Set Of Key Genes Research Articles

The Role of BAG3 Protein Interactions in Cardiomyopathies.

Bcl-2-associated athanogene 3 (BAG3) plays an important function in cellular protein quality control (PQC) maintaining proteome stability. Mutations in the BAG3 gene result in cardiomyopathies. Due to its roles in cardiomyopathies and the complexity of BAG3-protein interactions, it is important to understand these protein interactions given the importance of the multifunctional cochaperone BAG3 in cardiomyocytes, using an in vitro cardiomyocyte model. The experimental assay was conducted using high pressure liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) in the human AC16 cardiomyocyte cell line with BioID technology. Proteins with BAG3-interaction were identified in all the 28 hallmark gene sets enriched in idiopathic cardiomyopathies and/or ischemic disease. Among the 24 hallmark gene sets enriched in both idiopathic cardiomyopathies and ischemic disease, 15 gene sets had at least 3 proteins with BAG3-interaction. This study highlights BAG3 protein interactions, unveiling the key gene sets affected in cardiomyopathies, which help to explain the molecular mechanisms of the cardioprotective effects of BAG3. In addition, this study also highlighted the complexity of proteins with BAG3 interactions, implying unwanted effects of BAG3.

Comparative genomics of Metarhizium brunneum strains V275 and ARSEF 4556: unraveling intraspecies diversity.

Entomopathogenic fungi belonging to the Order Hypocreales are renowned for their ability to infect and kill insect hosts, while their endophytic mode of life and the beneficial rhizosphere effects on plant hosts have only been recently recognized. Understanding the molecular mechanisms underlying their different lifestyles could optimize their potential as both biocontrol and biofertilizer agents, as well as the wider appreciation of niche plasticity in fungal ecology. This study describes the comprehensive whole genome sequencing and analysis of one of the most effective entomopathogenic and endophytic EPF strains, Metarhizium brunneum V275 (commercially known as Lalguard Met52), achieved through Nanopore and Illumina reads. Comparative genomics for exploring intraspecies variability and analyses of key gene sets were conducted with a second effective EPF strain, M. brunneum ARSEF 4556. The search for strain- or species-specific genes was extended to M. brunneum strain ARSEF 3297 and other species of genus Metarhizium, to identify molecular mechanisms and putative key genome adaptations associated with mode of life differences. Genome size differed significantly, with M. brunneum V275 having the largest genome amongst M. brunneum strains sequenced to date. Genome analyses revealed an abundance of plant-degrading enzymes, plant colonization-associated genes, and intriguing intraspecies variations regarding their predicted secondary metabolic compounds and the number and localization of Transposable Elements. The potential significance of the differences found between closely related endophytic and entomopathogenic fungi, regarding plant growth-promoting and entomopathogenic abilities, are discussed, enhancing our understanding of their diverse functionalities and putative applications in agriculture and ecology.

Selective regulation of a defined subset of inflammatory and immunoregulatory genes by an NF-κB p50-IκBζ pathway.

The five NF-κB family members and three nuclear IκB proteins play important biological roles, but the mechanisms by which distinct members of these protein families contribute to selective gene transcription remain poorly understood, especially at a genome-wide scale. Using nascent transcript RNA-seq, we observed considerable overlap between p50-dependent and IκBζ-dependent genes in Toll-like receptor 4 (TLR4)-activated macrophages. Key immunoregulatory genes, including Il6, Il1b, Nos2, Lcn2, and Batf, are among the p50-IκBζ-codependent genes. IκBζ-bound genomic sites are occupied at earlier time points by NF-κB dimers. However, p50-IκBζ codependence does not coincide with preferential binding of either p50 or IκBζ, as RelA co-occupies hundreds of genomic sites with the two proteins. A common feature of p50-IκBζ-codependent genes is a nearby p50/RelA/IκBζ-cobound site exhibiting p50-dependent binding of both RelA and IκBζ. This and other results suggest that IκBζ acts in concert with RelA:p50 heterodimers. Notably, p50-IκBζ-codependent genes comprise a high percentage of genes exhibiting the greatest differential expression between TLR4-stimulated and tumor necrosis factor receptor (TNFR)-stimulated macrophages. Thus, our genome-centric analysis reveals a defined p50-IκBζ pathway that selectively activates a set of key immunoregulatory genes and serves as an important contributor to differential TNFR and TLR4 responses.

Transcriptome sequencing reveals novel biomarkers and immune cell infiltration in esophageal tumorigenesis.

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies worldwide, and its development comprises a multistep process from intraepithelial neoplasia (IN) to carcinoma (CA). However, the critical regulators and underlying molecular mechanisms remain largely unknown. To explore the genes and infiltrating immune cells in the microenvironment that are associated with the multistage progression of ESCC to facilitate diagnosis and early intervention. A mouse model mimicking the multistage development of ESCC was established by providing warter containing 4-nitroquinoline 1-oxide (4NQO) to C57BL/6 mice. Moreover, we established a control group without 4NQO treatment of mice. Then, transcriptome sequencing was performed for esophageal tissues from patients with different pathological statuses, including low-grade IN (LGIN), high-grade IN (HGIN), and CA, and controlled normal tissue (NOR) samples. Differentially expressed genes (DEGs) were identified in the LGIN, HGIN, and CA groups, and the biological functions of the DEGs were analyzed via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The CIBERSORT algorithm was used to detect the pattern of immune cell infiltration. Immunohistochemistry (IHC) was also conducted to validate our results. Finally, the Luminex multiplex cytokine analysis was utilized to measure the serum cytokine levels in the mice. Compared with those in the NOR group, a total of 681541, and 840 DEGs were obtained in the LGIN, HGIN, and CA groups, respectively. Using the intersection of the three sets of DEGs, we identified 86 genes as key genes involved in the development of ESCC. Enrichment analysis revealed that these genes were enriched mainly in the keratinization, epidermal cell differentiation, and interleukin (IL)-17 signaling pathways. CIBERSORT analysis revealed that, compared with those in the NOR group, M0 and M1 macrophages in the 4NQO group showed stronger infiltration, which was validated by IHC. Serum cytokine analysis revealed that, compared with those in the NOR group, IL-1β and IL-6 were upregulated, while IL-10 was downregulated in the LGIN, HGIN, and CA groups. Moreover, the expression of the representative key genes, such as S100a8 and Krt6b, was verified in external human samples, and the results of immunohistochemical staining were consistent with the findings in mice. We identified a set of key genes represented by S100a8 and Krt6b and investigated their potential biological functions. In addition, we found that macrophage infiltration and abnormal alterations in the levels of inflammation-associated cytokines, such as IL-1β, IL-6, and IL-10, in the peripheral blood may be closely associated with the development of ESCC.

Biological agent exerts therapeutic effects by reversing abnormalities in amino acid metabolic pathways in psoriasis.

Psoriasis is a common chronic inflammatory skin disease with a complex pathogenesis involving immune system dysregulation and inflammation. Previous studies have indicated that metabolic abnormalities are closely related to the development and occurrence of psoriasis. However, the specific involvement of amino acid metabolism in the pathogenesis of psoriasis remains unclear. In this study, we conducted a comprehensive analysis of amino acid metabolism pathway changes in psoriasis patients using transcriptome data, genome-wide association studies (GWASs) data, and single-cell data. Our findings revealed 11 significant alterations in amino acid metabolism pathways within psoriatic lesions, with notable restorative changes observed after biological therapy. Branched-chain amino acids, tyrosine and arginine metabolism have a causal relationship with the occurrence of psoriasis and may play a crucial role by promoting the proliferation and differentiation of the keratinocytes or immune-related pathways. Activation of phenylalanine, tyrosine and tryptophan biosynthesis suggests a favourable prognosis of psoriasis after treatment. Additionally, we identified the abnormal metabolic pathways in specific cell types and key gene sets that contribute to amino acid metabolic disorders in psoriasis. Overall, our study enhances understanding of the role of metabolism in the pathogenesis of psoriasis and provides potential targets for developing new therapeutic strategies for the disease.

PANoptosis-related signature in melanoma: Transcriptomic mapping and clinical prognostication.

Programmed cell death plays a pivotal role in maintaining tissue homeostasis, and recent advancements in cell biology have uncovered PANoptosis-a novel paradigm integrating pyroptosis, apoptosis, and necroptosis. This study investigates the implications of PANoptosis in melanoma, a formidable skin cancer known for its metastatic potential and resistance to conventional therapies. Leveraging bulk and single-cell transcriptome analyses, machine learning modeling, and immune correlation assessments, we unveil the molecular intricacies of PANoptosis in melanoma. Single-cell sequencing identifies diverse cell types involved in PANoptosis, while bulk transcriptome analysis reveals key gene sets correlated with PANoptosis. Machine learning algorithms construct a robust prognostic model, demonstrating consistent predictive power across diverse cohorts. Patients with different cohorts can be divided into high-risk and low-risk groups according to this PANoptosis score, with the high-risk group having a significantly worse prognosis. Immune correlation analyses unveil a link between PANoptosis and immunotherapy response, with potential therapeutic implications. Mutation analysis and enrichment studies provide insights into the mutational landscape associated with PANoptosis. Finally, we used cell experiments to verify the expression and function of key gene PARVA, showing that PARVA was highly expressed in melanoma cell lines, and after PARVA is knocked down, cell invasion, migration, and colony formation ability were significantly decreased. This study advances our understanding of PANoptosis in melanoma, offering a comprehensive framework for targeted therapeutic interventions and personalized medicine strategies in combating this aggressive malignancy.

The dynamic immune response of the liver and spleen in leopard coral grouper (Plectropomus leopardus) to Vibrio harveyi infection based on transcriptome analysis.

Leopard coral grouper (Plectropomus leopardus) is one of the most important cultured fish in the Pacific and Indian oceans. Vibrio harveyi is a serious pathogen causing serious skin ulceration and high mortality in P. leopardus. To gain more insight into the tissue-specific and dynamic immune regulation process of P. leopardus in response to V. harveyi infection, RNA sequencing (RNA-seq) was used to examine the transcriptome profiles in the spleen and liver at 0, 6, 12, 24, 48, and 72h post-infection. The upregulated differentially expressed genes (DEGs) were predominantly involved in the immune response in the spleen and liver at the early infection stage (6-12 h), and downregulated DEGs were mainly involved in metabolic processes in the liver at the early and middle infection stage (6-48 h). Moreover, an overview of the immune response of P. leopardus against V. harveyi was exhibited including innate and adaptive immune-related pathways. Afterwards, the results of WGCNA analysis in the spleen indicated that TAP2, IRF1, SOCS1, and CFLAR were the hub genes closely involved in immune regulation in the gene co-expression network. This study provides a global picture of V. harveyi-induced gene expression profiles of P. leopardus at the transcriptome level and uncovers a set of key immune pathways and genes closely linked to V. harveyi infection, which will lay a foundation for further study the immune regulation of bacterial diseases in P. leopardus.

Mitochondrial dysfunction and disulfidptosis co-regulate neuronal cell in neuropathic pain based on bioinformatics analysis.

Neuropathic pain (NP) affects approximately 6.9-10% of the world's population and necessitates the development of novel treatments. Mitochondria are essential in the regulation of cell death. Neuroimmune mechanisms are implicated in various forms of cell death associated with NP. However, the specific involvement of mitochondrial dysfunction and disulfidptosis in NP remains uncertain. Further research is required to gain a better understanding of their combined contribution. Our comprehensive study employs a variety of bioinformatic analysis methods, including differential gene analysis, weighted gene co-expression network analysis, machine learning, functional enrichment analysis, immune infiltration, sub-cluster analysis, single-cell dimensionality reduction and cell-cell communication to gain insight into the molecular mechanisms behind these processes. Our study rationally defines a list of key gene sets for mitochondrial dysfunction and disulfidptosis. 6 hub mitochondrial genes and 3 disulfidptosis-related genes (DRGs) were found to be associated with NP. The key genes were predominantly expressed in neurons and were lowly expressed in the NP group compared to SHAM. In addition, our macrophages used the APP (Amyloid precursor protein)-CD74 (MHC class II invariant chain) pathway to interact with neurons. These results suggest that NP is interconnected with the mechanistic processes of mitochondrial dysfunction and disulfidptosis, which may contribute to clinically targeted therapies.

EPCO-18. HETEROCHROMATIN DYSFUNCTION IMPACTING GENOMIC TOPOLOGY AND SUPERENHANCER LANDSCAPES PROMOTES ATRX-DEFICIENT GLIOMAGENESIS

Abstract Mutational inactivation of the SWI/SNF chromatin regulator ATRX occurs frequently in diffuse gliomas. Whether and how ATRX deficiency promotes oncogenesis remains unclear, despite its implication across a broad array of physiological processes. We sought to delineate the molecular mechanisms by which global epigenomic dysfunction promotes oncogenic phenotypes in ATRX-deficient glioma models. Building on earlier work implicating chromatin accessibility and transcriptional shifts, we employed integrated epigenomic profiling in Atrx-intact and -deficient murine neuroepithelial progenitor cells (mNPCs), validating findings will functional approaches in human glioma stem cells (GSCs) of appropriate genotype. We found that ATRX deficiency dramatically impacted the integrity of large heterochromatin domains genome-wide, with tangible effects on underlying gene expression. This process fundamentally altered chromatin topology, as assessed by Hi-C analysis, and associated superenhancer landscapes, influencing key developmental gene sets like the HOXA cluster. Pharmacological inhibition of HOXA signaling in GSCs selectively reduced proliferation, increased apoptosis, and impaired in vivo growth in the ATRX-deficient context. Finally, our results pointed to derepression of LINE1 endogenous retroviral elements as key mediators of ATRX-deficient heterochromatin dysfunction. Our work implicates novel and targetable molecular mechanisms involving complex epigenomic rewiring and chromatin topology in ATRX-deficient oncogenesis. In doing so, we advance the understanding of a deadly brain tumor along with broader conceptions of epigenetic mechanisms as fundamental drivers in cancer.

G-CSF Induces MAIT Cells to Exert Anti-Intestinal Gvhd Effects Dependent on CXCR6 Mediated Chemotaxis

Background: Graft-versus-host disease (GVHD) is a major complication leading to transplantation failure and affecting overall survival after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Granulocyte colony-stimulating factor (G-CSF) can induce T-cell tolerance and altering graft cell components to enhance GVHD prevention in HSCT. MAIT cells are a group of innate immune T cells. It has unique biological properties, including mucosal tissue enrichment, activation of microbial riboflavin derivatives and tissue repair properties, which determine MAIT cells play an important role in mucosal immunity. Previous studies found that a high MAIT cell counts in G-CSF-induced grafts (G-grafts) is associated with a low incidence of gut acute GVHD (aGVHD). However, the effect of G-CSF mobilization on the phenotype, function and its regulatory mechanism in GVHD of MAIT cells has not been elucidated. Methods: MAIT cells in PB samples from four healthy donors before and after G-CSF treatment were isolated for Single-cell RNA sequencing (Figure A). Flow cytometry, In vitro experiment and NOD-SCID-IL-2Rg−/− mice (NSG mice) were performed to observe the phenotypic, functional changes and the dynamic distribution of G-CSF induced donor-derived MAIT cells in recipients. Results: A total of 80709 MAIT cells were divided into 14 clusters. Based on key type-associated marker genes and gene sets, MAIT0 (clusters 5 and 9), MAIT1 (cluster 7), MAIT2 (clusters 4 , 11), Cycling MAIT (clusters 12, 13), Activation (clusters 0, 8), ISG (cluster 10) and MAIT17 (clusters 1,2,3,6) cells were identified (Figure B,C). The subset frequencies and expression signatures of immunosuppression (MAIT2 and Cycling cells from cluster 12) and tissue repair (Activation and MAIT17) were both increased at both transcriptome (Figure D) and protein levels, suggesting that G-CSF enhanced the immune tolerance and tissue repair of MAIT cells. In vitro further confirmed that G-CSF-induced MAIT cells showed a stronger inhibition for T cell proliferation (Figure E). Besides, overexpressed genes related to immune regulation in G-CSF induced MAIT cells were strongly enriched in cluster 12 with high CSF3R (G-CSF receptor) expression (Figure F). The cluster 12 also showed the enrichment of IL-17 and TNF signaling pathway favoring tissue repair function, while downregulation of Graft-versus-host disease pathway upon G-CSF mobilization, indicating that G-CSF-CSF3R interaction is the potential mechanism by which G-CSF mediates the immune regulation of MAIT cells. Based on whether recipients develop gut aGVHD or not after allo-HSCT, the matched donor grafts after G-CSF mobilization were divided into two groups termed as post-G-CSF-no gut aGVHD (n=3) and post-G-CSF-gut aGVHD group (n=1), respectively. MAIT cells in post-G-CSF-no gut aGVHD group overexpressed CSF3R and its related target genes, immunosuppression and tissue repair signatures compared with post-G-CSF-gut aGVHD. Besides, MAIT cells from G-PB of recipients without gut aGVHD had a higher CD114 expression (encoded by CSF3R) compared with gut aGVHD (Figure G). These results suggest that the enhanced immunosuppression and tissue repair function of MAIT cells induced by G-CSF may exert anti-gut aGVHD effects. The NSG mice confirmed MAIT cells in G-PB to tissue chemotaxis especially gut tissues in the recipient. A higher frequency of MAIT cells was detected in gut tissues in the low GVHD score group (GVHD Score＜3) compared with the high GVHD score group on post-transplant day 14 (Figure H), suggesting recruited MAIT cells in gut tissues favor anti-gut aGVHD effect. Moreover, CXCR6 was the most differentially expressed chemotactic receptor gene between post-G-CSF-no gut aGVHD and post-G-CSF-gut aGVHD group (Figure I). At the protein level, the expression of CXCR6 were significantly upregulated upon G-CSF administration (Figure I), while that of CCR6 and CXCR6 was non-significant. These results suggest that CXCR6 is necessary for G-CSF induced MAIT cell recruitment to the gut tissue. Conclusions G-CSF-CSF3R interactions enhance immunosuppression and tissue repair functions of MAIT cells, while CXCR6 recruits these functional MAIT cells from PB to gut tissues to exert anti-gut aGVHD effect. Hence, CSF3R and CXCR6 expression in G-CSF mobilized MAIT cells is crucial to exert anti-gut aGVHD effect, and has the potential to become predictive markers of gut aGVHD.

Network Modeling of Apoptosis-Related Genes Reveal a High-Risk Cluster in Multiple Myeloma

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. Recent studies have shown the complexity of biological systems associated with poor outcomes in MM. One hallmark of cancer pathogenesis, applicable to MM, is the dysregulation of apoptotic cell death. Understanding the relationship between known drivers of MM and critical pathways in the apoptosis gene network is key towards identifying novel therapeutic targets. Recently, there has been a surge of interest in developing network-based approaches to study gene interactions and use machine learning tools to further elucidate useful biological factors. It is well-known that genes operate as network systems; however, interpretable computational methods are still limited. In this work, we combine a set of network analysis tools to provide novel biological insights into how the apoptosis network is dysregulated in MM. We identify a set of genes associated with poor outcomes in MM using both univariate and network-based approaches. Genomic and clinical data, including RNA-sequencing (RNA-seq) and copy number alteration (CNA), for 659 subjects were obtained from the Multiple Myeloma Research Foundation's CoMMpass (IA19) database. The apoptosis gene set is defined using the apoptosis hallmark pathway provided by the gene set enrichment analysis tool. The interactions between the given list of genes are provided via MetaCore. Univariate gene modeling is done using a Cox proportional hazards model. To determine the relationship between genes, we used Ollivier-Ricci curvature (ORC), a measure of network robustness. The ORC value between two genes incorporates information about both the two genes in question and their local neighborhoods, a concept critical for understanding the role a neighborhood of genes has on a given connection. Once edge information is computed, we used a uniform manifold approximation and projection (UMAP) to reduce the complexity of the dataset. The resulting projection is clustered using k-means clustering, and survival analysis of the given clusters is done using the Kaplan-Meier (KM) method. To understand which features are most informative, we used a random forest to predict the cluster labels using the RNA-seq data. After five-fold cross-validation, feature importance was computed using random forest's permutation importance methodology. All statistical significance testing was corrected for multiple comparisons via the Benjamini-Hochberg false discovery rate method with an alpha set to 0.05. Using RNA-seq data of genes associated with apoptosis, we identified nineteen apoptosis genes associated with poor prognosis in MM. Some of these genes, such as ANXA1 and WEE1 are known to have an effect in MM, while others, such as AVPR1A have yet to be studied extensively for their role in MM. When examining CNA data associated with apoptosis, a similar pattern emerged - nineteen genes were associated with poor prognosis. However, between the two key gene sets found by RNA-seq and CNA, only FAS appeared in both lists. FAS, Fas Cell Surface Death Receptor, is critical for triggering apoptosis. Half of the 37 genes identified using RNA-seq and CNA data are directly connected to the TP53 gene. While TP53 mutations are not a marker of the presence of MM itself, TP53 mutations have been shown to be associated with poorer outcomes. After reducing the complexity of the Ollivier-Ricci curvature analysis of the RNA-seq apoptosis network using UMAPs, the data revealed five clusters with KM curves for progression-free survival were significant (p<0.001). To identify the genes most impactful for separating these clusters, we trained a random forest model on the RNA-seq - note, it was the edge robustness values that were clustered - and evaluated its performance for predicted class membership. The model had an overall accuracy of approximately 78% with F1 scores for each class ranging from 61% to 87%. The top three features associated with the model include CTNNB1, RELA, and LEF1. Of note, CTNNB1 and RELA are directly interacted with the TP53 gene. Because these three genes discriminate between all five clusters, their expression levels may play a mediating effect on MM outcomes. Further investigation with external datasets is needed to validate these results.

P26-06: Possibility for Liver Toxicity Evaluation by Gene Set Enrichment Analysis (GSEA) using Key Event-Specific Gene Sets Applying Gene Expression Data Obtained in Rat Primary Hepatocytes

P26-06: Possibility for Liver Toxicity Evaluation by Gene Set Enrichment Analysis (GSEA) using Key Event-Specific Gene Sets Applying Gene Expression Data Obtained in Rat Primary Hepatocytes

77 (P7-9). Exploring the differential expression of a set of key genes involved in the regulation and functioning of the stomach in the post-weaned pig

77 (P7-9). Exploring the differential expression of a set of key genes involved in the regulation and functioning of the stomach in the post-weaned pig

Exploring the Differential Expression of a Set of Key Genes Involved in the Regulation and Functioning of the Stomach in the Post-Weaned Pig.

Despite playing a key role in digestion, there is only a broad characterization of the spatiotemporal development of the three glandular regions of the stomach (cardiac, fundic and pyloric) in the weaned pig. Hence, the objective of this experiment was to explore the differential expression (DE) of a panel of key genes within the three glandular regions of the stomach. Eight pigs were sacrificed at d 8 post-weaning, and three mucosal samples were collected from each stomach's glandular regions. The expression of a panel of genes were measured using QPCR. The true cardiac gland region was characterized by increased expression of PIGR, OLFM4, CXCL8 and MUC2 relative to the two other regions (p < 0.05). The fundic gland region was characterized by increased expression of ATP4A, CLIC6, KCNQ1, HRH2, AQP4, HDC, CCKBR, CHIA, PGA5, GHRL and MBOAT4 compared to the two other regions (p < 0.05). The pyloric gland region was characterized by exclusive expression of GAST (p < 0.05). A transition region between the cardiac and fundic region (cardiac-to-oxyntic transition) was observed with a gene expression signature that resembles a cross of the signatures found in the two regions. In conclusion, unique gene expression signatures were identifiable in each of the glandular regions, with a cardiac-to-oxyntic transition region clearly identifiable in the post-weaned pigs' stomachs.

Integrated LC/MS-based lipidomics and transcriptomics analyses revealed lipid composition heterogeneity between pectoralis intramuscular fat and abdominal fat and its regulatory mechanism in chicken

Intramuscular fat (IMF) content is conducive to multiple meat quality properties, while abdominal fat (AF) is treated as waste product in chicken industry. However, the heterogeneity and distinct regulatory mechanisms of lipid composition between the IMF and AF are still unclear. In this study, we carried out non-targeted lipidomics analyses of pectoralis IMF and AF, and detected a total of 423 differential lipid molecules (DLMs) between chicken IMF and AF, including 307 up-regulated and 116 down-regulated DLMs in pectoral IMF. These DLMs exhibited the definite alteration of lipid composition. The up-reglated DLMs in IMF were mainly glycerophospholipids (GPs), including the bulk of phosphatidylcholines (PC, PC (P) and PC (O)), phosphatidylethanolamines (PE, PE (P) and PE (O)), phosphatidylglycerols (PG) and phosphatidylinositol (PI), while the up-reglated DLMs in AF were mainly glycerolipids (GLs), including most of triacylglycerols (TG) and diacylglycerols (DG). We further identified 28 main DLMs contributing to the heterogeneous deposition of IMF and AF, including 11 TGs common to IMF and AF, 12 PCs/PC (P)s specific to IMF and 5 DGs specific to AF. Further integration of transcriptome with the main DLMs by weighted gene co-expression network analysis (WGCNA), we found five key gene sets that included 386 unique genes promoting IMF deposition in pectoralis, 213 unique genes promoting AF deposition, 6 unique genes detrimental to AF deposition, 7 common genes that promote IMF deposition in pectoralis while adversely affect AF deposition, and 28 genes that only promoted IMF deposition in pectoralis but had no effect on AF deposition. In addition, we also observed the expression characteristics of key genes in vivo and in vitro, and found that transmembrane protein family gene TMEM164 might be mainly involved in the positive regulation of intramuscular fat deposition in pectoralis and zinc finger protein family gene ZNF488 had a potential unique positive regulatory function on abdominal fat deposition. These findings provide new perspectives for understanding IMF and AF heterodeposition and will serve as a valuable information resource for improving meat quality via breeding selection in chicken.

Identification of key genes for IgA nephropathy based on machine learning algorithm and correlation analysis of immune cells

IntroductionThe pathogenesis and progression mechanism of Immunoglobulin A nephropathy (IgAN) is not fully understood. There is a lack of panoramic analysis of IgAN immune cell infiltration and algorithms that are more efficient and accurate for screening key pathogenic genes. MethodsRNA sequencing (RNA-seq) data sets on IgAN were downloaded from the Gene Expression Omnibus (GEO) database, including GSE93798, GSE35489, and GSE115857. The RNA-seq data set of kidney tissue as control samples were downloaded from the Genotype-Tissue Expression (GTEx) database. Three machine learning algorithms—weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO), and support vector machine—were used to identify the key pathogenic gene sets of the IgAN disease. The ssGSEA method was applied to calculate the immune cell infiltration (ICI) of IgAN samples, whereas the Spearman test was used for correlation analysis. The receiver operator characteristic curve (ROC) was used to evaluate the diagnostic efficacy of key genes. The correlation between the key genes and ICI was analyzed using the Spearman test. ResultsA total of 177 genes were screened out as differentially expressed genes (DEGs) for IgAN, including 135 up-regulated genes and 42 down-regulated genes. The DEGs were significantly enriched in the inflammatory- or immune-related pathways (gene sets). Activating transcription factor 3 (AFT3), C-X-C Motif Chemokine Ligand 6 (CXCL6), and v-fos FBJ murine osteosarcoma viral oncogene homolog B (FOSB) were identified using WGCNA, support vector machine, and LASSO algorithms. These three genes revealed good diagnostic efficacy in the training and test cohorts. The CXCL6 expression positively correlated with activated B cells and memory B cells. ConclusionATF3, FOSB, and CXCL6 genes were identified as potential biomarkers of IgAN. These three genes exhibited good diagnostic efficacy for IgAN. We described the landscape of immune cell infiltration for IgAN. Activated B cells and memory B cells were more highly expressed in the IgAN samples than in the control samples. CXCL6 seems crucial to the pathogenesis of IgAN and may induce IgAN by enriching immune cells. Our study may contribute to developing CXCL6 inhibitors that target B cells for IgAN therapy.

Integrated metabolic and transcriptional analysis reveals the role of carotenoid cleavage dioxygenase 4 (IbCCD4) in carotenoid accumulation in sweetpotato tuberous roots

BackgroundPlant carotenoids are essential for human health, having wide uses in dietary supplements, food colorants, animal feed additives, and cosmetics. With the increasing demand for natural carotenoids, plant carotenoids have gained great interest in both academic and industry research worldwide. Orange-fleshed sweetpotato (Ipomoea batatas) enriched with carotenoids is an ideal feedstock for producing natural carotenoids. However, limited information is available regarding the molecular mechanism responsible for carotenoid metabolism in sweetpotato tuberous roots.ResultsIn this study, metabolic profiling of carotenoids and gene expression analysis were conducted at six tuberous root developmental stages of three sweetpotato varieties with different flesh colors. The correlations between the expression of carotenoid metabolic genes and carotenoid levels suggested that the carotenoid cleavage dioxygenase 4 (IbCCD4) and 9-cis-epoxycarotenoid cleavage dioxygenases 3 (IbNCED3) play important roles in the regulation of carotenoid contents in sweetpotato. Transgenic experiments confirmed that the total carotenoid content decreased in the tuberous roots of IbCCD4-overexpressing sweetpotato. In addition, IbCCD4 may be regulated by two stress-related transcription factors, IbWRKY20 and IbCBF2, implying that the carotenoid accumulation in sweeetpotato is possibly fine-tuned in responses to stress signals.ConclusionsA set of key genes were revealed to be responsible for carotenoid accumulation in sweetpotato, with IbCCD4 acts as a crucial player. Our findings provided new insights into carotenoid metabolism in sweetpotato tuberous roots and insinuated IbCCD4 to be a target gene in the development of new sweetpotato varieties with high carotenoid production.

Identification of Novel Core Genes Involved in Malignant Transformation of Inflamed Colon Tissue Using a Computational Biology Approach and Verification in Murine Models.

Inflammatory bowel disease (IBD) is a complex and multifactorial systemic disorder of the gastrointestinal tract and is strongly associated with the development of colorectal cancer. Despite extensive studies of IBD pathogenesis, the molecular mechanism of colitis-driven tumorigenesis is not yet fully understood. In the current animal-based study, we report a comprehensive bioinformatics analysis of multiple transcriptomics datasets from the colon tissue of mice with acute colitis and colitis-associated cancer (CAC). We performed intersection of differentially expressed genes (DEGs), their functional annotation, reconstruction, and topology analysis of gene association networks, which, when combined with the text mining approach, revealed that a set of key overexpressed genes involved in the regulation of colitis (C3, Tyrobp, Mmp3, Mmp9, Timp1) and CAC (Timp1, Adam8, Mmp7, Mmp13) occupied hub positions within explored colitis- and CAC-related regulomes. Further validation of obtained data in murine models of dextran sulfate sodium (DSS)-induced colitis and azoxymethane/DSS-stimulated CAC fully confirmed the association of revealed hub genes with inflammatory and malignant lesions of colon tissue and demonstrated that genes encoding matrix metalloproteinases (acute colitis: Mmp3, Mmp9; CAC: Mmp7, Mmp13) can be used as a novel prognostic signature for colorectal neoplasia in IBD. Finally, using publicly available transcriptomics data, translational bridge interconnecting of listed colitis/CAC-associated core genes with the pathogenesis of ulcerative colitis, Crohn's disease, and colorectal cancer in humans was identified. Taken together, a set of key genes playing a core function in colon inflammation and CAC was revealed, which can serve both as promising molecular markers and therapeutic targets to control IBD and IBD-associated colorectal neoplasia.

Transcriptomic Analysis Revealed Key Defense Genes and Signaling Pathways Mediated by the Arabidopsis thaliana Gene SAD2 in Response to Infection with Pseudomonas syringae pv. Tomato DC3000.

Nucleocytoplasmic transport receptors play key roles in the nuclear translocation of disease resistance proteins, but the associated mechanisms remain unclear. The Arabidopsis thaliana gene SAD2 encodes an importin β-like protein. A transgenic Arabidopsis line overexpressing SAD2 (OESAD2/Col-0) showed obvious resistance to Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) compared to the wild type (Col-0), but the knockout mutant sad2-5 was susceptible. Transcriptomic analysis was then performed on Col-0, OESAD2/Col-0, and sad2-5 leaves at 0, 1, 2, and 3 days post-inoculation with Pst DC3000. A total of 1825 differentially expressed genes (DEGs) were identified as putative biotic stress defense genes regulated by SAD2, 45 of which overlapped between the SAD2 knockout and overexpression datasets. Gene Ontology (GO) analysis indicated that the DEGs were broadly involved in single-organism cellular metabolic processes and in response to stimulatory stress. Kyoto Encyclopedia of Genes and Genomes (KEGG) biochemical pathway analysis revealed that many of the DEGs were associated with the biosynthesis of flavonoids and other specialized metabolites. Transcription factor analysis showed that a large number of ERF/AP2, MYB, and bHLH transcription factors were involved in SAD2-mediated plant disease resistance. These results provide a basis for future exploration of the molecular mechanisms associated with SAD2-mediated disease resistance and establish a set of key candidate disease resistance genes.

Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits

Integrative genetic association methods have shown great promise in post-GWAS (genome-wide association study) analyses, in which one of the most challenging tasks is identifying putative causal genes and uncovering molecular mechanisms of complex traits. Recent studies suggest that prevailing computational approaches, including transcriptome-wide association studies (TWASs) and colocalization analysis, are individually imperfect, but their joint usage can yield robust and powerful inference results. This paper presents INTACT, a computational framework to integrate probabilistic evidence from these distinct types of analyses and implicate putative causal genes. This procedure is flexible and can work with a wide range of existing integrative analysis approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly desirable feature, we further propose an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated probabilistic evidence. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. We apply the proposed methods to analyze the multi-tissue eQTL data from the GTEx project and eight large-scale complex- and molecular-trait GWAS datasets from multiple consortia and the UK Biobank. Overall, we find that the proposed methods markedly improve the existing putative gene implication methods and are particularly advantageous in evaluating and identifying key gene sets and biological pathways underlying complex traits.