Summary: Soybean (Glycine max) is a major contributor to the world oilseed production. Its seed oil content has been increased through soybean domestication and improvement. However, the genes underlying the selection are largely unknown. The present contribution analyzed the expression patterns of genes in the seed oil quantitative trait loci with strong selective sweep signals, then used association, functional study and population genetics to reveal a sucrose efflux transporter gene, GmSWEET39, controlling soybean seed oil content and under selection. GmSWEET39 is highly expressed in soybean seeds and encodes a plasma membrane‐localized protein. Its expression level is positively correlated with soybean seed oil content. The variation in its promoter and coding sequence leads to different natural alleles of this gene. The GmSWEET39 allelic effects on total oil content were confirmed in the seeds of soybean recombinant inbred lines, transgenic Arabidopsis, and transgenic soybean hairy roots. The frequencies of its superior alleles increased from wild soybean to cultivated soybean, and are much higher in released soybean cultivars. The findings herein suggest that the sequence variation in GmSWEET39 affects its relative expression and oil content in soybean seeds, and GmSWEET39 has been selected to increase seed oil content during soybean domestication and improvement.

Soybean is one of the most important oil crops in the world. Revealing the molecular basis and exploring key candidate genes for seed oil synthesis has great significance for soybean improvement. In this study, we found that oil accumulation rates and gene expression levels changed dynamically during soybean seed development. The expression levels of genes in metabolic pathways such as carbon fixation, photosynthesis, glycolysis, and fatty acid biosynthesis were significantly up-regulated during the rapid accumulation of oil in developing soybean seeds. Through weighted correlation network analysis, we identified six co-expression modules associated with soybean seed oil content and the pink module was the most positively correlated (r = 0.83, p = 7 × 10⁻⁴) network. Through the integration of differential expression and co-expression analysis, we predicted 124 candidate genes potentially affecting soybean seed oil content, including seven genes in lipid metabolism pathway, two genes involved in glycolysis, one gene in sucrose metabolism, and 12 genes belonged to transcription factors as well as other categories. Among these, three genes (GmABI3b, GmNFYA and GmFAD2-1B) have been shown to control oil and fatty acid content in soybean seeds, and other newly identified candidate genes would broaden our knowledge to understand the molecular basis for oil accumulation in soybean seeds.

Following recent developments and refinement, CRISPR-Cas9 gene-editing technology has become increasingly mature and is being widely used for crop improvement. The application of CRISPR/Cas9 enables the generation of transgene-free genome-edited plants in a short period and has the advantages of simplicity, high efficiency, high specificity, and low production costs, which greatly facilitate the study of gene functions. In plant molecular breeding, the gene-editing efficiency of the CRISPR-Cas9 system has proven to be a key step in influencing the effectiveness of molecular breeding, with improvements in gene-editing efficiency recently becoming a focus of reported scientific research. This review details strategies and methods for improving the efficiency of CRISPR/Cas9 gene editing in plant molecular breeding, including Cas9 variant enzyme engineering, the effect of multiple promoter driven Cas9, and gRNA efficient optimization and expression strategies. It also briefly introduces the optimization strategies of the CRISPR/Cas12a system and the application of BE and PE precision editing. These strategies are beneficial for the further development and optimization of gene editing systems in the field of plant molecular breeding.

Aluminum (Al) toxicity is a major factor limiting crop productivity on acid soils. Soybean (Glycine max) is an important oil crop and there is great variation in Al tolerance in soybean germplasms. However, only a few Al-tolerance genes have been reported in soybean. Therefore, the purpose of this study was to identify candidate Al tolerance genes by comparative transcriptome analysis of two contrasting soybean varieties in response to Al stress. Two soybean varieties, M90-24 (M) and Pella (P), which showed significant difference in Al tolerance, were used for RNA-seq analysis. We identified a total of 354 Al-tolerance related genes, which showed up-regulated expression by Al in the Al-tolerant soybean variety M and higher transcript levels in M than P under Al stress. These genes were enriched in the Gene Ontology (GO) terms of cellular glucan metabolic process and regulation of transcription. Five out of 11 genes in the enriched GO term of cellular glucan metabolic process encode cellulose synthases, and one cellulose synthase gene (Glyma.02G205800) was identified as the key hub gene by co-expression network analysis. Furthermore, treatment of soybean roots with a cellulose biosynthesis inhibitor decreased the Al tolerance, indicating an important role of cellulose production in soybean tolerance to Al toxicity. This study provides a list of candidate genes for further investigation on Al tolerance mechanisms in soybean.

Genetic transformation plays a vital role in gene functional study and molecular breeding of soybean. Conventional soybean transformation methods using chemical selectable markers, such as antibiotic or herbicide resistance genes, rely on the identification of positive transgenic lines at advanced developmental stages, making selection procedure labor intensive and time consuming. Utilization of a visual maker to track the transgene would avoid the uncertainty and blindness in the transformation process. In this research, we used green fluorescent protein (GFP) as the selectable marker to detect transgenics at early stages of soybean development. Positive transformants were detected recurrently during each stage of the process based on visualization of the green fluorescence signal, which help us to discard the non-transgenic ones in each stage to reduce the unnecessary experimental cost and lab space. In addition, the positive transgenic seeds can be identified before planting for early detection of transgene and obtain homozygous lines in advance. The method established in this study is also a useful reference for other plant species.