Spatially resolved epigenomic profiling of single cells in complex tissues.

The recent development of spatial omics methods has enabled single-cell profiling of the transcriptome and 3D genome organization with high spatial resolution. Expanding the repertoire of spatial omics tools, a spatially resolved single-cell epigenomics method will accelerate understanding of the spatial regulation of cell and tissue functions. Here, we report a method for spatially resolved epigenomic profiling of single cells using in situ tagmentation and transcription followed by multiplexed imaging. We demonstrated the ability to profile histone modifications marking active promoters, putative enhancers, and silent promoters in individual cells, and generated high-resolution spatial atlas of hundreds of active promoters and putative enhancers in embryonic and adult mouse brains. Our results suggested putative promoter-enhancer pairs and enhancer hubs regulating developmentally important genes. We envision this approach will be generally applicable to spatial profiling of epigenetic modifications and DNA-binding proteins, advancing our understanding of how gene expression is spatiotemporally regulated by the epigenome.

The spindle checkpoint proteins BUB1 and BUBR1: (SLiM)ming down to the basics.

Benzimidazole 1 (BUB1) and budding uninhibited by benzimidazole 1-related 1 (BUBR1) are multidomain paralogs with key roles in chromosome alignment during mitosis and the spindle assembly checkpoint (SAC), an evolutionarily conserved signaling pathway that monitors errors in chromosome segregation during cell division in eukaryotes. Although BUB1 and BUBR1 share a similar domain organization and short linear interaction motifs (SLiMs), they control distinct aspects of chromosome congression and the SAC. Here we discuss the roles of BUB1 and BUBR1 SLiMs in mitosis and complement this with additional insights gleamed from studying their evolution. We show that BUB1 and BUBR1 SLiMs form highly specific interactions that are carefully orchestrated in space and time and contend that they define BUB1 and BUBR1 as organizing hubs that drive SAC signaling and ensure genome stability.

The in vivo functional significance of PUF hub partnerships in C. elegans germline stem cells.

PUF RNA-binding proteins are conserved stem cell regulators. Four PUF proteins govern self-renewal of Caenorhabditis elegans germline stem cells together with two intrinsically disordered proteins, LST-1 and SYGL-1. Based on yeast two-hybrid results, we previously proposed a composite self-renewal hub in the stem cell regulatory network, with eight PUF partnerships and extensive redundancy. Here, we investigate LST-1-PUF and SYGL-1-PUF partnerships and their molecular activities in their natural context - nematode stem cells. We confirm LST-1-PUF partnerships and their specificity to self-renewal PUFs by co-immunoprecipitation and show that an LST-1(AmBm) mutant defective for PUF-interacting motifs does not complex with PUFs in nematodes. LST-1(AmBm) is used to explore the in vivo functional significance of the LST-1-PUF partnership. Tethered LST-1 requires this partnership to repress expression of a reporter RNA, and LST-1 requires the partnership to co-immunoprecipitate with NTL-1/Not1 of the CCR4-NOT complex. We suggest that the partnership provides multiple molecular interactions that work together to form an effector complex on PUF target RNAs in vivo. Comparison of LST-1-PUF and Nanos-Pumilio reveals fundamental molecular differences, making LST-1-PUF a distinct paradigm for PUF partnerships.

ATX1 and HUB1/2 promote recruitment of the transcription elongation factor VIP2 to modulate the floral transition in Arabidopsis.

Histone 2B ubiquitination (H2Bub) and trimethylation of H3 at lysine 4 (H3K4me3) are associated with transcription activation. However, the function of these modifications in transcription in plants remains largely unknown. Here, we report that coordination of H2Bub and H3K4me3 deposition with the binding of the RNA polymerase-associated factor VERNALIZATION INDEPENDENCE2 (VIP2) to FLOWERING LOCUS C (FLC) modulates flowering time in Arabidopsis. We found that RING domain protein HISTONE MONOUBIQUITINATION1 (HUB1) and HUB2 (we refer as HUB1/2), which are responsible for H2Bub, interact with ARABIDOPSIS TRITHORAX1 (ATX1), which is required for H3K4me3 deposition, to promote the transcription of FLC and repress the flowering time. The atx1-2 hub1-10 hub2-2 triple mutant in FRIGIDIA (FRI) background displayed early flowering like FRI hub1-10 hub2-2 and overexpression of ATX1 failed to rescue the early flowering phenotype of hub1-10 hub2-2. Mutations in HUB1 and HUB2 reduced the ATX1 enrichment at FLC, indicating that HUB1 and HUB2 are required for ATX1 recruitment and H3K4me3 deposition at FLC. We also found that the VIP2 directly binds to HUB1, HUB2, and ATX1 and that loss of VIP2 in FRI hub1-10 hub2-2 and FRI atx1-2 plants resulted in early flowering like that observed in FRI vip2-10. Loss of function of HUB2 and ATX1 impaired VIP2 enrichment at FLC, and reduced the transcription initiation and elongation of FLC. In addition, mutations in VIP2 reduced HUB1 and ATX1 enrichment and H2Bub and H3K4me3 levels at FLC. Together, our findings revealed that HUB1/2, ATX1, and VIP2 coordinately modulate H2Bub and H3K4me3 deposition, FLC transcription, and flowering time.

Modular brain network in volitional eyes closing: enhanced integration with a marked impact on hubs.

Volitional eyes closing would shift brain's information processing modes from the "exteroceptive" to "interoceptive" state. This transition induced by the eyes closing is underpinned by a large-scale reconfiguration of brain network, which is still not fully comprehended. Here, we investigated the eyes-closing-relevant network reconfiguration by examining the functional integration among intrinsic modules. Our investigation utilized a publicly available dataset with 48 subjects being scanned in both eyes closed and eyes open conditions. It was found that the modular integration was significantly enhanced during the eyes closing, including lower modularity index, higher participation coefficient, less provincial hubs, and more connector hubs. Moreover, the eyes-closing-enhanced integration was particularly noticeable in the hubs of network, mainly located in the default-mode network. Finally, the hub-dominant modular enhancement was positively correlated to the eyes-closing-reduced entropy of BOLD signal, suggesting a close connection to the diminished consciousness of individuals. Collectively, our findings strongly suggested that the enhanced modular integration with substantially reorganized hubs characterized the large-scale cortical underpinning of the volitional eyes closing.

Pain experience reduces social avoidance to others in pain: a c-Fos-based functional connectivity network study in mice.

Pain experience increases individuals' perception and contagion of others' pain, but whether pain experience affects individuals' affiliative or antagonistic responses to others' pain is largely unknown. Additionally, the neural mechanisms underlying how pain experience modulates individuals' responses to others' pain remain unclear. In this study, we explored the effects of pain experience on individuals' responses to others' pain and the underlying neural mechanisms. By comparing locomotion, social, exploration, stereotyped, and anxiety-like behaviors of mice without any pain experience (naïve observers) and mice with a similar pain experience (experienced observers) when they observed the pain-free demonstrator with intraperitoneal injection of normal saline and the painful demonstrator with intraperitoneal injection of acetic acid, we found that pain experience of the observers led to decreased social avoidance to the painful demonstrator. Through whole-brain c-Fos quantification, we discovered that pain experience altered neuronal activity and enhanced functional connectivity in the mouse brain. The analysis of complex network and graph theory exhibited that functional connectivity networks and activated hub regions were altered by pain experience. Together, these findings reveal that neuronal activity and functional connectivity networks are involved in the modulation of individuals' responses to others' pain by pain experience.

Dynamical changes of interaction across functional brain communities during propofol-induced sedation.

It is crucial to understand how anesthetics disrupt information transmission within the whole-brain network and its hub structure to gain insight into the network-level mechanisms underlying propofol-induced sedation. However, the influence of propofol on functional integration, segregation, and community structure of whole-brain networks were still unclear. We recruited 12 healthy subjects and acquired resting-state functional magnetic resonance imaging data during 5 different propofol-induced effect-site concentrations (CEs): 0, 0.5, 1.0, 1.5, and 2.0 µg/ml. We constructed whole-brain functional networks for each subject under different conditions and identify community structures. Subsequently, we calculated the global and local topological properties of whole-brain network to investigate the alterations in functional integration and segregation with deepening propofol sedation. Additionally, we assessed the alteration of key nodes within the whole-brain community structure at each effect-site concentrations level. We found that global participation was significantly increased at high effect-site concentrations, which was mediated by bilateral postcentral gyrus. Meanwhile, connector hubs appeared and were located in posterior cingulate cortex and precentral gyrus at high effect-site concentrations. Finally, nodal participation coefficients of connector hubs were closely associated to the level of sedation. These findings provide valuable insights into the relationship between increasing propofol dosage and enhanced functional interaction within the whole-brain networks.

Error-Prone Splicing Controlled by the Ubiquitin Relative Hub1.

Accurate pre-mRNA splicing is needed for correct gene expression and relies on faithful splice site recognition. Here, we show that the ubiquitin-like protein Hub1 binds to the DEAD-box helicase Prp5, a key regulator of early spliceosome assembly, and stimulates its ATPase activity thereby enhancing splicing and relaxing fidelity. High Hub1 levels enhance splicing efficiency but also cause missplicing by tolerating suboptimal splice sites and branchpoint sequences. Notably, Prp5 itself is regulated by a Hub1-dependent negative feedback loop. Since Hub1-mediated splicing activation induces cryptic splicing of Prp5, it also represses Prp5 protein levels and thus curbs excessive missplicing. Our findings indicate that Hub1 mediates enhanced, but error-prone splicing, a mechanism that is tightly controlled by a feedback loop of PRP5 cryptic splicing activation.

Distinct dynamics and proximity networks of hub proteins at the prey-invading cell pole in a predatory bacterium.

In bacteria, cell poles function as subcellular compartments where proteins localize during specific lifecycle stages, orchestrated by polar "hub" proteins. Whereas most described bacteria inherit an "old" pole from the mother cell and a "new" pole from cell division, generating cell asymmetry at birth, non-binary division poses challenges for establishing cell polarity, particularly for daughter cells inheriting only new poles. We investigated polarity dynamics in the obligate predatory bacterium Bdellovibrio bacteriovorus, proliferating through filamentous growth followed by non-binary division within prey bacteria. Monitoring the subcellular localization of two proteins known as polar hubs in other species, RomR and DivIVA, revealed RomR as an early polarity marker in B. bacteriovorus. RomR already marks the future anterior poles of the progeny during the predator's growth phase, during a precise period closely following the onset of divisome assembly and the end of chromosome segregation. In contrast to RomR's stable unipolar localization in the progeny, DivIVA exhibits a dynamic pole-to-pole localization. This behavior changes shortly before the division of the elongated predator cell, where DivIVA accumulates at all septa and both poles. In vivo protein interaction networks for DivIVA and RomR, mapped through endogenous miniTurbo-based proximity labeling, further underscore their distinct roles in cell polarization and reinforce the importance of the anterior "invasive" cell pole in prey-predator interactions. Our work also emphasizes the precise spatiotemporal order of cellular processes underlying B. bacteriovorus proliferation, offering insights into the subcellular organization of bacteria with filamentous growth and non-binary division.IMPORTANCEIn bacteria, cell poles are crucial areas where "hub" proteins orchestrate lifecycle events through interactions with multiple partners at specific times. While most bacteria exhibit one "old" and one "new" pole, inherited from the previous division event, setting polar identity poses challenges in bacteria with non-binary division. This study explores polar proteins in the predatory bacterium Bdellovibrio bacteriovorus, which undergoes filamentous growth followed by non-binary division inside another bacterium. Our research reveals distinct localization dynamics of the polar proteins RomR and DivIVA, highlighting RomR as an early "hub" marking polar identity in the filamentous mother cell. Using miniTurbo-based proximity labeling, we uncovered their unique protein networks. Overall, our work provides new insights into the cell polarity in non-binary dividing bacteria.

Generic model to unravel the deeper insights of viral infections: an empirical application of evolutionary graph coloring in computational network biology.

PURPOSE: Graph coloring approach has emerged as a valuable problem-solving tool for both theoretical and practical aspects across various scientific disciplines, including biology. In this study, we demonstrate the graph coloring's effectiveness in computational network biology, more precisely in analyzing protein-protein interaction (PPI) networks to gain insights about the viral infections and its consequences on human health. Accordingly, we propose a generic model that can highlight important hub proteins of virus-associated disease manifestations, changes in disease-associated biological pathways, potential drug targets and respective drugs. We test our model on SARS-CoV-2 infection, a highly transmissible virus responsible for the COVID-19 pandemic. The pandemic took significant human lives, causing severe respiratory illnesses and exhibiting various symptoms ranging from fever and cough to gastrointestinal, cardiac, renal, neurological, and other manifestations. METHODS: To investigate the underlying mechanisms of SARS-CoV-2 infection-induced dysregulation of human pathobiology, we construct a two-level PPI network and employed a differential evolution-based graph coloring (DEGCP) algorithm to identify critical hub proteins that might serve as potential targets for resolving the associated issues. Initially, we concentrate on the direct human interactors of SARS-CoV-2 proteins to construct the first-level PPI network and subsequently applied the DEGCP algorithm to identify essential hub proteins within this network. We then build a second-level PPI network by incorporating the next-level human interactors of the first-level hub proteins and use the DEGCP algorithm to predict the second level of hub proteins. RESULTS: We first identify the potential crucial hub proteins associated with SARS-CoV-2 infection at different levels. Through comprehensive analysis, we then investigate the cellular localization, interactions with other viral families, involvement in biological pathways and processes, functional attributes, gene regulation capabilities as transcription factors, and their associations with disease-associated symptoms of these identified hub proteins. Our findings highlight the significance of these hub proteins and their intricate connections with disease pathophysiology. Furthermore, we predict potential drug targets among the hub proteins and identify specific drugs that hold promise in preventing or treating SARS-CoV-2 infection and its consequences. CONCLUSION: Our generic model demonstrates the effectiveness of DEGCP algorithm in analyzing biological PPI networks, provides valuable insights into disease biology, and offers a basis for developing novel therapeutic strategies for other viral infections that may cause future pandemic.

Identification of hub genes and pathways associated with cellular senescence in diabetic foot ulcers via comprehensive transcriptome analysis.

This research aimed to find important genes and pathways related to cellular senescence (CS) in diabetic foot ulcers (DFU) and to estimate the possible pathways through which CS affects diabetic foot healing. The GSE80178 dataset was acquired from the Gene Expression Omnibus (GEO) database, containing six DFU and three diabetic foot skin (DFS) samples. The limma package was used to identify differentially expressed genes (DEGs). At the same time, DEGs associated with CS (CS-DEGs) were found using the CellAge database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the CS-DEGs. A protein-protein interaction (PPI) network was built using the String database, and the cytoHubba plug-in within Cytoscape helped identify hub genes. Lastly, the miRNA-TF-mRNA regulatory network for these hub genes was established. In total, 66 CS-DEGs were obtained. These genes mainly focus on CS, Kaposi sarcoma-associated herpesvirus infection and Toll-like receptor signalling pathway. Eight hub genes were identified to regulate cell senescence in DFU, including TP53, SRC, SIRT1, CCND1, EZH2, CXCL8, AR and CDK4. According to miRNA-TF-mRNA regulatory network, hsa-mir-132-3p/SIRT1/EZH2 axis is involved in senescence cell accumulation in DFU.

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and in vitro experiments.

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through in vitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration in vitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

Contribution of FOS in neutrophils to venous thromboembolism via miR-144 based on bioinformatic prediction and validation.

The Finkel-Biskis-Jinkins Osteosarcoma (c-Fos; encoded by FOS) plays an important role in several cardiovascular diseases, including atherosclerosis and stroke. However, the relationship between FOS and venous thromboembolism (VTE) remains unknown. We identified differentially expressed genes in Gene Expression Omnibus dataset, GSE48000, comprising VTE patients and healthy individuals, and analysed them using CIBERSORT and weighted co-expression network analysis (WGCNA). FOS and CD46 expressions were significantly downregulated (FOS p = 2.26E-05, CD64 p = 8.83E-05) and strongly linked to neutrophil activity in VTE. We used GSE19151 and performed PCR to confirm that FOS and CD46 had diagnostic potential for VTE; however, only FOS showed differential expression by PCR and ELISA in whole blood samples. Moreover, we found that hsa-miR-144 which regulates FOS expression was significantly upregulated in VTE. Furthermore, FOS expression was significantly downregulated in neutrophils of VTE patients (p = 0.03). RNA sequencing performed on whole blood samples of VTE patients showed that FOS exerted its effects in VTE via the leptin-mediated adipokine signalling pathway. Our results suggest that FOS and related genes or proteins can outperform traditional clinical markers and may be used as diagnostic biomarkers for VTE.

Structures of calmodulin-melittin complexes show multiple binding modes lacking classical anchoring interactions.

Calmodulin (CaM) is a Ca2+ sensor protein found in all eukaryotic cells that regulates a large number of target proteins in a Ca2+ concentration-dependent manner. As a transient-type hub protein, it recognizes linear motifs of its targets, though for the Ca2+-dependent binding, no consensus sequence was identified. Its complex with melittin, a major component of bee venom, is often used as a model system of protein-protein complexes. Yet, the structural aspects of the binding are not well understood, as only diverse, low-resolution data are available concerning the association. We present the crystal structure of melittin in complex with Ca2+-saturated CaMs from two, evolutionarily distant species, Homo sapiens and Plasmodium falciparum, representing three binding modes of the peptide. Results-augmented by molecular dynamics simulations-indicate that multiple binding modes can exist for CaM-melittin complexes, as an intrinsic characteristic of the binding. While the helical structure of melittin remains, swapping of its salt bridges and partial unfolding of its C-terminal segment can occur. In contrast to the classical way of target recognition by CaM, we found that different sets of residues can anchor at the hydrophobic pockets of CaM, which were considered as main recognition sites. Finally, the nanomolar binding affinity of the CaM-melittin complex is created by an ensemble of arrangements of similar stability-tight binding is achieved not by optimized specific interactions but by simultaneously satisfying less optimal interaction patterns in co-existing different conformers.

Stress combinations and their interactions in plants database: a one-stop resource on combined stress responses in plants.

We have developed a compendium and interactive platform, named Stress Combinations and their Interactions in Plants Database (SCIPDb; http://www.nipgr.ac.in/scipdb.php), which offers information on morpho-physio-biochemical (phenome) and molecular (transcriptome and metabolome) responses of plants to different stress combinations. SCIPDb is a plant stress informatics hub for data mining on phenome, transcriptome, trait-gene ontology, and data-driven research for advancing mechanistic understanding of combined stress biology. We analyzed global phenome data from 939 studies to delineate the effects of various stress combinations on yield in major crops and found that yield was substantially affected under abiotic-abiotic stresses. Transcriptome datasets from 36 studies hosted in SCIPDb identified novel genes, whose roles have not been earlier established in combined stress. Integretome analysis under combined drought-heat stress pinpointed carbohydrate, amino acid, and energy metabolism pathways as the crucial metabolic, proteomic, and transcriptional components in plant tolerance to combined stress. These examples illustrate the application of SCIPDb in identifying novel genes and pathways involved in combined stress tolerance. Further, we showed the application of this database in identifying novel candidate genes and pathways for combined drought and pathogen stress tolerance. To our knowledge, SCIPDb is the only publicly available platform offering combined stress-specific omics big data visualization tools, such as an interactive scrollbar, stress matrix, radial tree, global distribution map, meta-phenome analysis, search, BLAST, transcript expression pattern table, Manhattan plot, and co-expression network. These tools facilitate a better understanding of the mechanisms underlying plant responses to combined stresses.

Co-expression network analysis of diverse wheat landraces reveals markers of early thermotolerance and a candidate master regulator of thermotolerance genes.

Triticum aestivum L. (bread wheat) is a crop relied upon by billions of people around the world, as a major source of both income and calories. Rising global temperatures, however, pose a genuine threat to the livelihood of these people, as wheat growth and yields are extremely vulnerable to damage by heat stress. Here we present the YoGI wheat landrace panel, comprising 342 accessions that show remarkable phenotypic and genetic diversity thanks to their adaptation to different climates. We quantified the abundance of 110 790 transcripts from the panel and used these data to conduct weighted co-expression network analysis and to identify hub genes in modules associated with abiotic stress tolerance. We found that the expression of three hub genes, all heat-shock proteins (HSPs), were significantly correlated with early thermotolerance in a validation panel of landraces. These hub genes belong to the same module, with one (TraesCS4D01G207500.1) being a candidate master-regulator potentially controlling the expression of the other two hub genes, as well as a suite of other HSPs and heat-stress transcription factors (HSFs). In this work, therefore, we identify three validated hub genes, the expression of which can serve as markers of thermotolerance during early development, and suggest that TraesCS4D01G207500.1 is a potential master regulator of HSP and HSF expression - presenting the YoGI landrace panel as an invaluable tool for breeders wishing to determine and introduce novel alleles into modern varieties, for the production of climate-resilient crops.

Network visualization of genes involved in skeletal muscle myogenesis in livestock animals.

BACKGROUND: Muscle growth post-birth relies on muscle fiber number and size. Myofibre number, metabolic and contractile capacities are established pre-birth during prenatal myogenesis. The aim of this study was to identify genes involved in skeletal muscle development in cattle, sheep, and pigs - livestock. RESULTS: The cattle analysis showed significant differences in 5043 genes during the 135-280 dpc period. In sheep, 444 genes differed significantly during the 70-120 dpc period. Pigs had 905 significantly different genes for the 63-91 dpc period.The biological processes and KEGG pathway enrichment results in each species individually indicated that DEGs in cattle were significantly enriched in regulation of cell proliferation, cell division, focal adhesion, ECM-receptor interaction, and signaling pathways (PI3K-Akt, PPAR, MAPK, AMPK, Ras, Rap1); in sheep - positive regulation of fibroblast proliferation, negative regulation of endothelial cell proliferation, focal adhesion, ECM-receptor interaction, insulin resistance, and signaling pathways (PI3K-Akt, HIF-1, prolactin, Rap1, PPAR); in pigs - regulation of striated muscle tissue development, collagen fibril organization, positive regulation of insulin secretion, focal adhesion, ECM-receptor interaction, and signaling pathways (PPAR, FoxO, HIF-1, AMPK). Among the DEGs common for studied animal species, 45 common genes were identified. Based on these, a protein-protein interaction network was created and three significant modules critical for skeletal muscle myogenesis were found, with the most significant module A containing four recognized hub genes - EGFR, VEGFA, CDH1, and CAV1. Using the miRWALK and TF2DNA databases, miRNAs (bta-miR-2374 and bta-miR-744) and transcription factors (CEBPB, KLF15, RELA, ZNF143, ZBTB48, and REST) associated with hub genes were detected. Analysis of GO term and KEGG pathways showed that such processes are related to myogenesis and associated with module A: positive regulation of MAP kinase activity, vascular endothelial growth factor receptor, insulin-like growth factor binding, focal adhesion, and signaling pathways (PI3K-Akt, HIF-1, Rap1, Ras, MAPK). CONCLUSIONS: The identified genes, common to the prenatal developmental period of skeletal muscle in livestock, are critical for later muscle development, including its growth by hypertrophy. They regulate valuable economic characteristics. Enhancing and breeding animals according to the recognized genes seems essential for breeders to achieve superior gains in high-quality muscle mass.

RNA sequencing identifies key genes involved in intramuscular fat deposition in chickens at different developmental stages.

BACKGROUND: Intramuscular fat (IMF) is an important factor in meat quality, and triglyceride (TG) and Phospholipids (PLIP), as the main components of IMF, are of great significance to the improvement of meat quality. RESULTS: In this study, we used 30 RNA sequences generated from the transcriptome of chicken breast muscle tissues at different developmental stages to construct a gene expression matrix to map RNA sequence reads to the chicken genome and identify the transcript of origin. We used weighted gene co-expression network analysis (WGCNA) and identified 27 co-expression modules, 10 of which were related to TG and PLIP. We identified 150 highly-connected hub genes related to TG and PLIP, respectively, which were found to be mainly enriched in the adipocytokine signaling pathway, MAPK signaling pathway, mTOR signaling pathway, FoxO signaling pathway, and TGF-beta signaling pathway. Additionally, using the BioMart database, we identified 134 and 145 candidate genes related to fat development in the TG-related module and PLIP-related module, respectively. Among them, RPS6KB1, BRCA1, CDK1, RPS3, PPARGC1A, ACSL1, NDUFAB1, NDUFA9, ATP5B and PRKAG2 were identified as candidate genes related to fat development and highly-connected hub genes in the module, suggesting that these ten genes may be important candidate genes affecting IMF deposition. CONCLUSIONS: RPS6KB1, BRCA1, CDK1, RPS3, PPARGC1A, ACSL1, NDUFAB1, NDUFA9, ATP5B and PRKAG2 may be important candidate genes affecting IMF deposition. The purpose of this study was to identify the co-expressed gene modules related to chicken IMF deposition using WGCNA and determine key genes related to IMF deposition, so as to lay a foundation for further research on the molecular regulation mechanism underlying chicken fat deposition.

Spatiotemporal transcriptomic plasticity in barley roots: unravelling water deficit responses in distinct root zones.

BACKGROUND: Drought poses a major threat to agricultural production and thus food security. Understanding the processes shaping plant responses to water deficit is essential for global food safety. Though many studies examined the effect of water deficit on the whole-root level, the distinct functions of each root zone and their specific stress responses remain masked by this approach. RESULTS: In this study, we investigated the effect of water deficit on root development of the spring barley (Hordeum vulgare L.) cultivar Morex and examined transcriptomic responses at the level of longitudinal root zones. Water deficit significantly reduced root growth rates after two days of treatment. RNA-sequencing revealed root zone and temporal gene expression changes depending on the duration of water deficit treatment. The majority of water deficit-regulated genes were unique for their respective root zone-by-treatment combination, though they were associated with commonly enriched gene ontology terms. Among these, we found terms associated with transport, detoxification, or cell wall formation affected by water deficit. Integration of weighted gene co-expression analyses identified differential hub genes, that highlighted the importance of modulating energy and protein metabolism and stress response. CONCLUSION: Our findings provide new insights into the highly dynamic and spatiotemporal response cascade triggered by water deficit and the underlying genetic regulations on the level of root zones in the barley cultivar Morex, providing potential targets to enhance plant resilience against environmental constraints. This study further emphasizes the importance of considering spatial and temporal resolution when examining stress responses.

Key gene modules and hub genes associated with pyrethroid and organophosphate resistance in Anopheles mosquitoes: a systems biology approach.

Indoor residual spraying (IRS) and insecticide-treated nets (ITNs) are the main methods used to control mosquito populations for malaria prevention. The efficacy of these strategies is threatened by the spread of insecticide resistance (IR), limiting the success of malaria control. Studies of the genetic evolution leading to insecticide resistance could enable the identification of molecular markers that can be used for IR surveillance and an improved understanding of the molecular mechanisms associated with IR. This study used a weighted gene co-expression network analysis (WGCNA) algorithm, a systems biology approach, to identify genes with similar co-expression patterns (modules) and hub genes that are potential molecular markers for insecticide resistance surveillance in Kenya and Benin. A total of 20 and 26 gene co-expression modules were identified via average linkage hierarchical clustering from Anopheles arabiensis and An. gambiae, respectively, and hub genes (highly connected genes) were identified within each module. Three specific genes stood out: serine protease, E3 ubiquitin-protein ligase, and cuticular proteins, which were top hub genes in both species and could serve as potential markers and targets for monitoring IR in these malaria vectors. In addition to the identified markers, we explored molecular mechanisms using enrichment maps that revealed a complex process involving multiple steps, from odorant binding and neuronal signaling to cellular responses, immune modulation, cellular metabolism, and gene regulation. Incorporation of these dynamics into the development of new insecticides and the tracking of insecticide resistance could improve the sustainable and cost-effective deployment of interventions.