ABSTRACT
Abiotic stresses are the major stressors affecting wheat (Triticum aestivum L.) production worldwide. The world population is increasing continuously. It is very difficult to feed the population because one-third world's population consumes wheat as a staple food. Among all abiotic stresses, salinity is one that led to a drastic reduction in wheat crop fitness and productivity. Thus, understanding the effects of salinity stress becomes indispensable for wheat improvement programs which have depended mainly on the genetic variations present in the wheat genome through conventional breeding. Therefore, an experiment was conducted using a complete randomized design with four replications, to determine the selection criteria for salinity-tolerant germplasm based on morphophysiological traits at the seedling stage. Three levels of salt solutions, i.e., 4, 8, and 12 dSm-1 were applied and the performance of different genotypes under these three salinities levels was observed. Results depicted that leaf water content and relative water content were correlated with each other. Notably, selection based on these traits increased the performance of other characters. The genotypes G11, G13, G18, G22, and G36 performed best in the salinity stress. So, these genotypes are considered salinity-tolerant genotypes. The genotypes G4, G17, G19, G30, and G38 performed worst in the stress and these were salinity-susceptible genotypes. From the results of the principal component (PC) analysis, the first five PCs were indicated to have a substantial genetic variation from the total of 14 PCs. These PCs showed 75, 73, 65.324, and 65.162% of total variation under normal, salinity level 4, 8, and 12 dSm-1, respectively. Stomatal conductance, fresh shoot weight and fresh root weight, and dry shoot weight and dry root weight were not significant and negatively associated with all other traits studied, except for relative water and leaf water content. Overall, the results suggested that selection based on leaf water content and relative water content at the seedling stage would genetically improve salinity tolerance. Genotypes with good performance under salt stress conditions may be useful in future breeding programs and will be effective in developing high-yielding salt-tolerant wheat varieties.
ABSTRACT
Plants are regularly exposed to biotic and abiotic stresses that adversely affect agricultural production. Omics has gained momentum in the last two decades, fueled by statistical methodologies, computational capabilities, mass spectrometry, nucleic-acid sequencing, and peptide-sequencing platforms. Functional genomics-especially metabolomics, transcriptomics, and proteomics-have contributed substantially to plant molecular responses to stress. Recent progress in reverse and forward genetics approaches have mediated high-throughput techniques for identifying stress-related genes. Furthermore, web-based genetic databases have mediated bioinformatics techniques for detecting families of stress-tolerant genes. Gene ontology (GO) databases provide information on the gene product's functional features and help with the computational estimation of gene function. Functional omics data from multiple platforms are useful for positional cloning. Stress-tolerant plants have been engineered using stress response genes, regulatory networks, and pathways. The genome-editing tool, CRISPR-Cas9, reveals the functional features of several parts of the plant genome. Current developments in CRISPR, such as de novo meristem induction genome-engineering in dicots and temperature-tolerant LbCas12a/CRISPR, enable greater DNA insertion precision. This review discusses functional omics for molecular insight and CRISPR-Cas9-based validation of gene function in crop plants. Omics and CRISPR-Cas9 are expected to garner knowledge on molecular systems and gene function and stress-tolerant crop production.
Subject(s)
Crops, Agricultural/growth & development , Gene Editing/methods , Plant Proteins/genetics , CRISPR-Cas Systems , Crops, Agricultural/genetics , Gene Expression Regulation, Plant , Genomics , Metabolomics , Reverse Genetics , Stress, PhysiologicalABSTRACT
Endophytic fungi (EF) are a group of fascinating host-associated fungal communities that colonize the intercellular or intracellular spaces of host tissues, providing beneficial effects to their hosts while gaining advantages. In recent decades, accumulated research on endophytic fungi has revealed their biodiversity, wide-ranging ecological distribution, and multidimensional interactions with host plants and other microbiomes in the symbiotic continuum. In this review, we highlight the role of secondary metabolites (SMs) as effectors in these multidimensional interactions, and the biosynthesis of SMs in symbiosis via complex gene expression regulation mechanisms in the symbiotic continuum and via the mimicry or alteration of phytochemical production in host plants. Alternative biological applications of SMs in modern medicine, agriculture, and industry and their major classes are also discussed. This review recapitulates an introduction to the research background, progress, and prospects of endophytic biology, and discusses problems and substantive challenges that need further study.
ABSTRACT
In the third sentence of "SNP calling and SNPLDB assembly" in "Materials and methods" of the published manuscript, four numbers related to the DNA sequencing data are not correct. The error does not affect any results and conclusions of the article. The four incorrect numbers are 1144.56, 110.87, 3.86 and 4.57, while the correct numbers should be 1219.6, 101.1, 4.4 × and 3.7, respectively, and the correct sentence is given below.
ABSTRACT
MAIN CONCLUSION: RTM-GWAS identified 111 DT QTLs, 262 alleles with high proportion of QEI and genetic variation accounting for 88.55-95.92% PV in NAM, from which QTL-allele matrices were established and candidate genes annotated. Drought tolerance (DT) is one of the major challenges for world soybean production. A nested association mapping (NAM) population with 403 lines comprising two recombinant inbred line (RIL) populations: M8206 × TongShan and ZhengYang × M8206 was tested for DT using polyethylene-glycol (PEG) treatment under spring and summer environments. The population was sequenced using restriction-site-associated DNA sequencing (RAD-seq) filtered with minor allele frequency (MAF) ≥ 0.01, 55,936 single nucleotide polymorphisms (SNPs) were obtained and organized into 6137 SNP linkage disequilibrium blocks (SNPLDBs). The restricted two-stage multi-locus genome-wide association studies (RTM-GWAS) identified 73 and 38 QTLs with 174 and 88 alleles contributed main effect 40.43 and 26.11% to phenotypic variance (PV) and QTL-environment interaction (QEI) effect 24.64 and 10.35% to PV for relative root length (RRL) and relative shoot length (RSL), respectively. The DT traits were characterized with high proportion of QEI variation (37.52-41.65%), plus genetic variation (46.90-58.40%) in a total of 88.55-95.92% PV. The identified QTLs-alleles were organized into main-effect and QEI-effect QTL-allele matrices, showing the genetic and QEI architecture of the three parents/NAM population. From the matrices, the possible best genotype was predicted to have a weighted average value over two indicators (WAV) of 1.873, while the top ten optimal crosses among RILs with 95th percentile WAV 1.098-1.132, transgressive over the parents (0.651-0.773) but much less than 1.873, implying further pyramiding potential. From the matrices, 134 candidate genes were annotated involved in nine biological processes. The present results provide a novel way for molecular breeding in QTL-allele-based genomic selection for optimal cross selection.
