Breeding for higher yield, early maturity, wider adaptability and waterlogging tolerance in soybean (Glycine max L.): A case study

Photoperiod-mediated rapid generation advancement in soybean (Glycine max (L.) Merr.)

Soybean is a short-day crop and the long-duration variety takes 120 days for maturity. A protocol for rapid generation advancement in soybean breeding is worthwhile keeping in view its utility. The study emphasizes standardisation of physical conditions, especially using warm white and cool white light-emitting diodes to hasten flowering and pod setting in soybean (DS9712 genotype). Complete open flowers were obtained with a 16 L/8D (dark/light) photoperiod in 30 days. The results also highlighted the application of interventions of physical conditions and inputs, especially during the reproductive phase to shorten the seed-to-seed generation time by around 15 days in a low-cost method for soybean breeding. Breeding will be revolutionised in case economic speed breeding is combined with modern breeding technologies, thereby resulting in more generations per year.

Biochemical and morpho-physiological insights revealed low moisture stress adaptation mechanisms in cotton (Gossypium hirsutum L.)

Cotton (Gossypium hirsutum L.) is a multipurpose crop. Abiotic stresses, especially extreme heat and drought, limit crop growth and thus reduce cotton yield by about 50%. In this study, 30 cotton genotypes were tested against low moisture stress in a pot experiment in triplicates along with control under wire house conditions. At the 3-4 leaf stage, different morpho-physiological and biochemical parameters were measured in order to select the low moisture stress-tolerant genotypes. For the selection of the best performing genotypes, Multi-Trait Genotype-Ideotype Distance Index (MGIDI) was used for the ranking of genotypes on the basis of multiple indices. For biochemical traits, 09 (TPC, TF, TSP, MDA, SOD, POD, CAT, APX, and Proline) out of 24 showed significant genotypic effects and were used for MGIDI. Eight genotypes (N-812 N-1296 N-696 N-377 N-121-896 N-T86, and N-3496) were observed to be best performing than others at 25% selection pressure (SI = 25%). For morpho-physiological traits, 14 out of 15 showed significant genotypic effects and used for MGIDI. Ten genotypes (N-1237 N-812 N-1296 N-696 N-9078 N-377 N-512 N-121 N-375, and N-896) were observed to be best performing at 35% selection pressure (SI = 35%). Six genotypes, i.e. N-812-1296 N-696 N-377 N-121, and N-896 were found common in both MGIDI analysis. In conclusion, three genotypes, i.e. N-696, N-896, and N-T86 proved to be most resilient to low moisture stress. Develop protocols, identified genotypes and markers that can be used for development of climate-smart cotton genotypes.

Assessment of genetic diversity by phenological traits, field performance, and Start Codon Targeted (SCoT) polymorphism marker of seventeen soybean genotypes (Glycine max L.)

The Egyptian-farmed soybeans have a wide range of genetic diversity which is most important in plant improvement programs in order to develop new higher yielding soybean genotypes. The present study is designed to determine the genetic variability among seventeen genotypes of cultivated soybean (Glycine max L.) by examining the phenotypic level at the seedling stage, field performance over two years 2022/2023 and genetically using Start Codon Targeted (SCoT) markers. Results indicated that the SCoT markers, 100 seed weight, and tip angle (TA) traits were positively correlated with H2L12, DR 101, H15L5, and H117 genotypes. In addition, the number of branches per plant and plant height were associated with H113, H32, Crowford, H129, and D7512035. Furthermore, the length of the first internode (LFI), root width (RW), root length (RL), and shoot length (SL) were more associated with Giza 111, NC105, and Hutcheson. The hierarchical cluster analysis (HCA) and its associated heatmap explored the differences among the genotypes. It showed that all examined parameters were clustered into four distinct clusters. The obtained results showed that genotypes NC105, H30, D75_12035, and H2L12 have promising phenological and morphological traits besides tracking the inheritance of nearby genes surrounding the ATG translation start codon since they are in a monoclades. The obtained results will help the breeder plan appropriate selection strategies for improving seed yield in soybeans through hybridization from divergent clusters.

Subcellular Proteomics to Elucidate Soybean Response to Abiotic Stress

Climate change jeopardizes soybean production by declining seed yield and quality. In this review, the morphophysiological alterations of soybean in response to abiotic stress are summarized, followed by illustrations of cellular metabolisms and regulatory mechanisms to organellar stress based on subcellular proteomics. This highlights the communications associated with reactive oxygen species scavenging, molecular chaperones, and phytohormone signals among subcellular compartments. Given the complexity of climate change and the limitations of plants in coping with multiple abiotic stresses, a generic response to environmental constraints is proposed between calcium and abscisic acid signals in subcellular organelles. This review summarizes the findings of subcellular proteomics in stressed soybean and discusses the future prospects of subcellular proteomics for promoting the improvement of climate-tolerant crops.

Identification and genetic diversity analysis of high-yielding charcoal rot resistant soybean genotypes

Charcoal rot disease caused by Macrophomina phaseolina (Tassi) Goid is one of the most devastating diseases in soybean in India. During 2018, 226 diverse soybean genotypes were evaluated for genetic resistance under hot-spot conditions. Out of them, a subset of 151 genotypes were selected based on Percent Disease Incidence (PDI) and better agronomic performance. Out of these 151 genotypes evaluated during 2019, 43 genotypes were selected based on PDI and superior agronomic performance for further field evaluation and molecular characterization. During 2020 and 2021, these forty-three genotypes, were evaluated for PDI, Area Under Disease Progress Curve (AUDPC), and grain yield. In 2020, genotype JS 20-20 showed least PDI (0.42) and AUDPC (9.37).Highest grain yield was recorded by the genotype JS 21-05 (515.00 g). In 2021, genotype JS 20-20 exhibited least PDI (0.00) and AUDPC (0.00).Highest grain yield was recorded in JS 20-98 (631.66 g). Across both years, JS 20-20 had the least PDI (0.21) and AUDPC (4.68), while grain yield was highest in JS 20-98 (571.67 g). Through MGIDI (multi-trait genotype-ideotype distance) analysis, JS 21-05 (G19), JS 22-01 (G43), JS 20-98 (G28) and JS 20-20 (G21) were identified as the ideotypes with respect to the traits that were evaluated. Two unique alleles, Satt588 (100 bp) on linkage group K (Chromosome no 9) and Sat_218 (200 bp) on linkage group H (Chromosome no 12), were specific for thetwo resistant genotypes JS 21-71and DS 1318, respectively. Through cluster analysis, it was observed that the genotypes bred at Jabalpur were more genetically related.

The intervention of classical and molecular breeding approaches to enhance flooding stress tolerance in soybean - An review

Abiotic stresses and climate changes cause severe loss of yield and quality of crops and reduce the production area worldwide. Flooding stress curtails soybean growth, yield, and quality and ultimately threatens the global food supply chain. Flooding tolerance is a multigenic trait. Tremendous research in molecular breeding explored the potential genomic regions governing flood tolerance in soybean. The most robust way to develop flooding tolerance in soybean is by using molecular methods, including quantitative trait loci (QTL) mapping, identification of transcriptomes, transcription factor analysis, CRISPR/Cas9, and to some extent, genome-wide association studies (GWAS), and multi-omics techniques. These powerful molecular tools have deepened our knowledge about the molecular mechanism of flooding stress tolerance. Besides all this, using conventional breeding methods (hybridization, introduction, and backcrossing) and other agronomic practices is also helpful in combating the rising flooding threats to the soybean crop. The current review aims to summarize recent advancements in breeding flood-tolerant soybean, mainly by using molecular and conventional tools and their prospects. This updated picture will be a treasure trove for future researchers to comprehend the foundation of flooding tolerance in soybean and cover the given research gaps to develop tolerant soybean cultivars able to sustain growth under extreme climatic changes.

A GBS-based genome-wide association study reveals the genetic basis of salinity tolerance at the seedling stage in bread wheat (Triticum aestivum L.)

High salinity levels affect 20% of the cultivated area and 9%–34% of the irrigated agricultural land worldwide, ultimately leading to yield losses of crops. The current study evaluated seven salt tolerance-related traits at the seedling stage in a set of 138 pre-breeding lines (PBLs) and identified 63 highly significant marker-trait associations (MTAs) linked to salt tolerance. Different candidate genes were identified in in silico analysis, many of which were involved in various stress conditions in plants, including glycine-rich cell wall structural protein 1-like, metacaspase-1, glyceraldehyde-3-phosphate dehydrogenase GAPA1, and plastidial GAPA1. Some of these genes coded for structural protein and participated in cell wall structure, some were linked to programmed cell death, and others were reported to show abiotic stress response roles in wheat and other plants. In addition, using the Multi-Trait Genotype-Ideotype Distance Index (MGIDI) protocol, the best-performing lines under salt stress were identified. The SNPs identified in this study and the genotypes with favorable alleles provide an excellent source to impart salt tolerance in wheat.

Mepiquat chloride inhibits soybean growth but improves drought resistance

Soybeans are an important economic crop. As the most widely used growth regulator globally, the molecular mechanism of mepiquat chloride (DPC) in soybean remains unknown. In this study, RNA sequencing technology combined with ultra-performance liquid chromatography and tandem mass spectrometry were used to analyze the changes in the leaf transcriptome and metabolomics of soybean leaves at the seedling stage under DPC stress. The results showed that differentially expressed genes related to photosynthesis and cell wall synthesis were significantly downregulated at the transcriptional level. In addition, the syntheses of gibberellin, zeatin, brassinolide, and other plant hormones were inhibited in the signal transduction pathway of plant hormones, thereby inhibiting plant growth. In contrast, at the metabolic level, the expression levels of flavonoid differential metabolites were significantly increased, and the proportions of flavonoids in the two varieties were 61.5 and 66%, respectively. The combined analysis of transcriptome and metabolomics showed that the differential expressed genes and metabolites were mainly enriched in the isoflavonoid biosynthesis and flavonoid biosynthesis pathways. Principally, DPC inhibited plant growth but improved drought resistance. Our study is the first to report the molecular mechanism of DPC regulation in soybean, providing useful insights into the rational application of DPC in soybean.

Transcriptomic Analysis Reveals the Regulatory Networks and Hub Genes Controlling the Unsaturated Fatty Acid Contents of Developing Seed in Soybean

Soybean [Glycine max (L.) Merr.] is one of the most important crops, which produces about 25% of the world's edible oil. The nutritional value of soybean oil depends mostly on the relative contents of three unsaturated fatty acids (UFAs), i.e., oleic acid, linoleic acid (LA), and linolenic acid. However, the biosynthetic mechanism of UFAs remains largely unknown, and there are few studies on RNA-seq analysis of developing seeds. To identify the candidate genes and related pathways involved in the regulation of UFA contents during seed development in soybean, two soybean lines with different UFA profiles were selected from 314 cultivars and landraces originated from Southern China, and RNA-seq analysis was performed in soybean seeds at three developmental stages. Using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, a series of genes and pathways related to fatty acid metabolism were identified, and 40 days after flowering (DAF) was found to be the crucial period in the formation of UFA profiles. Further, weighted gene co-expression network analysis identified three modules with six genes whose functions were highly associated with the contents of oleic and LA. The detailed functional investigation of the networks and hub genes could further improve the understanding of the underlying molecular mechanism of UFA contents and might provide some ideas for the improvement in fatty acids profiles in soybean.