Agriculture Communications最新文献

Here, we unravel the transcriptional mechanisms that govern porcine muscle myogenesis, a crucial aspect of pork production. Through single cell RNA-sequencing of longissimus dorsi (LD) muscle from 3-day-old piglets, we delineated 5 major cell types from 14,002 cells—muscle cells, fibro-adipogenic progenitors, mural cells, endothelial cells, and immune cells. Within the muscle cell clusters, we specifically identified muscle satellite cells and myoblasts, with 5,388 differentially expressed genes distinguishing the cell populations. Furthermore, our investigation led to the identification of novel cell surface markers for porcine muscle satellite cells, namely ITGA7, SDC2, and SDC4. In addition, we found 55 transcription factors, including AHCTF1, CEBPD, and MAX, which contribute to the regulation of muscle development. Through predictive receptor–ligand analysis, we uncovered 16 secretory factors with associated cellular communication channels influencing porcine skeletal muscle development. Notably, we identified the secretory factor ANGPTL4 as an inhibitor of porcine muscle satellite cell proliferation and differentiation, and confirmed its function through the in vitro treatment of cell lines. We propose that ANGTPL4 is a potential target for the treatment of myopathy. Taken together, our findings contribute to the identification and characterization of myogenic genes and regulatory networks, which enhances our understanding of porcine muscle satellite cell myogenesis and offers potential avenues for optimizing pork production.

Postharvest diseases in lily plants are prevalent during storage and transportation, leading to potentially catastrophic economic losses for the lily industry. Specifically, bulb rot has been observed in Lanzhou lily (Lilium davidii var. unicolor) during cold storage in Beijing, China. In this study, fungal isolates were obtained from decayed bulbs using a conventional fungal separation method, and these isolates were confirmed to be the causative agent of lily bulb rot, according to Koch postulates. A representative isolate, LZ-3-10, was selected for further identification. Based on morphological features and internal transcribed spacer sequencing results, the LZ-3-10 isolate was identified as Rhizopus arrhizus. Subsequently, an endophytic bacterial strain exhibiting robust antagonistic ability, Bacillus siamensis B55, was screened from the roots of lily plants. Evaluation of its biocontrol ability revealed that strain B55 could effectively protect L. davidii var. unicolor bulbs from infection by LZ-3-10, demonstrating a biocontrol efficacy of 51.2 ​% and significantly reducing the severity of lily Rhizopus rot. In summary, this study identifies R. arrhizus as the cause of postharvest bulb rot in L. davidii var. unicolor and, for the first time, showcases the biocontrol activity of the endophytic bacterial strain B. siamensis B55 against the isolated pathogenic fungus. These findings not only provide insights into lily bulb rot but also highlight the potential of B. siamensis B55 as a biocontrol agent for managing this disease during postharvest storage.

A novel lignin-based humic acid liquid fertilizer (LHF) was prepared by supplementing traditional humic acid fertilizer with lignin. The impact of LHF treatments in two distinct red soils was assessed through examination of soil nutrient content, enzyme activity, microbial abundance, and banana biomass. Compared to the conventional composite liquid fertilizer (CF) treatment, LHF treatment improved soil nutrients, including ammonium nitrogen, nitrate nitrogen, available nitrogen, available phosphorus, and organic matter. These improvements correlated with shifts in enzymatic activities and increases in microbial populations. The LHF treatments significantly promoted nutrient uptake in banana seedlings, and consequently, accelerated growth. This system allowed for precise determination of correlations between soil physicochemical properties and soil microorganisms, increasing our fundamental understanding of the impact of soil fertilization on microbial communities. The integration of lignin into liquid fertilizers represents a step forward in the research and development of high-efficiency fertilizers. Through the improvement of soil fertility and nutrient uptake, lignin application has the potential to significantly contribute to the advancement of sustainable agriculture.

We used peptide profiling to investigate the effects of different forms of κ-carrageenan (a typical hydrocolloid) on the in vitro gastrointestinal digestibility of frankfurters. All incorporated forms of κ-carrageenan were found to decrease the digestibility of meat proteins in the frankfurters, although the effects varied for some peptide fragments. Particle size analysis and super-resolution microscopy revealed that addition of κ-carrageenan in a water suspension resulted in the lowest protein digestibility for frankfurters, followed by κ-carrageenan in a powder form and in a brine suspension. Peptide profiling identified 63 peptides common to all frankfurters after gastrointestinal digestion. In addition, 9 new peptide fragments related to myofibrillar proteins and sarcoplasmic proteins were observed in digestion products from frankfurters that contained κ-carrageenan. Addition of the κ-carrageenan water suspension resulted in a unique pattern of peptide abundance after gastrointestinal digestion of the frankfurters. This pattern was not observed with the powder or brine suspension, both of which contained higher abundances of myosin peptides. However, it is still unclear how different forms of κ-carrageenan caused changes in specific digestion sites, and further investigation is needed to understand this phenomenon. These findings provide novel insights into the effects of various forms of κ-carrageenan on the digestibility of meat proteins in emulsified meat products.

Improving the robustness of fish stock has become a key issue in the advancement of aquaculture, as diseases and harsh aquatic conditions impact industry sustainability and yield. In this study, we identify several genetic loci that link swimming performance to disease resistance in large yellow croaker, and apply genomic selection (GS) for swimming performance to generate offspring with both enhanced swimming performance and disease resistance. First, we classified our reference population as superior swimmers (SS) or inferior swimmers (IS) by swimming tests and assessed inherent disease resistance. Consistent with previous research, SS displayed enhanced resistance to the parasite Cryptocaryon irritans. Through genotyping of parental reference and candidate populations, we generated a single nucleotide polymorphism (SNP) database, containing 45832 high-quality SNPs in total. We applied multitrait genome-wide association study analysis of swimming performance and disease resistance to this dataset and identified three linked SNPs, which were associated with 48 potential candidate genes, including pp3r1b, mapk12b, mapk11, and tnfrsf11a. Next, we generated a GS model using the BayesB method and calculated the candidate population's genetic estimated breeding value (GEBV). Individuals with GEBV's in the top 12 ​% were selected as broodstocks for breeding selective lines (SL), and the remaining individuals were used as the control group (CG). We found that SL exhibited both increased swimming performance and resistance to C. irritans compared to CG. Our study reveals the genetic basis related to swimming performance and disease resistance. This work has implications for designing multitrait breeding strategies and improving whole-fish fitness, both of which are critical in aquaculture.

Insulin-like growth factor 3 (IGF3) plays an essential role in the reproductive system and influences the liver of teleosts. However, the mechanism of IGF3 action on the liver remains unknown. In this study, we analyzed the transcriptome patterns and enzymatic activities in the liver of Scatophagus argus following IGF3 injection. We identified 155 differentially expressed genes (DEGs), which were enriched in terms ‘retinol metabolism’, ‘steroid hormone biosynthesis’, ‘epidermal growth factor receptor tyrosine kinase inhibitor resistance’, and ‘one carbon pool by folate’ in Kyoto Encyclopedia of Genes and Genomes pathway analysis. Notable DEGs included inhbb, shmt2, slc2a5, cyp1a1, got1, mid1ip1, sstr5, hnf6, slc39a14, and hspa1a. The activities of amylase, lipase, malic enzyme, fatty acid synthase, and lipoprotein lipase increased significantly, whereas those of phospholipid hydroperoxide glutathione peroxidase and pyruvate kinase decreased significantly. The combined analysis of transcriptome patterns and enzyme activities suggests IGF3 may promote energy storage and protein synthesis by the liver. These findings indicate IGF3 may support the liver to promote ovarian development and maturation in S. argus.

One of the main factors affecting meat quality is the feeding regimen, which impacts muscle growth, fat accumulation, and fatty acid composition. This study characterized the lipid and metabolite profiles in Tan lamb using lipidomics and metabolomics to investigate the influence of standardized feeding and conventional grazing regimens on meat quality. We identified 813 lipids across five categories and 86 metabolites, including peptides, amino acids, carnitines, and nucleosides in Tan lamb. The standardized feeding regimen yielded fewer saturated fatty acids (SFAs), an increased n-6 polyunsaturated fatty acid (PUFA) content, and a higher PUFA/SFA ratio than the conventional grazing regimen. In addition, this regimen elevated the levels of bioactive peptides, vitamin B2 cofactors, and nucleosides. Analysis of purine metabolism and aminoacyl-tRNA biosynthesis revealed improved flavor and increased protein synthesis under the standardized feeding regimen. Therefore, the standardized feeding regimen enhances nutritional value and improves lamb flavor, making it suitable for Tan sheep feeding.

MicroRNA (miRNA) is an important regulator of gene expression in plants that functions to regulate plant development and growth. Signature sequences and secondary structures that are formed as a result of RNA processing during miRNA biogenesis can be used to identify unique miRNAs and has led to the development of multiple bioinformatic tools for miRNA prediction. Artificial intelligence (AI), particularly machine learning (ML), has enabled significant progress to be made in various tasks such as image recognition, regulatory element identification in genomes, and gene expression prediction. AI-based tools have also been used to predict plant miRNAs and are as accurate as pattern-based tools. In this review, we focus on the use of AI to predict plant miRNAs. We demonstrate how to establish a predictive ML model to predict miRNAs and describe the potential pitfalls at each step. We then introduce tools based on ML that have been published and systematically assess their performance. Finally, we discuss how new AI tools should be developed for plant miRNA researchers.