Multiomics dissection of Brassica napus L. lateral roots and endophytes interactions under phosphorus starvation.

Many plants associate with endophytic microbes that improve root phosphorus (P) uptake. Understanding the interactions between roots and endophytes can enable efforts to improve P utilization. Here, we characterize the interactions between lateral roots of endophytes in a core collection of 50 rapeseed (Brassica napus L.

PNNGS, a multi-convolutional parallel neural network for genomic selection.

Genomic selection (GS) can accomplish breeding faster than phenotypic selection. Improving prediction accuracy is the key to promoting GS. To improve the GS prediction accuracy and stability, we introduce parallel convolution to deep learning for GS and call it a parallel neural network for genomic selection (PNNGS).

Advancing PAM-less genome editing in soybean using CRISPR-SpRY.

Although CRISPR-Cas9 technology has been rapidly applied in soybean genetic improvement, it is difficult to achieve the targeted editing of the specific loci in the soybean complex genome due to the limitations of the classical protospacer adjacent motif (PAM). Here, we developed a PAM-less genome editing system mediated by SpRY in soybean. By performing targeted editing of representative agronomic trait targets in soybean and evaluating the results, we demonstrate that the SpRY protein can achieve efficient targeted mutagenesis at relaxed PAM sites in soybean.

DEKR-SPrior: An Efficient Bottom-Up Keypoint Detection Model for Accurate Pod Phenotyping in Soybean.

The pod and seed counts are important yield-related traits in soybean. High-precision soybean breeders face the major challenge of accurately phenotyping the number of pods and seeds in a high-throughput manner. Recent advances in artificial intelligence, especially deep learning (DL) models, have provided new avenues for high-throughput phenotyping of crop traits with increased precision.

CropMetabolome: a comprehensive metabolome database for major crops cross eight categories.

Chemical compositions of crops are of great agronomical importance, as crops serve as resources for nutrition, energy, and medicines for human and livestock. For crop metabolomics research, the lack of crop reference metabolome and high-quality reference compound mass spectra, as well as utilities for metabolic profiling, has hindered the discovery and functional study of phytochemicals in crops. To meet these challenging needs, we have developed the Crop Metabolome database (abbreviated as CropMetabolome) that is dedicated to the construction of crop reference metabolome, repository, and dissemination of crop metabolomic data, and profiling and analytic tools for metabolomics research.

Residual networks without pooling layers improve the accuracy of genomic predictions.

Residual neural network genomic selection is the first GS algorithm to reach 35 layers, and its prediction accuracy surpasses previous algorithms. With the decrease in DNA sequencing costs and the development of deep learning, phenotype prediction accuracy by genomic selection (GS) continues to improve. Residual networks, a widely validated deep learning technique, are introduced to deep learning for GS.

Cytochrome is Involved in the Biosynthesis of Glycitein in Soybean.

Isoflavones, the major secondary metabolites of interest due to their benefits to both human and plant health, are exclusively produced by legumes. In this study, we profiled the isoflavone content in dry seeds from 211 soybean [ (L.) Merr.

Long noncoding RNAs underlie multiple domestication traits and leafhopper resistance in soybean.

The origin and functionality of long noncoding RNA (lncRNA) remain poorly understood. Here, we show that multiple quantitative trait loci modulating distinct domestication traits in soybeans are pleiotropic effects of a locus composed of two tandem lncRNA genes. These lncRNA genes, each containing two inverted repeats, originating from coding sequences of the MYB genes, function in wild soybeans by generating clusters of small RNA (sRNA) species that inhibit the expression of their MYB gene relatives through post-transcriptional regulation.

Arabidopsis transcription factor TCP4 controls the identity of the apical gynoecium.

The style and stigma at the apical gynoecium are crucial for flowering plant reproduction. However, the mechanisms underlying specification of the apical gynoecium remain unclear. Here, we demonstrate that Class II TEOSINTE BRANCHED 1/CYCLOIDEA/PCF (TCP) transcription factors are critical for apical gynoecium specification in Arabidopsis (Arabidopsis thaliana).

Time-Series Field Phenotyping of Soybean Growth Analysis by Combining Multimodal Deep Learning and Dynamic Modeling.

The rate of soybean canopy establishment largely determines photoperiodic sensitivity, subsequently influencing yield potential. However, assessing the rate of soybean canopy development in large-scale field breeding trials is both laborious and time-consuming. High-throughput phenotyping methods based on unmanned aerial vehicle (UAV) systems can be used to monitor and quantitatively describe the development of soybean canopies for different genotypes.

MutL homolog 1 participates in interference-sensitive meiotic crossover formation in soybean.

MutL homolog 1 (MLH1), a member of the MutL homolog family, is required for normal recombination in most organisms. However, its role in soybean (Glycine max) remains unclear to date. Here, we characterized the Glycine max female and male sterility 1 (Gmfms1) mutation that reduces pollen grain viability and increases embryo sac abortion in soybean.

A transformer-based genomic prediction method fused with knowledge-guided module.

Genomic prediction (GP) uses single nucleotide polymorphisms (SNPs) to establish associations between markers and phenotypes. Selection of early individuals by genomic estimated breeding value shortens the generation interval and speeds up the breeding process. Recently, methods based on deep learning (DL) have gained great attention in the field of GP.

RefMetaPlant: a reference metabolome database for plants across five major phyla.

Plants are unique with tremendous chemical diversity and metabolic complexity, which is highlighted by estimates that green plants collectively produce metabolites numbering in the millions. Plant metabolites play crucial roles in all aspects of plant biology, like growth, development, stress responses, etc. However, the lack of a reference metabolome for plants, and paucity of high-quality standard compound spectral libraries and related analytical tools, have hindered the discovery and functional study of phytochemicals in plants.

The nuclear pore Y-complex functions as a platform for transcriptional regulation of FLOWERING LOCUS C in Arabidopsis.

The nuclear pore complex (NPC) has multiple functions beyond the nucleo-cytoplasmic transport of large molecules. Subnuclear compartmentalization of chromatin is critical for gene expression in animals and yeast. However, the mechanism by which the NPC regulates gene expression is poorly understood in plants.

UV-B irradiation-activated E3 ligase GmILPA1 modulates gibberellin catabolism to increase plant height in soybean.

Plant height is a key agronomic trait that affects yield and is controlled by both phytohormone gibberellin (GA) and ultraviolet-B (UV-B) irradiation. However, whether and how plant height is modulated by UV-B-mediated changes in GA metabolism are not well understood. It has not been reported that the E3 ubiquitin ligase Anaphase Promoting Complex/Cyclosome (APC/C) is involved in the regulation of plant growth in response to environmental factors.

Syntaxin of plants71 plays essential roles in plant development and stress response via regulating pH homeostasis.

SYP71, a plant-specific Qc-SNARE with multiple subcellular localization, is essential for symbiotic nitrogen fixation in nodules in , and is implicated in plant resistance to pathogenesis in rice, wheat and soybean. SYP71 is proposed to participate in multiple membrane fusion steps during secretion. To date, the molecular mechanism underlying SYP71 regulation on plant development remains elusive.

Combination of Hairy Root and Whole-Plant Transformation Protocols to Achieve Efficient CRISPR/Cas9 Genome Editing in Soybean.

The new gene-editing technology CRISPR/Cas system has been widely used for genome engineering in various organisms. Since the CRISPR/Cas gene-editing system has a certain possibility of low efficiency and the whole plant transformation of soybean is time-consuming and laborious, it is important to evaluate the editing efficiency of designed CRISPR constructs before the stable whole plant transformation process starts. Here, we provide a modified protocol for generating transgenic hairy soybean roots to assess the efficiency of guide RNA (gRNA) sequences of the CRISPR/Cas constructs within 14 days.

: A Novel Seed-Developing Gene in .

Soybean-seed development is controlled in multiple ways, as in many known regulating genes. Here, we identify a novel gene, (), involved in seed development, by analyzing a T-DNA mutant (). The mutant is a random mutant of the transgenic line, with phenotypes with small and brown seed coats.

Genetic dissection reveals the complex architecture of amino acid composition in soybean seeds.

Five loci related to soybean protein and amino acid contents were colocated by performing linkage mapping and GWAS. The haplotype analysis showed that Glyma.08G109100 may be useful to improve the soybean seed composition.

SYNTAXIN OF PLANTS81 regulates root meristem activity and stem cell niche maintenance via ROS signaling.

Root growth and development depend on continuous cell division and differentiation in root tips. In these processes, reactive oxygen species (ROS) play a critical role as signaling molecules. However, few ROS signaling regulators have been identified.