Regulatory Elements Research Articles

High-resolution snapshots of the talin auto-inhibitory states suggest roles in cell adhesion and signaling

Talin regulates crucial cellular functions, including cell adhesion and motility, and affects human diseases. Triggered by mechanical forces, talin plays crucial roles in facilitating the formation of focal adhesions and recruiting essential focal adhesion regulatory elements such as vinculin. The structural flexibility allows talin to fine-tune its signaling responses. This study presents our 2.7 Å cryoEM structures of talin, which surprisingly uncovers several auto-inhibitory states. Contrary to previous suggestions, our structures reveal that (1) the first and last three domains are not involved in maintaining talin in its closed state and are mobile, (2) the talin F-actin and membrane binding domain are loosely attached and thus available for binding, and (3) the main force-sensing domain is oriented with its vinculin binding sites ready for release. These structural snapshots offer insights and advancements in understanding the dynamic talin activation mechanism, which is crucial for mediating cell adhesion.

Big data and artificial intelligence-aided crop breeding: Progress and prospects.

The past decade has witnessed rapid developments in gene discovery, biological big data (BBD), artificial intelligence (AI)-aided technologies, and molecular breeding. These advancements are expected to accelerate crop breeding under the pressure of increasing demands for food. Here, we first summarize current breeding methods and discuss the need for new ways to support breeding efforts. Then, we review how to combine BBD and AI technologies for genetic dissection, exploring functional genes, predicting regulatory elements and functional domains, and phenotypic prediction. Finally, we propose the concept of intelligent precision design breeding (IPDB) driven by AI technology and offer ideas about how to implement IPDB. We hope that IPDB will enhance the predictability, efficiency, and cost of crop breeding compared with current technologies. As an example of IPDB, we explore the possibilities offered by CropGPT, which combines biological techniques, bioinformatics, and breeding art from breeders, and presents an open, shareable, and cooperative breeding system. IPDB provides integrated services and communication platforms for biologists, bioinformatics experts, germplasm resource specialists, breeders, dealers, and farmers, and should be well suited for future breeding.

Lignin valorization to bioplastics with an aromatic hub metabolite-based autoregulation system

Exploring microorganisms with downstream synthetic advantages in lignin valorization is an effective strategy to increase target product diversity and yield. This study ingeniously engineers the non-lignin-degrading bacterium Ralstonia eutropha H16 (also known as Cupriavidus necator H16) to convert lignin, a typically underutilized by-product of biorefinery, into valuable bioplastic polyhydroxybutyrate (PHB). The aromatic metabolism capacities of R. eutropha H16 for different lignin-derived aromatics (LDAs) are systematically characterized and complemented by integrating robust functional modules including O-demethylation, aromatic aldehyde metabolism and the mitigation of by-product inhibition. A pivotal discovery is the regulatory element PcaQ, which is highly responsive to the aromatic hub metabolite protocatechuic acid during lignin degradation. Based on the computer-aided design of PcaQ, we develop a hub metabolite-based autoregulation (HMA) system. This system can control the functional genes expression in response to heterologous LDAs and enhance metabolism efficiency. Multi-module genome integration and directed evolution further fortify the strain’s stability and lignin conversion capacities, leading to PHB production titer of 2.38 g/L using heterologous LDAs as sole carbon source. This work not only marks a leap in bioplastic production from lignin components but also provides a strategy to redesign the non-LDAs-degrading microbes for efficient lignin valorization.

Oryza sativa Stress Associated Protein (OsSAP) Promoter Modulates Gene Expression in Response To Abiotic Stress by Utilizing Cis Regulatory Elements Within The Promoter Region

The occurrence of extreme weather patterns induced by climate change has resulted in abiotic stress problems impacting the growth and productivity of plants. Rice (Oryza sativa), a staple food source for most Asians, is similarly affected by these challenges. Previous studies have identified the Oryza sativa Stress Associated Protein (OsSAP) genes to play a significant role in responding to abiotic stress. Among the 18 Stress Associated Protein members, OsSAP4 was highly expressed during drought and salinity conditions. Therefore, further experiments have been conducted, focusing specifically on the promoter region, to comprehend its regulation in response to abiotic stresses. Various types of cis-elements binding sites have been identified within the OsSAP4 promoter, encompassing MYB, CAMTA, CPP, C3H, HDZIP, bZIP, WRKY, and ERF. However, promoter analysis revealed that the distribution of the Cis-Regulatory elements bound by the Ethylene Response Factor (ERF) was the most prominent in the OsSAP4 promoter. Consequently, an analysis of promoter regulation was conducted using GUS reporter in Arabidopsis thaliana (A. thaliana) on two different sizes of OsSAP4 promoter sequences, each containing different quantities of ERF transcription factor binding sites. A noticeable difference in GUS staining activity was observed between pOsSAP4(1524 pb)::GUS and pOsSAP4(460 pb)::GUS, where pOsSAP4(1524 pb)::GUS exhibited higher GUS staining activity than pOsSAP4(460 pb)::GUS. The differences in GUS staining analysis are evident at the vegetative stage (leaf), silique, and inflorescence stages. This implies the participation of various other cis-element binding sites that influence the expression pattern of the OsSAP4 promoter during abiotic stress.

Novel Fosfomycin Resistance Mechanism in Pseudomonas entomophila Due to Atypical Pho Regulon Control of GlpT

Background/Objectives: Pseudomonas entomophila is a ubiquitous bacterium capable of killing insects of different orders and has become a model for host–pathogen studies and a promising tool for biological pest control. In the human pathogen Pseudomonas aeruginosa, spontaneous resistance to fosfomycin arises almost exclusively from mutations in the glycerol-3-phosphate transporter (GlpT), the drug’s sole entry route in this species. Here, we investigated whether this specificity is conserved in P. entomophila, as it could provide a valuable marker system for studying mutation rates and spectra and for selection in genetic engineering. Methods: We isolated 16 independent spontaneous fosfomycin-resistant mutants in P. entomophila, and studied the genetic basis of the resistance using a combination of sequencing, phenotyping and computational approaches. Results: We only found two mutants without alterations in glpT or any of its known regulatory elements. Whole-genome sequencing revealed unique inactivating mutations in phoU, a key regulator of the phosphate starvation (Pho) regulon. Computational analyses identified a PhoB binding site in the glpT promoter, and experiments showed that phoU inactivation reduced glpT expression nearly 20-fold. While placing a sugar-phosphate transporter under the Pho regulon may seem advantageous, bioinformatic analysis shows this configuration is atypical among pseudomonads. Conclusions: this atypical Pho regulon control of GlpT probably reflects the peculiarities of P. entomophila’s habitat and lifestyle; highlighting how readily regulatory evolution can lead to the rapid divergence of resistance mechanisms, even among closely related species.

Deep learning revealed the distribution and evolution patterns for invertible promoters across bacterial lineages.

Invertible promoters (invertons) are crucial regulatory elements in bacteria, facilitating gene expression changes under stress. Despite their importance, their prevalence and the range of regulated gene functions are largely unknown. We introduced DeepInverton, a deep learning model that identifies invertons across a broad phylogenetic spectrum without using sequencing reads. By analyzing 68 733 bacterial genomes and 9382 metagenomes, we have uncovered over 200 000 nonredundant invertons and have also highlighted their abundance in pathogens. Additionally, we identified a post-Cambrian Explosion increase of invertons, paralleling species diversification. Furthermore, we revealed that invertons regulate diverse functions, including antimicrobial resistance and biofilm formation, underscoring their role in environmental adaptation. Notably, the majority of inverton identifications by DeepInverton have been confirmed by the in vitro experiments. The comprehensive inverton profiles have deepened our understanding of invertons at pan-genome and pan-metagenome scales, enabling a broad spectrum of applications in microbial ecology and synthetic biology.

Unveiling miRNA-Gene Regulatory Axes as Promising Biomarkers for Liver Cirrhosis and Hepatocellular Carcinoma.

Liver cirrhosis, a severe scarring condition of the liver with the potential to progress to hepatocellular carcinoma (HCC), necessitates the development of reliable biomarkers for early detection due to the asymptomatic nature of its early stages. Recent discoveries in microRNAs (miRNAs) hold promise for a noninvasive test, with the potential to significantly improve patient outcomes. Building upon these promising findings, this study investigates gene expression data, identifying distinct sets of DEGs and DEMs using GEO2R. Subsequently, a gene-miRNA network was constructed using Cytoscape to explore potential interactions between DEMs and their target genes (DEGs). Boxplot analysis was carried out to identify and validate differences in gene expression between healthy and diseased tissues. This analysis revealed four significantly differentially expressed genes: CAV1, PEA15, EMP1, and ENAH. Notably, subsequent survival analysis demonstrated that EMP1 and ENAH significantly impact overall patient survival. Intriguingly, the constructed network identified several potential regulatory axes: hsa-miR-191-5p/ENAH, hsa-miR-3158-3p/ENAH, hsa-miR-371a-5p/ENAH, and hsa-miR-6753-5p/EMP1. Crucially, a direct comparison of DEGs and DEMs between liver cirrhosis and HCC pinpointed AGO3, NCOA3, and TNPO1, along with their regulatory elements, as potential key drivers of HCC development in cirrhotic patients, underscoring their importance as targets for early diagnostic and therapeutic strategies. Finally, immunohistochemical (IHC) analysis not only validates our findings but also reiterates the novelty of the identified genes. Overall, elucidating the role of these novel genes and regulatory elements could pave the way for an earlier and more accurate diagnosis of liver diseases.

Balancing act: How cholesterol and phospholipids influence juvenile mud crab Scylla paramamosain growth and lipid metabolism

A 2 × 3 two-factor experiment was designed to assess the effects of dietary cholesterol (CHO) and phospholipids (PLs) on growth and lipid metabolism in early juvenile mud crabs (0.01 g crab−1). The experimental diets were designed with two CHO levels: 0.40 % (LCH) and 0.80 % (HCH), and three PLs levels: 1.80 % (LPL), 2.50 % (MPL), and 3.20 % (HPL). The 58-day aquaculture trial demonstrated that the LCH-HPL group achieved the best growth performance in mud crabs, characterized by the highest final body weight, weight gain, and specific growth rate. Regarding whole-body composition, dietary PLs increased total cholesterol (T-CHO), PLs, triglyceride (TG), and crude lipid content in the LCH groups. Mud crabs in the HCH groups had a higher proportion of saturated fatty acids, a lower proportion of monounsaturated fatty acids, and increased gene expression of sterol regulatory element binding protein 1c (srebp-1c) and fatty acid synthase (fas) compared to those in the LCH groups. As the dietary PLs increased, mud crabs in the LCH groups exhibited up-regulation in the expression of genes, including srebp-1c, fas, elongation of very long-chain fatty acid protein 4 (elovl4), elovl6, and Δ9-fatty acid desaturase (Δ9-fad). In the HCH groups, elevated dietary PLs resulted in the down-regulation of fatty acid binding protein (fabp) gene expression. In addition, high levels of dietary CHO and PLs (HCH-HPL) inhibited the catalase activity of mud crabs, resulting in a significant increase in the malondialdehyde content. Correlation analysis revealed that dietary CHO was positively correlated with the expression of long-chain polyunsaturated fatty acids synthesizing genes, and dietary PLs were positively correlated with the whole-body lipid content of mud crabs. Additionally, a positive correlation was found between the growth performance and whole-body content of crude protein, crude lipid, and antioxidant capacity in mud crabs.

New Insights on the potential therapeutic effects of glibenclamide and Obeticholic acid against Alloxan-Induced diabetes mellitus in rat model

Diabetes mellitus (DM) represents a highly prevalent metabolic disorder across the globe. This study aimed to determine the ameliorative efficacy of glibenclamide (Gli) and obeticholic acid (OCA) against biochemical and pathological changes related to alloxan-induced diabetes. Twenty male Wistar rats were allocated into four groups; Control group, Diabetic group: received intraperitoneal injection of alloxan (120 mg/kg) for induction of diabetes, Diabetic + Gli group: Diabetic rats treated daily with oral Gli (5 mg/kg) and Diabetic + OCA group: Diabetic rats treated daily with oral OCA (10 mg/kg). All rats were subjected to 30 days treatments. Our results indicated that Gli successfully ameliorated hyperglycemia and dyslipidemia with a significant decline in serum pancreatic lipase activity and increased insulin level, while OCA had the same effect but without any enhancement in serum insulin levels. Additionally, the disturbances in liver function-related parameters and the evoked oxidative stress, interleukin(IL)-6 and IL-10 in the liver and pancreas were abrogated upon treatment with Gli and OCA. Furthermore, Gli and OCA increased AMP-activated protein kinase (P-AMPK), insulin receptor substrate 1 (IRS1), farnesoid X receptor (FXR), and glucagon-like peptide-1 receptor (GLP-1R) expressions and downregulated sterol regulatory element binding protein-1c mRNA expression. Besides, Gli and OCA have alleviated diabetes-induced histopathological distortions in hepatic and pancreatic tissues and enhanced the immunoexpression of insulin, and proliferating cell nuclear antigen with decreased immune reactivity of glucagon within pancreatic tissues. Gli and OCA decreased the immune reactivity of nuclear factor kappa B and increased the glycogen content of hepatic tissues. In conclusion, OCA is efficacious in the management of dyslipidemia and hyperglycemia of DM and its related oxidative stress.

Genome-Wide Identification and Analysis of Phospholipase C Gene Family Reveals Orthologs, Co-Expression Networks, and Expression Profiling Under Abiotic Stress in Sorghum bicolor.

Phospholipase C (PLC) is an essential enzyme involved in lipid signaling pathways crucial for regulating plant growth and responding to environmental stress. In sorghum, 11 PLC genes have been identified, comprising 6 PI-PLCs and 5 NPCs. Through phylogenetic and interspecies collinearity analyses, structural similarities between SbPLCs and ZmPLCs proteins have been observed, with a particularly strong collinearity between SbPLCs and OsPLCs. Promoter function analysis has shown that SbPLCs are significantly enriched under abiotic stress and hormonal stimuli, like ABA, jasmonic acid, drought, high temperature, and salt. Gene co-expression networks, constructed using a weighted gene co-expression network analysis (WGCNA), highlight distinct expression patterns of SbPLC1, SbPLC3a, and SbPLC4 in response to abiotic stress, providing further insights into the expression patterns and interactions of SbPLCs under various environmental stimuli. qRT-PCR results reveal variations in expression levels among most SbPLCs members under different stress conditions (drought, NaCl, NaHCO3), hormone treatments (ABA), and developmental stages, indicating both specific and overlapping expression patterns. This comprehensive analysis offers valuable insights into the roles of SbPLCs in sorghum, shedding light on their specific expression patterns, regulatory elements, and protein interactions across different environmental stimuli and developmental stages.

Chromatin remodelling drives immune cell-fibroblast communication in heart failure.

Chronic inflammation and tissue fibrosis are common responses that worsen organ function, yet the molecular mechanisms governing their cross-talk are poorly understood. In diseased organs, stress-induced gene expression changes fuel maladaptive cell state transitions1 and pathological interaction between cellular compartments. Although chronic fibroblast activation worsens dysfunction in the lungs, liver, kidneys and heart, and exacerbates many cancers2, the stress-sensing mechanisms initiating transcriptional activation of fibroblasts are poorly understood. Here we show that conditional deletion of the transcriptional co-activator Brd4 in infiltrating Cx3cr1+ macrophages ameliorates heart failure in mice and significantly reduces fibroblast activation. Analysis of single-cell chromatin accessibility and BRD4 occupancy in vivo in Cx3cr1+ cells identified a large enhancer proximal to interleukin-1β (IL-1β, encoded by Il1b), and a series of CRISPR-based deletions revealed the precise stress-dependent regulatory element that controls Il1b expression. Secreted IL-1β activated a fibroblast RELA-dependent (also known as p65) enhancer near the transcription factor MEOX1, resulting in a profibrotic response in human cardiac fibroblasts. In vivo, antibody-mediated IL-1β neutralization improved cardiac function and tissue fibrosis in heart failure. Systemic IL-1β inhibition or targeted Il1b deletion in Cx3cr1+ cells prevented stress-induced Meox1 expression and fibroblast activation. The elucidation of BRD4-dependent cross-talk between a specific immune cell subset and fibroblasts through IL-1β reveals how inflammation drives profibrotic cell states and supports strategies that modulate this process in heart disease and other chronic inflammatory disorders featuring tissue remodelling.

Rapid, Sensitive, and Specific Microbial Whole-Cell Biosensor for the Detection of Histamine: A Potential Food Toxin.

Histamine is a biogenic amine; its level indicates food quality, as elevated levels cause food poisoning. Therefore, monitoring food at each step during processing until it reaches the consumer is crucial, but current techniques are complicated and time-consuming. Here, we designed a Pseudomonas putida whole-cell biosensor using a histamine-responsive genetic element expressing a fluorescent protein in the presence of the cognate target. We improved the performance of the proposed biosensor by optimizing the chassis, genetic regulatory element, and reporter gene. A sensitive and rapid biosensor variant was obtained with a limit of detection (LOD) of 0.39 ppm, manifesting a linear response (R2 = 0.98) from 0.28 to 18 ppm in 90 min. The biosensor showed minimal cross-reactivity with other biogenic amines and amino acids prevalent in food, making it highly specific. The biosensor effectively quantified histamine in spiked fish, prawn, and wine samples with a satisfactory recovery. Additionally, a colorimetric sensor variant PAlacZ was developed enabling histamine quantification in seafood via a smartphone application, with an LODgray of 0.23 ppm, exhibiting a linear response from 0 to 2.24 ppm. Overall, this study reports an efficient, specific, and highly sensitive biosensor with strong potential for the on-site detection of histamine, ensuring food safety.

A genome-to-proteome atlas charts natural variants controlling proteome diversity and forecasts their fitness effects.

- Proteome diversity arises from natural genetic variants, with divergent proteomes in closely related parents and progeny. - Cis- regulatory elements had strong individual impacts, but coherent trans effects combined to dominate protein expression. - Directional selection and frequent transgression suggest much of the proteome is under selective pressure. - Many trans -regulators are enzymes or transporters, with fewer than 4% of pQTLs linking known interactors. - Genome-to-proteome connections predicted the fitness impact of mutations under various stresses, including a strong but hidden causal variant in IRA2/ NF1.

Optimization of a novel expression system for recombinant protein production in CHO cells

Chinese hamster ovary (CHO) cells are common mammalian cell lines for expressing recombinant proteins, yet the expression level of recombinant proteins is still hindered. Vector optimization and cell line modification are the key factors to improve the expression of recombinant proteins. In this study, the vector was optimized by adding the regulatory elements Kozak and Leader to the upstream of target gene to detect the transient and stable expression of recombinant proteins. Results indicated that the expression level of target proteins with the addition of regulatory elements was significantly increased compared with the control group. In addition, the inhibition of apoptotic pathway has great potential to increase recombinant protein production, and Apaf1 protein dependent on the mitochondrial apoptosis pathway plays an important role in this respect. The knockout of apoptotic gene Apaf1 in CHO cells can also increase recombinant protein production. Therefore, the vector was optimized by adding regulatory elements, and the cell line was modified by using CRISPR/Cas9 technology to establish a novel CHO cell expression system, which remarkably improved the expression level of recombinant proteins and laid the foundation for the large-scale production of recombinant proteins.

Splicing Dysregulation of Non-Canonical GC-5' Splice Sites of Breast Cancer Susceptibility Genes ATM and PALB2.

Background/Objectives: The non-canonical GC-5' splice sites (5'ss) are the most common exception (~1%) to the classical GT/AG splicing rule. They constitute weak 5'ss and can be regulated by splicing factors, so they are especially sensitive to genetic variations inducing the misrecognition of their respective exons. We aimed to investigate the GC-5'ss of the breast/ovarian cancer susceptibility genes, ATM (exon 50), BRIP1 (exon 1), and PALB2 (exon 12), and their dysregulation induced by DNA variants. Methods: Splicing assays of the minigenes, mgATM_49-52, mgBRIP1_1-2, and mgPALB2_5-12, were conducted to study the regulation of the indicated GC-5'ss. Results: A functional map of the splicing regulatory elements (SRE) formed by overlapping exonic microdeletions revealed three essential intervals, ATM c.7335_7344del, PALB2 c.3229_3258del, and c.3293_3322del, which are likely targets for spliceogenic SRE-variants. We then selected 14 ATM and 9 PALB2 variants (Hexplorer score < -40) located at these intervals that were assayed in MCF-7 cells. Nine ATM and three PALB2 variants affected splicing, impairing the recognition of exons 50 and 12, respectively. Therefore, these variants likely disrupt the active SREs involved in the inclusion of both exons in the mature mRNA. DeepCLIP predictions suggested the participation of several splicing factors in exon recognition, including SRSF1, SRSF2, and SRSF7, involved in the recognition of other GC sites. The ATM spliceogenic variants c.7336G>T (p.(Glu2446Ter)) and c.7340T>A (p.(Leu2447Ter)) produced significant amounts of full-length transcripts (55-59%), which include premature termination stop codons, so they would inactivate ATM through both splicing disruption and protein truncation mechanisms. Conclusions: ATM exon 50 and PALB2 exon 12 require specific sequences for efficient recognition by the splicing machinery. The mapping of SRE-rich intervals in minigenes is a valuable approach for the identification of spliceogenic variants that outperforms any prediction software. Indeed, 12 spliceogenic SRE-variants were identified in the critical intervals.

Machine Learning-Based Detection of Bladder Cancer by Urine cfDNA Fragmentation Hotspots that Capture Cancer-Associated Molecular Features.

cfDNA fragmentomics-based liquid biopsy is a potential option for noninvasive bladder cancer (BLCA) detection that remains an unmet clinical need. We assessed the diagnostic performance of cfDNA hotspot-driven machine-learning models in a cohort of 55 BLCA patients, 51 subjects with benign conditions, and 11 healthy volunteers. We further performed functional bioinformatics analysis for biological understanding and interpretation of the tool's diagnostic capability. Urinary cfDNA hotspots-based machine-learning model enabled effective BLCA detection, achieving high performance (area under curve 0.96) and an 87% sensitivity at 100% specificity. It outperformed models using other cfDNA-derived features. In stage-stratified analysis, the sensitivity at 100% specificity of the urine hotspots-based model was 71% and 92% for early (low-grade Ta and T1) and advanced (high-grade T1 and muscle-invasive) disease, respectively. Biologically, cfDNA hotspots effectively retrieved regulatory elements and were correlated with the cell of origin. Urine cfDNA hotspots specifically captured BLCA-related molecular features, including key functional pathways, chromosome loci associated with BLCA risk as identified in genome-wide association studies, or presenting frequent somatic alterations in BLCA tumors, and the transcription factor regulatory landscape. Our findings support the applicability of urine cfDNA fragmentation hotspots for noninvasive BLCA diagnosis, as well as for future translational study regarding its molecular pathology and heterogeneity.

Translating weighted probabilistic bits to synthetic genetic circuits.

Synthetic genetic circuits in plants could be the next technological horizon in plant breeding, showcasing potential for precise patterned control over expression. Nevertheless, uncertainty in metabolic environments prevents robust scaling of traditional genetic circuits for agricultural use, and studies show that a deterministic system is at odds with biological randomness. We analyze the necessary requirements for assuring Boolean logic gate sequences can function in unpredictable intracellular conditions, followed by interpreted pathways by which a mathematical representation of probabilistic circuits can be translated to biological implementation. This pathway is utilized through translation of a probabilistic circuit model presented by Pervaiz that works through a series of bits; each composed of a weighted matrix that reads inputs from the environment and a random number generator that takes the matrix as bias and outputs a positive or negative signal. The weighted matrix can be biologically represented as the regulatory elements that affect transcription near promotors, allowing for an electrical bit to biological bit translation that can be refined through tuning using invertible logic prediction of the input to output relationship of a genetic response. Failsafe mechanisms should be introduced, possibly through the use of self-eliminating CRISPR-Cas9, dosage compensation, or cybernetic modeling (where CRISPR is clustered regularly interspaced short palindromic repeats and Cas9 is clustered regularly interspaced short palindromic repeat-associated protein 9). These safety measures are needed for all biological circuits, and their implementation is needed alongside work with this specific model. With applied responses to external factors, these circuits could allow fine-tuning of organism adaptation to stress while providing a framework for faster complex expression design in the field.

Genetic Variation, Polyploidy, Hybridization Influencing the Aroma Profiles of Rosaceae Family.

The fragrance and aroma of Rosaceae plants are complex traits influenced by a multitude of factors, with genetic variation standing out as a key determinant which is largely impacted by polyploidy. Polyploidy serves as a crucial evolutionary mechanism in plants, significantly boosting genetic diversity and fostering speciation. This review focuses on the Rosaceae family, emphasizing how polyploidy influences the production of volatile organic compounds (VOCs), which are essential for the aromatic characteristics of economically important fruits like strawberries, apples, and cherries. The review delves into the biochemical pathways responsible for VOC biosynthesis, particularly highlighting the roles of terpenoids, esters alcohols, aldehydes, ketones, phenolics, hydrocarbons, alongside the genetic mechanisms that regulate these pathways. Key enzymes, such as terpene synthases and alcohol acyltransferases, are central to this process. This review further explores how polyploidy and hybridization can lead to the development of novel metabolic pathways, contributing to greater phenotypic diversity and complexity in fruit aromas. It underscores the importance of gene dosage effects, isoenzyme diversity, and regulatory elements in determining VOC profiles. These findings provide valuable insights for breeding strategies aimed at improving fruit quality and aligning with consumer preferences. Present review not only elucidates the complex interplay between genomic evolution and fruit aroma but also offers a framework for future investigations in plant biology and agricultural innovation.

Mulea: An R package for enrichment analysis using multiple ontologies and empirical false discovery rate

Traditional gene set enrichment analyses are typically limited to a few ontologies and do not account for the interdependence of gene sets or terms, resulting in overcorrected p-values. To address these challenges, we introduce mulea, an R package offering comprehensive overrepresentation and functional enrichment analysis. mulea employs a progressive empirical false discovery rate (eFDR) method, specifically designed for interconnected biological data, to accurately identify significant terms within diverse ontologies. mulea expands beyond traditional tools by incorporating a wide range of ontologies, encompassing Gene Ontology, pathways, regulatory elements, genomic locations, and protein domains. This flexibility enables researchers to tailor enrichment analysis to their specific questions, such as identifying enriched transcriptional regulators in gene expression data or overrepresented protein domains in protein sets. To facilitate seamless analysis, mulea provides gene sets (in standardised GMT format) for 27 model organisms, covering 22 ontology types from 16 databases and various identifiers resulting in almost 900 files. Additionally, the muleaData ExperimentData Bioconductor package simplifies access to these pre-defined ontologies. Finally, mulea's architecture allows for easy integration of user-defined ontologies, or GMT files from external sources (e.g., MSigDB or Enrichr), expanding its applicability across diverse research areas. mulea is distributed as a CRAN R package downloadable from https://cran.r-project.org/web/packages/mulea/ and https://github.com/ELTEbioinformatics/mulea. It offers researchers a powerful and flexible toolkit for functional enrichment analysis, addressing limitations of traditional tools with its progressive eFDR and by supporting a variety of ontologies. Overall, mulea fosters the exploration of diverse biological questions across various model organisms.

A Soybean Pyrroline-5-Carboxylate Dehydrogenase GmP5CDH1 Modulates Plant Growth and Proline Sensitivity

Soybean [Glycine max (L.) Merr.], as a globally commercialized crop, is an important source of protein and oil for both humans and livestock. With more frequent extreme weather disasters, abiotic stress has become one of the critical factors restricting soybean production. Proline (Pro) is a well-known substance in plants that responds to abiotic stress. To identify potential effector genes involved in soybean resistance to abiotic stress, we focused on the pyrroline-5-carboxylate dehydrogenase (P5CDH) which is a key enzyme in the degradation process of Pro. Through homologous sequence alignment, phylogenetic tree, and predicted expression, we chose GmP5CDH1 (Glyma.05G029200) for further research. Tissue-specific expression assay showed that GmP5CDH1 had higher expression levels in soybean seed and cotyledon development. Subcellular localization assay revealed that GmP5CDH1 was a nuclear-membrane-localized protein. As the result of the predicted cis-acting regulatory element indicates, the expression level of GmP5CDH1 was induced by low temperature, drought, salt stress, and ABA in soybean. Next, we constructed transgenic Arabidopsis overexpressing GmP5CDH1. The results showed that GmP5CDH1 also strongly responded to exogenous Pro, and overcame the toxicity of abiotic stress on plants by regulating the endogenous concentration of Pro. The interaction between GmP5CDH1 and GmSAM1 was validated through yeast two-hybrid, LUC fluorescence complementary, and BIFC. In conclusion, overexpression of a soybean pyrroline-5-carboxylate dehydrogenase GmP5CDH1 regulates the development of Arabidopsis thaliana by altering proline content dynamically under salt stress, especially improving the growth of plants under exogenous Pro.