Environmental and genetic regulation of plant height in soybean

CRISPR/Cas9-mediated editing of GmDWF1 brassinosteroid biosynthetic gene induces dwarfism in soybean

KEY MESSAGE

The study on the GmDWF1-deficient mutant dwf1 showed that GmDWF1 plays a crucial role in determining soybean plant height and yield by influencing the biosynthesis of brassinosteroids. Soybean has not adopted the Green Revolution, such as reduced height for increased planting density, which have proven beneficial for cereal crops. Our research identified the soybean genes GmDWF1a and GmDWF1b, homologous to Arabidopsis AtDWF1, and found that they are widely expressed, especially in leaves, and linked to the cellular transport system, predominantly within the endoplasmic reticulum and intracellular vesicles. These genes are essential for the synthesis of brassinosteroids (BR). Single mutants of GmDWF1a and GmDWF1b, as well as double mutants of both genes generated through CRISPR/Cas9 genome editing, exhibit a dwarf phenotype. The single-gene mutant exhibits moderate dwarfism, while the double mutant shows more pronounced dwarfism. Despite the reduced stature, all types of mutants preserve their node count. Notably, field tests have shown that the single GmDWF1a mutant produced significantly more pods than wild-type plants. Spraying exogenous brassinolide (BL) can compensate for the loss in plant height induced by the decrease in endogenous BRs. Comparing transcriptome analyses of the GmDWF1a mutant and wild-type plants revealed a significant impact on the expression of many genes that influence soybean growth. Identifying the GmDWF1a and GmDWF1b genes could aid in the development of compact, densely planted soybean varieties, potentially boosting productivity.

Genome-wide association study reveals SNP markers controlling drought tolerance and related agronomic traits in chickpea across multiple environments

Chickpea, renowned for its exceptional nutritional value, stands as a crucial crop, serving as a dietary staple in various parts of the world. However, its productivity faces a significant challenge in the form of drought stress. This challenge highlights the urgent need to find genetic markers linked to drought tolerance for effective breeding programs. The primary objective of this study is to identify genetic markers associated with drought tolerance to facilitate effective breeding programs. To address this, we cultivated 185 chickpea accessions in two distinct locations in Lebanon over a two-year period, subjecting them to both irrigated and rain-fed environments. We assessed 11 drought-linked traits, including morphology, growth, yield, and tolerance score. SNP genotyping revealed 1344 variable SNP markers distributed across the chickpea genome. Genetic diversity across populations originating from diverse geographic locations was unveiled by the PCA, clustering, and structure analysis indicating that these genotypes have descend from five or four distinct ancestors. A genome-wide association study (GWAS) revealed several marker trait associations (MTAs) associated with the traits evaluated. Within the rainfed conditions, 11 significant markers were identified, each associated with distinct chickpea traits. Another set of 11 markers exhibited associations in both rainfed and irrigated environments, reflecting shared genetic determinants across these conditions for the same trait. The analysis of linkage disequilibrium (LD) highlighted two genomic regions with notably strong LD, suggesting significant interconnections among several investigated traits. This was further investigated by the correlation between major markers associated with these traits. Gene annotation of the identified markers has unveiled insights into 28 potential genes that play a role in influencing various chickpea drought-linked traits. These traits encompass crucial aspects such as blooming organ development, plant growth, seed weight, starch metabolism, drought regulation, and height index. Among the identified genes are CPN60-2, hsp70, GDSL(GELP), AHL16, NAT3, FAB1B, bZIP, and GL21. These genes collectively contribute to the multifaceted response of chickpea plants to drought stress. Our identified genetic factors exert their influence in both irrigated and rainfed environments, emphasizing their importance in shaping chickpea characteristics.

PH13 improves soybean shade traits and enhances yield for high-density planting at high latitudes

Shading in combination with extended photoperiods can cause exaggerated stem elongation (ESE) in soybean, leading to lodging and reduced yields when planted at high-density in high-latitude regions. However, the genetic basis of plant height in adaptation to these regions remains unclear. Here, through a genome-wide association study, we identify a plant height regulating gene on chromosome 13 (PH13) encoding a WD40 protein with three main haplotypes in natural populations. We find that an insertion of a Ty1/Copia-like retrotransposon in the haplotype 3 leads to a truncated PH13H3 with reduced interaction with GmCOP1s, resulting in accumulation of STF1/2, and reduced plant height. In addition, PH13H3 allele has been strongly selected for genetic improvement at high latitudes. Deletion of both PH13 and its paralogue PHP can prevent shade-induced ESE and allow high-density planting. This study provides insights into the mechanism of shade-resistance and offers potential solutions for breeding high-yielding soybean cultivar for high-latitude regions.

Genetic Diversity Analysis of Soybean Collection Using Simple Sequence Repeat Markers

Soybean [Glycine max (L.) Merr.] is a nutrient-rich crop that offers a sustainable source of dietary protein and edible oil. Determining the level of genetic diversity and relationships between various genetic resources involved in breeding programs is very important in crop improvement strategies. This study evaluated 100 soybean accessions with diverse origins for 10 important agronomic traits, including plant height (PH), an important plant adaptation-related trait impacting yield, in conditions in southeastern Kazakhstan for 2 years. The comparison of different groups of PH (tall, middle, and short) using a t-test suggested that the group of plants with the tallest PH provided a higher yield (p < 0.001) in relatively dry field conditions. The genetic diversity of the accessions was estimated using 25 simple sequence repeat (SSR) markers previously known to be associated with plant height. The results showed a significant variation among different groups of origin for all measured agronomic traits, as well as high genetic diversity, with the PIC (polymorphism information content) varying from 0.140 to 0.732, with an average of 0.524. Nei's diversity index ranged between 0.152 and 0.747, with an average of 0.526. The principal coordinate analysis (PCoA) of the studied soybean collection showed that Kazakhstan accessions were genetically distant from European, East Asian, and North American cultivars. Twelve out of twenty-five SSR markers demonstrated significant associations with ten studied agronomic traits, including PH (p < 0.05). Six SSRs with pleiotropic effects for studied traits were selected, and their haplotypes with phenotypic effects were generated for each soybean accession. The obtained results can be used in soybean improvement programs, including molecular-assisted breeding projects.

Effects of Genotype and Climate on Productive Performance of High Oleic Carthamus tinctorius L. under Rainfed Conditions in a Semi-Arid Environment of Sicily (Italy)

Safflower (Carthamus tinctorius L.) is a promising oilseed crop for cultivation in central Southern Italy due to its high tolerance to drought and salinity stress and appreciable seed and oil yields. The genetic diversity of cultivars and climate factors can affect fatty acid composition and yield traits. This study aimed to assess the effects of genotype and climate conditions on the productive performance of eight high oleic safflower genotypes under rainfed conditions in Sicily (Italy). These genotypes were compared to the Montola 2000 cultivar, which was used as a reference. Tests were carried out during the growing seasons of 2014-2015 and 2015-2016. The experimental design was a randomized complete block design with three replications. Morphological and yield components were significantly affected by genotype while the year had a significant effect on plant height only. In general, CTI 17 produced the highest seed yield (1.40 t ha^-1) and oil yield (0.58 t ha^-1). The seed oil content was found on 40.2% of dry matter, on average. The "genotype" factor significantly affected oil content and fatty acid composition. Oleic acid content was on average 66.1% and did not vary greatly over the two growing seasons. The above- and belowground plant parts showed the highest carbon content and the lowest nitrogen content as a percentage of dry matter. The results indicate that, under rainfed conditions, yield parameters of high oleic safflower genotypes can be profitable in southern Italy though significantly dependent upon genotype.

Development of SNP marker panels for genotyping by target sequencing (GBTS) and its application in soybean

A high-throughput genotyping platform with customized flexibility, high genotyping accuracy, and low cost is critical for marker-assisted selection and genetic mapping in soybean. Three assay panels were selected from the SoySNP50K, 40K, 20K, and 10K arrays, containing 41,541, 20,748, and 9670 SNP markers, respectively, for genotyping by target sequencing (GBTS). Fifteen representative accessions were used to assess the accuracy and consistency of the SNP alleles identified by the SNP panels and sequencing platform. The SNP alleles were 99.87% identical between technical replicates and 98.86% identical between the 40K SNP GBTS panel and 10× resequencing analysis. The GBTS method was also accurate in the sense that the genotypic dataset of the 15 representative accessions correctly revealed the pedigree of the accessions, and the biparental progeny datasets correctly constructed the linkage maps of the SNPs. The 10K panel was also used to genotype two parent-derived populations and analyze QTLs controlling 100-seed weight, resulting in the identification of the stable associated genetic locus Locus_OSW_06 on chromosome 06. The markers flanking the QTL explained 7.05% and 9.83% of the phenotypic variation, respectively. Compared with GBS and DNA chips, the 40K, 20K, and 10K panels reduced costs by 5.07% and 58.28%, 21.44% and 65.48%, and 35.74% and 71.76%, respectively. Low-cost genotyping panels could facilitate soybean germplasm assessment, genetic linkage map construction, QTL identification, and genomic selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01372-6.

RP, R. L. R. Population structure and genetic diversity characterization of soybean for seed longevity

Seed longevity is an important trait in the context of germplasm conservation and economics of seed production. The identification of populations with high level of genetic variability for seed longevity and associated traits will become a valuable resource for superior alleles for seed longevity. In this study, Genotyping-by-sequencing (GBS)-single nucleotide polymorphism (SNP) approach, simple sequence repeats (SSR) markers and agro-morphological traits have been explored to investigate the diversity and population structure of assembled 96 genotypes. The GBS technique performed on 96 genotypes of soybean (Glycine max (L.) Merrill) resulted in 37,897 SNPs on sequences aligned to the reference genome sequence. The average genome coverage was 6.81X with a mapping rate of 99.56% covering the entire genome. Totally, 29,955 high quality SNPs were identified after stringent filtering and most of them were detected in non-coding regions. The 96 genotypes were phenotyped for eight quantitative and ten qualitative traits by growing in field by following augmented design. The STRUCTURE (Bayesian-model based algorithm), UPGMA (Un-weighed Pair Group Method with Arithmetic mean) and principal component analysis (PCA) approaches using SSR, SNP as well as quantitative and qualitative traits revealed population structure and diversity in assembled population. The Bayesian-model based STRUCTURE using SNP markers could effectively identify clusters with higher seed longevity associated with seed coat colour and size which were subsequently validated by UPGMA and PCA based on SSR and agro-morphological traits. The results of STRUCTURE, PCA and UPGMA cluster analysis showed high degree of similarity and provided complementary data that helped to identify genotypes with higher longevity. Six black colour genotypes, viz., Local black soybean, Kalitur, ACC Nos. 39, 109, 101 and 37 showed higher seed longevity during accelerated ageing. Higher coefficient of variability observed for plant height, number of pods per plant, seed yield per plant, 100 seed weight and seed longevity confirms the diversity in assembled population and its suitability for quantitative trait loci (QTL) mapping.

Construction of prediction models for growth traits of soybean cultivars based on phenotyping in diverse genotype and environment combinations

As soybean cultivars are adapted to a relatively narrow range of latitude, the effects of climate changes are estimated to be severe. To address this issue, it is important to improve our understanding of the effects of climate change by applying the simulation model including both genetic and environmental factors with their interactions (G×E). To achieve this goal, we conducted the field experiments for soybean core collections using multiple sowing times in multi-latitudinal fields. Sowing time shifts altered the flowering time (FT) and growth phenotypes, and resulted in increasing the combinations of genotypes and environments. Genome-wide association studies for the obtained phenotypes revealed the effects of field and sowing time to the significance of detected alleles, indicating the presence of G×E. By using accumulated phenotypic and environmental data in 2018 and 2019, we constructed multiple regression models for FT and growth pattern. Applicability of the constructed models was evaluated by the field experiments in 2020 including a novel field, and high correlation between the predicted and measured values was observed, suggesting the robustness of the models. The models presented here would allow us to predict the phenotype of the core collections in a given environment.

The Organ Size and Morphological Change During the Domestication Process of Soybean

Soybean is one of the most important legume crops that can provide the rich source of protein and oil for human beings and livestock. In the twenty-one century, the total production of soybean is seriously behind the needs of a growing world population. Cultivated soybean [Glycine max (L.) Merr.] was domesticated from wild soybean (G. soja Sieb. and Zucc.) with the significant morphology and organ size changes in China around 5,000 years ago, including twisted stems to erect stems, small seeds to large seeds. Then it was spread worldwide to become one of the most popular and important crops. The release of the reference soybean genome and omics data provides powerful tools for researchers and breeders to dissect the functional genes and apply the germplasm in their work. Here, we summarized the function genes related to yield traits and organ size in soybean, including stem growth habit, leaf size and shape, seed size and weight. In addition, we also summarized the selection of organ traits during soybean domestication. In the end, we also discussed the application of new technology including the gene editing on the basic research and breeding of soybean, and the challenges and research hotspots in the future.