A Large Root Phenome Dataset Wide-Opened the Potential for Underground Breeding in Soybean

Comparative transcriptomic analysis of the nodulation-competent zone and inference of transcription regulatory network in silicon applied Glycine max [L.]-Merr. Roots

KEY MESSAGE

The study unveils Si's regulatory influence by regulating DEGs, TFs, and TRs. Further bHLH subfamily and auxin transporter pathway elucidates the mechanisms enhancing root development and nodulation. Soybean is a globally important crop serving as a primary source of vegetable protein for millions of individuals. The roots of these plants harbour essential nitrogen fixing structures called nodules. This study investigates the multifaceted impact of silicon (Si) application on soybean, with a focus on root development, and nodulation employing comprehensive transcriptomic analyses and gene regulatory network. RNA sequence analysis was utilised to examine the change in gene expression and identify the noteworthy differentially expressed genes (DEGs) linked to the enhancement of soybean root nodulation and root development. A set of 316 genes involved in diverse biological and molecular pathways are identified, with emphasis on transcription factors (TFs) and transcriptional regulators (TRs). The study uncovers TF and TR genes, categorized into 68 distinct families, highlighting the intricate regulatory landscape influenced by Si in soybeans. Upregulated most important bHLH subfamily and the involvement of the auxin transporter pathway underscore the molecular mechanisms contributing to enhanced root development and nodulation. The study bridges insights from other research, reinforcing Si's impact on stress-response pathways and phenylpropanoid biosynthesis crucial for nodulation. The study reveals significant alterations in gene expression patterns associated with cellular component functions, root development, and nodulation in response to Si.

Effects of irrigation on root growth and development of soybean: A 3-year sandy field experiment

Increasing the water use efficiency of crops is an important agricultural goal closely related to the root system -the primary plant organ for water and nutrient acquisition. In an attempt to evaluate the response of root growth and development of soybean to water supply levels, 200 genotypes were grown in a sandy field for 3 years under irrigated and non-irrigated conditions, and 14 root traits together with shoot fresh weight and plant height were investigated. Three-way ANOVA revealed a significant effect of treatments and years on growth of plants, accounting for more than 80% of the total variability. The response of roots to irrigation was consistent over the years as most root traits were improved by irrigation. However, the actual values varied between years because the growth of plants was largely affected by the field microclimatic conditions (i.e., temperature, sunshine duration, and precipitation). Therefore, the best linear unbiased prediction values for each trait were calculated using the original data. Principal component analysis showed that most traits contributed to principal component (PC) 1, whereas average diameter, the ratio of thin and medium thickness root length to total root length contributed to PC2. Subsequently, we focused on selecting genotypes that exhibited significant improvements in root traits under irrigation than under non-irrigated conditions using the increment (I-index) and relative increment (RI-index) indices calculated for all traits. Finally, we screened for genotypes with high stability and root growth over the 3 years using the multi-trait selection index (MTSI).Six genotypes namely, GmJMC130, GmWMC178, GmJMC092, GmJMC068, GmWMC075, and GmJMC081 from the top 10% of genotypes scoring MTSI less than the selection threshold of 7.04 and 4.11 under irrigated and non-irrigated conditions, respectively, were selected. The selected genotypes have great potential for breeding cultivars with improved water usage abilities, meeting the goal of water-saving agriculture.

Soybean Seedling Root Segmentation Using Improved U-Net Network

Soybean seedling root morphology is important to genetic breeding. Root segmentation is a key technique for identifying root morphological characteristics. This paper proposed a semantic segmentation model of soybean seedling root images based on an improved U-Net network to address the problems of the over-segmentation phenomenon, unsmooth root edges and root disconnection, which are easily caused by background interference such as water stains and noise, as well as inconspicuous contrast in soybean seedling images. Soybean seedling root images in the hydroponic environment were collected for annotation and augmentation. A double attention mechanism was introduced in the downsampling process, and an Attention Gate mechanism was added in the skip connection part to enhance the weight of the root region and suppress the interference of background and noise. Then, the model prediction process was visually interpreted using feature maps and class activation mapping maps. The remaining background noise was removed by connected component analysis. The experimental results showed that the Accuracy, Precision, Recall, F1-Score and Intersection over Union of the model were 0.9962, 0.9883, 0.9794, 0.9837 and 0.9683, respectively. The processing time of an individual image was 0.153 s. A segmentation experiment on soybean root images was performed in the soil-culturing environment. The results showed that this proposed model could extract more complete detail information and had strong generalization ability. It can achieve accurate root segmentation in soybean seedlings and provide a theoretical basis and technical support for the quantitative evaluation of the root morphological characteristics in soybean seedlings.

Utilization of Novel Perilla SSR Markers to Assess the Genetic Diversity of Native Perilla Germplasm Accessions Collected from South Korea

The Perilla crop is highly regarded in South Korea, both as a health food and traditional food. However, there is still a lack of Perilla SSR primer sets (PSPSs) for studying genetic variation among accessions of cultivated and weedy types of Perilla crop (CWTPC) from South Korea. In this study, 30 PSPSs were newly developed based on transcriptome contigs in P. frutescens, and 17 of these PSPSs were used to study the genetic diversity, phylogenetic relationships and structure population among 90 accessions of the CWTPC collected from South Korea. A total of 100 alleles were detected from selected 17 PSPSs, with an average of 5.9 alleles per locus. The gene diversity (GD) ranged from 0.164 to 0.831, with an average of 0.549. The average GD values from the cultivated var. frutescens, weedy var. frutescens, and weedy var. crispa, were 0.331, 0.588, and 0.389 respectively. In addition, most variance shown by Perilla SSR markers was within a population (73%). An analysis of the population structure and phylogenetic relationships showed that the genetic relationship among accessions of the weedy var. frutescens and weedy var. crispa is closer than that for the accessions of the cultivated var. frutescens. Based on association analysis between 17 PSPSs and three seed traits in 90 Perilla accessions, we detected 11 PSPSs that together were associated with the seed size and seed hardness traits. Therefore, the newly developed PSPSs will be useful for analyzing genetic variation among accessions of the CWTPC, association mapping, and selection of important morphological traits in Perilla crop breeding programs.

High-Throughput Phenotypic Characterization and Diversity Analysis of Soybean Roots (Glycine max L.)

Soybean (Glycine max L.) is a crop native to Northeast Asia, including China, Korea, and Japan, but currently cultivated all over the world. The National Agrobiodiversity Center in Korea at the Rural Development Administration (RDA) conserves approximately 26,000 accessions and conducts characterizations of its accessions, to accumulate new information. Roots are essential organs of a plant, providing mechanical support, as well as aiding water and nutrient acquisition. Currently, not much information is available in international gene banks regarding root characterization. We studied the root phenotype of 374 soybean accessions, using a high-throughput method. Eight root morphological traits (RMT) were studied and we observed that the surface area (SA), number of forks (NF), and number of tips (NT) had a positive correlation with total length (LENGTH), and that link average length (LAL) and other traits all had a negative correlation. Additionally, the correlation between seed traits (height, width, and 100-seed weight) and root traits was confirmed for the first time in this experiment. The germplasms were divided into three clusters by k-means clustering, and orthogonal projections to latent structures discriminant analysis (OPLS-DA) was used to compare clusters. The most distinctive characteristics between clusters were total lateral average length (LAD) and total lateral average length (DIAM). Cluster 3 had the highest LENGTH, SA, NF, and NF, whereas cluster 1 had the smallest LENGTH, SA, and NF. We selected the top 10 accessions for each RMT, and IT208321, IT216313, and IT216137 were nominated as the best germplasms. These accessions can be recommended to breeders as materials for breeding programs. This is a preliminary report on the characterization of the root phenotype at an international gene bank and will open up the possibility of improving the available information on accessions in gene banks worldwide.

High-Throughput Root Imaging Analysis Reveals Wide Variation in Root Morphology of Wild Adzuki bean (Vigna angularis) Accessions

Root system architecture and morphological diversification in wild accessions are important for crop improvement and productivity in adzuki beans. In this study, via analysis using 2-dimensional (2D) root imaging and WinRHIZO Pro software, we described the root traits of 61 adzuki bean accessions in their early vegetative growth stage. These accessions were chosen for study because they are used in Korea’s crop improvement programs; however, their root traits have not been sufficiently investigated. Analysis of variance revealed a significant difference between the accessions of all measured root traits. Distribution analysis demonstrated that most of the root traits followed normal distribution. The accessions showed up to a 17-fold increase in the values in contrasting accessions for the root traits. For total root length (TRL), the values ranged from 82.43 to 1435 cm, and for surface area (SA), they ranged from 12.30 to 208.39 cm². The values for average diameter (AD) ranged from 0.23 to 0.56 mm. Significant differences were observed for other traits. Overall, the results showed that the accession IT 305544 had the highest TRL, SA, and number of tips (NT), whereas IT 262477 and IT 262492 showed the lowest values for TRL, SA, and AD. Principal component analysis showed an 89% variance for PC1 and PC2. K-mean clustering explained 77.4% of the variance in the data and grouped the accessions into three clusters. All six root traits had greater coefficients of variation (≥15%) among the tested accessions. Furthermore, to determine which root traits best distinguished different accessions, the correlation within our set of accessions provided trait-based ranking depending on their contribution. The identified accessions may be advantageous for the development of new crossing combinations to improve root features in adzuki beans during the early growth stage. The root traits assessed in this study could be attributes for future adzuki bean crop selection and improvement.