Bacillus velezensis is well known as a plant growth-promoting rhizobacteria (PGPR) and biocontrol agent. Nevertheless, there are very few reports on the study of B. velezensis on tomato early blight, especially the biocontrol effects among different inoculation concentrations. In this study, an IAA-producing strain, Bacillus velezensis YXDHD1-7 was isolated from the tomato rhizosphere soil, which had the strongest inhibitory effect against Alternaria solani. Inoculation with bacterial suspensions of this strain promoted the growth of tomato seedlings effectively. Furthermore, inoculations at 10⁶, 10⁷, and 10⁸ cfu/mL resulted in control efficacies of 100%, 83.15%, and 69.90%, respectively. Genome sequencing showed that it possesses 22 gene clusters associated with the synthesis of antimicrobial metabolites and genes that are involved in the production of IAA. Furthermore, it may be able to produce spermidine and volatile compounds that also enhance plant growth and defense responses. Our results suggest that strain YXDHD1-7 prevents early blight disease by promoting growth and enhancing the defense enzyme activities in tomato plants. This strain is a promising candidate for an excellent microbial inoculant that can be used to enhance tomato production.

Paddy fields are the main agricultural source of greenhouse gas methane (CH₄) emissions. To enhance rice yield, various fertilization practices have been employed in rice paddies. However, the key microbial and abiotic factors driving CH₄ emissions under different fertilization practices in paddy fields remain largely uncharted. This study conducted field experiments in a traditional double-cropping rice area in South China, utilizing five different fertilization practices to investigate the key factors influencing CH₄ emissions. High-throughput sequencing and PICRUSt2 functional prediction were employed to investigate the contributions of soil physicochemical properties, CH₄-metabolizing microorganisms (methanogens and methanotrophs), and key genes (mcrA and pmoA) on CH₄ emissions. The results showed that CH₄ emission fluxes exhibited seasonal variations, with consistent patterns of change observed across all treatments for both early- and late-season rice. Compared to the no-fertilization (NF) treatment, cumulative CH₄ emissions were lower in early-season rice with green manure (GM) and straw returning (SR) treatments, as well as in late-season rice with GM treatment, while rice yields were maintained at higher levels. High-throughput sequencing analysis revealed that potential methanogens were primarily distributed among four orders: Methanobacteriales, Methanocellales, Methanomicrobiales, and Methanosarcinales. Furthermore, there was a significant positive correlation between the relative abundance of the CH₄-related key gene mcrA and these microorganisms. Functional analysis indicated that these potential methanogens primarily produce methane through the acetoclastic and hydrogenotrophic pathways. Aerobic CH₄-oxidizing bacteria, predominantly from the genus Methylocystis, were detected in all the treatments, while the CH₄ anaerobic-oxidizing archaea ANME-1b was only detected in chemical fertilization (CF) and cow manure (CM) treatments. Our random forest analysis revealed that the relative abundance of two methanogens (Methanocellales and Methanosarcinales) and two environmental factors (pH and DOC) had significant impacts on the cumulative CH₄ emissions. The variance decomposition analysis highlighted the CH₄-metabolizing microorganisms explained 50% of the variance in the cumulative CH₄ emissions, suggesting that they are the key microbial factors driving CH₄ emissions. These findings provide guidance for the development of rational measures to reduce CH₄ emissions in paddy fields.

Neocinnamomum caudatum (Nees) Merr. is an underutilized woody oil plant with seeds rich in long-chain fatty acids and polyunsaturated fatty acids. Reliable quantitative real-time PCR (RT-qPCR) analysis is essential for investigating the molecular mechanisms underlying seed oil biosynthesis, but suitable reference genes have not yet been validated in this species. Here, seven candidate reference genes, namely EF-1α, ACT2, ACT11, UBQ11, TUA, F-BOX, and GAPDH, were selected from transcriptomic data and evaluated in leaves, flowers, and developing seeds of N. caudatum. Their expression stability was assessed using geNorm, NormFinder, and BestKeeper, followed by comprehensive ranking with RankAggreg. Among all tested samples (leaves, flowers and developing seeds combined), GAPDH was identified as the most stable reference gene, whereas EF-1α was the least stable. For developing seeds alone, TUA showed the highest stability, while EF-1α exhibited poor stability. In leaf and flower samples, ACT11 was the most stable gene, whereas TUA was unsuitable for normalization. The expression patterns of NcFAD2 and NcFatB, two genes involved in fatty acid biosynthesis, were used to validate the selected reference genes. Stable reference genes and the optimized multi-gene combination generated consistent expression profiles, while unstable reference genes caused evident distortion. This study provides the first systematic evaluation of reference genes for qRT-PCR analysis in N. caudatum and offers a practical foundation for future functional studies of lipid metabolism in this woody oil plant.

Global warming has led to frequent occurrences of extreme heat, posing a huge threat to soybean (Glycine max L.) yield. As a major source of plant protein and oil, soybean is particularly sensitive to heat stress during its growth and development, especially in critical stages such as flowering and seed filling. Heat tolerance in crops is a complex trait governed by polygenic networks and environmental interactions; although existing studies have identified several heat-tolerance-related genes, the molecular regulatory networks regulating crop responses to heat stress remain elusive. This review synthesizes recent advances in soybean heat tolerance research, with a particular emphasis on physiological responses and molecular regulatory mechanisms under heat stress. We further evaluate the potential of modern technologies, including gene editing, marker-assisted selection, and pan-genomics, for the precise improvement of heat tolerance in soybean. Additionally, we outline sustainable agronomic practices and field management strategies to mitigate heat stress. The development of heat-tolerant soybean varieties depends not only on the identification of superior alleles but also requires a shift from gene-centric genetic improvement toward a system-wide solution that integrates “Genotype × Environment × Management”.

Perilla frutescens is a specialty oilseed crop rich in polyunsaturated fatty acids, particularly α-linolenic acid (ALA), and the molecular regulation of seed lipid metabolism is an active area of research. Reverse-transcription quantitative PCR (RT-qPCR) is essential for investigating the molecular mechanisms underlying seed oil biosynthesis; however, systematically validated reference genes are lacking for this species. Based on P. frutescens transcriptome data, seven commonly used housekeeping genes—PfActin, Pf18S (18S pre-ribosomal assembly protein GAR2-like), PfEF-1α, PfCYP, PfTUA, PfTUB, and PfGAPDH—were initially selected. After PfGAPDH was excluded because of its extremely low abundance and unstable expression, the remaining six candidates were evaluated in vegetative organs (leaves, stems, and roots), seeds at different developmental stages, and leaves subjected to PEG 6000 treatment. Expression stability was independently assessed using geNorm, NormFinder, and BestKeeper, and the resulting stability values were integrated with RefFinder. Pf18S showed the highest overall stability in the complete sample set and developing seeds. Under osmotic stress, PfTUB was the most stable single reference gene, and geNorm identified PfTUB + Pf18S as the optimal two-gene combination. In vegetative organs, PfTUB ranked first and PfTUA second, whereas PfEF-1α was among the least stable genes in most sample sets. The recommended two-gene combinations were PfTUA + PfTUB for vegetative organs, Pf18S + PfTUA for developing seeds, and PfTUB + Pf18S for osmotic stress. Biological validation showed that normalization to Pf18S reproduced spatiotemporal expression patterns of six key lipid-biosynthesis genes that were consistent with the dynamic accumulation of total seed oil and ALA. These results support a tiered normalization strategy using Pf18S for preliminary screening and condition-specific reference-gene pairs for precise quantification.

Cotton is a globally vital economic crop and the primary source of natural fiber. Continued world population growth keeps driving demand for cotton lint, while the increasing frequency of extreme weather events exposes cotton production to a range of abiotic stresses, including salinity, drought, and temperature extremes. As the very first step in plant development, the germination phase is particularly vulnerable to these stresses, which severely impair seed germination and seedling establishment through multi-faceted physiological and metabolic disruptions, ultimately compromising crop uniformity and yield potential. A thorough understanding of the underlying tolerance mechanisms holds significant potential for improving cotton germination performance under adverse conditions. However, the precise functions of stress-responsive genes and their regulatory networks during cotton germination remain largely unresolved, which restricts the targeted genetic improvement of stress resilience in breeding programs. Here we systematically review the impacts of these stresses on cotton germination and the morphological, physiological, and molecular pathways underlying stress tolerance, together with current mitigation strategies. Future research should integrate multi-omics technologies, real-time phenotyping, and controlled-environment simulations to elucidate the signal–transcription–metabolism–phenotype regulatory pathways operative during germination, thereby providing a theoretical basis for breeding stress-resilient cotton cultivars and optimizing precision sowing technologies.