton Gossypium arboreum, we combined Isoform-sequencing, strand-specific RNA-seq (ssRNA-seq), and cap analysis gene expression (CAGE-seq) with PolyA-seq and compiled a pipeline named plant full-length lncRNA to integrate multi-strategy RNA-seq data. In total, 9,240 lncRNAs from 21 tissue samples were identified. 4,405 and 4,805 lncRNA transcripts were supported by CAGE-seq and PolyA-seq, respectively, among which 6.7% and 7.2% had multiple transcription start sites (TSSs) and transcription termination sites (TTSs). We revealed that alternative usage of TSS and TTS of lncRNAs occurs pervasively during plant growth. Besides, we uncovered that many lncRNAs act in cis to regulate adjacent protein-coding genes (PCGs). It was especially interesting to observe 64 cases wherein the lncRNAs were involved in the TSS alternative usage of PCGs. We identified lncRNAs that are coexpressed with ovule- and fiber development-associated PCGs, or linked to GWAS single-nucleotide polymorphisms. We mapped the genome-wide binding sites of two lncRNAs with chromatin isolation by RNA purification sequencing. We also validated the transcriptional regulatory role of lnc-Ga13g0352 via virus-induced gene suppression assay, indicating that this lncRNA might act as a dual-functional regulator that either activates or inhibits the transcription of target genes.

QTL mapping of PEG-induced drought tolerance at the early seedling stage in sesame using whole genome re-sequencing

Improvement in sesame drought tolerance at seedling stage is important for yield stability. Genetic approaches combing with conventional breeding is the most effective way to develop drought-tolerant cultivars. In this study, three traits and their relative values, including seedling weight (SW), shoot length (SL) and root length (RL), were evaluated under control and osmotic conditions in a recombinant inbred line (RIL) population derived from cross of Zhushanbai and Jinhuangma. Significant variation and high broad sense heritability were observed for all traits except SW under stress condition in the population. With this population, a high-density linkage map with 1354 bin markers was constructed through whole genome re-sequencing (WGS) strategy. Quantitative trait loci (QTL) mapping was performed for all the traits. A total of 34 QTLs were detected on 10 chromosomes. Among them, 13 stable QTLs were revealed in two independent experiments, eight of them were associated with traits under water stress condition. One region on chromosome 12 related to RL under osmotic condition and relative RL had the highest LOD value and explained the largest phenotypic variation among all the QTLs detected under water stress condition. These findings will provide new genetic resources for molecular improvement of drought tolerance and candidate gene identification in sesame.

Detection of QTNs for kernel moisture concentration and kernel dehydration rate before physiological maturity in maize using multi-locus GWAS

Maize is China’s largest grain crop. Mechanical grain harvesting is the key technology in maize production, and the kernel moisture concentration (KMC) is the main controlling factor in mechanical maize harvesting in China. The kernel dehydration rate (KDR) is closely related to the KMC. Thus, it is important to conduct genome-wide association studies (GWAS) of the KMC and KDR in maize, detect relevant quantitative trait nucleotides (QTNs), and mine relevant candidate genes. Here, 132 maize inbred lines were used to measure the KMC every 5 days from 10 to 40 days after pollination (DAP) in order to calculate the KDR. These lines were genotyped using a maize 55K single-nucleotide polymorphism array. QTNs for the KMC and KDR were detected based on five methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, and ISIS EM-BLASSO) in the package mrMLM. A total of 334 significant QTNs were found for both the KMC and KDR, including 175 QTNs unique to the KMC and 178 QTNs unique to the KDR; 116 and 58 QTNs were detected among the 334 QTNs by two and more than two methods, respectively; and 9 and 5 QTNs among 58 QTNs were detected in 2 and 3 years, respectively. A significant enrichment in cellular component was revealed by Gene Ontology enrichment analysis of candidate genes in the intervals adjacent to the 14 QTNs and this category contained five genes. The information provided in this study may be useful for further mining of genes associated with the KMC and KDR in maize.

Random Amplified Polymorphic DNA (RAPD) and Derived Techniques

Understanding biology and genetics at molecular level has become very important for dissection and manipulation of genome architecture for addressing evolutionary and taxonomic questions. Knowledge of genetic variation and genetic relationship among genotypes is an important consideration for classification, utilization of germplasm resources, and breeding. Molecular markers have contributed significantly in this respect and have been widely used in plant science in a number of ways, including genetic fingerprinting, diagnostics, identification of duplicates and selection of core collections, determination of genetic distances, genome analysis, development of molecular maps, and identification of markers associated with desirable breeding traits. The application of molecular markers largely depends on the type of markers employed, distribution of markers in the genome, type of loci they amplify, level of polymorphism, and reproducibility of products. Among many DNA markers available, random amplified polymorphic DNA (RAPD) is the simplest, is cost-effective, and can be performed in a moderate laboratory for most of its applications. In addition, RAPDs can touch much of the genome and has the advantage that no prior knowledge of the genome under research is necessary. The recent improvements in the RAPD technique like arbitrarily primed polymerase chain reaction (AP-PCR), sequence characterized amplified region (SCAR), DNA amplification fingerprinting (DAF), sequence-related amplified polymorphism (SRAP), cleaved amplified polymorphic sequences (CAPS), random amplified microsatellite polymorphism (RAMPO), and random amplified hybridization microsatellites (RAHM) can complement the shortcomings of RAPDs and have enhanced the utility of this simple technique for specific applications. Simple protocols for these techniques are presented along with the applications of RAPD in genetic diversity analysis, mapping, varietal identification, genetic fidelity testing, etc.

Loci harboring genes with important role in drought and related abiotic stress responses in flax revealed by multiple GWAS models

QTNs associated with drought tolerance traits and indices were identified in a flax mini-core collection through multiple GWAS models and phenotyping at multiple locations under irrigated and non-irrigated field conditions. Drought is a critical phenomenon challenging today's agricultural sector. Crop varieties adapted to moisture deficit are becoming vital. Flax can be greatly affected by limiting moisture conditions, especially during the early development and reproductive stages. Here, a mini-core collection comprising genotypes from more than 20 major growing countries was evaluated for 11 drought-related traits in irrigated and non-irrigated fields for 3 years. Heritability of the traits ranged from 44.7 to 86%. Six of the 11 traits showed significant phenotypic difference between irrigated and non-irrigated conditions. A genome-wide association study (GWAS) was performed for these six traits and their corresponding stress indices based on 106 genotypes and 12,316 single nucleotide polymorphisms (SNPs) using six multi-locus and one single-locus models. The SNPs were then assigned to 8050 linkage disequilibrium (LD) blocks to which a restricted two-stage multi-locus multi-allele GWAS was applied. A total of 144 quantitative trait nucleotides (QTNs) and 13 LD blocks were associated with at least one trait or stress index. Of these, 16 explained more than 15% of the genetic variance. Most large-effect QTN loci harbored gene(s) previously predicted to play role(s) in the associated traits. Genes mediating responses to abiotic stresses resided at loci associated with stress indices. Flax genes Lus10009480 and Lus10030150 that are predicted to encode WAX INDUCER1 and STRESS-ASSOCIATED PROTEIN (SAP), respectively, are among the important candidates detected. Accessions with multiple favorable alleles outperformed others for grain yield, thousand seed weight and fiber/biomass in non-irrigated conditions, suggesting their potential usefulness in breeding and genomic selection.

Phenomics-based GWAS analysis reveals the genetic architecture for drought resistance in cotton

Drought resistance (DR) is a complex trait that is regulated by a variety of genes. Without comprehensive profiling of DR-related traits, the knowledge of the genetic architecture for DR in cotton remains limited. Thus, there is a need to bridge the gap between genomics and phenomics. In this study, an automatic phenotyping platform (APP) was systematically applied to examine 119 image-based digital traits (i-traits) during drought stress at the seedling stage, across a natural population of 200 representative upland cotton accessions. Some novel i-traits, as well as some traditional i-traits, were used to evaluate the DR in cotton. The phenomics data allowed us to identify 390 genetic loci by genome-wide association study (GWAS) using 56 morphological and 63 texture i-traits. DR-related genes, including GhRD2, GhNAC4, GhHAT22 and GhDREB2, were identified as candidate genes by some digital traits. Further analysis of candidate genes showed that Gh_A04G0377 and Gh_A04G0378 functioned as negative regulators for cotton drought response. Based on the combined digital phenotyping, GWAS analysis and transcriptome data, we conclude that the phenomics dataset provides an excellent resource to characterize key genetic loci with an unprecedented resolution which can inform future genome-based breeding for improved DR in cotton.

GWAS reveals consistent QTL for drought and salt tolerance in a MAGIC population of 550 lines derived from intermating of 11 Upland cotton (Gossypium hirsutum) parents

Cotton is grown in arid and semi-arid regions where abiotic stresses such as drought and salt are prevalent. There is a lack of studies that simultaneously address the genetic and genomic basis of tolerance to drought and salt stress. In this study, a multi-parent advanced generation inter-cross (MAGIC) population of 550 recombinant inbred lines (RILs) together with their 11 Upland cotton parents with a total of 473,516 polymorphic SNP markers was used to identify quantitative trait loci (QTL) for drought tolerance (DT) and salt tolerance (ST) at the seedling stage based on two replicated greenhouse tests. Transgressive segregation occurred in the MAGIC-RILs, indicating that tolerant and sensitive alleles recombined for tolerance to the abiotic stress during the intermating process for the population development. A total of 20 QTL were detected for DT including 13 and 7 QTL based on plant height (PH) and dry shoot weight (DSW), respectively; and 23 QTL were detected for ST including 12 and 11 QTL for PH and DSW, respectively. There were several chromosomes with QTL clusters for abiotic stress tolerance including four QTL on chromosome A13 and three QTL on A01 for DT, and four QTL on D08 and three QTL on A11 for ST. Nine QTL (21% of the 43 QTL) detected were in common between DT and ST, indicating a common genetic basis for DT and ST. The narrow chromosomal regions for most of the QTL detected in this study allowed identification of 53 candidate genes associated with responses to salt and drought stress and abiotic stimulus. The QTL identified for both DT and ST have significantly augmented the repertoire of QTL for abiotic stress tolerance that can be used for marker-assisted selection to develop cultivars with resilience to drought and/or salt and further genomic studies towards the identification of drought and salt tolerance genes in cotton.

A Dual Strategy of Breeding for Drought Tolerance and Introducing Drought-Tolerant, Underutilized Crops into Production Systems to Enhance Their Resilience to Water Deficiency

Water scarcity is the primary constraint on crop productivity in arid and semiarid tropical areas suffering from climate alterations; in accordance, agricultural systems have to be optimized. Several concepts and strategies should be considered to improve crop yield and quality, particularly in vulnerable regions where such environmental changes cause a risk of food insecurity. In this work, we review two strategies aiming to increase drought stress tolerance: (i) the use of natural genes that have evolved over time and are preserved in crop wild relatives and landraces for drought tolerance breeding using conventional and molecular methods and (ii) exploiting the reservoir of neglected and underutilized species to identify those that are known to be more drought-tolerant than conventional staple crops while possessing other desired agronomic and nutritive characteristics, as well as introducing them into existing cropping systems to make them more resilient to water deficiency conditions. In the past, the existence of drought tolerance genes in crop wild relatives and landraces was either unknown or difficult to exploit using traditional breeding techniques to secure potential long-term solutions. Today, with the advances in genomics and phenomics, there are a number of new tools available that facilitate the discovery of drought resistance genes in crop wild relatives and landraces and their relatively easy transfer into advanced breeding lines, thus accelerating breeding progress and creating resilient varieties that can withstand prolonged drought periods. Among those tools are marker-assisted selection (MAS), genomic selection (GS), and targeted gene editing (clustered regularly interspaced short palindromic repeat (CRISPR) technology). The integration of these two major strategies, the advances in conventional and molecular breeding for the drought tolerance of conventional staple crops, and the introduction of drought-tolerant neglected and underutilized species into existing production systems has the potential to enhance the resilience of agricultural production under conditions of water scarcity.

Recommendations for Choosing the Genotyping Method and Best Practices for Quality Control in Crop Genome-Wide Association Studies

High-throughput genotyping boosts genome-wide association studies (GWAS) in crop species, leading to the identification of single-nucleotide polymorphisms (SNPs) associated with economically important traits. Choosing a cost-effective genotyping method for crop GWAS requires careful examination of several aspects, namely, the purpose and the scale of the study, crop-specific genomic features, and technical and economic matters associated with each genotyping option. Once genotypic data have been obtained, quality control (QC) procedures must be applied to avoid bias and false signals in genotype–phenotype association tests. QC for human GWAS has been extensively reviewed; however, QC for crop GWAS may require different actions, depending on the GWAS population type. Here, we review most popular genotyping methods based on next-generation sequencing (NGS) and array hybridization, and report observations that should guide the investigator in the choice of the genotyping method for crop GWAS. We provide recommendations to perform QC in crop species, and deliver an overview of bioinformatics tools that can be used to accomplish all needed tasks. Overall, this work aims to provide guidelines to harmonize those procedures leading to SNP datasets ready for crop GWAS.

Natural Variation Uncovers Candidate Genes for Barley Spikelet Number and Grain Yield under Drought Stress

Drought stress can occur at any growth stage and can affect crop productivity, which can result in large yield losses all over the world. In this respect, understanding the genetic architecture of agronomic traits under drought stress is essential for increasing crop yield potential and harvest. Barley is considered the most abiotic stress-tolerant cereal, particularly with respect to drought. In the present study, worldwide spring barley accessions were exposed to drought stress beginning from the early reproductive stage with 35% field capacity under field conditions. Drought stress had significantly reduced the agronomic and yield-related traits such as spike length, awn length, spikelet per spike, grains per spike and thousand kernel weight. To unravel the genetic factors underlying drought tolerance at the early reproductive stage, genome-wide association scan (GWAS) was performed using 121 spring barley accessions and a 9K single nucleotide polymorphisms (SNPs) chip. A total number of 101 significant SNPs, distributed over all seven barley chromosomes, were found to be highly associated with the studied traits, of which five genomic regions were associated with candidate genes at chromosomes 2 and 3. On chromosome 2H, the region between 6469300693-647258342 bp includes two candidate drought-specific genes (HORVU2Hr1G091030 and HORVU2Hr1G091170), which are highly associated with spikelet and final grain number per spike under drought stress conditions. Interestingly, the gene expression profile shows that the candidate genes were highly expressed in spikelet, grain, spike and leaf organs, demonstrating their pivotal role in drought tolerance. To the best of our knowledge, we reported the first detailed study that used GWAS with bioinformatic analyses to define the causative alleles and putative candidate genes underlying grain yield-related traits under field drought conditions in diverse barley germplasm. The identified alleles and candidate genes represent valuable resources for future functional characterization towards the enhancement of barley cultivars for drought tolerance.

Interactional Effects of Climate Change Factors on the Water Status, Photosynthetic Rate, and Metabolic Regulation in Peach

Environmental stress factors caused by climate change affect plant growth and crop production, and pose a growing threat to sustainable agriculture, especially for tree crops. In this context, we sought to investigate the responses to climate change of two Prunus rootstocks (GF677 and Adesoto) budded with Catherina peach cultivar. Plants were grown in 15 L pots in temperature gradient greenhouses for an 18 days acclimation period after which six treatments were applied: [CO2 levels (400 versus 700 µmol mol-1), temperature (ambient versus ambient + 4°C), and water availability (well irrigated versus drought)]. After 23 days, the effects of stress were evaluated as changes in physiological and biochemical traits, including expression of relevant genes. Stem water potential decreased under drought stress in plants grafted on GF677 and Adesoto rootstocks; however, elevated CO2 and temperature affected plant water content differently in both combinations. The photosynthetic rate of plants grafted on GF677 increased under high CO2, but decreased under high temperature and drought conditions. The photosynthetic rates of plants grafted onto Adesoto were only affected by drought treatment. Furthermore, in GF677-Catherina plants, elevated CO2 alleviated the effect of drought, whereas in those grafted onto Adesoto, the same condition produced acclimation in the rate. Stomatal conductance decreased under high CO2 and drought stress in both grafted rootstocks, and the combination of these conditions improved water-use efficiency. Changes in the sugar content in scion leaves and roots were significantly different under the stress conditions in both combinations. Meanwhile, the expression of most of the assessed genes was significantly affected by treatment. Regarding genotypes, GF677 rootstock showed more changes at the molecular and transcriptomic level than did Adesoto rootstock. A coordinated shift was found between the physiological status and the transcriptomic responses. This study revealed adaptive responses to climate change at the physiological, metabolic, and transcriptomic levels in two Prunus rootstocks budded with 'Catherina'. Overall, these results demonstrate the resilient capacity and plasticity of these contrasting genotypes, which can be further used to combat ongoing climate changes and support sustainable peach production.

Linkage Analysis and Multi-Locus Genome-Wide Association Studies Identify QTNs Controlling Soybean Plant Height

Plant height is an important target for soybean breeding. It is a typical quantitative trait controlled by multiple genes and is susceptible to environmental influences. Here, we carried out phenotypic analysis of 156 recombinant inbred lines derived from "Dongnong L13" and "Henong 60" in nine environments at four locations over 6 years using interval mapping and inclusive composite interval mapping methods. We performed quantitative trait locus (QTL) analysis by applying pre-built simple-sequence repeat maps. We detected 48 QTLs, including nine significant QTLs detected by multiple methods and in multiple environments. Meanwhile, genotyping of all lines using the SoySNP660k BeadChip produced 54,836 non-redundant single-nucleotide polymorphism (SNP) genotypes. We used five multi-locus genome-wide association analysis methods to locate 10 quantitative trait nucleotides (QTNs), four of which overlap with previously located QTLs. Five candidate genes related to plant height are predicted to lie within 200 kb of these four QTNs. We identified 19 homologous genes in Arabidopsis, two of which may be associated with plant height. These findings further our understanding of the multi-gene regulatory network and genetic determinants of soybean plant height, which will be important for breeding high-yielding soybean.

Genome-wide association reveals genetic variation of lint yield components under salty field conditions in cotton (Gossypium hirsutum L.)

BACKGROUND

Salinity is one of the most significant environmental factors limiting the productivity of cotton. However, the key genetic components responsible for the reduction in cotton yield in saline-alkali soils are still unclear.

RESULTS

Here, we evaluated three main components of lint yield, single boll weight (SBW), lint percentage (LP) and boll number per plant (BNPP), across 316 G. hirsutum accessions under four salt conditions over two years. Phenotypic analysis indicated that LP was unchanged under different salt conditions, however BNPP decreased significantly and SBW increased slightly under high salt conditions. Based on 57,413 high-quality single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) analysis, a total of 42, 91 and 25 stable quantitative trait loci (QTLs) were identified for SBW, LP and BNPP, respectively. Phenotypic and QTL analysis suggested that there was little correlation among the three traits. For LP, 8 stable QTLs were detected simultaneously in four different salt conditions, while fewer repeated QTLs for SBW or BNPP were identified. Gene Ontology (GO) analysis indicated that their regulatory mechanisms were also quite different. Via transcriptome profile data, we detected that 10 genes from the 8 stable LP QTLs were predominantly expressed during fiber development. Further, haplotype analyses found that a MYB gene (GhMYB103), with the two SNP variations in cis-regulatory and coding regions, was significantly correlated with lint percentage, implying a crucial role in lint yield. We also identified that 40 candidate genes from BNPP QTLs were salt-inducible. Genes related to carbohydrate metabolism and cell structure maintenance were rich in plants grown in high salt conditions, while genes related to ion transport were active in plants grown in low salt conditions, implying different regulatory mechanisms for BNPP at high and low salt conditions.

CONCLUSIONS

This study provides a foundation for elucidating cotton salt tolerance mechanisms and contributes gene resources for developing upland cotton varieties with high yields and salt stress tolerance.

Insights into Drought Stress Signaling in Plants and the Molecular Genetic Basis of Cotton Drought Tolerance

Drought stress restricts plant growth and development by altering metabolic activity and biological functions. However, plants have evolved several cellular and molecular mechanisms to overcome drought stress. Drought tolerance is a multiplex trait involving the activation of signaling mechanisms and differentially expressed molecular responses. Broadly, drought tolerance comprises two steps: stress sensing/signaling and activation of various parallel stress responses (including physiological, molecular, and biochemical mechanisms) in plants. At the cellular level, drought induces oxidative stress by overproduction of reactive oxygen species (ROS), ultimately causing the cell membrane to rupture and stimulating various stress signaling pathways (ROS, mitogen-activated-protein-kinase, Ca2+, and hormone-mediated signaling). Drought-induced transcription factors activation and abscisic acid concentration co-ordinate the stress signaling and responses in cotton. The key responses against drought stress, are root development, stomatal closure, photosynthesis, hormone production, and ROS scavenging. The genetic basis, quantitative trait loci and genes of cotton drought tolerance are presented as examples of genetic resources in plants. Sustainable genetic improvements could be achieved through functional genomic approaches and genome modification techniques such as the CRISPR/Cas9 system aid the characterization of genes, sorted out from stress-related candidate single nucleotide polymorphisms, quantitative trait loci, and genes. Exploration of the genetic basis for superior candidate genes linked to stress physiology can be facilitated by integrated functional genomic approaches. We propose a third-generation sequencing approach coupled with genome-wide studies and functional genomic tools, including a comparative sequenced data (transcriptomics, proteomics, and epigenomic) analysis, which offer a platform to identify and characterize novel genes. This will provide information for better understanding the complex stress cellular biology of plants.

Analysis of Drought Tolerance and Associated Traits in Upland Cotton at the Seedling Stage

(1) Background: Upland cotton (Gossypium hirsutum L.) is the most important natural fiber worldwide, and it is extensively planted and plentifully used in the textile industry. Major cotton planting regions are frequently affected by abiotic stress, especially drought stress. Drought resistance is a complex, quantitative trait. A genome-wide association study (GWAS) constitutes an efficient method for dissecting the genetic architecture of complex traits. In this study, the drought resistance of a population of 316 upland cotton accessions was studied via GWAS. (2) Methods: GWAS methodology was employed to identify relationships between molecular markers or candidate genes and phenotypes of interest. (3) Results: A total of 8, 3, and 6 SNPs were associated with the euphylla wilting score (EWS), cotyledon wilting score (CWS), and leaf temperature (LT), respectively, based on a general linear model and a factored spectrally transformed linear mixed model. For these traits, 7 QTLs were found, of which 2 each were located on chromosomes A05, A11, and D03, and of which 1 was located on chromosome A01. Importantly, in the candidate regions WRKY70, GhCIPK6, SnRK2.6, and NET1A, which are involved in the response to abscisic acid (ABA), the mitogen-activated protein kinase (MAPK) signaling pathway and the calcium transduction pathway were identified in upland cotton at the seedling stage under drought stress according to annotation information and linkage disequilibrium (LD) block analysis. Moreover, RNA sequencing analysis showed that WRKY70, GhCIPK6, SnRK2.6, and NET1A were induced by drought stress, and the expression of these genes was significantly different between normal and drought stress conditions. (4) Conclusions: The present study should provide some genomic resources for drought resistance in upland cotton. Moreover, the germplasm of the different phenotypes, the detected SNPs and, the potential candidate genes will be helpful for molecular marker-assisted breeding studies about increased drought resistance in upland cotton.

Genetic Detection of Lint Percentage Applying Single-Locus and Multi-Locus Genome-Wide Association Studies in Chinese Early-Maturity Upland Cotton

Upland cotton (Gossypium hirsutum L.) is the most important source of natural fiber in the world. Early-maturity upland cotton varieties are commonly planted in China. Nevertheless, lint yield of early-maturity upland cotton varieties is strikingly lower than that of middle- and late-maturity ones. How to effectively improve lint yield of early maturing cotton, becomes a focus of cotton research. Here, based on 72,792 high-quality single nucleotide polymorphisms of 160 early-maturing upland cotton accessions, we performed genome-wide association studies (GWASs) for lint percentage (LP), one of the most lint-yield component traits, applying one single-locus method and six multi-locus methods. A total of 4 and 45 significant quantitative trait nucleotides (QTNs) were respectively identified to be associated with LP. Interestingly, in two of four planting environments, two of these QTNs (A02_74713290 and A02_75551547) were simultaneously detected via both one single-locus and three or more multi-locus GWAS methods. Among the 42 genes within a genomic region (A02: 74.31-75.95 Mbp) containing the above two peak QTNs, Gh_A02G1269, Gh_A02G1280, and Gh_A02G1295 had the highest expression levels in ovules during seed development from 20 to 25 days post anthesis, whereas Gh_A02G1278 was preferentially expressed in the fibers rather than other organs. These results imply that the four potential candidate genes might be closely related to cotton LP by regulating the proportion of seed weight and fiber yield. The QTNs and potential candidate genes for LP, identified in this study, provide valuable resource for cultivating novel cotton varieties with earliness and high lint yield in the future.