Betula platyphylla is a common tree species in northern China that has high economic and medicinal value. Our laboratory has been devoted to genome research on B. platyphylla for approximately 10 years. As primary organelle genomes, the complete genome sequences of chloroplasts are important to study the divergence of species, RNA editing and phylogeny. In this study, we sequenced and analyzed the complete chloroplast (cp) genome sequence of B. platyphylla. The complete cp genome of B. platyphylla was 160,518 bp in length, which included a pair of inverted repeats (IRs) of 26,056 bp that separated a large single copy (LSC) region of 89,397 bp and a small single copy (SSC) region of 19,009 bp. The annotation contained a total of 129 genes, including 84 protein-coding genes, 37 tRNA genes and 8 rRNA genes. There were 3 genes using alternative initiation codons. Comparative genomics showed that the sequence of the Fagales species cp genome was relatively conserved, but there were still some high variation regions that could be used as molecular markers. The IR expansion event of B. platyphylla resulted in larger cp genomes and rps19 pseudogene formation. The simple sequence repeat (SSR) analysis showed that there were 105 SSRs in the cp genome of B. platyphylla. RNA editing sites recognition indicated that at least 80 RNA editing events occurred in the cp genome. Most of the substitutions were C to U, while a small proportion of them were not. In particular, three editing loci on the rRNA were converted to more than two other bases that had never been reported. For synonymous conversion, most of them increased the relative synonymous codon usage (RSCU) value of the codons. The phylogenetic analysis suggested that B. platyphylla had a closer evolutionary relationship with B. pendula than B. nana. In this study, we not only obtained and annotated the complete cp genome sequence of B. platyphylla, but we also identified new RNA editing sites and predicted the phylogenetic relationships among Fagales species. These findings will facilitate genomic, genetic engineering and phylogenetic studies of this important species.

Cancer is still a severe health problem globally. The therapy of cancer traditionally involves the use of radiotherapy or anticancer drugs to kill cancer cells, but these methods are quite expensive and have side effects, which will cause great harm to patients. With the find of anticancer peptides (ACPs), significant progress has been achieved in the therapy of tumors. Therefore, it is invaluable to accurately identify anticancer peptides. Although biochemical experiments can solve this work, this method is expensive and time-consuming. To promote the application of anticancer peptides in cancer therapy, machine learning can be used to recognize anticancer peptides by extracting the feature vectors of anticancer peptides. Nevertheless, poor performance usually be found in training the machine learning model to utilizing high-dimensional features in practice. In order to solve the above job, this paper put forward a 19-dimensional feature model based on anticancer peptide sequences, which has lower dimensionality and better performance than some existing methods. In addition, this paper also separated a model with a low number of dimensions and acceptable performance. The few features identified in this study may represent the important features of anticancer peptides.

Background: Soybean (Glycine max), a vital grain and oilseed crop, serves as a primary source of plant protein and oil. Soil salinization poses a significant threat to soybean planting, highlighting the urgency to improve soybean resilience and adaptability to saline stress. Melatonin, recently identified as a key plant growth regulator, plays crucial roles in plant growth, development, and responses to environmental stress. However, the potential of melatonin to mitigate alkali stress in soybeans and the underlying mechanisms remain unclear. Results: This study investigated the effects of exogenous melatonin on the soybean cultivar Zhonghuang 13 under alkaline stress. We employed physiological, biochemical, transcriptomic, and metabolomic analyses throughout both vegetative and pod-filling growth stages. Our findings demonstrate that melatonin significantly counteracts the detrimental effects of alkaline stress on soybean plants, promoting plant growth, photosynthesis, and antioxidant capacity. Transcriptomic analysis during both growth stages under alkaline stress, with and without melatonin treatment, identified 2,834 and 549 differentially expressed genes, respectively. These genes may play a vital role in regulating plant adaptation to abiotic stress. Notably, analysis of phytohormone biosynthesis pathways revealed altered expression of key genes, particularly in the ARF (auxin response factor), AUX/IAA (auxin/indole-3-acetic acid), and GH3 (Gretchen Hagen 3) families, during the early stress response. Metabolomic analysis during the pod-filling stage identified highly expressed metabolites responding to melatonin application, such as uteolin-7-O-(2''-O-rhamnosyl)rutinoside and Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside, which helped alleviate the damage caused by alkali stress. Furthermore, we identified 183 differentially expressed transcription factors, potentially playing a critical role in regulating plant adaptation to abiotic stress. Among these, the gene SoyZH13_04G073701 is particularly noteworthy as it regulates the key differentially expressed metabolite, the terpene metabolite Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside. WGCNA analysis identified this gene (SoyZH13_04G073701) as a hub gene, positively regulating the crucial differentially expressed metabolite of terpenoids, Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside. Our findings provide novel insights into how exogenous melatonin alleviates alkali stress in soybeans at different reproductive stages. Conclusions: Integrating transcriptomic and metabolomic approaches, our study elucidates the mechanisms by which exogenous melatonin ameliorates the inhibitory effects of alkaline stress on soybean growth and development. This occurs through modulation of biosynthesis pathways for key compounds, including terpenes, flavonoids, and phenolics. Our findings provide initial mechanistic insights into how melatonin mitigates alkaline stress in soybeans, offering a foundation for molecular breeding strategies to enhance salt-alkali tolerance in this crop.

Soybean (Glycine max (L.) Merr.) is an important oilseed crop, known for its rich nutritional content and high-quality protein. To address the shortage of feed protein resources and better utilize soybeans as a raw material, this study investigated the feasibility of using whole-plant soybean (WPS) as silage. As the ensiling period is a critical fermentation parameter, identifying the optimal fermentation duration was a key objective. The research involves fermenting WPS for silage production, conducted over five fermentation durations: 7, 15, 30, 60, and 90 days. The fermentation quality, microbial community, and metabolome of WPS silage were analyzed across these different time points. WPS silage fermented for 30 days exhibited optimal fermentation characteristics, with the highest lactic acid (LA) content observed at 30 days (p < 0.05), while butyric acid (BA) was detected only at 60 and 90 days. At 30 days, Enterococcus genera reached its peak relative abundance and was identified as the dominant genus. Random forest analysis highlighted Pantoea genera as the most influential biomarker. Metabolomic analysis revealed that the metabolic pathways involved in the biosynthesis of essential amino acids valine, leucine, and isoleucine were significantly enhanced during the later stages of fermentation compared to the earlier stages. Under natural fermentation conditions, the optimal fermentation period for WPS silage is approximately 30 days. These findings provide a theoretical basis for the utilization of WPS and the subsequent optimization of fermentation quality.

Lipoxygenases (LOXs; EC1.13.11.12) are a family of iron- or manganese-containing dioxygenases that catalyze the oxygenation of polyunsaturated fatty acids (PUFAs) and play important roles in plant growth, development, and stress response. In this study, a total of 36 LOX gene family members were identified and annotated in Zhonghuang 13, a soybean cultivar bred by Chinese scientists in 2001. Sanger sequencing of the GmLOX1-coding sequence and colorimetric assays for the GmLOX1 protein showed that Zhonghuang 13 possessed the GmLOX1 gene. These LOX genes are divided into three subfamilies: 9-LOX, type Ⅰ 13-LOX and type II 13-LOX. In the 13-LOX group, the number of GmLOX members was the highest. These GmLOX genes are unevenly distributed on chromosomes 3, 7, 8, 10, 11, 12, 13, 15, 16, 19, and 20. Most of the 13-LOX genes exist in the form of gene clusters, indicating that these genes may originate from tandem duplications. The analysis of duplicated gene pairs showed that GmLOX genes underwent purifying selective pressure during evolution. The gene structures and conserved functional domains of these genes are quite similar. Compared to the orthologous gene pairs of LOX genes between wild soybean (Glycine soja W05) and Zhonghuang 13, the sequences of most gene pairs are relatively conserved. Many cis-elements are present in the promoter region and are involved in stress response, growth and development, hormone response and light response. The tissue-specific gene expression of GmLOX genes was evaluated. Represented by GmLOX1, GmLOX2, and GmLOX3, which were expressed at extremely high levels in seeds, they showed the characteristics of specific expression. This study provides detailed information on soybean lipoxygenase gene family members in Zhonghuang 13, which lays a foundation for further research.

Soybean (Glycine max Merr.), with a high nutritional value, is an important oil crop and a good protein feed crop. Due to the shortage of high-protein feed and the high import pressure on soybean, scarce high-protein feed is the main research target for improving feed quality. High-quality soybean (Qihuang 34) and high-yield silage maize (Zea mays L.) (Jingling silage 386) varieties were used as the experimental materials in this study. The silage quality and the microbial community of the mixed silage of soybean and maize were analyzed, and the compatible intercropping ratios of maize–soybean mixed silage were evaluated. This experiment designed five strip intercropping systems (SIS) in a randomized block. The intercropping row ratios of maize and soybean were 0:1 (pure soybean, S), 1:0 (pure maize, M), 1:1 (MS1), 1:3 (MS2), and 1:5 (MS3). Dry matter yield and fresh matter yield were improved in the treatments of MS1 and MS2. In the mixed silage systems of maize and soybean, with an increase in soybean proportion, crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF) contents gradually increased, but the contents of water-soluble carbohydrates (WSC) and dry matter (DM) reduced to different degrees (p < 0.05). Moreover, the soybean silage alone had a poor fermentation performance, as indicated by high pH, high acetic acid (AA), propionic acid (PA), butyric acid (BA), and ammonia-N (NH₃-N) concentrations, and low lactic acid (LA) concentration. By contrast, the mixed silage materials were conducive to reducing the pH, PA, BA, and NH₃-N, and increasing the LA content. The relative abundance of Lactobacillus and Weissella in the MS were higher, and the abundance of undesirable bacteria were lower than in the S. The MS2 materials had the lowest pH, the highest LA concentration, and the highest relative abundance of Lactobacillus and Weissella among the three mixed silage groups. Therefore, the mixed silage in the SIS modified the microbial communities and improved the feed fermentation quality while increasing yields. The better intercropping ratio of maize–soybean mixed silage was 1:3. These results could provide a theoretical basis for the wide application and popularization of soybean as a high-protein silage forage source.